National Institute on Drug Abuse

RESEARCH

MONOGRAPH SERIES

Emerging

Technologies and

New Directions in

Drug Abuse

Research

U.S. Department of Health and Human Services • Public Health Service • National Institutes of Health

112
Emerging Technologies

and New Directions in

Drug Abuse Research

Editors:

Rao S. Rapaka, Ph.D.

Alexandros Makriyannis, Ph.D.

Michael J. Kuhar. Ph.D.

Research Monograph 112

1991

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Alcohol, Drug Abuse, and Mental Health Administration

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, MD 20857
ACKNOWLEDGMENT

This monograph is based on the papers and discussion from a technical

review on “Emerging Technologies for Drug Abuse Research,” held on October

12-13, 1989, in Rockville, MD. The review meeting was sponsored by the

National Institute on Drug Abuse.

COPYRIGHT STATUS

The National Institute on Drug Abuse has obtained permission from the

copyright holders to reproduce certain previously published material as noted in

the text. Further reproduction of this copyrighted material is permitted only as

part of a reprinting of the entire publication or chapter. For any other use, the

copyright holder’s permission is required. All other material in this volume

except quoted passages from copyrighted sources is in the public domain and

may be used or reproduced without permission from the Institute or the authors.

Citation of the source is appreciated.

Opinions expressed in this volume are those of the authors and do not

necessarily reflect the opinions or official policy of the National Institute on Drug

Abuse or any other part of the U.S. Department of Health and Human Services.

The U.S. Government does not endorse or favor any specific commercial

product or company. Trade, proprietary, or company names appearing in this

publication are used only because they are considered essential in the context

of the studies reported herein.

NIDA Research Monographs are indexed in the Index Medicus. They are

selectively included in the coverage of American Statistics Index, Biosciences

Information Service, Chemical Abstracts, Current Contents, Psychological

Abstracts, and Psychopharmacology Abstracts.

DHHS publication number (ADM)91-1812

Printed 1991

i i
Foreword

In October 1989 the National Institute on Drug Abuse (NIDA) organized a

conference titled “Emerging Technologies for Drug Abuse Research” to discuss

the impact of new technological advances on drug abuse research. The

conference set as its principal goal the discussion of novel methodologies with

an emphasis on the important current and future directions in research related

to drugs of abuse.

In the past two decades we have witnessed not only the emergence of many

scientific discoveries but also an explosive growth in the development of new

methods that greatly enhance the quality and productivity of research. These

include the application of solid-phase peptide synthesis methods in the design

of novel peptide analogs, cDNA and cloning techniques in biological research,

spectroscopic methods in biochemical and biophysical research, novel imaging

techniques in biological research, high-performance, liquid chromatographic

methods in analysis and purification of biomolecules, and, importantly, the

application of computer technology across all scientific fields of research,

including the area of computer-aided drug design (CADD).

Hence, NIDA believed that it was timely to call together experts in these areas

and seek new directions and applications for NIDA-related research.

Discussions at this conference were centered on CADD of benzodiazepine

drugs, 3D-searching methodologies for drug design, design of selective

agonists for 5-HT receptors, application of spectroscopic techniques such as 2D

and 3D nuclear magnetic resonance (NMR), solid-state NMR, small-angle x-ray

diffraction, differential scanning calorimetry, positron emission tomography

(PET) and its application for studies on cocaine, autoradiographic and PET

studies of the cannabinoid receptor, cocaine antagonists, and modified solidphase peptide synthesis methods. It was clear from the discussions that these

techniques hold great promise in such areas as understanding the mechanisms

iii
of action of drugs, understanding the molecular determinants for interaction at

receptor types, understanding addictive behavior, and, finally, design of new

pharmacotherapies.

Marvin Snyder, Ph.D.

Director

Office of Policy and External Affairs

National Institute on Drug Abuse

For sale by the U.S. Government Printing Office

Superintendent of Documents, Mail Stop: SSOP, Washington, DC 20402-9328

ISBN 0-16-035851-5

i v
Contents

Page

Foreword iii

Emerging Technologies and New Directions in Drug Abuse

Research: An Overview 1

Rao S. Rapaka, Alexandros Makriyannis,

and Michael J. Kuhar

Voronoi Binding Site Models 7

Gordon M. Crippen

A Mechanistic Basis for Design of Selective Agonists for 5-HT

Receptors 21

Roman Osman and Harel Weinstein

Computer-Aided Drug Design for the Benzodiazepine

Receptor Site 43

Gilda H. Loew, Hugo O. Villar, Waymond Jung,

and M. Frances Davies

3D-Searching: An Overview of a New Technique for

Computer-Assisted Molecular Design 62

Robert S. Pearlman

Protein Structure Determination in Solution Using Nuclear Magnetic

Resonance Spectroscopy 76

Angela M. Gronenborn and G. Marius Clore

v
Combined Use of Solid-State Nuclear Magnetic Resonance

Spectroscopy, Small-Angle X-Ray Diffraction, and Differential

Scanning Calorimetry in Studies of Cannabinoid: Membrane

Interactions 106

Alexandros Makriyannis, De-Ping Yang,

and Thomas Mavromoustakos

Characterization and Localization of Cannabinoid Receptors in

Brain: An In Vitro Technique Using Slide-Mounted Tissue

Sections 129

Miles Herkenham

New Developments in Radiotracers for Positron Emission

Tomography 146

Joanna S. Fowler and Alfred P. Wolf

Use of Positron Emission Tomography To Study Cocaine in the

Human Brain 166

Nora D. Volkow, Joanna S. Fowler,

and Alfred P. Wolf

Development of Opioid Peptide Analogs as Pharmacologic

Tools and as Potential Drugs: Current Status and Future

Directions 180

Peter W. Schiller

Conformational Analysis of Opioid Receptor-Selective

Peptides Using Nuclear Magnetic Resonance and Theoretical

Calculations 198

Victor J. Hruby, Om Prakash,

Wieslaw Kazmierski, Catherine Gehrig,

and Terry O. Matsunaga

Peptidomimetic Opioids—Synthesis, Spectroscopy, and Computer

Simulations 218

Murray Goodman, Odile E. Said-Nejad,

Eduard Felder, Dale F. Mierke,

Toshimasa Yamazaki, and Peter W. Schiller

Modified Solid-Phase Methods for the Rapid Synthesis of

Opioid Peptides 239

Richard A. Houghten, John M. Ostresh,

and Suzanne M. Pratt

vi
Irreversible Ligands as Probes for Drug Receptors 256

Amy Hauck Newman

Important Compounds in the Cocaine Class: A Synthesis

Overview 284

F.I. Carroll and Anita H. Lewin

lmmunomodulatory Effects of Drugs of Abuse and the

Importance of Structure-lmmunomodulatory Activity Studies 300

Rao S. Rapaka and Charles P. Hoiberg

FDA Regulatory Requirements for Investigational New Drugs

and New Drug Applications: An Update 313

Charles P. Hoiberg and Rao S. Rapaka

List of NIDA Research Monographs 326

vii

Emerging Technologies and New

Directions in Drug Abuse Research:

An Overview

Rao S. Rapaka, Alexandros Makriyannis, and Michael J. Kuhar

During the past decade, many important advances in physicochemical

methodologies have been adopted successfully in drug research. The

concerted use of these methods coupled with computer-aided approaches for

drug design have produced a new era in drug discovery and in the

understanding of the molecular mechanisms of drug action. In October 1989,

the National Institute on Drug Abuse organized a conference to discuss these

advances as they apply to research on drugs of abuse. This volume draws to a

large extent from this event, and a summary of these contributions follows.

Of the 17 chapters included in this volume, 4 are dedicated to the use of

computer technology in drug research. Dr. Crippen discusses methods for

gaining information on receptor structure and the energetics involved in drugreceptor interactions. Calculations are based on observing the binding

constants of small ligands with several receptor preparations. The approach

consists of developing simple binding site models and, through computational

methods, exploring their interactions with drug molecules. In the second

chapter, Drs. Osman and Weinstein add an extra level of complexity in the

theoretical model of ligand-receptor interactions. Again, using biochemical and

pharmacological data as a starting point, the authors undertake computational

slmulations to develop a mechanism by which ligands can activate the 5-HT1A

receptor. This molecular model for receptor activation can differentiate between

agonist and antagonist response. Dr. Loew and coworkers discuss a further

expansion of this approach in describing a computer-aided approach for drug

design aimed at the benzodiazepine receptor site. As with other computational

approaches, receptor-binding and pharmacological data for a series of analogs

are used to identify and characterize the stereoelectronic properties associated

with agonist and antagonist activities, These stereoelectronic criteria are used in

turn in a three-dimensional search of databases of known compounds. Finally,

using stereoelectronic criteria complementary to those developed for the

ligands, the entire set of data is used to characterize the receptor-binding site.

1
The information developed in this manner can be used to characterize regions

in the GABA receptor subunits that could be good active site candidates.

Alternatively, the results can be used to develop receptor site models in

different, functionally unrelated protein structures already known.

The increasing importance of computer-aided searches for the discovery of new

lead compounds in drug therapy is outlined by Dr. Pearlman. The approach

described here is especially useful for designing novel drug molecules in cases

where only a limited knowledge is available on the structure of the site of action.

It Involves searching large databases of molecular structures for molecules that

satisfy the three-dimensional geometric criteria describing the pharmacophore.

The method was shown to be successful in the comprehensive computer-aided

design of ligands for the benzodiazepine receptor site described in the previous

chapter.

The next two chapters deal with novel developments in methodologies used to

probe macromolecular structures and ligand-biopolymer interactions. Drs.

Gronenborn and Clore describe the uses of multidimensional nuclear magnetic

resonance (NMR) methods to study the structure of proteins and their

interactions with ligands of biological significance. Indeed, two- and threedimensional NMR experiments now can be used effectively to determine the

structure and conformation of soluble proteins up to 25 kilodaltons in size. In

the other chapter, Dr. Makrlyannis and coworkers describe the combined use of

small-angle x-ray diffraction and solid-state NMR to study membrane structure

and drug membrane interactions. Because of their complexity and inherent

instability, membranes do not lend themselves to a detailed analysis of their

structure and dynamics by means of a single physicochemical method.

However, the combined techniques can provide detailed information on the

topography, orientation, and conformation of the drug molecule in the

membrane. The work described here deals with cannabinoids and model

membranes; however, the methods used should have more general applicability

for studying drug interactions with membrane-bound receptors.

Dr. Herkenham also discusses cannabinoids; he describes his experiments with

slide-mounted tissue sections to characterize and localize the newly discovered

“cannabinoid receptor.” This membrane-associated protein, which

stereoselectively binds cannabinomimetic molecules, recently has been cloned.

These new findings open a new era in cannabinoid research and enhance the

opportunities for designing novel analogs of therapeutic value.

Positron emission tomography (PET) is a radioimaging method that can be

used to measure receptor concentration and neurotransmitter activity, brain

2
glucose metabolism, cerebral blood flow, and pharmacokinetics in the living

brain. Therefore, the technique is uniquely suited for investigating the

neurochemical and physiological processes underlying drug addiction. The

group from the Brookhaven National Laboratory headed by Dr. Wolf has

contributed two chapters outlining the principles and applications of this method,

which requires muitidisciplinary skills. Drs. Fowler and Wolf briefly describe the

basis for and new developments in PET methodology, including the different

accelerators for isotope production and the synthesis of labeled tracers. They

then review the use of radiotracers for PET studies of the brain and for studying

the binding of therapeutic drugs and substances of abuse. In the other chapter,

Dr. Volkow and colleagues address the pharmacological and medical aspects of

PET. They focus on the action of cocaine in the human brain and review the

different experimental strategies currently used to study the drug’s effects on

the dopaminergic system.

The most extensive contribution in this volume deals with the structure-function

correlations of opioids. Dr. Schiller first reviews the current status of selective

opioid receptor ligands. There are three approaches used for the design of

opioid peptide analogs, The most direct one deals with substitution, deletion, or

addition of amino acids in the native ligands, which has resulted in the synthesis

of a variety of linear peptides. The second approach introduces conformational

restriction through cyclization as an additional element in drug design, and the

third uses bivalent compounds containing two opioid-receptor ligands. The

author concludes that substantial progress has been made toward the

development of analogs with high selectivity for mu- and delta-opioid receptors,

while promising efforts are being made for the development of ligands with

specificity for subtypes of kappa-, delta-, and mu-receptor classes.

Early clinical trials with enkephalin analogs are disappointing because of

serious side effects. However, it is hoped that these side effects will be

minimized when analogs with higher selectivity for the different opioid receptor

classes and subtypes are introduced. Also, encouraging from the therapeutic

point of view are the recent data indicating that opioids are able to produce

peripherally mediated analgesic effects, thus offering potential therapeutic

usefulness in hyperalgesia or painful inflammatory conditions.

The two additional chapters dealing with novel opioids introduce the combined

use of high-resolution NMR and computational methods as aids in drug design.

Small linear peptides are known to be flexible and adopt multiple conformations

that may allow them to interact with more than one receptor. It is hypothesized

that, through conformational constraints, the peptides will be forced to adopt a

single conformation and, consequently, show increased selectivity toward a

3
single receptor. Dr. Hruby and colleagues reflect on how conformational

constraints and topographical considerations can be used for the design of

receptor-specific opioid peptide ligands. The highly delta-opioid receptorselective [D-Pen2

,D-Pen5]-enkephalin is used as a model starting point for such

a design. In a different approach, cyclic somatostatin peptides are modified

strategically to give a cyclic octapeptide with high selectivity for opioid receptor

end only marginal somatostatin activity.

Dr. Goodman and colleagues, in dealing with the design of stereochemically

defined opioids, describe their “peptidomimetic retroinverso” modified

enkephalins and modified cyclic demorphins, whose conformations are

stabilized through intramolecular hydrogen bonding.

Three chapters discuss the use of organic synthesis for drug abuse research.

Dr. Houghten and coworkers deal with modified solid-phase methods for the

rapid synthesis of opioid peptides. The technique of multiple peptide synthesis

in small- and large-scale preparations using solid-phase methodology is

described. These relatively straightforward approaches are efficient and can be

used to obtain large numbers of synthetic peptides in milligram as well as

multigram quantities. They should be especially useful for applications in smallor medium-size research laboratories.

Dr. Newman reviews the use of irreversible ligands as probes for drug

receptors. Electrophilic and photoactivatable groups can be introduced on highaffinity receptor ligands to obtain useful receptor-selective irreversible probes

that attach covaiently to the receptor protein. These receptor probes can be

used for the neuroanatomical localization of receptor sites, the isolation and

purification of drug receptors, and in understanding the physiological and

pharmacological properties of these receptors. Such affinity labels are

described for the opioid, N-methyl-D-spartate, sigma, benzodiazepine, GABA,

dopamine, and serotonin receptors, all of which are of interest in drug abuse

research.

Because of its dominant role as a drug of abuse, cocaine has been the focus of

extensive work in search of a cocaine “antagonist.” Drs. Carroll and Lewin

provide an overview of the different approaches for the synthesis of cocaine

analogs.

The AIDS epidemic has intensified interest in the immunomodulatory effects of

drugs of abuse. Receptors for opiates, opioid peptides, phencyclidine,

benzodiazepine, and dopamine have been found on the cells of the immune

system. It also has been shown that several groups of drugs of abuse have

4
immunomodulatory effects. For example, morphine has immunosuppressive

effects, whereas many opioid peptides enhance the immune function.

Marijuana and THC have been found to suppress the immune system in

animals, but there is no conclusive evidence for such effects in humans. Drs.

Rapaka and Hoiberg make a case that immunomodulatory activity is subject to

specific structural requirements, and they stress the need for evaluation of

these effects for ail potential new drugs. Structure-activity relationship studies

on these drugs would be useful while evaluating the overall effects of drugs of

abuse.

Drs. Hoiberg and Rapaka describe the recent status of Food and Drug

Administration regulatory requirements for investigational new drugs and new

drug approval. They also describe the recent changes regarding requirements

for the submission of applications for investigational new drugs and new drugs.

Other topics of interest include orphan drug products and the innovative

procedures intended to facilitate and improve the review process.

This National Institute on Drug Abuse monograph mirrors the multidisciplinary

nature of current chemical research related to drugs of abuse and serves to

highlight some of the most important developments in methodology currently

used or of potential applicability in research related to drugs of abuse.

AUTHORS

Rao S. Rapaka, Ph.D.

Medication Development Division

National Institute on Drug Abuse

Room 11A-55

5600 Fishers Lane

Rockville, MD 20857

Alexandros Makriyannis, Ph.D.

Professor

Section of Medicinal Chemistry and Pharmacognosy

Institute of Materials Science

University of Connecticut School of Pharmacy

U92

Storrs, CT 06269

5
Michael J. Kuhar, Ph.D.

Professor

Johns Hopkins University School of Medicine

Chief

Neuroscience Branch

Addiction Research Center

National Institute on Drug Abuse

P.O. Box 5180

Baltimore, MD 21224

6
Voronoi Binding Site Models

Gordon M. Crippen

INTRODUCTION

The goal to develop improved methods for deducing the receptor structure and

energetics, given the observed binding constants for a series of small ligands, is

a commonly occurring problem in the search for better drugs, and many

research groups are turning to computer-aided drug design techniques for help.

For example, what can we say about the shape and intermolecular forces

governing the binding of competitive inhibitors of an enzyme, given their binding

constants but without knowing the enzyme’s x-ray crystal structure? The

algorithm for deducing this should be as little influenced as possible by the

preconceptions of the investigator, and the amount of detail in the result should

correspond to the quality of the data. The technique is to construct a simplified

picture of the site that still allows the ligands to explore their full range of

energetically allowed conformations and alternate orientations within the site.

Binding energies are modeled as a sum of interactions between ligand atoms

and the regions of the site they occupy.

A review of the Journal of Medicinal Chemistry indicates at least 10 articles per

issue are published in which the authors have measured some biological

activity or the binding affinity to some receptor for a series of compounds, and

they attempt to comprehend the resulting data. Nearly all these discussions are

cast in the language of the organic/medicinal chemist: What is the effect of

different substituents at different positions on the parent compound? There are

two pervasive assumptions in these qualitative discussions and in most

quantitative structure-activity relationship (QSAR) methods—namely, that the

compounds are clearly so closely related structurally that one may

unambiguously superimpose them; indeed, they all bind in analogous

orientations at the receptor site. The first assumption is often a consequence of

everyone’s natural tendency to modify promising compounds in hopes of

improving them but sometimes the set of compounds is extremely varied, as in

the case of the benzodiazepine receptor, which also binds ß-carbolines (Haefely

1988). The second assumption is often valid (Cheung et al. 1986), even though

we know that the ligand-receptor complex forms by a random approach of the

ligand tumbling in the solvent and tending to remain for longer periods in

7
whatever states correspond to exceptionally low free energy. There are,

however, dramatic exceptions to the assumption, where small changes in the

chemical structure lead to complete reversals in the mode of binding (Roberts et

al. 1981).

Many methods have been devised to correlate the structure of compounds with

their quantitatively measured binding to various receptors, starting with the

pioneering work of Free and Wilson (1964) Hansch and Fujita (1964) and Kier

(1971). Hansch’s approach is probably the most frequently used method today,

and it virtually defines the QSAR field. The investigator must assume that

chemically similar compounds bind to the receptor such that atoms common to

several compounds lie always at the same positions. Then the binding is fit in a

least squares sense to a linear combination of selected physicochemical

properties of the entire molecules and the various substituents. For example, a

favorite property is the octanol/water partition coefficient. Some methods are

intended to correlate chemical structural and topological (Ray et al. 1981)

features with activity even more empirically by cluster analysis and related

approaches (Rubin and Willett 1983; Wiliett 1982; Peredunova and Kruglyak

1983). If the chemical similarity between active compounds is minimal, then

searches for common atoms responsible for activity (Danziger and Dean 1985),

called the pharmacophore, sometimes take into account conformational

flexibility, but generally rely on some superposition hypothesis from the

investigator (Andrews and Lloyd 1983; Brint and Willett 1987). Marshall’s group

has devoted considerable effort to examining different conformations of active

compounds and comparing the geometric and steric differences between active

and inactive compounds, given a hypothesis for superimposing the molecules

(Humblet and Marshall 1981; Motoc 1984; Motoc et al. 1985; Cramer and

Bunce 1987). See the following references (Karfunkel 1986; Kuz’min and

Krutius 1986; Motoc 1979) for other methods of overlapping molecules to

develop an image of the receptor.

Although the usual methods are varied in detail and in the degree of

conformational, geometric, and steric realism, the site tends to be viewed as the

complement of the commonality of the active molecules in a chosen

superposition. There may be a geometric component to the site model, at least

implicitly, embodied in the hypothesized molecular superposition. The model

also may be quantitative, assigning contributions to the total binding due to the

various substituents at different positions on the parent compound. We always

have advocated making an explicit model of the site so as to make the

geometric and energetic features clear and to facilitate comparisons with other

experiments such as x-ray crystallography. But given explicit site geometry and

interactions with the ligands, would the ligands choose to bind to the site in the

hypothesized modes? The answer generally is “no”: They would change their

8
conformation and positioning relative to the site in a manner unanticipated by

the investigator so as to achieve a more favorable energy of interaction.

Revising the site model to incorporate this additional aspect of realism requires

a basic rethinking of how QSAR is done. The ideas of pharmacophore, steric

tolerance, conformational analysis on the ligands, and substituent effects all

become intertwined It is fair to say that our QSAR studies are unique in the

field for having directly addressed the issue. The costs are much lengthier

computer calculations by much more complicated algorithms, but we believe the

benefit is a shift away from purely empirical correlations toward models that can

be verified by other physical experiments and that will have enhanced predictive

ability.

METHODS

An enormous amount of work over the past 2 years has been summarized in a

few papers. It is difficult to describe because of the number of new concepts we

have introduced (rather than their difficulty): (1) the “linearized” representation

of the rigid valence geometry of organic compounds, (2) a global summary of

the conformation space of a molecule so represented, (3) modeling of binding

sites in terms of Voronoi polyhedra, and (4) the relationship between the

accuracy of the experimental binding data and the geometric resolution of the

deduced binding site. An overview is presented here, and the reader may refer

to other references as well (Crippen and Havel 1988; Crippen 1987).

1. We need a compact description of organic molecules that lends itself to

receptor site modeling, and it is particularly important to be able to treat the

conformational flexibility that arises from rotations about single bonds. Our

linearized representation of a molecule involves assuming fixed bond

lengths and vicinal bond angles, specifying the overall translation of the

molecule with respect to an external reference frame by a vector w pointing

to a centrally located atom, and setting up local coordinate systems in

terms of unit vectors u1

, u2, ... for mutually rigid groups of atoms, as

illustrated in figure 1. Then the position of every atom can be given as a

linear combination of the translation vector and the unit vectors. This turns

out not only to facilitate binding site modeling, but also has led to a new

algorithm for calculating atomic coordinates subject to distance constraints,

as in the determination of solution conformation by two-dimensional nuclear

magnetic resonance (Crippen 1989).

2. Most methods for developing QSARs make assumptions about the

orientation of the ligand molecule in the binding site and its conformation

upon binding. To avoid making such assumptions, we must have a

convenient summary of the global range of conformations that are

9
FIGURE 1. Linearized representation of the rigid valence geometry of a

molecule. Note that planar groups require only two-dimensional

local coordinate systems.

energetically accessible. The linearized representation of a molecule

automatically incorporates correct bond lengths and angles, and it holds

such items as benzene rings rigid. As can be seen in figure 1, some unit

vectors, such as 2 and 4, have a fixed dot product by construction; but

others, such as 1 and 4, have a range of dot product values as the

molecule rotates about single bonds. Thus, we see in figure 2 that the rigid

valence geometry is represented as points in the unit vector space, while

the entire (energetically or sterically) allowed conformation space can be

summarized as a rectangular region in the space of unit vector dot

products.

3. Instead of concentrating on the common features of several tightly binding

molecules, we construct an explicit model of the binding site. To be able to

express precise and indeterminate structural features of the site, we have

chosen to represent it as a set of Voronoi polyhedra. These constitute a

mathematically convenient way to divide up all three-dimensional space

10
FIGURE 2. How to describe the molecular structure and conformational

flexibility in the linearized representation. Each program should

have more than three axes, but these illustrate features seen in

figure 1.

into convex, nonoverlapping regions bounded by planar surfaces. To

specify a region, one only needs to choose the Cartesian coordinates of the

corresponding “generating point,” and then the region is defined as the set

of points closer to that generating point than to any other generating point.

For example, figure 3 shows a model of a binding site built out of one finite

tetrahedral region surrounded by four infinite regions. The central region

can be thought of as the empty space inside the real receptor site, the left

infinite region may represent the solvent, and the other three might be

sterically forbidden regions, representing the walls of the real site. Adding

more (finite) regions would add detail to the picture, if justifiable. At the

opposite extreme, the trivial site, consisting of a single infinite region,

corresponds to interaction with only solvent and puts no geometric

demands on the molecule. A two-region site would have a single plane

slicing all space in half and might be used to represent an interface

between aqueous solvent and a lipid layer.

4. Generally, one fits a model to experiment in a least squares sense to find a

single “best” approximation to the given data. There is a dangerous

tendency to overinterprat imprecise data and not to realize the range of

models that adequately explain the data, especially when there are so few

observations that the usual statistical tests cannot be applied. Voronoi

binding site models avoid these pitfalls by insisting that the calculated free

energy of binding must lie within the experimentally determined range (i.e.,

anywhere within the error bars) for every molecule in the study. In a study

11
FIGURE 3. An example of a five-region Voronoi site model consisting of a

finite central tetrahedral region surrounded by four infinite regions,

indicated by portions of their boundary planes

on 12 polychlorinated biphenyls binding to prealbumin (Boulu and Crippen

1989b), it was shown that a three-region site model is necessary and

sufficient to account for relatively high-accuracy data; but if the assumed

experimental error expands beyond a certain point, only a single

featureless region is required. There is apparently no other method in the

literature that gives this sensible linkage between accuracy of the input data

and spatial resolution of the resulting model.

Although it is not immediately obvious, these four ideas tightly interlock

mathematically to permit efficient computer programs for generating the

linearized representation of a series of ligand molecules, searching over the

entire allowed conformation space of each, and examining all geometrically

allowed ways each molecule has of fitting into a given Voronoi site model.

From this, another program can be used to adjust the energies of interaction

between the various regions and the atoms lying within them to achieve the

“absolute” fit mentioned above. Not surprisingly, bringing all these computer

12
algorithms up to a practical level has been extremely time consuming. Since

our first version of these programs (Crippen 1987), we have been able to treat

molecules with 36 atoms, including all hydrogens so that editing out

presumably unimportant atoms is no longer necessary. In addition, many subtle

errors have been eliminated from the determination of all allowed binding

modes; and this, the most time-consuming part of the calculation, has been

speeded up by orders of magnitude.

To explain what we intend to do next with this approach to modeling Iigandreceptor interactions, it will help to illustrate the current state of the art on a

simple example. Suppose we have a single, rigid, linear molecule having atoms

A, B, and C, as shown in figure 4. If the investigator proposes a two-region site,

both regions will be infinite and separated by a plane, as shown. The next step

is to find all geometrically allowed binding modes, where a mode states the

region in which each atom lies. Thus, having all three atoms in region 1 is one

possible mode, but with such a low resolution site, there is no attempt to specify

where in that region the molecule is located or what its orientation might be.

Even in such a simple example, not all 23

=8 modes are possible because the

linear molecule cannot bend enough to put atom B in one region while keeping

A and C in the other. It is convenient to think of enumerating all the allowed

modes by traversing a tree of possibilities, as shown in figure 5. Every “leaf” of

the tree along the bottom row of the figure corresponds to a placement of the

entire molecule in the site in a particular mode, and our programs for doing this

come up with a set of Cartesian coordinates for the atoms. For a site with many

regions, the tree becomes very broad, and for a molecule with many atoms, the

tree becomes very deep. So, it is important to prune the tree at as high a level

as possible, with as little computational expense as possible. In this example,

the two disallowed modes can be excluded immediately on noting that B is in

the convex hull defined by A and C, and Voronoi regions are always convex; we

have found similar rules extremely helpful with realistic ligand molecules (Boulu

and Crippen 1989a).

Suppose the molecule in this example is nitrous oxide, so that atoms A and B

are of type N, and atom C is of type O. If we denote the interaction between

region 1 and nitrogen by and so on, then the calculated free energy of

binding for a particular mode is assumed to be

(1)

13
FIGURE 4. All geometrically allowed binding modes for a linear molecule

having three atoms in a two-region site

FIGURE 5. The tree of possible binding modes corresponding to figure 4

14
and the molecule will choose the energetically best mode

(2)

(using the sign convention that greater values denote stronger binding). If there

is an experimentally determined range of binding, to then we insist

that the model must agree with experiment completely, rather than

approximately

(3)

Equation 3 is linear in the so it is relatively easy to adjust the four

parameters, and so that equation 3 is satisfied. This can be

done by defining a penalty function that is zero only when the best

mode for each molecule in the study has a calculated binding energy in the

correct range. Because the best mode may change when the interaction

parameters are varied, the penalty function can be constructed to be

continuous, but only piecewise linear (for example, as in figure 6). Note also

that even in simple situations, the penalty function can have multiple minima of

zero depth, corresponding to different sets of optimal binding modes being

equally able to explain the data, or a minimum may not reach to zero,

corresponding to almost but not quite satisfying equation 3 for some of the

molecules. We have been successful in locating completely correct solutions

by the subgradient optimization technique.

To show how this works with real data (Boulu and Crippen 1990), consider the

noncovalent, reversible, competitive binding of 10 polycyclic aromatic

hydrocarbons to a carcinogen binding protein isolated from mouse liver. The

experimental binding data determined by Marietta and coworkers (Collins and

Marletta 1984, 1986; Barton and Marletta 1988) includes an estimate of the

experimental errors, as shown in table 1.

The given binding data show that the affinity of a ligand increases roughly with

the number of carbons and hydrogens until a critical molecular size is reached

and then remains constant for molecules bigger than pyrene. Hence, a simple

correlation between IogP and binding, for example, is impossible. In fact, most

methods of QSAR would have difficulty in the initial step of superimposing these

compounds to find a pharmacophore, because they do not form a congeneric

series. Apparently, there must be a hydrophobic-preferring binding pocket of

some limited size, large enough to accept all of pyrene, but not much bigger.

Note also that because compound 2 binds better than 5 while having similar

numbers of atoms, the central hydrophobic pocket may be narrow. The

simplest way to achieve such a Voronoi model is to use five regions, as shown

15
FIGURE 6. A portion of one example of the continuous but piecewise linear

function F that must be minimized to determine the interaction

energy parameters—hatched areas correspond to solution sets.

in figure 3. The central tetrahedron, r1, is supposed to be the hydrophobic

binding pocket; the infinite region opening up on the left, r2, represents access

to the solvent; and the other three regions are a priori chosen to be infinitely

repulsive, so as to represent the sterically forbidden walls of the binding pocket.

After some experimentation, we adjusted the geometry so that the leftward

facing side of the inner tetrahedron (which opens out onto the solvent region) is

an equilateral triangle having side length 9 Å, and the remaining three edges

have length 13 Å. Then the program for determining interaction parameters

automatically was able to find the values shown in table 2. An amino group is

mildly repelled by the solvent region, but more so by the interior pocket, and C

and H atoms experience virtually no interaction with the solvent region.

Because we are fitting binding affinities that are proportional to the free energy

of transfer from solvent to the bound state, these calculated weak interaction

parameters with r2 are indeed gratifying bonuses.

16
TABLE 1. Observed and calculated binding of the compounds of figure 7 for

a five-region site shown in figure 3

Compound

Optimal

Modeb

1 benzo[a]pyrene 17.7 19.0 18.9

2 dibenzo[a,c]anthracene 17.3 18.6 18.2

3 chrysene 16.7 18.0 18.0

4 pyrene 16.3 17.6 16.4

5 cyclopenta[c,d]pyrene 15.6 17.6 15.6

6 fluoranthrene 16.7 18.0 18.0

7 1-aminonaphthalene 10.6 11.9 11.6

8 2-aminofluorene 13.8 15.1 14.1

9 1-aminoanthracene 14.9 16.2 14.9

10 9-aminophenanthrene 14.9 16.2 14.9

15C&8H

14C&8H

14C&8H

13C&7H

13C&6H

14C&8H

10C&6H

(NH2 in r1)

11C&7H

(NH2 in r2)

12C&7H

(NH2 in r2

)

13C&7H

(NH2 in r1)

a

The are given as in KI, where KIis the association constant of the

competitor with the receptor.

b

 The optimal modes are given as the number of C and H atoms lying in r1, the

rest being in r2.

FIGURE 7. Competitive inhibitors of [

3H]benzo[a]pyrene binding. Numbering

corresponds to table 1.

17
TABLE 2. Interaction parameters in in KI

 units for the site model

corresponding to table 1

Atom

Site Regions

r1

r2

H 0.81 -0.01

C 0.83 0.03

NH2-1.43 -0.65

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263:5825-5832, 1988.

Boulu, L.G., and Crippen, G.M. Voronoi binding site models: Calculation of

binding modes and influence of drug binding data accuracy. J Comput Chem

10:673-682, 1989b.

Boulu, L.G., and Crippen, G.M. Voronoi receptor site models. In: Rein, R., and

Golombek, A., eds. Computer-Assisted Modeling of Receptor-Ligand

Interactions: Theoretical Aspects and Applications to Drug Design. New

York: Alan R. Liss, Inc., 1989a. pp. 267-277.

Boulu, L.G., and Crippen, G.M. Voronoi binding site model of a polycyclic

aromatic hydrocarbon-binding protein. J Med Chem 33:771-775, 1990.

Brint, A.T., and Willett, P. Pharmacophoric pattern matching in files of 3d

chemical structures: Comparison of geometric searching algorithms. J Mol

Graphics 5:49-56, 1987.

Cheung, H.T.A.; Searle, M.S.; Feeney, J.; Birdsall, B.; and Roberts, G.C.K.

Trimethoprim binding to lactobacillus casei dihydrofolate reductase: A 13C

NMR study using selectively 13C-enriched trimethoprim. Biochemistry

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Collins, S., and Marletta, M.A. Carcinogen-binding proteins. High-affinity

binding sites for benzo[a]pyrene in mouse liver distinct from the Ah receptor.

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Collins, S., and Marletta, M.A. Purification of a benzo[a]pyrene binding protein

by affinity chromatography and photoaffinity labeling. Biochemistry 25:4322-

4329, 1986.

Cramer, R.D., and Bunce, J.D. The Dylomms method: Initial results from a

comparative study of approaches to 3d QSAR. Pharmacochem Libr

10(QSAR Drug Des. Toxicology):3-12, 1987.

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Crippen, G.M. Voronoi binding site models. J Comput Chem 8:943-955, 1987.

Crippen, G.M. Linearized embedding: A new metric matrix algorithm for

calculating molecular conformations subject to geometric constraints.

J Comput Chem 10:896-902, 1989.

Crippen, G.M., and Havel, T.F. Distance geometry and molecular conformation.

In: Bawden, D. Chemometrics Research Studies Series. New York:

Research Studies Press (Wiley), 1988.

Danziger, D.J., and Dean, P.M. The search for functional correspondences in

molecular structure between two dissimilar molecules. J Theor Biol 116:215-

224, 1985.

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studies. J Med Chem 7:395-399, 1964.

Haefely, W.E. Benzodiazepines. Int Anesthesiol Clin 26:262-272, 1988.

Hansch, C., and Fujita, T. analysis. A method for the correlation of

biological activity and chemical structure. J Am Chem Soc 86:1616-1626,

1964.

Humblet, C., and Marshall, G.R. Three-dimensional computer modeling as an

aid to drug design. Drug Dev Res 1:409-434, 1981.

Karfunkel, H.R. Chemical complement simulation and quantitative structure

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Kier, L.B. Molecular Orbital Theory in Drug Research. New York: Academic

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Kuz’min, V.E., and Krutius, S. Analysis of structure-activity correlation on the

basis of structural correspondence within the receptor lattice model. KhimFarm Zh 20:791-794, 1986.

Motoc, I. On the minimal steric difference method (mtd). 1. Critical evaluation

and improvement. MATCH 5:275-280, 1979.

Motoc, I. Biological receptor maps. 1. Steric maps. The Sibis method. Quant

Struct-Act Relat Pharmacol Chem Biol 3(2):43-47, 1984.

Motoc, I.; Marshall, G.R.; and Labanowski, J. Molecular shape descriptors. 3.

Steric mapping of biological receptor. Z Naturforsch [A]: Phys Phys Chem

Kosmophys 40A:1121-1127, 1985.

Peredunova, I.V., and Kruglyak, Y.A. Program for determining the relation

between the structure of chemical compounds and their properties (logicalstructural scheme for discerning trends). Zh Strukt Khim 24(1):166-167,

1983.

Ray, S.K.; Basak, S.C.; Raychaudhury, C.; Roy, A.B.; and Ghosh, J.J.

Quantitative structure-activity relationship studies of bioactive molecules

using structural information indexes. lndian J Chem [B] 20B:894-897, 1981.

Roberts, G.C.K.; Feeney, J.; Burgen, A.S.V.; and Daluge, S. The charge state

of trimethoprim bound to lactobacillus casei dihydrofolate reductase. FEBS

Lett 131:85-88, 1981.

19
Rubin, V., and Willett, P. A comparison of some hierarchal monothetic divisive

clustering algorithms for structure-property correlation. Anal Chim Acta

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ACKNOWLEDGMENTS

This work was supported by National Institutes of Health grant GM-37123 and

National Science Foundation grant DMB-8705006.

AUTHOR

Gordon M. Crippen, Ph.D.

Professor

College of Pharmacy

University of Michigan

Ann Arbor, Ml 48109

20
A Mechanistic Basis for Design of

Selective Agonists for 5-HT Receptors

Roman Osman and Harel Weinstein

INTRODUCTION

Insight into the processes that define receptor function has come from

experimental efforts at the cellular, tissue, and whole-organ levels (Black et al.

1987). However, an understanding of the molecular pharmacology of receptors

still is hampered by the lack of structural information, at the detailed atomic

level, about the receptor and effector molecules responsible for most

measurable biological activities. With the development of theoretical

approaches and efficient computational algorithms (Dean 1987; Brooks et al.

1988; Beveridge and Jorgensen 1986) the experimental approaches are

complemented by molecular models of receptor systems constructed with the

aid of theoretical methods. Such models are based on inferences from studies

carried out in a variety of disciplines and experimental approaches, including

chemistry, molecular pharmacology, enzymatics, and molecular biophysics of

proteins (Richards 1983; Fersht 1985; Weinstein 1986, 1987; Dean 1987;

Austin et al. 1987; Oxender 1987). It is now evident that theoretical chemistry,

in a variety of forms (e.g., quantum chemistry, molecular modeling, molecular

mechanics), has provided the formal means to unify the inferences obtained in

a heuristic process of learning from the various models about the molecular

mechanisms that describe the interaction of ligands with protein targets and the

consequences of these interactions (Weinstein 1986; Dean 1987; Brooks et at.

1988). Key components of activity on receptors (e.g., selective recognition and

triggering of response) can be understood from such models at the molecular

level, based on the properties of the interacting molecules and the results of

their interactions.

As reviewed and described below, a combination of theoretical and

experimental studies led to the proposed mechanistic models for the selectivity

of different 5-HT receptors and the activation of the 5-HT1A receptor. These

studies also provided the first indications of the possible mechanisms for

recognition and triggering of a response at the 5-HT2 receptor. The

computational exploration of such processes inside proteins that serve as

21
receptor models, as described briefly in this review and in more detail in

previous publications (Mercier et al. 1988a, 1988b; Weinstein et al. 1988;

Weinstein and Osman 1989a), demonstrates the significant progress

achievable from heuristic models based on solid physicochemical principles and

cognate experimental data. Notably, these types of models have made it

possible to probe the molecular basis of the observed efficacy of ligands in

eliciting the pharmacological responses, thus yielding insight into the molecular

details of the difference between agonists and antagonists. Such explorations

of activation models provide a new level of understanding of the mechanisms

underlying the classical pharmacological properties of agonists, partial agonists,

or antagonists and lead to the definition of structural correlates of

pharmacological efficacy. They also provide a basis for a rational approach to

the design of compounds with predetermined efficacy (i.e., full and partial

agonists and antagonists).

HEURISTIC SCHEMES FOR THE STUDY OF RECEPTOR MECHANISMS

AND LIGAND DESIGN

Because the mechanism of receptor occlusion by binding appeared to be

understood, antagonists have been the subject of rational drug design for some

time. In contrast, compounds with agonist activity still are obtained mostly by

serendipity or from extensions of known templates through structural analogy.

As shown in the heuristic approach to design (figure 1), which was defined

recently (Weinstein and Osman 1989b, 1990) the rational design of antagonists

is guided by structural correlates of affinity (e.g., the “interaction

pharmacophore”) (Weinstein 1975; Weinstein et al. 1978) which is based on

the mechanistic hypothesis that certain structural elements of the ligand

(components of the pharmacophore) confer selectivity and affinity at receptors

through specific types of interactions. The assumption is that these interactions

are quantified by the results of receptor-binding assays. In spite of caveats and

limitations of this assumption relating structure to measured affinity (Weinstein

1987), this approach to structure-activity relations often has been successful

when applied to the design of antagonists. But the situation is more

complicated for agonists. Although efficacy, like binding affinity, is readily

measurable in pharmacological assays (Clancy and Maayani 1985), there has

been no way to identify an “activation pharmacophore” that includes structural

elements of the ligand that are involved in eliciting the response. Thus,

guidelines for the design of agonists based on connecting molecular structure to

efficacy (as opposed to affinity) did not exist. This shortcoming is attributable,

at least in part, to the lack of mechanistic models for the way in which ligands

trigger a response at the receptor. Simulations of recognition mechanisms as

part of a heuristic approach (figure 1) help identify possible molecular

mechanisms for receptor activation based on the changes induced in the

22
FIGURE 1. Outline of a hierarchical approach to ligand design based on a

procedure of heuristic modeling of ligand-receptor interaction that

leads to the identification of structures with predetermined

pharmacological properties

23
models of recognition sites and thus provide a link to the pharmacological

concepts of affinity and efficacy.

Our approach in relating the molecular mechanisms to the classical

pharmacological concepts is anchored in the relatively recent formulation of the

operational model of agonist action by Black and Leff (1983). In this formalism,

the classical pharmacological concept of efficacy has been identifled with a

parameter, KE, that relates to a specific mechanism: the transduction of the

agonist-receptor complex into a pharmacological effect. This approach helps

overcome a major shortcoming of earlier versions of receptor theory (Clark

1926; Ariens 1954; Stephenson 1956; Furchgott 1964; Furchgott and Bursztyn

1967), which had difficulties in proposing practicable ways to measure efficacy

or, better yet, intrinsic efficacy of agonists (DeLean et al. 1978; Kenakin 1982).

The operational model of Black and Leff (1983) demonstrated that a hyperbolic

nature of the stimulus-effect relationship is a necessary outcome from the

hyperbolic nature of the relationship between the pharmacological effect and

the concentration of the agonist. This relationship also is consistent with many

experimental findings. More importantly, efficacy, named in this model the

“transducer ratio,” assumed the form where [Ro

] is the total number of

receptors and KE is defined operationally as the concentration of the agonistreceptor complex that yields half-maximal response. Black’s KE differs from

Furchgott’s which remains unexplained in chemical terms, because it has a

clear meaning in well-understood responsive systems such as the activation of

adenylate cyclase by ß-adrenergic agonists (DeLean et al. 1978). In such

systems KE becomes the affinity of the agonist-receptor complex to the effector

and thus acquires a well-defined chemical identity. As stated explicitly, because

“intrinsic efficacy is attributed to chemical binding it makes this property of

agonists accessible in the search for new drugs so that efficacy as well as

affinity can be associated with the chemical properties of substances and thus

incorporated into structure-activity calculations” (Black and Leff 1983). These

concepts then can be used to relate the results from pharmacological

characterizations of receptor systems to those from the simulations of molecular

mechanisms in protein models of receptors. Thus, the expression of drug

efficacy through the effects on the energetics of the activation mechanisms

should correlate with the efficacy obtained from pharmacological

measurements. As described below, this expression of efficacy in terms of the

energetics of the underlying mechanism is obtained from the application of

methods from theoretical chemistry in computational simulations of the

molecular processes occurring at the receptor.

24
MOLECULAR DETERMINANTS FOR RECOGNITION AT THE 5-HT1A AND 5-

HT2 RECEPTORS

Recognition Elements at the 5-HT1A Sites

The major determinants for ligand selectivity at these receptors were

determined in early studies to reside in the electrostatic properties of 5-HT

ligands, such as those expressed in the molecular electrostatic potential (MEP)

they generate (Weinstein et al. 1979, 1981a). The directionality and the shape

of the MEP, in its relation to the positively charged end of the side chain of 5-HT

congeners, were shown to be predictive of the relative affinities of these

compounds as well as of other classes of compounds, including fused ring

structures derived from tryptamine and ergoline derivatives (Weinstein et al.

1987). Experimental testing of compounds designed to probe the spatial

relationship among the various molecular determinants for recognition in each

molecule showed (Mazurek et al. 1984) that the molecular determinants for 5-

HT-like recognition have to be assembled in a specific geometric template. This

template was defined from the properties of the more rigid Iigands to make it

predictive of the activity ranking of new compounds (Weinstein et al. 1979,

1981a).

Topological considerations of the relations between the molecular determinants

for ligand recognition at the receptor (i.e., the recognition template) have gained

in importance with the recent discoveries of sequence similarities between the

genes encoding various subtypes of 5-HT receptors as well as ß-adrenergic

receptors. These new findings (Fargin et al. 1988; Julius et al. 1988; Strader et

al. 1989) show that the receptor proteins are likely to include anionic binding

sites for the cationic side chains of the natural ligands that are similar or even

identical (e.g., the conserved Asp observed in 5-HT and ß2

-adrenergic receptor

sequences). However, the recognition sites in the receptors most likely will

discriminate between the ligands on the basis of the topology of their other

recognition elements. Studies of this type of topology (Weinstein et al. 1981a;

Mazurek et al. 1984) must be continued in the context of stearic probing of the

ligand orientation in the receptor recognition site of structural models of the

authentic receptors (see below).

To be believable and useful, the proposed molecular determinants for

recognition and the specific requirements for the orientation of ligands at the

receptor (Weinstein et al. 1981a, 1987) must be consistent with chemical

information and the principles of chemical reactivity. Computational simulations

based on quantum mechanical methods provide excellent means to test the

validity of such a reactivity characteristic. For example, an electrostatic

orientation vector has been defined that describes an optimal 5-HT-like

25
orientation of the electrostatic potential of any ligand designed to mimic 5-HT at

the receptor (Weinstein et al. 1978, 1979) and has been tested as to whether it

determines the mode of interaction of the molecules with compatible reactants.

Because the nature of the recognition elements proposed for the 5-HT

congeners and the related compounds was primarily electrostatic (including

polarization), chemical intuition suggested the choice of stacking as a likely form

of interaction. Experimental data pointed to stacking complexes with

imidazolium cation as a specific model (Shinitzky and Katchalski 1968). Using

a stacking model of interaction between imidazolium and a large number of 5-

HT congeners, the computational simulation of complexation revealed the clear

energetic preference for specific mutual orientations in the stacking complexes,

thus explaining the success of criteria based on the shape of the MEP and the

orientation vector defined from it (Weinstein et al. 1981b). However, the

quantum mechanical simulations of the interactions between the various 5-HT

congeners and the model recognition site provided more than a validation of the

reactivity criteria that were used as molecular determinants (Weinstein et al.

1978, 1981b). They also yielded valuable insight into the consequences of

ligand-receptor complexation. Rigorous evaluation of these consequences in

terms of energy and structure lead (see below) to the identification of molecular

determinants for receptor activation and to criteria for design of agonists.

Recognition Elements at 5-HT2 Sites

Current evidence shows that the 5-HT1A and the 5-HT2 receptors are different

protein molecules. The effector mechanisms associated with each receptor are

also different. The 5-HT1A receptor modulates adenylate cyclase activity in the

brain (Shenker et al. 1987; DeVivo and Maayani 1986), whereas the 5-HT2

receptor stimulates phosphoinositide turnover (Sanders-Bush 1988). The

amino acid sequences of the 5-HT1A and 5-HT2 receptors point to significant

differences in specific regions (Hartig 1989) suggesting that different

mechanisms might be involved with the recognition process at the two

receptors. Binding studies support this idea: 8-OH-DPAT has a high affinity

(KD=1.7nM) for 5-HT1A sites but a low affinity (KD=7,100 nM) for 5-HT2 sites. In

contrast, ketanserin has a high affinity (KD=1.4 nM) for 5-HT2 sites but a low

affinity (KD=1,900 nM) for 5-HT1A sites. Serotonin has a high affinity (KD=2.9 nM

for the 5-HT1A receptor sites and a low affinity (KD=2,950 nM) for 5-HT2. We

have begun to explore the differences between the recognition processes at the

two receptors by comparing the determinants for recognition at the 5-HT2

receptor to those at the 5-HT1A receptor modeled by the imidazolium cation in

our previous work (see section above and references therein). To this end, we

explored the interaction of 5-HT and 6-HT with an indole molecule, which

represents a possible tryptophan residue, as the ligand-recognition site in the 5-

HT2 receptor.

26
The energy of interaction (ESCAN) between the indole molecule, modeling the 5-

HT2 recognition site, and 5-HT or 6-HT was scanned over an entire surface by

means of an interaction potential summing the electrostatic and dispersion

energies of interaction for a given configuration of ligand-indole dimer

ESCAN=EQQ+EDISP, where EQQ designates the electrostatic component of the

energy and EDISP the dispersion component energy. The electrostatic

interaction energy was calculated as described before (Weinstein et al. 1981b)

with a monopole-monopole approximation using atomic Mulliken charges

obtained from a self-consistent field calculation with an LP-3G basis set (Topiol

and Osman 1980). The dispersion energy was calculated from the interaction

of bond polarizabilities according to the method of Claverie (1978).

The scan of the interaction surface of indole with 5-HT is different from that with

6-HT (Rubenstein and Osman, in press). Each map of the interaction energy as

a function of the mutual positions of the ligand (5-HT or 6-HT) and the

recognition site (indole) is characterized by a region of weak interaction that

spans the indole ring and the hydroxyl group. The difference in the positions of

the OH substitution in the two ligands leads to a large difference in the

character of the contour maps. When the scanning molecule is close to the

oxygen atom, the magnitude of ESCAN is small. As a result of the pronounced

effect of the oxygen atom on the shape of the contour map, the position of a

local minimum in the 5-HT scan corresponds to a position of weak interaction in

6-HT. For this minimum In the 5-HT scan, the value of ESCAN is -7.39 kcal/mol at

an orientation angle of 260°, whereas for the same position in the 6-HT scan,

the value of ESCAN is -1.61 kcal/mol at a similar orientation angle of 290°. This

difference of 5.78 kcal/mol in the interaction energy comes primarily from the

electrostatic interaction. For 5-HT at this position, EQQ is -3.72 kcal/mol and

EDISP is -3.67 kcal/mol. The corresponding values for the 6-HT are +2.45 and

-4.06, respectively. Thus, the difference in EQQ is responsible for the selectivity

demonstrated by the model for a neutral recognition site in the receptor. If one

assumes that the interaction geometry of 5-HT relative to the recognition site is

optimal at the local minimum identified by the scan, then it corresponds In this

recognition model to the high-affinity binding configuration of 5-HT at the 5-HT2

receptor. Based on the much lower interaction energy of 6-HT at this position,

the latter ligand would be expected to have a much lower affinity for the 5-HT2

receptor because it will have an unfavorable electrostatic interaction with the

receptor site. Experimental measurements show a large difference in the

affinities of 5-HT and 6-HT for the 5-HT2 receptor (250 nM vs. >10,000 nM in

the isolated rabbit aorta (Clancy and Maayani 1985).

The scanning position that most clearly distinguishes between 5-HT and 6-HT

was selected for more detailed investigations of the variation in scan energies

with the orientation angle (Rubenstein and Osman, in press). These showed

27
that the magnitude of EDISP is generally greater than that of EQQ and that the

variations of these components of the interaction energy are almost exactly outof-phase. EQQ varies over a range of approximately 4.8 kcal/mol, whereas EDISP

varies only over a range of approximately 1.5 kcal/mol. Consequently, the

electrostatic interaction determines the preferred orientation and establishes a

molecular correlate of selectivity, whereas the dispersion energy provides the

major contribution to the stabilization of the complex (i.e., a major component of

ligand affinity; ESCF is -2.70 kcal/mol, whereas the EDISP is -3.67 kcal/mol). This

is in clear contrast to the results obtained from the model recognition site of the

5-HT1A receptor—charged imidazolium/the proton-transfer model (Osman et al.

1987)—for which the preferred orientation and the major component of

stabilization were electrostatic.

The charge redistribution upon formation of the recognition complex, calculated

by integration In planes parallel to the molecules in the complex in a manner

described earlier in our publications (Weinstein et al. 1978), shows a depletion

of electron density midway between the indole planes. This is attributable to

electron repulsion between the molecules. Simultaneously, the electrons in

each molecule are polarized in a direction perpendicular to the indole plane, so

that the negative end of each induced dipole points toward the region between

the planes. The electron density redistribution in the 5-HT/indole complex

contrasts sharply with that in the 5-HT/imidazolium cation complex (i.e., the 5-

HT1A recognition model), which we reported previously (Weinstein et al. 1978).

In the latter case, 5-HT was more extensively polarized (toward the

imidazolium), and the imidazolium was slightly polarized away from the 5-HT.

In the imidazolium complex, the 5-HT was polarized nearly eight times more

than in the complex with indole. The polarization pattern in the 5-HT/

imidazolium complex was shown to be characteristic of a strong electrostatic

interaction; in the complex with indole, the electrostatic contribution to the

stabilization is much less important.

Assessment of the roles that receptor-recognition models (indole for 5-HT2 and

imidazolium for 5-HT1A) play in the interactions of ligands at 5-HT receptors

requires additional experimental information about the structures of the receptor

proteins. At the present stage, models of the kind used in the work on 5-HT1A

(see below) can help explore whether the demonstrated selectivity of different

drugs toward the known 5-HT receptors can be correlated with the

discriminating properties of the models. The different mechanisms that are

responsible for affinity in the two models—dispersion in the neutral model and

electrostatics In the charged model—illustrate the possible basis for specificity

of ligands toward the various 5-HT receptors. Such differences can be used in

probing the validity of the models (e.g., by simulating interactions with ligands

designed to test the ability of the models to discriminate specificities for the

28
different receptor models and by testing the ability to predict ligand selectivity

toward specific receptor sites). Once proven to have predictive value, the

models can serve as direct guides in the design of new selective ligands.

AN ACTIVATION MECHANISM OF A 5-HT1A RECEPTOR

The computational simulation of the recognition complex between imidazolium

and 5-HT congeners led to the suggestion that interaction with the ligand could

induce the imidazolium to donate a proton to an acceptor (Osman et al. 1985).

The mechanism was simulated computationally with quantum mechanical

methods and was found to constitute a plausible primary event in the activation

of a 5-HT receptor (Osman et al. 1987). The simulations revealed the

mechanism by which the binding of the ligand to the receptor model lowered the

barrier for the transfer of the proton from imidazolium to an acceptor and

increased the energetic driving force for the process (i.e., the energy difference

between the reactants and the products). More importantly, these quantum

mechanical simulations pointed to the properties that made the model capable

of discriminating between agonists (receptor activators) and antagonists

(receptor blockers). However, because the electrostatic field generated by the

ligand was shown to be a crucial factor in the activation and because of specific

steric requirements for the mutual orientation of the recognition site and the

ligand, the activation model was expected to be affected by its environment in

the receptor. The exploration of this effect required the simulation of the

activation process inside the protein environment.

The Receptor Activation Mechanism in a Protein Environment

Following the heuristic strategy (figure 1) (Weinstein and Osman 1989b), the

lack of three-dimensional structure for a receptor makes it necessary to identify

a suitable protein to explore the effect of an environment on the activation

mechanism. Actinidin, a thiol proteinase for which the structure is known from

x-ray crystallography (Baker 1980; Baker and Drenth 1987) and is available in

the Protein Data Bank (Bernstein et al. 1977), was selected for this heuristic

study. This protein was chosen because it contains an appropriate

juxtaposition of the groups that form the proton transfer complex proposed for

the activation mechanism (Osman et al. 1985, 1987) and because it also

contains an intrinsic model for an indole-derivative ligand that can be mutated to

simulate known and putative ligands (figure 2). One possible proton transfer

system in actinidin consists of His-162 hydrogen bonded to Cys-25 through

ND1; another consists of Asn-182 hydrogen bonded to NE2 of His-162. The

indole side chain of Trp-184, which can mimic ligands that are 5-HT derivatives,

is in close proximity to this system and is aligned in a nearly stacking geometry

with the imidazole ring of His-162 (figure 2). The structure of the protein is well

29
FIGURE 2. Proposed folding model for 5-HT receptor sequences (fop part of

the figure), taken from Hartig (1989), and the -carbon chain of

actinidin, our receptor model protein (in the lower part of the

figure). The proton transfer system in the receptor recognition

model in actinidin consists of His-162 hydrogen bonded to Cys-25

through ND1 and of Asn-182 hydrogen bonded to NE2 of His-162.

The indole side chain of Trp-184, which can mimic ligands that

are 5-HT derivatives, is in close proximity to this system and is

30
aligned in a nearly stacking geometry with the imidazole ring of

His- 162. The side chains of these residues are outlined in the

figure over the -carbon structure of actinidin. As described in

the text, the -helices can modulate the activation mechanism

simulated inside the protein. Therefore, it is interesting to note

that the tentative model of the folding of the 5-HT2 receptor—to

which we added the indication of the residues specific to the 5-

HT1A receptor and their location in the otherwise highly

homologous sequence of the 5-HT2 receptor—places the putative

binding sites so that they are surrounded by the transmembranal

helices. The same residues considered in the heuristic model to

be involved in the proton transfer-based activation model explored

inside actinidin are present in a favorable juxtaposition in the

folding model shown in the top part of the figure. The His and

Asn residues identified in the figure are specific to the 5-HT1A

sequence and are not present in the other 5-HT receptor

sequences; they flank a Cys residue common to the other

sequences and are close to the Asp considered to be involved

with the recognition of the cationic side chain of neurotransmitters

(Strader et al. 1989 and text).

characterized and contains the same elements of secondary and tertiary

structure that have been proposed for a variety of membrane proteins, including

the 5-HT receptors (Hartig 1989) (figure 2). The general basis for the heuristic

approach to simulate the receptor activation mechanism inside this protein

model is the premise that the structural elements (e.g., helices, ß-sheets), which

are conserved across different proteins and have similar properties (e.g.,

electrostatic), also conserve the role they would play in intramolecular

processes. It must be emphasized, however, that the proton transfer that

simulates the activation mechanism is in a direction opposite to that considered

to occur in the enzymatic process of thiol proteases.

Given the nature of the proposed activation mechanism, the strong effect of the

protein on the simulated activation process would be expected to come from the

electrostatic field it generates in the vicinity of the proton transfer complex.

Such effects can be calculated in several variants of the semiclassical

approaches combining quantum mechanical methods and classical

electrostatics (Dijkman et al. 1989; Mercier et al. 1988b). In this approach, the

entire system is divided into a domain described by quantum mechanics

(termed “the quantum motif”) and a domain described with classical

electrostatics. An iterative perturbation scheme developed recently (Mercier et

al. 1989) also includes terms representing the polarization of the protein

31
induced by the quantum motif and the polarization of the quantum motif induced

by the polarized protein (Mercier et al. 1988b). The energy and charge

distribution of the quantum motif in the classical electrostatic field can be

calculated following either the direct reaction field approach (Dijkman et al. 1989

and references therein) or within the perturbation scheme (Mercier et al. 1989),

which is based on the electron group formalism of McWeeny and Sutcliffe

(1969).

Results from such calculations (Mercier et al. 1988b, 1989; Weinstein et al.

1988; Weinstein and Osman 1989a) showed that the six -helices in actinidin

(figure 2 in Mercier et al. 1988b) contribute differently to the energy of proton

transfer between His-162 and the thiol side chain of Cys-25. For example, the

interaction with the largest helix, A1, acts in opposition to the proton transfer

through the effect of a large helix dipole, whereas helix A3 affects the proton

transfer in nearly equal proportions through the field of its charged residues

(which favors the process) and its helix dipole (which opposes it). The effect of

the other helices, A2, A4, and A5, reflects mainly the contribution from their

charged residues; but when these residues are eliminated in computersimulated mutations, the effects of their helix dipoles are revealed (Mercier et al.

1988b). These significant effects of -helical structure indicate the essential

role that the helical motifs predicted for the structures of the membrane-bound

receptors (figure 2) could play in receptor mechanisms.

The other possible proton transfer model in actinidin also involves His-162 from

which the proton can move to Asn-182. This proton transfer process shows

greater sensitivity to the ß-sheet structures in the protein (Weinstein et al. 1988;

Weinstein and Osman 1989a), but neither the His-162/Cys-25 nor the His-162/

Asn-182 complex is strongly affected by the near neighbors surrounding them.

When the effect of the entire protein structure is calculated, the protein

environment is found to oppose the transfer of a proton in either the His-162/

Cys-25 or the His-162/Asn-182 systems. Yet it became clear that specific

contributions from secondary elements such as the helices, or from specific

charged residues, can modulate the magnitude of this effect. It is therefore

interesting to note that a tentative model of the folding of the 5-HT2

 receptor

(Hartig 1989) places the putative binding sites so that it is surrounded by the

transmembranal helices. In particular, a speculative model (figure 2) would

indicate that the same residues considered to be involved in the proton transferbased activation model explored inside actinidin are present in a favorable

juxtaposition in the folding model shown in figure 2. Quite intriguing is the fact

that the His and Asn residues highlighted in the figure are specific to the 5-HT1A

sequence and are not present in the other 5-HT receptor sequences discussed

recently (Hartig 1989). They flank a Cys residue common to the other

sequences and are close to the Asp considered to be involved with the

32
recognition of the anionic side chain (Strader et al. 1989). This situation could

be fortuitous, but it deserves and will receive additional attention in relation to

our models of recognition and activation of the 5-HT receptors, especially in

collaborative studies with molecular biologists interested in using selected

mutations to probe the residues essential for receptor function.

The finding that the protein structure acts to reduce the probability of the proton

transfer supports the use of this protein as a heuristic model for receptor

activation, for it shows how the protein can prevent a spontaneous triggering of

the receptor activation mechanism. This modulation of the barrier, and the

concomitant increase in the energy drive for the reaction (i.e., the difference in

energy between the system before and after the proton transfer), is achieved

through the difference in the interaction of the proton acceptor, and of the

proton donor, with the protein. The difference is attributable to the change in

the electronic structure of the quantum motif as a result of the movement of the

proton.

More importantly, the calculations described below showed how the barrier to

proton transfer may be overcome if the charge distribution of the proton transfer

complex is altered by interaction with a ligand. Because not all the ligands will

affect equally the electronic structure of the proton transfer complex, they will

have different effects on the height of the barrier and the driving energy. On

this basis, they will be expected to exhibit different efficacies in activating the

receptor (see below).

Role of the Ligand In the Activation lnside a Protein: An Expression of

Pharmacological Efficacy

To probe the effect of the ligand on the proton transfer model of receptor

activation inside the protein environment, we turned to the His-162/Asn-182

complex because it interacts more closely with Trp-184, which represents the

ligand. Like the His-162/Cys-25, the His-162/Asn-182 complex also is not much

affected by the near neighbors in the active site. When the entire protein

structure is considered, the effect of the protein environment again is found to

oppose the transfer of a proton in the His-162/Asn-182 system, as in the His162/Cys-25 complex. Yet it became clear from calculations (Weinstein et al.

1988; Weinstein and Osman 1989a) that the ligands—simulated by the side

chain of Trp-184 or by other structures replacing that residue with side chains

representing compounds with known activities at the 5-HT1A receptor—will lower

the energy barrier of the proton transfer process. The ligands shown in table 1

lower the energy barrier Barrier) for proton transfer and increase the driving

force Minima) for this process. (For descriptions of the electronic

mechanism involved and the method of calculation, see Mercier and colleagues

33
1988b, 1989; Weinstein and coworkers 1988.) As shown in table 1, the effect

of the listed ligands follows, within each structural group, a rank order that is

compatible with the pharmacological data on the intrinsic activity of these

compounds. (Note that these results of the simulation of the receptor activation

process do not reflect the affinities of the compounds.) The ligand-protein

interactions were calculated here without the required optimization of the

orientation between the ligand and the recognition (activation) site (Osman et al.

1987). Even in the common orientation, the calculations show that the ligands

do not affect equally the electronic structure of the proton transfer complex, so

that they produce different effects on the height of the barrier and on the driving

force.

TABLE 1. The effect of 5-HT agonists on the barrier and driving force for the

proton transfer from His-162 to Asn-182 inside actinidin

Liganda E Barrierb E Minimab

5-OH TRYP -2.5 -4.4

TRYP -2.4 -4.2

4-OH TRYP -2.1 -3.6

6-OH TRYP -1.4 -2.5

7-OH TRYP -1.0 -1.8

4,5-MDOX TRYP -1.7 -3.4

5,6-MDOX TRYP -1.6 -2.8

5-CONH2 TRYP -1.5 -2.5

a

The indole portion of the ligands is superimposed on the indole of Trp-184.

b

In kcal/mol

As with the effect of the total protein environment on the His-162/Cys-25

complex (Mercier et al. 1988a) and on the His-162/Asn-182 pair (Weinstein and

Osman 1989a), the lowering of the barrier for the His-162/Asn-182 complex by

the ligands is determined by their effect on the proton donor/acceptor pair and

not by an effect on the moving proton (Weinstein et al. 1988; Weinstein and

Osman 1989a). This interaction changes with the rearrangement of the

electronic structures of the donor and acceptor moieties. It follows that the

evaluation of the effect of both the protein and the ligands on the barrier is

dependent on the adequate representation of the changes that occur in the

electronic structure of the complex during the process of proton transfer.

34
Taken together, the results show that an exploration of the determinants for the

formation of a ligand-receptor complex inside the protein produces information

concerning the elements of recognition within the constraints of a protein

structure, as well as the conditions necessary to overcome the barrier and to

trigger the proton transfer as a result of the interaction with the recognition site.

A mechanistic picture emerges in which receptor occupancy by a partial agonist

does not result in the proton transfer (the trigger is not activated because the

barrier is still too high or because the driving energy is not negative enough; see

table 1), so that the conformational change required for interaction with the

effector (e.g., G-protein) does not occur. Thus, although occupied, the receptor

is not activated and does not produce a response. It is possible to envision a

mechanism in which the kinetics of the proton transfer is the rate-limiting

element, so that the height of the barrier (and the ability of various ligands to

reduce it) determines efficacy. However, at this point we have not distinguished

this criterion from the one that would be established if the conformational

change induced in the receptor structure as a result of the proton transfer (a

change required to increase the affinity of the receptor-effector complex) is the

rate-determining step. in the latter case, the energy drive (i.e., E Minima in

table 1) would be the discriminant criterion for efficacy. Results in table 1

indicate that at this stage the rank order predicted by both criteria would be the

same for the ligands we have considered at this first level of computational

simulation.

The receptor activation model we have simulated inside the protein clearly is

predictive of a relative pharmacological efficacy. As with the mechanistic

picture of partial agonism on ß-adrenergic receptors that emerges from

experimental results (Benovic et al. 1988), the present model still must

consider the possibility that partial agonism also may result from a partial

rearrangement of the structure that would affect the rate of the formation of

receptor-effector complexes due to an enhanced rate of reversal of the

activated state. This situation also is reflected in the effect of ligand-binding on

the energetics of the proton transfer mechanism. A refinement of the proposed

mechanistic descriptions of partial agonism will require the computational

simulation and analysis of the protein dynamics related to the binding and

activation mechanism, which represents a major challenge for the future of such

simulations of receptor mechanisms (see Conclusion).

It thus becomes clear how the exploration of the determinants for the formation

of a ligand-receptor complex inside the protein produces information concerning

the elements of recognition within the constraints of a protein structure, as well

as the conditions necessary to trigger a response. As described earlier

(Weinstein et al. 1987), information concerning elements of recognition is

essential to understand receptor specificity of agonists and antagonists, while

35
insight into the activation mechanism describes discriminant molecular

determinants of agonists (Weinstein and Osman 1989b, 1989a).

CONCLUSION: IMPLICATIONS FOR RECEPTOR CLASSlFlCATlON AND

DISCRIMINANT DRUG DESIGN

The investigatlon of the binding event between the drug-receptor complex and

an effector is severely limited as an approach to the elucidation of the molecular

mechanism of receptor function by the lack of a three-dimensional structure of a

receptor. However, the elucidation of molecular events that can relate the

binding of a ligand to subsequent molecular processes leading to receptor

activation is helped by the heuristic approach that we developed (figure 1). The

molecular events that ensue as a consequence of the binding of the drug to the

receptor constitute the trigger for its activation. The simulations can reveal their

relation to efficacy by analyzing the changes induced in the surroundings of the

recognition site of the receptor by its interaction with the agonist. Identifying

these local consequences of ligand-receptor interaction, as has been done in

our work on the 5-HT1A receptor, has led to the definition of molecular correlates

of efficacy. Such correlates depend on the mechanistic hypothesis concerning

the relationship between the interaction of the drug with the receptor and the

manner in which the response is triggered. The mechanistic description of

pharmacological efficacy that emerged from the simulation of the receptor

mechanism according to this hypothesis is based on a quantitative scale,

relating the changes that the ligand produces in the triggering mechanism to the

structure of that ligand.

The mechanistic hypothesis and its corollaries can be exploited as a solid basis

for the design of ligands with predetermined pharmacological properties. The

designs can be tested through simulations with the receptor models to refine the

structures according to practical constraints imposed by chemical synthesis.

Our findings also showed how the approach is conducive (1) to criteria that can

be used to discriminate among such receptor subtypes and (2) to their

classification according to mechanistic considerations. These criteria are based

on differences in the physicochemical nature of the forces that determine the

ligand-receptor interactions and their mechanistic consequences and

complement our newly gained insight into receptor mechanisms at the

molecular level.

As information on the protein sequences of the authentic 5-HT receptors is

rapidly accumulating (Weinstein and Osman 1989b; Fargin et al. 1988; Julius et

al. 1988; Strader et al. 1989; Raymond et al. 1989), the exploration of the

heuristic approach reviewed here becomes more directly pertinent to the

specific receptor system and more desirable. However, it is important to note

36
that a full implementation of this strategy taxes the extreme frontiers of current

theoretical methodology and computational power, because it requires

simulations of the electronic mechanisms inside proteins and the dynamic

changes in the structures and environments of complex macromolecular

systems.

The latter is required to obtain a mechanistic picture of the part of the activation

process that is responsible for the propagation of the triggering event into the

rest of the protein structure. It is reasonable to expect that an understanding of

the mechanism of activation of the receptor for interaction with the effector

system will require discrete molecular representations of the specific structural

rearrangements that cause an increase in the probability of forming the

receptor-effector complex. Such a representation will constitute a molecular

description of the functional role played by the ligand-occupied receptor in the

generation of the response to ligand-binding and may lead to the design of

therapeutic agents of a new kind, that is, those addressing directly the receptoreffector coupling mechanism.

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ACKNOWLEDGMENTS

The various computations for this study were performed on the supercomputer

systems at the Pittsburgh Supercomputer Center and the Cornell National

Supercomputer Facility—both of which are sponsored by the National Science

Foundation—as well as at the Advanced Scientific Computing Laboratory at the

Frederick Cancer Research Facility of the National Cancer institute (Laboratory

for Mathematical Biology). The authors acknowledge these resources and the

generous allocations of computer time at the University Computer Center of the

City University of New York. This work was supported in part by National

Institute on Drug Abuse grant DA-01875 and Research Scientist Development

Award DA-00060 to Harel Weinstein.

AUTHORS

Roman Osman, Ph.D.

Professor

Departments of Physiology and Biophysics and of Pharmacology

Harel Weinstein, D.Sc.

Professor and Chairman

Department of Physiology and Biophysics

Professor

Department of Pharmacology

41
Mail Box 1218

Mount Sinai School of Medicine of the City University of New York

New York, NY 10029-6574

42
Computer-Aided Drug Design for the

Benzodiazepine Receptor Site

Gilda H. Loew, Hugo O. Villar, Waymond Jung, and hf. Frances

Davies

INTRODUCTION

Benzodiazepine (BDZ) receptor ligands are widely used as therapeutic agents

in the treatment of anxiety and related emotional disorders, insomnia, and

epilepsies and as a premeditation in anesthesia. All of their uses result from a

complex and challenging pharmacology. The first characteristic of the

pharmacology of these drugs is that the activation of the BDZ receptor has

several behavioral correlates, including muscle relaxation and sedative/

hypnotic, anticonvulsant, amnestic, hyperphagic, and anxiolytic effects. The

second unique trait of the BDZ receptor pharmacology is the discovery that

some chemical agents could induce functional effects opposite to those of the

BDZs by binding to the same receptor site (Poic et al. 1982). Hence, the BDZ

receptor ligands are categorized as agonists, inverse agonists, and antagonists.

Although agonists have the pharmacological profiles indicated above (i.e.,

similar to diazepam), inverse agonists induce opposite behavioral effects to

those of diazepam. Thus, the pharmacological profile of inverse agonists

includes convulsant or proconvulsant, anorectic, anxiogenenic, and procognitive

actions. Antagonists are able to block equally the action of agonists and

inverse agonists. A third characteristic of these drugs is the number of diverse

chemical families that can activate or block the activation of the receptor,

among which BDZ, ß-carbolines, imidazobenzodiazepines, pyrazoloquinolines,

imidazopyridines, imidazopyrimidines, hydroxiquinolines, and

triazoiopyridazines are the most thoroughly studied.

The BDZ receptor is part of the GABAA receptor /Cl ionophore supercomplex

(Schofield et al. 1988; Stephenson 1988). Although initial studies seemed to

indicate that BDZ binds to the -subunit and that GABA binds to the ß-subunit

of this complex, recently it has been proposed that the ß-, and -subunits

contribute to the formation of a functional BDZ site (Pritchett et al. 1989). These

three subunits, as well as variants of them, recently have been cloned and

sequenced. There is evidence that some differences in the subunits may result

43
in receptors possessing slightly different pharmacologies (Pritchett et al. 1989),

although the importance of these diversities to in vivo behavioral endpoints still

is undetermined. As this relationship becomes clearer, one strategy for

development of BDZ receptor ligands with a subset of behavioral properties

would be to design analogs with high affinity for only one receptor subtype,

using the known receptor sequence information and a knowledge of the

distribution of each subunit within the brain.

Ligands of the BDZ receptor also can differ in their ability to activate the

receptor; some have been shown to be partial agonists or partial inverse

agonists (Petersen et al. 1984). It has been hypothesized that less total

receptor activation is required to achieve a complete anxiolytic effect in

comparison to the receptor activation needed to produce sedation or muscle

relaxation (Gardner 1989). If this is the case, then it is possible that a partial

agonist for these endpoints would be a better anxiolytic therapeutic agent than

the traditionally sought full agonist.

One of the major areas of interest in this family of drugs is the design of

compounds capable of inducing only one pharmacological action, devoid of

secondary actions, through the GABAA/BDZ receptor. Therefore, a rational

approach to understanding the mechanisms through which each response is

elicited becomes essential. To this end, we have been using the techniques of

computational chemistry, together with in vivo and in vitro pharmacology, to

identify stereoelectronic modulators of receptor recognition and activation to

specific endpoints. The experimental studies have been carried out to ensure

consistency of the data used as the basis for identifying plausible

stereoelectronic modulators of receptor recognition and activation.

The innovative iterative approach was used to characterize this receptor and

the design of new analogs, schematized in figure 1. In this approach, an initial

set of in vivo and in vitro experimental data is generated, which provides the

experimental observations on which a molecular mechanism for receptor

recognition and activation is based. In this way, three-dimensional (3D)

structural and electronic requirements can be developed. Once a working

hypothesis is generated, it is used to identify and design new probes for the

characterization of the recognition or activation processes. This step has a dual

purpose: It provides a further test of the working hypotheses and also can lead

to the identification of clinically promising new analogs not heretofore

associated with the GABAA/BDZ receptor. The derivation of the hypotheses

and the design of new analogs based on it are carried out using the techniques

of computational chemistry.

To profit fully from this scheme, the design and selection of new plausible

ligands are essential, should be unbiased by subjective preconceptions, and

44
FIGURE 1. Iterative approach to the selection of new therapeutically useful

BDZ receptor ligands

45
should cover most chemical families—the next step In this approach to

computer-aided drug design (CADD). Promising new analogs are selected in

two qualitatively different ways, both using the stereoelectronic properties

postulated as modulators of receptor recognition and activation. In the first

approach, these criteria are used as the basis for a 3D search of a database of

known compounds. This automated, 3D search strategy is the second

computational component in the three-component approach to CADD. This

particular tool permits the retrieval, from a pharmacological database containing

3D structural information, all compounds fulfilling user-specified 3D

stereoelectronic requirements that were developed using computational

chemistry. Another way of obtaining new compounds is to use the

stereoelectronic criteria identified as the basis for rational modification of known

analogs, which then are proposed for synthesis. In either case, whether a

compound has been selected from a database or by rational modification of

known analogs, a complete theoretical analysis should be performed. This

theoretical analysis should be done to verify that the analogs proposed for

further testing not only satisfy the steric criteria but also fulfill the electronic

criteria for binding and activity.

Successful candidates then either can be acquired, if obtained from the

database, or synthesized and subjected to further pharmacological testing.

This step also has the dual function of further testing working hypotheses and

possibly leading to useful new therapeutic agents. The first pharmacological

evaluation is to determine if the therapeutic agents bind to the receptor as

expected. If not, they can be used to refine the criteria for receptor recognition.

For each compound that has affinity for the receptor, several endpoints for its

activation then can be determined. For the BDZ ligands, these behavioral

endpoints include anticonvulsant, hyperphagic, and anxioiytic profiles. These

responses are used because they allow characterization not only of agonist and

antagonist but also of inverse agonist activity. The in vitro endpoints include

electrophysiological effects on chloride ion channel conductance, because BDZ

ligands bind to and modulate the effect of GABA on its chloride ion channel

receptor. The endpoints also include the modulation of these ligands on the

effect of GABA in model tissues.

All of these pharmacological studies combined should allow a classification of

each new compound as agonist, antagonist, or inverse agonist and provide a

measure of their efficacy. If the original working hypothesis proves correct and

the compounds behave as originally proposed, the procedure should lead to

new potentially useful analogs, which should be tested further for detrimental

effects (such as alcohol and barbiturates potentiation). Conversely, if a

particular compound fails to elicit the predicted pharmacological actions, the

46
new information should be added to the initial pool of data to refine the existing

model or help in producing an entirely new hypothesis.

The stereoelectronic properties of ligands identified as important for recognition

and activation also can be used to further probe, by complementarity, the

structural characteristics of the receptor-binding site. We have developed a

program (RECEPTORSEARCH) that searches the database of proteins with

known structure for those with binding site motifs that satisfy these

requirements. These proteins can serve as heuristic models for the receptor

and allow the explicit characterization of drug-receptor interactions, as well as

an evaluation of the role of the protein in them. Thus, this iterative,

interdisciplinary approach to rational drug design embodies three closely related

computational components: the techniques of theoretical chemistry, 3D

searching strategies for ligands, and complementary 3D searching strategies for

their macromolecular receptors.

The particular example of this interdisciplinary, three-component computational

approach described in this chapter is based on experimental data for the

anticonvulsant and binding studies of the BDZ receptor ligands generated in our

laboratory. Using these data, we have developed a working hypothesis for the

recognition and activation of the receptor in terms of electronic and 3D

structural requirements using the techniques of theoretical chemistry (Villar et

al. 1989). The development of such hypotheses, central to the approach

proposed, is described in the next section. The other two computational tools

we have used—3D searching strategies for potential BDZ ligands and for

heuristic receptors for them—have been applied for the first time to drugs of

abuse. Both techniques are described in the final two sections using the BDZ

receptor ligands as an example.

MOLECULAR DETERMINANTS OF BDZ RECEPTOR AFFINITIES AND

ANTICONVULSANT ACTIVITIES

We have determined convulsant activity profiles and receptor-binding affinities

for 15 compounds from five different chemical families that are known to bind to

the BDZ receptor (Villar et al. 1989). These compounds were evaluated to

obtain an initial set of consistent pharmacological data for modeling purposes.

The analogs selected belong to diverse chemical families; for each of those

families, compounds with different pharmacological profiles were included.

Their structures and profiles are shown in figure 2. The compounds were

studied using the MNDO/H semiempirical technique (Goldblum 1987) and

several properties were determined for each molecule.

47
FIGURE 2. Fifteen analogs that constituted the initial set of compounds to be

pharmacologically evaluated and modeled

48
Among the properties calculated and examined for their relevance were

polarization volumes and partition coefficients as an indication of the strength of

dispersion forces, as a measure of probability of stacking, and as a measure of

the extent of the hydrophobic interactions. These properties did not seem to

correlate with the experimental results for activation or recognition. In general,

ail compounds had large partition coefficients, indicating a highly lipophilic

binding site (Villar and Loew 1989).

Heats of protonation at competing sites of each analog also were calculated.

These quantities were used as a measure of the strength of the interaction of

different proton-accepting atoms in the drug with proton-donating receptor

subsites. The analysis of the results for the set of compounds chosen indicated

that there were at least two proton-accepting sites at an approximately constant

distance of 3.5Å for all analogs. Such consistency in the distance between the

two proton-accepting sites suggests that both sites could be involved in

receptor recognition. Further plausibility of this hypothesis is provided by the

observation that affinity is reduced greatly when one of the proton acceptors is

blocked or not present, as in the ß-carboline FG-7142, where the ß-N forms a

competing internal hydrogen bond.

A third feature common to all compounds in this initial set is the presence of a

highly lipophilic region. Whereas the two proton-accepting sites appear to

modulate recognition, the relative orientation of the most lipophilic region of

each compound with respect to these two sites seems to modulate activity. As

shown in figure 3, the angle formed by the two proton-accepting sites and the

lipophilic area clearly discriminates among agonists, antagonists, and inverse

agonists. The angle was found to be 140° to 150° for agonists, 105° to 110° for

antagonists, and 95° to 100° for inverse agonists. These three different sets of

values indicate that when anchored by two common recognition sites, the

aromatic rings of all agonists, antagonists, and inverse agonists in the diverse

chemical families would occupy unique regions of the receptor according to

their pharmacological profile. Thus, the different spatial positions occupied by

the lipophilic ring appear to modulate the activation mechanism. This aromatic

lipophilic ring wmmon to all high-affinity analogs could participate in stacking

interactions, with an aromatic side-chain at the receptor-binding site. The

nature and consequences of this interaction could be a determining feature in

the pharmacological action of the drug.

These criteria identified for BDZ ligand receptor recognition and activation

imply, by complementarity, that the receptor-binding site has two protondonating amino acids and an aromatic residue in particular spatial orientation.

In addition, these results imply a sterically inaccessible region of the receptor.

No high-affinity binder to this site, in the classes studied, has lipophilic groups

49
FIGURE 3. Position of the most lipophilic ring relative to the two most

favorable proton-accepting sires. The angle q is displayed for

flunitrazepam and ß-CCM as examples.

occupying areas of the receptor corresponding to values between 110° and

140° the orientation angle with respect to the two recognition sites. This gap

suggests the presence of a sterically inaccessible region of the receptor.

Thus far, our studies agree with our own and other previously published models

regarding BDZ receptor recognition (Loew et al. 1984, 1985; Codding and Muir

1985; Fryer et al. 1986; Tebib et al. 1987; Borea et al. 1987). There is

widespread agreement in implicating two proton-accepting sites in recognition,

but no previous study has characterized them for these diverse families.

Additional sites also could be involved in recognition (Alien et al. 1988)

although there is no compelling evidence for this idea. Our model also has

identified for the first time specific candidate modulators of activity—supporting

previous notions that interaction of the ligand with different regions of the

receptor somehow should be involved in the activation mechanisms for agonism

and inverse agonism. No previous model has explicitly defined semiquantitative

50
stereochemical requirements for both activation and recognition, as described in

the previous paragraph. However, the model obtained was based on certain

assumptions, and its validity is subject to them.

The first important assumption is that at physiological temperatures the ligands

studied are binding to either a single receptor subtype or to several similar ones

with equal affinity and that the anticonvulsant effect observed is elicited by

binding to such a site(s). The question of GABAA/BDZ receptor heterogeneity is

the subject of current intense pharmacological and molecular biological

investigations. Our own and previous receptor-binding studies at 0°C provide

strong evidence for receptor heterogeneity (Toll et al. 1984; Sieghart and

Karobath 1980; Braestrup and Nielsen 1981). It is interesting to note that

receptor-binding studies at higher temperatures consistently indicated that

receptor heterogeneity becomes undetectable at more physiologically relevant

temperatures (Gee and Yamamura 1982; Gee et al. 1984; Villar et al. 1989).

Because only one site was found at 25°C in our competitive binding studies, it

was assumed that all the compounds were acting through this site. If the further

pharmacological studies that are planned (which include additional analogs)

reveal the existence of GABAA/BDZ receptor heterogeneity at physiological

temperatures, the current model will be refined to include identification of criteria

of recognition and activation at each site. In an intensive effort, the techniques

of recombinant DNA are being applied actively to the GABAA/BDZ receptor and

have led to the cloning and sequencing of at least 10 variations of subunits that

currently are being expressed and tested for functionality in various

combinations (Levitan et al. 1988; Schofield et al. 1988). The information from

these efforts appears to be consistent with the need for three subunits to

produce a functional chloride ion channel that can be modulated by BDZs.

However, the evidence for either functionally significant heterogeneity or for the

minimum number and nature of the subunits needed is not conclusive.

Another assumption made is that. because no endogenous ligands for this site

have been characterized fully, no attempt was made to include its effects in our

studies. Current information in this matter is also inconclusive (Davis et al.

1985; Gardner 1989). If endogenous ligands eventually are identified, the

behavioral data should be reinterpreted to account for the interplay between the

administered drug and the endogenous ligand. The existence of these and

other possible reasons for the limitation of our current model is why an iterative

approach to the design of new drugs is important. The procedure outlined in

figure 1 makes optimum use of the information existing at any one time in the

study of receptor-ligand interactions and provides the means of making use of

new developments.

51
in the spirit of this iterative approach, we have estabilshed a set of

stereoelectronic requirements for binding and activation of the BDZ receptor.

As described in the next sections, these criteria have been used in the

identification and design of new analogs for pharmacological evaluation. The

new drugs are both suggested modifications of the existing families and more

innovative, entirely new classes that have been identified using recently

developed computational chemistry tools such as 3D searching strategies and

searches for heuristic models for the receptor as described below.

DESIGN OF BDZ RECEPTOR LIGANDS BASED ON 3D SEARCHING

The use of chemical databases is becoming standard in pharmacological and

chemical research, but so far their use has been limited mostly to the industrial

environment (Martin et al. 1988; Sheridan and Venkataraghavan 1987; Borman

1989; Sheridan et al. 1989). The defining feature of a chemical database is the

capability of storing and retrieving information based on a two-dimensional (2D)

chemical structure (connectivity) for all the entries. The 2D information ensures

that only one representation is associated with each entry. The information

stored constitutes the identifier (IDtype) for a given compound. This IDtype then

is used to recover all pharmacological and physicochemical information stored

as data types. When 3D structural information for each compound is included

as an additional data type, a 3D database is generated. The necessary 3D

structures could come from a variety of sources because they must be

generated in record numbers. Experimentally, techniques such as singlecrystal x-ray diffraction structures are widely used. There is also a rapidly

growing use of a computer program called CONCORD for the determination of

these structures. This program uses artificial intelligence and energyminimization techniques to produce structures of medium-size molecules in a

few seconds. The speed of this program for the determination of such

structures makes the generation of 3D databases (Borman 1989) a reasonable

endeavor.

The 3D structural information in a 3D chemical database could be used to

retrieve the stored structures for structure-activity relationship purposes or as a

starting point for quantum mechanical calculations. More creatively, a 3D

database could be searched to retrieve all compounds with given structural

features; that is, given 3D stereoelectronic requirements for a certain activity or

affinity at a given receptor, the information in the database could be searched to

retrieve all compounds that fulfill such requirements. The tool required for such

purpose is called a 3D searching algorithm.

Systems that combine 3D databases and 3D searching capabilities have been

described in the literature. The searching strategy could be different and even

52
could be based on different criteria such as shape-similarity algorithms. In

particular, we have been offered the use of the system developed under the

supervision of Dr. Yvonne Martin at Abbott Laboratories. This system consists

of the MENTHOR database (Martin et al. 1988) derived from the MedChem

software developed by DAYLIGHT information Systems, and a 3D searching

algorithm developed at Abbott called ALADDIN (Van Drie et al. 1989). The 3D

structures stored in the MENTHOR database were generated using the

CONCORD software. The molecular determinants described in the previous

section provide the necessary input for a 3D searching strategy.

The 3D searching can be used with two basic purposes: (1) selection of new

compounds that fulfill the requirements of the model but have never been tested

in relation to the binding site in question or (2) validation of the proposed model

pharmacophore.

The first purpose is straightforward. As a result of 3D searching in a reasonable

size database, new plausible probes for the characterization of the site could be

retrieved. These compounds then should undergo pharmacological screening.

The validation of a proposed model can be achieved by its success or failure in

(1) finding families of compounds known to bind to the specific receptor but not

originally included in the development of the model and (2) finding compounds

that fulfill the criteria but do not bind to the receptor.

In these studies, we have applied this automated capability for the first time to

drugs of abuse. A 3D search was performed on an extensive database of

known compounds using our stereoelectronic criteria for BDZ ligand-receptor

rewgnition and activation. Specifically, we have retrieved 200 compounds

using the criteria of 3.0 Å to 4.2 Å separation between two proton-acceptor

centers, an angle of 140° to 150° with a lipophilic aromatic ring for agonists, and

90° to 120° for antagonists and inverse agonists. Among the compounds

retrieved were triazoiam, alprazolam, and brotizoiam, all well-known agonists at

the BDZ receptor belonging to chemical families unrelated to the five initially

used in the derivation of the model. Furthermore, most of the 1, 4 BDZ and

additional compounds from the other families included in the study were

obtained as a result of the search. As a further test of our hypothesis, a

retrieval of compounds with disallowed angle values between 120° and 140o

also was made, resulting in the retrieval of some low-affinity binders.

Specifically, these were purine-like compounds, with angles between the two

proton acceptors and the lipophilic ring of 132° to 136°. That compounds only

with no or low affinity were found (if they contained iipophilic groups forming an

angle of 120° to 140° relative to the proton acceptors) reinforces the hypothesis

of a sterically hindered region in that area of the receptor. Other families of

53
compounds retrieved included known antibiotics, which could be ruled out easily

because of their highly hydrophilic nature.

Taken together, these findings clearly reinforce our working hypothesis. Hence,

this procedure affords an easy first step in the validation of hypothetical

requirements for high-affinity binding to a receptor, before starting the more

expensive and time-consuming stages of synthesis and evaluation of new

analogs. This type of validation procedure also provides an alternative to

extensive animal studies, greatly reducing the number of such studies needed

to develop a satisfactory model for drug-receptor interaction and activation.

Moreover, the large number of chemical families included in a database

decreases the possibility of an incorrect hypothesis resulting from a biased

initial set of compounds. The 3D-searching procedures used also allowed the

identification of six promising new families of compounds not yet considered to

be ligands for the BDZ/GABAA receptor. This process is applicable to any drugreceptor system, provided a well-considered hypothesis about the mechanism

of activation and recognition has been developed.

SEARCH FOR A HEURISTIC MODEL FOR DRUG-RECEPTOR

INTERACTION

The same criteria developed for ligand requirements for activation or recognition

at a receptor can be used, by complementarity, for the purpose of finding a

heuristic model for the receptor. The known crystal structures of proteins

(mainly soluble enzymes) and ligand-protein complexes could serve as models

for other biologically important proteins, including receptors. These models

could be used for explicit characterization of ligand-receptor interactions and

could help explain the role of the protein structure beyond the binding site in

both the recognition and activation processes (Weinstein 1987; Weinstein et al.

1985).

Because multiple subunits of the GABAA/BDZ receptor have been cloned and

sequenced, it also should be possible to attempt a completely different

approach to building a 3D structure for the binding site of the BDZ ligands. This

approach would use current biochemical and pharmacological information about

the position and nature of the binding site, as well as information on the

different subunits of other ligand-gated ion channel receptors. This information

would serve as a guide in the use of the diverse techniques of protein modeling

to obtain a verifiable description of the binding site. If validated, this approach

could provide a more realistic description of the actual binding site than the one

provided by a heuristic receptor model. However, the BDZ receptor ligands

require at least three receptor subunits for them to bind and modulate the

effects of GABA on the ion channel. This finding indicates that the problem of

54
modeling the site could involve consideration of more that the interaction of the

ligands with a single subunit of the receptor. In collaboration with Dr. Victor

Cockcroft (trained in the laboratory of Dr. Barnard), we have begun the first step

in such a study; Dr. Cockcroft studies the molecular biology and functionality of

the receptor. Specifically, we are beginning to construct and test candidate

BDZ-binding regions in the N-terminal extracellular regions of the -1 and -2

subunits of the GABAA receptor.

RECEPTORSEARCH can search the protein data bank (or any other data bank

of known structures of macromolecules) for structures of plausible heuristic

receptor models containing a binding site with user-specified criteria suitable for

any class of ligands. This searching procedure forms the third component of

the CADD approach. It complements the searching procedure, ALADDIN, used

to identify new ligands. ALADDIN searches a database of known drugs, trying

to find compounds with specific stereoelectronic requirements that are

postulated to be important for recognition and/or activation. In the

RECEPTORSEARCH program, we use complementarity criteria for the

receptor-binding site to search the protein data bank for macromolecules with

3D arrangements of functional groups that could lead to a favorable interaction

with the drug and thus serve as models for the binding site.

The features characterized by RECEPTORSEARCH are distances and

orientations among proton-donating or -accepting groups, as well as possible

centers for stacking, such as aromatic rings. In the case of centers with the

capability of docking by hydrogen bonding, the program also checks for

directionality (i.e., proper orientation of the hydrogen donor or acceptors in the

macromolecule).

For both types of criteria, distance and orientation, a small conformational

change in the crystal structure found in the database could make possible an

otherwise unfavorable interaction. To allow for such flexibility, a range of

acceptable values can be specified for acceptance or rejection of a certain

crystal structure as a plausible model.

We have used the RECEPTORSEARCH program to search the protein crystal

structures contained in the Brookhaven Databank for a heuristic model for the

BDZ receptor. The input data provided to the program were the positions of the

two proton-donating sites, as well as that of the center of the aromatic ring of

the receptor that could take part in stacking with agonists. Using these strict

criteria, deoxymyogiobin (deoxyMb) was the only protein that fulfilled the

requirements for the interaction of BDZ agonist ligands. The residues involved

in recognition according to this model were HIS 113, ARG 31, and SER 35. To

further characterize and test this site, fiunitrazepam was docked in it. As shown

in figure 4a, the histidine residue can participate in a stacked complex with the

55
most lipophilic, fused benzene ring, while the arginine and serine provide the

two proton-donating residues necessary for recognition. Other residues, such

as LEU 32 and 29, PHE 33, ILE 28, ASP 27, GLN 26, and SER 117, make up

the ligand-binding pocket. The interaction of the lipophilic ring with the histidine

could constitute the charge-transfer complex that we have implicated in

activation. As seen in figure 4b, the lipophilic ring of the antagonist, ZK 93426,

docked in that site does not interact with the histidine and could not form such a

charge-transfer complex.

FIGURE 4a. DeoxyMb provides a heuristic model for the BDZ receptor-ligand

binding site. Two proton-donating residues, ARG 31 and SER

35, constitute the common recognition sites. Flunitrazepam is

displayed in the cavity. The interaction of its freely rotating ring

with an electron-donating residue such as HIS 113 would

provide the activation mechanism.

56
FIGURE 4b. The antagonist ZK 93426 is represented. In this case, there is

no interaction with the HIS 113 residue

The site found in deoxyMb is in a highly hydrophilic area on the surface of the

protein. it is known that BDZ ligands bind to the extracellular N-terminal region

of either an -subunit of the GABAA receptor. Thus, it is possible that a

region near the binding site is exposed to an aqueous environment near the

surface of the receptor. However, most BDZ ligands are highly lipophilic, which

is an indication of the nonhydrophilic nature of the binding site of these

compounds. Thus, this particular model may not be entirely useful in

understanding the changes induced in the macromolecule because of its

interaction with the ligand. Nevertheless, this model could provide some

insights into the mechanism of interaction.

An additional plausible component of the activation mechanism is that agonists

also could induce a change in the conformational state of the macromolecule to

allow for stacking between the lipophilic ring and the aromatic residue of the

macromolecule. Allowing for this possibility, we have found two additional

57
heuristic models, an FAB immunoglobin and a tripsinogen with more

hydrophobic, buried binding sites. We are in the process of characterizing the

docking of diverse ligands to the binding sites identified in these models.

CONCLUSIONS

This chapter describes a model that characterizes plausible molecular

modulators of receptor recognition and activation for the BDZ receptor ligands.

These modulators are expressed in the form of 3D structural and electronic

requirements for interaction as well as activation. The structural requirements

of the model then were used to perform 3D searches for other potential BDZ

ligands, using a 3D database. Among the retrieved structures were those of

known BDZ receptor iigands that were not included in the original set used to

develop the working hypothesis. This finding constitutes a validation of the

hypothesis developed. The same hypothesis then was used, by

complementarity, to search for a heuristic model for the BDZ receptor. To

achieve this goal, a program called RECEPTORSEARCH was developed that

searches a data bank of protein-crystal structures for macromolecules that

satisfy certain user-supplied criteria (i.e., those derived from the working

hypothesis). As a result of this search, deoxyMb (and possibly two other

proteins) was found to have the necessary features for a favorable interaction

with the BDZ ligands. Because the proposed binding site in deoxyMb is on the

surface of the enzyme, it may not constitute the most desirable description for

the site.

The interdisciplinary mechanistic approach to CADD described includes three

computational components embodying the techniques of theoretical chemistry

and 3D ligand and macromolecular database searching. This integrated

approach has been applied for the first time to a family of drugs of abuse. The

methods and protocols used can be applied to any other drugs of abuse or, in

general, to the study of therapeutic agents that exert their effect by binding to

specific receptors.

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ACKNOWLEDGMENT

This work was prepared with support from National institute on Drug Abuse

grant DA-02880.

AUTHORS

Gilda H. Loew, Ph.D.

President

Hugo O. Villar, Ph.D.

Director

Computational Pharmacology Department

Waymond Jung

Research Assistant

M. Frances Davies, Ph.D.

Director

Experimental Pharmacology Department

Molecular Research Institute

845 Page Mill Road

Palo Alto, CA 94304

81
3D-Searching: An Overview of a New

Technique for Computer-Assisted

Molecular Design

Robert S. Pearlman

INTRODUCTION

This chapter provides a rudimentary introduction to the fundamentals of threedimensional (3D)-searching—a powerful new technique for computer-assisted

molecular design (for a more detailed review, see Martin et al. 1990). Following

brief remarks relating this technique to other more familiar techniques, there is a

brief indication of the essential software components required to implement 3Dsearching capabilities. Although the original presentation at the National

Institute on Drug Abuse (NIDA) Technical Review in Washington, DC,

concluded with an example of an application to drug design, the reader is

referred to another chapter in this monograph (Loew et al.) for an interesting

example. This chapter closes with a prospective look at the future of 3Dsearching and some cautionary comments regarding its use.

3D-SEARCHING—ITS RELATIONSHIP TO OTHER TECHNIQUES

In most cases, the design of novel herbicides, pesticides, or therapeutic agents

involves the search for molecular ligands that effectively bind to a biomolecular

receptor. Ligand-receptor binding depends on the chemical and geometric

compiementarity of the ligand and receptor. For example, if the receptor site

contains a hydrogen-bond donor then the iigand should contain a hydrogenbond acceptor; if the receptor site includes a region of significant positive

charge then the ligand should contain a complementary region of negative

charge. Moreover, these chemical features of the ligand must be positioned

relative to each other in 3-space so that they can all interact with the

corresponding features of the receptor in an optimal or near optimal fashion. In

the context of drug design, the specific chemical and geometric criteria leading

to significant drug-receptor affinity are referred to as the pharmacophore.

62
Usually, the search for novel bioactive compounds is undertaken after one or

more active compounds already is known. Thus, one important aspect of

molecular design involves extending known “leads”—modifying and exploring

within a class of chemical structures, some of which are already known to

possess the desired activity. However, another important aspect of molecular

design involves the search for new lead compounds—new chemical classes

that also meet the chemical and geometric criteria necessary for significant

ligand-receptor binding. Discovery of new leads is usually far more difficult than

extension of existing leads.

By performing screening procedures on a computer rather than in the

laboratory, computer-assisted molecular design can increase greatly the

efficiency of the discovery/design process. Computer-assisted molecular

design can be performed at different levels (involving different techniques)

depending on the level of knowledge regarding the structure of the particular

receptor.

if the 3D coordinates of all atoms in the receptor are known, then the stability

and structure of the ligand-receptor complex can be investigated using

techniques generally referred to as “molecular modeling.” These techniques

involve calculation of ligand-receptor interaction energies and computer graphic

display of the ligand-receptor complex. The computer graphic display provides

invaluable qualitative insights that can assist the chemist in imagining how

modification of the ligand structure might affect ligand-receptor interaction. The

calculated interaction energies provide quantitatlve indications of the relative

affinities various ligands have for the receptor. Clearly, molecular modeling

involves a detailed analysis of the complementarity of ligand and receptor

structure. However, this sort of molecular modeling rarely can be applied

because the detailed structure of the receptor is usually unknown.

When beginning a molecular design effort with little or no knowledge of the

receptor structure, the only option is to attempt to develop empirical quantitative

structure-activity relationships (QSARs). QSARs are established by considering

the activities of a structurally homologous series of ligands. Although these

relationships consider the chemical differences between the substituent groups

of the series of ligands, the 3D geometric relationships between the substituent

groups are not addressed explicitly. Extrapolation of a given QSAR to

proposed ligands dissimilar to those of the original series is not valid. Thus,

QSARs may be useful in extending a series but will not be useful for discovering

new leads.

Between the two extremes of complete knowledge and no knowledge of the

receptor structure lies the increasingly common situation in which the

63
investigator has acquired limited knowledge of the structure of the receptor.

More precisely, at least a crude description of the pharmacophore has been

obtained—an indication of the types of substituent groups and the 3D geometric

arrangement of those substituent groups leading to favorable ligand-receptor

interaction. Under these circumstances, computer-assisted molecular design

and discovery can be accomplished by searching large databases of 3D

molecular structures for compounds that satisfy the chemical and 3D geometric

criteria that constitute the description of the pharmacophore. It is only within the

last few years that the pharmaceutical industry has been in a position to explore

the utility of 3D-searching; already the results have been most encouraging. In

every case, the search not only has returned “hits” (compounds that satisfy the

search criteria) similar to known active compounds but also has returned hits

that were entirely unexpected, new classes of compounds. Thus, 3D-searching

provides an automated mechanism for discovering new lead compounds.

Four essential elements to implement 3D-searching capabilities are discussed

below: (1) many interesting 3D molecular structures, (2) a chemical database

management system, (3) the 3D-searching software, and (4) rationally

determined search criteria.

STRUCTURES FOR 3D-SEARCHING

The tremendous potential of 3D-searching has been recognized by leaders in

pharmaceutical research for many years. Perhaps the earliest efforts were

those of Peter Gund and his collaborators in the mid-1970s (Gund et al. 1974;

Gund 1977). Since then, various groups in academia and industry have

reported efforts to develop 3D-searching algorithms (see below), but only within

the last few years did 3D-searching become a realistic technique for molecular

design. Interestingly, the delay was due primarily to the fact that there were no

large databases of interesting 3D structures on which to perform the search.

Until recently, the Cambridge Structural Database (CSD) of x-ray and neutron

diffraction results was the only resource for 3D structures. Although the CSD

contains structural information for approximately 70,000 compounds, many of

these are inorganics or metallo-organics of little or no interest to those

searching for new bioactive compounds; furthermore, the low accuracy

(resolution) of many of the organic structures in the database renders them of

little value for 3D-searching purposes. Many of the remaining organic

compounds (approximately 30,000) are of little interest from a pharmaceutical

perspective. Building up a large database of interesting 3D structures by

performing molecular mechanics or molecular orbital geometry optimizations of

crude 3D structures input by some manual technique would take a tremendous

amount of time and effort. Such efforts have been undertaken by various

64
pharmaceutical and chemical companies, but the resulting databases usually

contain between 500 and 2,000 structures—not nearly enough to enable

profitable 3D-searching.

Several groups have reported on their efforts to develop computer programs for

the automatic conversion of two-dimensional (2D) molecular “structures” (i.e.,

connection tables) to 3D coordinates (Wipke et al. 1972; Wenger and Smith

1982; Wipke and Hahn 1986; Dolata et al. 1987; Cohen et al. 1981; Trindle

1986). However, each of these efforts suffered one or more drawbacks that

precluded the use of the program as a generally applicable, production-level

software tool. In contrast, the CONCORD program for the rapid generation of

high-quality approximate 3D molecular structures (Pearlman 1987a; Pearlman

et al. 1987) provides a method offering the required level of reliability, accuracy,

speed, and general applicability and has thereby enabled the practical

application of 3D-searching methodologies. Several large databases of

CONCORD-generated 3D structures are commercially available: the MACCS

Drug Data Report (approximately 10,000 compounds) and the Fine Chemicals

Directory (approximately 65,000 compounds) from Molecular Design Ltd.

(MDL); the POMONA-90C database of approximately 70,000 compounds from

Daylight Chemical Information Systems (Daylight); and approximately 4 million

structures from the Registry File of Chemical Abstracts Service. Of even

greater interest to industrial scientists is the use of CONCORD to convert their

corporate databases of proprietary structures (often more than 100,000) from

2D to 3D. Much of the excitement over 3D-searching in industry stems from the

fact that companies are finding that compounds they synthesized, recorded,

patented, and abandoned during discovery efforts made years ago for other

purposes are turning out to be new lead compounds discovered by 3Dsearching associated with current discovery efforts.

The CONCORD program is a hybrid of an “expert system” approach and a

“pseudomolecular mechanics” approach to structure building (Pearlman 1987b).

Bond-lengths are assigned from a very extensive table (Allen et al. 1987). For

most acyclic substructures, the bond angles and torsion angles are assigned by

performing a rule-based logical analysis that seeks to optimize 1--4 interactions.

This logical analysis is at least 1,000 times faster than performing the

analogous task using a molecular mechanics approach. However, this

approach cannot be applied to rings or ringsystems; minimization of

conformational energy is required. Whereas molecular mechanics and

molecular orbital geometry optimization procedures minimize energy as a

function of many independent atomic coordinates, CONCORD recognizes the

correlation of atomic coordinates within a given ring and minimizes a univariate

strain function. The overall algorithm is quite fast; Rusinko and colleagues

(1989) reported the conversion of a corporate database of approximately

65
250,000 compounds at the rate of 0.5 seconds per compound on a VAX 8700;

of course, faster speeds are being achieved on faster machines.

The minimal input required by CONCORD is the 2D connection table: an

indication of which atoms are bonded to one another and the types (e.g., single,

double) of the bonds. Because a given 2D connection table may correspond to

more than one stereochemical isomer, specific stereochemical information also

must be attached to the connection table to ensure that the desired isomer is

constructed. The MACCS MOLfile format used by MDL is an extremely

common format for this type of information, and CONCORD fully supports the

input and output of MDL MOLfiles. CONCORD also supports use of the

SMILES chemical line notation (Anderson et al. 1987; Weininger 1988)—an

increasingly popular mechanism for providing the same connection table

information in a compact format used by the chemical database software tools

distributed by Daylight.

The structures generated by CONCORD are usually in excellent agreement

with the lowest energy structures optimized using molecular mechanics or

molecular orbital methods. However, some limitations should be noted.

CONCORD will not generate inorganic or metallo-organic structures. Also, it

was not intended for use on highly flexible structures (e.g., peptides,

macrocycles, polymers) for which the preferred conformation is ill-defined. The

issue of conformational flexibility in the context of 3D-searching is addressed

later in this chapter.

CHEMICAL DATABASE MANAGEMENT SOFTWARE

General purpose database management software permits storage and retrieval

of information by reference to certain storage keys or identifiers. For example,

a corporate personnel database would enable access to a variety of personnelrelated data by reference to employee name or employee number. The way in

which information is accessed in a general purpose database reflects the

perception that information is related to entire objects (e.g., employees, in the

foregoing example). Perhaps the most fundamental difference between a

general purpose and a chemical database is that a chemical database system

reflects the fact that chemical compounds (or structures) are composed of

atoms and substructures; the internal parts of these chemical objects are of as

much interest as the entire objects.

To access information at the structural and substructural levels, chemical

database management software uses the chemical structure to derive the

identifiers by which the compound will be identified. The user specifies a

structure by specifying its connection table, either by sketching the structure

66
using a simple light-pen or digitizing tablet or by entering a chemical line

notation, which is immediately converted to a connection table. Using

modifications of the classic Morgan algorithm (Morgan 1965; Wipke and Dyott

1974; Weininger et al. 1989), the connection table then is reordered in a

canonically unique fashion. Because the connection table of an N-atom

molecule can be input in at least N! ways, this unique reordering is essential for

the task of exact structure matching. It also greatly facilitates the

implementation of substructural matching capabilities—finding all compounds in

the database that contain the user-specified substructure.

In addition to being searchable by structure and substructure, a chemical

database management system also should support the capabilities expected of

a general purpose database management system. It is important that the

structural information and various property-related information (e.g.,

experimental biological activity data, physical properties such as partition

coefficient, atomic properties such as partial charge) be readily accessible

within a single software environment. It is also important that the chemical

database management software be tightly interfaced to the molecular modeling

software environment.

Several pharmaceutical companies developed “in-house” database

management systems to meet these objectives. However, two systems are

commercially available: the MACCS-II system distributed by MDL and the

Daymenus system distributed by Daylight. Both systems are widely used and

accepted.

3D-SEARCH SOFTWARE

The features of the pharmacophore that constitute the 3D-search criteria should

be perceived as falling into two categories: 2D chemical substructures and the

3D geometric relationships between the substructures. Then, conceptually, 3Dsearching can be perceived as being accomplished in two corresponding

phases. In the first phase, the 2D substructural searching capabilities of the

chemical database management software are used to screen out those

compounds in the database that could not possibly meet the 3D-search criteria

because they do not contain the required chemical substructures in any relative

positions. This 2D substructural screening takes little time and eliminates the

vast majority of compounds in the database. Those compounds that remain

then are subjected to geometric screening, which also can be perceived as

being accomplished in two phases. It is relatively easy to screen compounds

for simple distance-related criteria. In fact, when the 3D structural database is

being constructed (or updated), the various types of interatomic separations

(i.e., atom types and interatomic distances) contained within each structure are

67
recorded in much the same way as are the atom types. Different programs

implement these distance keys in different ways, but the objective is the same:

to screen out compounds that could not possibly meet the 3D-search criteria

because they do not contain required atoms separated by required distances.

Like the 2D substructural screens, these distance screens require little

computer time and further reduce the number of compounds that must be

subjected to the final phase of searching.

In the final phase of 3D-searching, the atomic coordinates of each compound

are examined in detail to determine whether the required chemical

substructures occupy positions in 3-space that will satisfy the 3D geometric

criteria. These criteria can involve much more than simple interatomic distance

constraints. The atomic coordinates can be used to define various objects, and

the search constraints can be formulated in terms of these objects. For

example, suppose that two of the substructural features of a particular

pharmacophore are a carboxylete group and an aromatic ring. One geometric

constraint might be the distance between the carbon of the carboxylate and the

centroid of the ring. Another constraint might be the dihedral angle between

one of the carbon-oxygen bonds of the carboxylate group and the plane of the

aromatic ring. Atomic coordinates also can be used to define points that, in

turn, are used to define “forbidden regions”—regions of space around the

essential features of the pharmecophore, which, if occupied, would lead to

sterically unfavorable interaction between the ligand and receptor.

Several groups have made significant contributions to the development of 3Dsearching software (Gund et al. 1974; Ullman 1976; Jekes et al. 1987; Sheridan

et al. 1989a; Van Drie et al. 1989, and others). These efforts have resulted in

working systems. However, because 3D-searching builds on the searching

capabilities of chemical database management software and because only two

chemical database management software packages are commercially available,

it should not be surprising that only two 3D-searching packages are

commercially available. MDL distributes MACCS-3D as an add-on option to its

MACCS-II database management system. Daylight now distributes ALADDIN,

which, although developed at Abbott Laboratories by John Van Drie working

with Yvonne Martin, is based in part on Daylight searching capabilities.

3D-SEARCH CRITERIA

The first three essential elements of 3D-searching—a mechanism for rapid 3D

structure generation, software for managing chemical databases, and software

for performing the search—might be regarded as “software tools” that can be

readily applied to any 3D-searching problem. In contrast, the fourth essential

element of 3D-searching—rationaI 3D-search criteria—must be tailored

68
specifically for each new discovery problem. Defining the search criteria

requires substantial effort on the user’s part, whereas performing the search

requires relatively little user input.

The approach to computer-assisted molecular design and the approach to

developing 3D-search criteria depend on how much is known about the

structure of the receptor. If the structure of the receptor is known, it is a

relatively straightfomard matter to develop chemical and geometric criteria for

complementary ligands that could interact favorably. Most often, however, the

structure of the receptor is not known and attempts to formulate the search

criteria are based solely on the structures of a few ligands that have been found

to exhibit the desired bioactivity.

Inferring 3D-search criteria from known ligand structures is relatively

straightforward when the ligands are fairly rigid. However, if the known ligands

are flexible structures that could undergo significant conformational distortion

during the binding process (i.e., if the bound conformation could be significantly

different than the low energy conformation), then establishing rational 3Dsearch criteria is a far more complex process. Indeed, it may be impossible to

determine accurately the geometry of the receptor. It is possible, however, to

determine how the “conformation space” accessible to each ligand in the

training set compares with the conformation space accessible to all other

ligands in the set. More precisely, a search can be undertaken for those

regions of space that are conformationally accessible to all ligands in the

training set. The geometric constraints derived in this manner may not be

particularly specific but are at least guaranteed to include the bound

conformations of all ligands in the training set. Techniques for performing this

sort of systematic search of the conformation space of a set of compounds were

developed by Marshall and coworkers (1979) and Mayer and coworkers (1987)

and recently were refined with respect to computational efficiency by

Dammkoehler and colleagues (1989). The SYBYL molecular modeling

package (Tripos Associates) includes conformational searching features that

are useful in this regard. Once the regions of conformational space common to

all ligands in the training set have been identified, a description of these regions

must be specified in terms that the searching software can understand. As

previously indicated, this primarily involves specifying ranges of distances and

angles between objects defined in terms of the coordinates of the key features

of the pharmacophore. The breadth of the ranges at least should be sufficient

to include all active members of the training set.

There are several aspects to the efficiency with which a search is

accomplished. For a database of given size, an obvious measure of efficiency

is the central processing unit (CPU) time required to complete the search.

69
Because the 2D substructural screens and distance screens are performed so

rapidly, greater specificity regarding these aspects of the search criteria will

result in fewer compounds for which more CPU-intensive 3D examination is

required. In contrast, as the specificity of the 3D criteria is increased by adding

additional geometric constraints, the required CPU time increases

proportionally. Another measure of searching efficiency is the ratio of the

number of hits to the number of compounds in the database. If the search

criteria are not specific, they might be satisfied by large numbers of compounds

and the search might result in so many hits as to be of little value. Most of

these hits would not possess the correct geometry required for receptor binding.

Clearly, the geometric criteria should be as detailed as possible but expressed

as concisely as possible. A third aspect of searching efficiency is the ratio of

the number of truly active hits to the total number of hits returned by the search.

Although this aspect is related to the preceding aspect, it differs in an

interesting way. If 3D geometric criteria are formulated by examining a training

set composed only of ligands known to bind well with the receptor, then the user

has failed to provide information concerning the “forbidden regions,” which, if

occupied, result in sterically unfavorable ligand-receptor interactions. The

resulting hit list might contain many compounds that satisfy all the criteria

specified for receptor affinity but contain substructures extending into the

unspecified forbidden region(s). Thus, it is important to include active and

rationally selected inactive compounds in the process of defining the 3D-search

criteria.

It is instructive to contrast 2D- and 3D-searching in terms of the type of

information used to formulate the search criteria. Because ligand-receptor

interaction depends on the complementarity of two 3D objects, the inability

explicitly to include 3D considerations in the specification of 2D substructural

search criteria is an obvious disadvantage. However, there is another important

distinction to be made. When specifying 2D substructural searching criteria, the

user not only specifies the key substructural features identified as essential

elements of the pharmacophore but also specifies, to some extent, the chemical

environment surrounding these features. Any efforts to specify (albeit crudely)

the geometric relationship between the substructural features involves

specifying even more of the chemical structure of the hits that the search

returns. Therefore, the 2D hit list reflects the structures the user had in mind

while formulating the search criteria and rarely contains any surprises. In

contrast, 3D-search criteria allow the user to specify the essential

pharmacophore features and their geometric relationship in geometric rather

than chemical structural terms. The correspondence between 3D-search

criteria and 3D-search hits is far less explicit than the correspondence between

the criteria and hits of a 2D-search. Thus, the hits returned by a 3D-search are

70
likely to include more structurally diverse compounds—surprising new leads—

that the user did not have in mind when formulating the search criteria.

3D-SEARCH EXAMPLES

As of this writing, the essential elements required for 3D-searching have been

available for less than a year. Nevertheless, accounts of successful 3Dsearching efforts already are being presented at meetings and are beginning to

appear in the literature (Sheridan et al. 1989b; Van Drie et al. 1989). Obviously,

other industrial examples are of proprietary interest and cannot be published at

this time. Loew and colleagues (this volume) used 3D-searching to identify

novel benzodiazepine receptor ligands.

USE OF 3D-SEARCHING AND FUTURE DEVELOPMENTS

The aforementioned examples (and others) leave absolutely no doubt that,

even in its current state of development, 3D-searching works. It already is

proving to be a useful technique for the extension of existing leads and the

discovery of new leads to bioactive compounds; however, some proposed

improvements and caveats are discussed below.

As currently implemented, 3D-searching does a poor job in accounting for the

possible flexibility of ligands. Let us assume that we have applied the

techniques of systematic conformational searching to a training set of flexible

ligands and have thereby formulated 3D-search criteria that reflect the required

conformation of a ligand once it is bound to the receptor. Let us also assume

that we have stored in the database the low-energy conformation of each of

these ligands (such as would be generated by CONCORD or some geometry

optimization procedure). If the bound conformations are significantly different

than the low-energy conformations, it is entirely possible that a search based on

these 3D-search criteria would not return the compounds in the training set

used to formulate the search criteria. Moreover, other compounds for which the

low-energy conformation does not satisfy the search criteria but which could be

distorted so as to match the criteria would not be returned as hits. Although this

appears to be an undesirable situation, before we consider how it might be

remedied, let us consider its positive aspects. There are numerous

contributions to the overall free energy of ligand-receptor interaction (which, of

course, determines the stability of the ligand-receptor complex). The most

obvious contribution is the electronic intermolecular interaction energy that

results when the key features of the pharmacophore are placed close to the

corresponding features of the receptor. If the 3D-search criteria accurately

reflect the ligand-receptor interaction, the intermolecular interaction energy

contribution of all hits will be roughly equivalent. Another contribution to the

71
overall free energy of interaction is the energy required to distort the ligand from

its preferred conformation to its bound conformation. This energy will be

positive and, therefore, will be an unfavorable contribution to the binding

process. Thus, a compound for which the preferred conformation closely

approximates the bound conformation would be expected to yield a more stable

ligand-receptor complex than compounds that must undergo conformational

distortion to bind. Thus, although the aforementioned search example might fail

to return flexible compounds that could be distorted so as to match the search

criteria, the compounds that are returned would be expected to bind to the

receptor more effectively. (Relatively rigid compounds satisfying the search

criteria might be expected to bind even more effectively because their

complexation would not entail as large a decrease in conformational entropy.)

If receptor affinity were the only factor to be considered, then we might be

satisfied with a search strategy that returns only compounds for which the

prefer red conformation satisfies the search criteria. However, issues such as

toxicity, transportability, and “patent-ability” often prompt us to consider ligands

for which receptor binding requires conformational distortion. How can the 3Dsearch procedure be modified so that these types of compounds will be found?

One approach is to relax the 3D-search criteria until the list of hits includes the

flexible, known-active compounds included in the training set. This may prove

satisfactory in some cases but in other cases will result in such vague 3D

geometric constraints that the search will offer little advantage over a simple

2D-search. Another approach frequently suggested is to store multiple

conformations of each compound in the database. Obviously, storing additional

conformations cannot reduce (can only increase) the number of compounds

returned by a 3D-search, generating considerable interest in this approach.

However, there are some significant problems that have not received the same

degree of attention as have the potential benefits. For simplicity, let us imagine

that we only need to consider conformational changes resulting from rotations

about single bonds between sp3-hybridized atoms. Let us begin by assuming

that we consider storing just three conformations (dihedral angels of 60, 180,

and 300 degrees) per rotatable bond. If there were only three such

independently rotatable bonds in a compound, there would be 3

3

=27

conformations to be stored. In reality, most compounds in a real database

possess at least that many conformational possibilities. Recalling that

computer-assisted 3D-searching is only worthwhile when performed on

databases containing many thousands of compounds, it is clear that storage of

multiple conformations would lead to substantial disk requirements. The CPU

time required to perform the search also would increase substantially. These

increases might be regarded as worthwhile if this strategy were guaranteed to

return a substantially larger hit list. Unfortunately, it does not. Although the

72
three dihedral angles mentioned above might correspond to local minima in the

conformational energy surface of an isolated compound, the conformational

energy surface of the same compound interacting with the receptor will be

entirely different. Strong, specific intermolecular interactions (such as

hydrogen-bonding) can result in a bound conformation near a local maximum of

the conformational energy surface of the isolated compound. Decreasing the

torsion-angle increment in an attempt to include these sorts of conformations

would result in much larger numbers of conformations to be stored per

compound.

The 3D geometric phase of current 3D-search algorithms examines each

conformation, asking the question, “Does this conformation satisfy the search

criteria?” Rather than applying this type of search algorithm to databases

containing many conformations of each compound, it is more logical to develop

new searching algorithms that examine databases containing only low-energy

conformations and that scan the conformational space of potential hits at

search time. These new search algorithms will ask, “Could this compound be

distorted so as to satisfy the search criteria and, if so, how much conformational

energy will be required?” Most of the software technology required for this next

generation of search algorithms already exists; such products probably will be

available during the coming year.

Another improvement that could and should be made soon is to provide a

quantitative indication of how well each compound on the hit list satisfies the

search criteria. As previously explained, the search criteria specify ranges of

acceptable distances and angles. Current searching software returns a list of

compounds that lie somewhere within the acceptable limits. An indication of

how close a compound is to the center of the acceptable ranges could be useful

in prioritizing the subsequent laboratory testing efforts. This “goodness of hit”

concept also could be extended to the chemical aspects of the search criteria.

For example, if a hydrogen-bond acceptor was stipulated as a key substructural

feature, a basicity index that distinguished carbonyl oxygens from etheric

oxygens from amides might prove quite useful.

Thus far, the focus has been on the chemical structural complementarity

between the ligand and receptor, that is, the electronic intermolecular

interaction energy and the conformational energy contributions to the overall

free energy of interaction. However, Amidon and colleagues (1979) pointed out

the importance of considering the free energy of desolvation, which contributes

to the free energy of intermolecular interaction in solution; desolvation usually is

addressed in current molecular modeling efforts. An earlier hypothesis states

that if two ligands present to the receptor the same key substructural features in

essentially the same geometric disposition, then the electronic intermolecular

73
interaction between the receptor and the two ligands will be roughly the same.

It is presumed that, if the chemical nature of the framework connecting the key

substructural features had a significant effect on the stabiltty of the ligandreceptor complex, then aspects of the framework would have been identified as

key features of the pharmawphore. However, the free energy required to

desolvate the framework of two dissimilar ligands might differ by several kcal/

mol. Identifying those portions of hit compounds that must be desolvated and

including an estimate of the desolvation energy as part of the aforementioned

effort to quantitate goodness of hit might prove useful.

The foregoing discussion pertains to various factors that contribute to ligandreceptor affinity. However, even the simplest models of bioactivity involve at

least two processes. First, the compound must be transported to the biophase;

then it must interact with the receptor. Both processes depend on the chemical

structure of the compound. Therefore, rational molecular design efforts should

consider the effect of structure on both of these essential aspects of bioactivity.

It does little good to identify compounds that exhibit high in vitro receptor affinity

but low in vivo bioactivity due to poor transport properties. As with other

receptor affinity-oriented techniques for computer-assisted molecular design,

3D-searching should be used in conjunction with a method for estimating the

permeability of hit compounds through relevant biological barriers. Such a

method has been developed by Skell and Pearlman (in preparation).

CONCLUSION

3D-searching for pharmacophores within large databases of 3D chemical

structures is proving to be a powerful new technique for computer-assisted

molecular design. In particular, it has proven useful not only for the exploration

of existing lead compounds but also for the discovery of entirely novel leads to

bioactive agents. Four essential elements are available, thereby enabling 3Dsearching: a method for the rapid generation of large databases of 3D

molecular structures, software for the management of and 2D substructural

searching within chemical databases, software to perform the 3D geometric

aspects of 3D-searching, and techniques for the formulation of rational 3Dsearch criteria.

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Constrained search of wnformational hyperspace. J Comput-Aided Mol Des

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Dolata, D.P.; Leach, A.R.; and Prout, K. WIZARD: Al in conformational

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Computational Chemistry. New York: VCH Publishers, Inc., 1990. pp. 213-

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Pearlman, R.S. CONCORD User’s Manual. St. Louis: Tripos Associates,

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Pearlman, R.S. Rapid generation of high quality approximate 3D molecular

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Pearlman, R.S.; Balducci, R.; Rusinko, A.; and Skell, J.M. CONCORD. St.

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Sheridan, R.P.; Nilakantan, R.; Rusinko, A.; Bauman, N.; Haraki, K.; and

Venkataraghavan, R. 3DSEARCH: A system for three-dimensional

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Searching for pharmacophores in large databases and its use in drug design.

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Trindle, C. An intelligent sketch pad as input to molecular structure programs.

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Chemistry. Washington, DC: American Chemical Society, 1986. pp. 156-

168.

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Machinery 16:31-42, 1976.

Van Drie, J.H.; Weininger, D.; and Martin, Y.C. ALADDIN: An integrated tool

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Weininger, D.; Weininger, A.; and Weininger, J.L. SMILES 2. Algorithm for

generation of unique SMILES notation. J Chem Inf Comput Sci 29:97-104,

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Wenger, J.C., and Smith, D.H. Deriving three-dimensional representations of

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1982.

Wipke, T., and Dyott, T.M. Stereochemically unique naming algorithm. J Am

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ACKNOWLEDGMENTS

The author acknowledges support received from the R.A. Welch Foundation

(grant F-1024) and the U.S. Environmental Protection Agency (grant CR813639-01).

76
AUTHOR

Robert S. Pearlman, Ph.D.

Professor and Director

Laboratory for Molecular Graphics and Theoretical Modeling

University of Texas College of Pharmacy

Austin, TX 78712

77
Protein Structure Determination in

Solution Using Nuclear Magnetic

Resonance Spectroscopy

Angela M. Gronenborn and G. Marius Clore

INTRODUCTION

Over the past few years, we have witnessed a renewed interest in protein

studies, especially those aimed at understanding their structures, functions, and

physiological roles. Some of this increased enthusiasm can be attributed to a

variety of technological advances in the area of modern molecular biology, in

particular, molecular cloning of protein encoding genes. The resulting wealth of

data is clearly impressive; however, amino acid sequences are of limited value

in understanding protein function. We need to know the three-dimensional

structure before we can begin to make progress in analyzing the intricate

reactions carried out by proteins such as catalysis, ligand binding, gene

regulation, and assembly. The design of modified proteins, rational design of

drugs, and attempts at de novo design of protein molecules all have to be

based on concepts at the atomic level in 3D space, thereby creating an

increasing need for detailed structural analysis.

Until recently, the only experimental technique available for determining 3D

structures has been single crystal x-ray diffraction, and most of our structural

knowledge about proteins is based on those crystal structures. There are

approximately 400 coordinate sets available to date, comprising about 120

different protein folds. Analyzing protein structures by crystallography can be a

slow and difficult undertaking because the first and possibly hardest task

involves growing x-ray, quality-grade crystals, which have to be well ordered to

give rise to good diffraction patterns. Even if this task is accomplished, a

second hurdle still needs to be overcome, as the phases have to be solved,

commonly achieved by collecting data on heavy atom derivatives. Thus,

despite spectacular advances in protein crystallography, we are faced with an

enormous gap between the available primary sequence data and the tertiary

structure data on proteins.

76
Over the past 10 years, a second method for determining protein structures has

been developed and is by now well established. This method makes use of

NMR spectroscopy. Unlike crystallography, NMR measurements are carried

out in solution under potentially physiological conditions and are therefore not

hampered by the ability or inability of a protein to crystallize.

The principal source of information used to solve 3D protein structures by NMR

spectroscopy resides in short interproton distances supplemented by torsion

angles. The distances are derived from nuclear Overhauser effect (NOE)

measurements, because the size of the NOE between two protons is

proportional to r

6

, where r is the distance between them. Torsion angles are

obtained from an analysis of three-bond coupling constants that are related to

dihedral angles. An essential prerequisite for obtaining interproton distance

restraints and torsion angle restraints is the assignment of the NMR spectrum,

that is, the identity of every proton resonance has to be determined. This is not

a trivial task considering that the proton spectrum of even a small protein

comprising only 80 amino acids contains approximately 650 resonances. All

these exhibit several cross-peaks in the 2D spectrum, and the number of crosspeaks whose identity has to be ascertained can easily rearch several thousand.

Complete spectral assignment is, therefore, an integral part of the structure

determination.

Although it was appreciated relatively early on that NMR could in principle

provide the necessary information to obtain 3D structures, only recently has this

goal been realized. The reasons for this are threefold: (1) The development of

2D NMR experiments (Jeener 1971; Jeener et al. 1979; Aue et al. 1976)

alleviated problems associated with resonance overlap, which for

macromolecules prevents any analysis of the traditional one-dimensional

spectrum. This is achieved by spreading all the information out in a plane,

thereby permitting a detailed interpretation of the pertinent spectral features.

This conceptual idea has been extended more recently to 3D NMR (Oschkinat

et al. 1988, 1989; Vuister et al. 1988; Fesik and Zuiderweg 1988; Zuiderweg

and Fesik 1989; Marion et al. 1989a, 1989b), again relieving problems arising

from spectral crowding; and it is the 3D approach in particular that will extend

the present limits with respect to the size of the proteins that can be studied.

(2) The availability of high-field magnets (500 and 600 MHz) has resulted in

spectrometers with a significant increase in the signal-to-noise ratio and better

spectral resolution, and continuing development in this area again will extend

the limits even further. (3) Suitable mathematical algorithms and computational

approaches, which convert the NMR-derived restraints into 3D structures, have

been developed (Havel and Wüthrich 1984; Havel et al. 1983; Braun and Go

1985; Clore et al. 1985, 1986; Kaptein et al. 1985; Billeter et al. 1987; Nilges et

al. 1988a, 1988b, 1988c; Litharge et al. 1987), and several robust and efficient

methods are available.

79
This chapter outlines the general methodology for protein structure

determinations by NMR (figure 1); however, no attempt is made to provide an

indepth description of either the general NMR theory or the details of the

mathematical algorithms. Emphasis is placed on the application of NMR to

structural studies, and two examples from the authors’ laboratory are used to

illustrate various points.

FIGURE 1. Flow chart of the various steps involved in determining the 3D

structure of a protein in solution by NMR

THE NUCLEAR OVERHAUSER EFFECT

The principles of 2D NMR have been discussed in depth (Ernst et al. 1986) and

the authors deliberately refrain from explaining the basic NMR experiment

because this would be beyond the scope of the present article. Only the

relevant NMR parameters are briefly introduced.

NMR-derived protein structures are mainly based on NOE measurements that

can demonstrate the proximity of protons in space and that allow the

determination of their approximate separation (Overhauser 1953a, 1953b;

80
FIGURE 2. The basis of the NOE

rij=distance between the protons i and j

=cross-relaxation rate;

N, NOE, =correlation time

Solomon 1955, Noggle and Schirmer 1971). The principle of the NOE is

relatively straightforward and is summarized in figure 2. Consider the simplest

system with only two protons, each of which possesses a property known as

cross-relaxation. Because the cross-relaxation rates in both directions are

equal, the magnetization of the two protons at equilibrium is equal. The

81
approximate chemical analogy of such a system would be one with two

interconverting species with an equilibrium constant of 1. The cross-relaxation

rate is proportional to two variables: r-6 where r is the distance between the two

protons, and the effective correlation time of the interproton vector. It

follows that if the magnetization of one of the spins is perturbed, the

magnetization of the second spin will change. In the case of macromolecules,

the cross-relaxation rates are positive and the leakage rate from the system is

small, so that in the limit, the magnetization of the two protons would be

equalized. The change in magnetization of proton i upon perturbation of the

magnetization of proton j is known as the nuclear Overhauser effect. The initial

buildup rate of the NOE is equal to the cross-relaxation rate and, hence,

proportional to r

-6

.

SEQUENTIAL RESONANCE ASSIGNMENT

Sequential resonance assignment of the 1H-NMR spectra of proteins relies on

two sorts of experiments: (1) those demonstrating through-bond scaler

connectivities, and (2) those demonstratlng through-space (<5 Å) connectivities.

The former, which are generally referred to as correlation experiments, serve to

group together protons belonging to the same residue. The latter involve the

detection of NOES and serve to connect one residue with its immediate

neighbors in the linear sequence of amino acids.

The first step in the assignment procedure lies in identifying spin systems, that

is to say, protons belonging to one residue unit in the polypeptide chain. Such

experiments have to be carried out in H2O and D2O, the former to establish

connectivities involving the exchangeable NH protons, and the latter to identify

connectivities between nonexchangeable protons. Some spin systems are

characteristic of several different amino acids. This is the case for Gly, Ala, Thr,

Leu, lle, and Lys. Others are characteristic of several different amino acids.

For example, Asp, Asn, Cys, Ser, and the aliphatic protons of all aromatic

amino acids belong to the AMX spin system (i.e., they all have one CaH and two

C

ßH protons). The experiments used for the identification of amino acid types

are collectively known as correlation experiments and comprise COSY (Aue et

al. 1976) and COSY-type and HOHAHA (Davis and Bax 1985; Bax and Davis

1985, Bax 1988) experiments.

A schematic representation of cross-peak patterns observed in HOHAHA

spectra for the various spin systems is illustrated in figure 3, and an example of

a protein HOHAHA spectrum in H2O is shown in figure 4.

Once a few spin systems have been identified, one can then proceed to identify

sequential through-space connectivities involving the NH, C

aH, and CßH protons

82
FIGURE 3. Schematic representation of cross-peak patterns observed in

HOHAHA spectra for various spin systems. In a COSY spectrum,

only direct connectivities are observed.

83
FIGURE 4. 600 MHz HOHAHA spectrum of IL-8 in H2O showing the NH(F2)-

aliphatic (F1) region of the spectrum. Peaks are labeled at the

positions of the direct NH-CaH connectivities.

SOURCE: Clore et al. 1989.

FIGURE 5. Schematic illustration of the connectivities used for sequential

resonance assignment of protein spectra

84
by means of 2D NOE spectroscopy (NOESY [Macura and Ernst 1980; Macura

et al. 1981]). For the purpose of sequential assignment, the most important

connectivities are the C

aH(i)-NH(i+1,2,3,4), CßH(i)-NH(i+1), NH(i)-NH(i+1), and

C

aH(i)-CßH(i+3) NOES. This is illustrated schematically in figure 5, and an

example of a NOESY spectrum is shown in figure 6.

FIGURE 6. 600 MHz NOESY spectrum of IL-8 in H2O showing the NH(F1)-

NH(F2) region (A) and the NH(F2)-CaH/CßH(F1) region (B) of the

spectrum. A stretch of NH(i)-NH(i+1) connectivities extending

from residues 54 to 72 is indicated in (A) and sequential C

aH(i)-

NH(i+1) connectivities are marked in (B). In addition, several

long-range NOES are labeled.

SOURCE: Clore et al. 1989.

As proteins get larger, problems associated with chemical shift dispersion

become increasingly severe. One approach for alleviating such problems in the

sequential assignment of proteins involves correlating proton-proton throughspace and through-bond connectivities with the chemical shift of a directly

bonded NMR active nucleus, such as 15N or 13C. This experiment can be

carried out on uniformly labeled protein samples that can be easily obtained if

the gene for the protein under investigation has been cloned and

overexpressed.

85
A further avenue for large proteins involves the application of 3D NMR. For 15N

3D spectra, the normal rules for making sequence specific assignments can be

readily applied. The only difference to the normal 2D case is that connections

between one residue and the next must be made not only between different

sets of peaks but also between different planes of the spectrum. The major

advantage going from 2D to 3D is that the distribution of overlapping or closely

spaced cross-peaks throughout the entire cube removes most of the

ambiguities present in the 2D spectrum.

IDENTIFICATION OF SECONDARY STRUCTURE ELEMENTS

Because each type of secondary structure element is characterized by a

particular pattern of short-range (Ii-jI<5) NOES (Wüthrich 1986; Wüthrich et al.

1982, 1984; Billeter et al. 1982; Wagner and Wüthrich 1982), qualitative

interpretation of the sequential NOES allow the identification of regular secondary

structure elements. This is illustrated in figure 7. Thus, for example, helices are

characterized by a stretch of strong or medium NH(i)-NH(i+1) NOES, and medium

or weak C

aH(i)-NH(i+3) NOES, CaH(i)-CßH(i+3) NOES, and CaH(i)-NH(i+1) NOES,

sometimes supplemented by NH(i)-NH(i+2) and C

aH(i)-NH(i+4) NOES. On the

other hand, strands are characterized by strong CaH(i)-NH(i+1) NOES and by the

absence of other short-range NOES involving the NH and C

aH protons. ß-Sheets

can be identified and aligned from interstrand NOES involving the NH, C

aH, and

C

ßH protons. It also should be pointed out that the identification of secondary

structure elements is aided by (1) NH exchange data in that slowly exchanging NH

protons usually are involved in hydrogen bonding and by (2) 3JHNa coupling

constant data. Figure 8 illustrates the application of this method to the protein

interleukin-8 (IL-8) (Clore et al. 1989). Inspection of the short-range NOE data

immediately enables one to identify three ß-strands, several turns, and a long helix

at the carboxy terminus. Although very effective, it should be realized that this

kind of secondary structure determination can be used only in a qualitative

fashion, and accurate positioning of the identified secondary structure elements

can be accomplished only after the complete 3D protein structure has been

determined.

NMR-DERIVED RESTRAINTS

Because of the <r-6> dependence of the NOE, approximate interproton distance

restraints can be derived from the initial slope of the time dependence of the

NOE. Because initial slope measurements are not entirely trivial, one generally

resorts to a qualitative classification of NOES. Empirically, the type of

classification used is one in which strong, medium, and weak NOES correspond

to distance ranges of approximately 1.8-2.7 Å, 1.8-3.3 Å, and 1.8-5.0 Å, where

the lower limit of 1.8 Å corresponds to the sum of the van der Waals radii of two

86
FIGURE 7. Characteristic patterns of short-range NOES involving the NH,

C

aH, and CßH protons seen in various regular secondary structure

elements. The NOES are classified as strong, medium, and weak,

reflected in the thickness of the lines.

87
FIGURE 8. Pattern of short-range NOES involving the NH, C

aH, and CßH

protons, as well as the CßH protons, for IL-8. The intensities of

the NOES are indicated by the thickness of the Iines. In addition,

slowly exchanging backbone amide protons and values of 3

JHNa

are indicated. The secondary structure deduced from these data

is shown at the bottom of the figure.

SOURCE: Clore et al. 1989.

protons. By using such a scheme, variations in effective correlation times do not

introduce errors into the distance restraints. Rather, they only result in an

increase in the estimated range for a particular interproton distance.

Vicinal spin-spin coupling constants can provide useful information

supplementing the interproton distance restraints derived from NOE data. In

particular, ranges of torsion angles can be estimated from the size of the

coupling constants. The latter may be obtained by analyzing the multiplex

patterns in COSY and COSY-like (e.g., DQF-COSY, E-COSY, Z-COSY) spectra.

The easiest coupling constants to determine in proteins are the 3

JHNa coupling

constants that can be obtained by measuring the peak-to-peak separation of

the antiphase components of the C

aH-NH COSY cross-peaks. The size of the

3

JHNa coupling constant is related to the backbone torsion angle through a

Karplus-type relationship (Karplus 1963; Pardl et al. 1984).

88
x1 Side-chain torsion angle restraints and stereospecific assignments can be

obtained by analyzing the pattern of 3Jaß coupling constants and the relative

intensities of the intraresidue NOES from the NH and CaH protons on the one

hand to the two CßH protons on the other, and, in the case of valine, to the CyH3

protons. The 3Jaß coupling constants are related to the x1torsion angle and are

best measured from correlation spectra, which yield reduced multiplets such as

ß-COSY, E-COSY, P.E.COSY, or z-COSY.

ASSIGNMENT OF LONG-RANGE (Ii-jI>5) NOES IN PROTEINS

In globular proteins, the linear amino acid chain is folded into a tertiary structure

such that protons far apart in the sequence may be close together in space.

These protons give rise to tertiary NOES whose identification is essential for

determining the polypeptide fold. Once complete assignments have been

made, many such long-range NOES can be identified in a straightforward

manner. It is usually the case, however, that the assignment of several longrange NOE cross-peaks remains ambiguous due to resonance overlap. In

some cases, this ambiguity can be removed by recording additional spectra.

Where ambiguities still remain, it is often possible to resolve them by deriving a

low-resolution structure on the basis of the available data (i.e., the secondary

structure and the assignment of a subset of all the long-range NOES) either by

model building or by distance geometry calculations. This low-resolution

structure then can be used to test possible assignments of certain long-range

NOES. For larger proteins, it becomes increasingly difficult to assign tertiary

NOES because of the associated overlap problems. In these cases, the 3D

approach will become a necessity, in particular, 13C 3D experiments because

they allow editing with respect to particular side-chain positions for which the

individual NOES then can be extracted. In figure 9, all experimental short- and

intermediate-range NOE restraints (A) and all long-range NOE restraints (B)

that were measured from the NOESY spectra are shown as dotted lines

superimposed on the framework of the finally determined structure of hirudin,

illustrating the dense network of distances throughout the protein core.

TERTIARY STRUCTURE DETERMINATION

Several different approaches can be used to determine the 3D structure of a

protein from experimental NMR data. The simplest approach, at least

conceptually, is model building. This can be carried out either with real models

or by means of interactive molecular graphics. It suffers, however, from the

disadvantage that no unbiased measure of the size of the conformational space

consistent with the NMR data can be obtained. Consequently, there is no

guarantee that the modeled structure is the only one consistent with the

experimental data. Furthermore, in this way, nothing more than a low-resolution

structure can be obtained.

89
FIGURE 9. Short-range interresidue and intraresidue (A) and long-range

interresidue NOE distance restraints (B) shown as dashed lines

superimposed on a framework of the final hirudin structure in a

smoothed backbone representation

The main computational methods for generating structures from NMR data

comprise as a common feature a conformational search to locate the global

minimum of a target function that is made up of stereochemical and

experimental NMR restraints. The descent to the global minimum region is not

a simple straightforward path as the target function is characterized by many

false local minima that have to be avoided or surmounted by all the methods.

There are essentially two general classes of methods. The first can be termed

real-space methods. These include restrained least squares minimization in

torsion angle space with either a variable target function (Braun and Go 1985)

or a sequence of ellipsoids of constantly decreasing volume, each of which

contains the minimum of the target function (Billeter et al. 1987), and restrained

molecular dynamics (Clore et al. 1985, 1986; Kaptein et al. 1985) and

dynamical simulated annealing (Nilges et al. 1988a, 1988b, 1988c) in Cartesian

coordinate space. All real-space methods require initial structures. These can

be (1) random structures with correct covalent geometry; (2) structures that are

far from the final structure (e.g., a completely extended strand); (3) structures

made up of a completely random array of atoms; and (4) structures generated

by distance space methods. They should not, however, comprise structures

derived by model building, as this inevitably biases the final outcome. Because

these methods operate in real space, great care generally has to be taken to

90
ensure that incorrect folding of the polypeptide chain does not occur. A new

real-space approach involving the use of dynamical simulated annealing,

however, has succeeded in circumventing this problem (Nilges et al. 1988a). In

contrast to the real-space methods, the folding problem does not exist in the

second class of methods that operates in distance space and is generally

referred to as metric matrix distance geometry (Crippen 1977). Here, the

coordinates of the calculated structure are generated by a projection from

N(N-1)/2D distance space (where N is the number of atoms) into 3D Cartesian

coordinate space by a procedure known as embedding (Crippen and Havel

1988).

A flow chart of the calculational strategy that is generally used to solve protein

structures is shown in figure 10. Because a detailed description of all the

various methods would go far beyond the scope of this chapter, the interested

reader is referred to the references cited above. (A comparison between the

different methods is given in Clore and Gronenborn 1989.) All the methods are

comparable in convergence power. In general, however, the structures

generated by dynamical simulated annealing or refined by restrained molecular

dynamics tend to be better in energetic terms than the structures generated by

the other methods, particularly with respect to nonbonded contacts and

agreement with the experimental NMR data.

To assess the uniqueness and the precision of the structures determined by

any of the above methods, it is essential to calculate a reasonable number of

structures with the same experimental data set, but with different starting

structures or conditions and to examine their atomic rms distribution. If these

calculations result in several different folds of the protein while satisfying the

experimental restraints, then the data is not sufficient to determine a unique

structure, and either more data must be gathered or the structure determination

has to be abandoned. If, however, convergence to a single fold is achieved

with only small deviations from idealized covalent geometry, exhibiting good

nonbonded contacts in addition to satisfying the experimental restraints, then

one can be confident that a realistic and accurate picture of the solution

structure of the protein has been obtained. The spread observed in the

superposition within the family of structures, or a plot of the rms distribution with

respect to the mean, allows one to assess the precision associated with

different regions of the protein.

EXAMPLES OF NMR SOLUTION STRUCTURES

Hirudin

Hirudin is a small 65-residue protein from the leech and is the most potent

natural inhibitor of coagulation known. It acts by interacting specifically with

91
FIGURE 10. Calculational strategy used to solve 3D structures of

macromolecules on the basis of NMR data

thrombin, thereby preventing the cleavage of fibrinogen. Two recombinant

hirudin variants have been examined by NMR: namely, wild-type hirudin and

the Lys-47 Glu mutant (Folkers et al. 1988). Analysis of the NMR data

indicated that hirudin consists of an N-terminal compact domain (residues 1 to

92
49) held together by three disulfide bonds and a disordered C-terminal tail

(residues 50 to 65). Evidence for the presence of a flexible C-terminal tail was

provided by the absence of any intermediate-range or long-range NOES beyond

amino acid 49. Therefore, structure calculations were restricted to the Nterminal domain using the hybrid distance geometry-dynamical simulated

annealing method. Experimental input data comprised 701 and 677

approximate interproton distance restraints derived from NOE data for the wildtype and mutant hirudin, respectively, 26 backbone and 18 x1

torsion angle

restraints derived from NOE and three-bond coupling constant data, and eight

backbone hydrogen bonds identified on the basis of NOE and amide exchange

data were used as experimental input data. A total of 32 structures were

computed for the wild-type and the mutant hirudins (figure 11). The structure of

residues 2 to 30 and 37 to 48 constitute the core of the N-terminal domain

formed by a triple-stranded antiparallel ß-sheet, and the atomic rms difference

between the individual structures and the mean structure is ~0.7 Å for the

backbone atoms and ~1 Å for all atoms. The orientation of the exposed finger

of antiparallel ß-sheet (residues 31 to 36) with respect to the core could not be

determined because no long-range NOES were observed between the exposed

finger and the core. This is easily appreciated from figure 11 because the

structures in that region exhibit a large spread. Locally, however, the

polypeptide fold of residues 31 to 36 is reasonably well defined.

FIGURE 11. Superposition of the backbone (N, C

a

, C) atoms of 32 dynamical

simulated annealing structures of wild-type hirudin (A) and the

Lys-47 Glu mutant (B) for the first 49 amino acids.The wildtype and mutant structures were calculated on the basis of 701

and 677 interproton distance restraints, respectively, 26 and 1

18 x1 torsion angle restraints.

SOURCE: Folkers et al. 1988.

93
The first five residues form an irregular strand that leads into a loop closed off at

its base by the disulfide bridge between Cys-6 and Cys-14. This is followed by

a miniantiparallel ß-sheet formed by residues 14 to 16 (strand I) and 21 to 22

(strand I’) connected by a type II turn. This ß-sheet is distorted by a ß-bulge at

Cys-16. Strand I’ leads into a second antiparallel ß-sheet formed by residues

27 to 31 (strand II) and 36 to 40 (strand II’) connected by a ß-turn (residues 32

to 35). In addition, residues 10 to 11 exhibit features of a ß-bulge with the

amide of Gly-10 and the carbonyl oxygen atom of Glu-11 hydrogen bonded to

the carbonyl and amide groups, respectively, of Cys-28. Finally, strand II’ leads

into an irregular strand that folds back onto the protein such that residue 47

(Lys in the wild type, Glu in the mutant) is in close proximity to residues in the

loop closed off by the disulfide bridge between Cys-6 and Cys-14. Not only the

backbone but also many of the side-chain conformations are well defined,

especially those in the interior of the protein.

A superposition of the core (residues 1 to 30 and 37 to 49) of the restrained

minimized mean structures of the wild-type and mutant hirudin provides a good

representation of the differences between the two structures (figure 12, panel

A). Regions of noticeable difference can be identified where the atomic rms

difference between the two mean structures is larger than the atomic rms

distribution of the individual structures about their respective means. This

analysis indicates the presence of clear differences for the backbone atoms of

residues 3, 5, 8, 11 to 15, 22, 26, and 27. In the mutant, the backbone atoms of

residues 3, 4, and 11 to 15 are slightly closer to that of residues 45 to 47 than in

the wild type, a change that can be rationalized in terms of the shorter length of

the Glu side-chain relative to that of Lys. Concomitantly, the backbone of

residue 8 appears to be pushed away in the wild-type structure. Residues 22,

26, and 27 also move in the same direction as residues 11 to 15, but this is

secondary to the perturbation of residues 11 to 15 and can be attributed to the

presence of numerous contacts between residues 8 to 11 on the one hand and

28 to 30 on the other, including hydrogen bonds between Cys-28 and Gly-10

and between Cys-28 and Glu-11. There seem to be no significant differences,

however, with respect to the side-chain positions within the errors of the

coordinates, even within the immediate vicinity of residue 47 (figure 12,

panel B).

At this point, it may be worth mentioning that NMR can have two important

applications with respect to genetically engineered proteins. The structural

studies on hirudin were first initiated using natural protein extracted from the

whole body of leeches (Clore et al. 1987b). All further work was subsequently

carried out on recombinant products, either comprising the wild-type sequence

or mutants thereof (Folkers et al. 1988). It was a fast, easy task to assess the

structural identity of the recombinant product, because only a comparison of the

94
FIGURE 12. (A) Superposition of the core (residues 1 to 30 and 37 to 49) of

the restrained minimized mean structure of wild-type (thick lines)

and Lys-47 Glu mutant (thin lines) hirudin

SOURCE: Folkers et al. 1989.

(B) View of all atoms around the site of mutation

SOURCE: Folkers et al. 1988.

appropriate 2D spectra had to be carried out. These spectra can be regarded

as a fingerprint of a particular protein and, hence, a reflection of the 3D

structure in solution. Simple overlay often allows one to ascertain whether the

recombinant product is folded indistinguishably from the natural counterpart. In

the same way, NMR can establish whether the structure of a mutant is

essentially unchanged from the wild-type one, because similar spectra will arise

from closely related structures. Analyses of that kind can be carried out without

a full assignment of the spectra or a complete structure calculation, thus

providing a useful tool for guiding genetic engineering projects.

lnterleukin-8

Communications between different cells of the immune system is achieved in

part by a complex cascade of interacting proteins known as cytokines, one of

which is IL-8, also known as neutrophil activation factor, monocyte-derived

neutrophil chemotactic factor (for a review, see Matsushima and Oppenheim

1989). IL-8 is a dimeric protein composed of two identical subunits, each of

Mr~8,000, which is released from several cell types, including monocytes,

fibroblasts, endothelial cells, and keratinocytes, in response to an inflammatory

stimulus.

95
The pleiotropic properties of IL-8 have important consequences from a medical

and clinical perspective. High levels of IL-8 are found in the synovial fluid of

rheumatoid arthritis patients and in psoriatic lesions, and the role of IL-8 in

several other inflammatory conditions, such as glomerulonephritis, uveities, and

asthma, is being investigated (Matsushima and Oppenheim 1989).

The structure of recombinant IL-8 was determined using the hybrid distance

geometry-dynamical simulated annealing method (Nilges et al. 1988b, 1988c).

The total number of experimental restraints used in the final calculations was

2,242 for the dimer. These comprised a total of 899 interproton distance

restraints within each monomer made up of 392 short-range (Ii-j<5) and 185

long-range (Ii-jI>5 interresidue and 270 intraresidue interproton distance

restraints and 52 hydrogen bonding restraints, 70 interproton distance and 12

hydrogen bonding restraints between the two monomers, and 181 torsion angle

restraints per monomer. The latter comprised 68 61 and 52x1 torsion

angle restraints. Stereospecific assignments were obtained for 38 of the 55 ßmethylene groups per monomer and for the -methylene groups of both glycine

residues. The latter, and four of the ß-methylene stereospecific assignments,

could only be obtained after the initial rounds of calculations.

A total of 30 final simulated annealing (SA) structures were computed. All the

structures satisfy the experimental restraints, and there are no interproton

distance violations greater than 0.3 Å. The deviations from idealized covalent

geometry are small, and the nonbonded contacts as judged by the value of the

quartic van der Waals repulsion term and by the Lennard-Jones van der Waals

energy are good. Residues 1 to 5 of both subunits are completely illdetermined, because no sequential NOES were observed for the first three

residues and only (i,i+1) sequential NOES were observed from residues 3 to 6.

The remainder of the structure, however, is exceptionally well determined with

an overall atomic rms difference between the individual dimer SA structures and

the mean coordinate positions of 0.41±0.08 Å for the backbone atoms and

0.90±0.08 Å for all atoms. The average angular rms difference for the

torsion angles is 8.7±5.9°, and the backbone torsion angles for all nonglycine

residues lie in the allowed region of the Ramachandran plot. The majority of

side-chain positions are also well defined. However, 18 side chains have

atomic rms distributions about the mean coordinate positions larger than 1 Å.

All these are highly solvent accessible, and in the case of eight of them, the 3

Jaß

coupling constants are indicative of multiple x1 side-chain conformations.

Three views of the overall polypeptide fold are shown in figure 13. The

approximate overall dimensions of the IL-8 dimer (excluding side chains) are

30 Å long, 26 Å wide, and 18 Å deep in the view shown in figure 13, panel A.

The structure essentially consists of two antiparallel -helices lying on top of a

96
FIGURE 13. Three stereoviews showing best fit superpositions of the

backbone (N, C

a

, C) atoms of the 30 SA structures of IL-8. The

molecule is viewed down the C2 symmetry axis in (A), which is

located in the center of the ß-sheet halfway between the Ca atom

positions of Arg-26 of the two subunits. The views in (B) and (C)

are rotations about the C2 axis, which lies parallel to the plane of

the paper.

SOURCE: Clore et al. 1990.

97
six-stranded antiparallel ß-sheet. The surface under the ß-sheet is concave

and, except for two lie residues, is composed entirely of hydrophilic and

charged residues. The two symmetry-related helices are ~24 Å long and

separated by a center-to-center distance of ~14 Å. The angle (~172°) between

the long axes of the two helices is slightly less than 180° due to the righthanded twist of the ß-sheet below and, in particular, of strand 1 of one subunit

and strand 1’ of the other. The view of IL-8 shown in figure 13, panel A, is one

looking down the C2

 symmetry axis that is located in the center of the ß-sheet

halfway between the Ca atom positions of Arg-26 of the two subunits; the views

in figure 13, panels B and C, are rotations about the C2 axis that lies parallel to

the plane of the paper. The orientation depicted in figure 13, panel C,

demonstrates most strikingly the exposed position of the two -helices on the

top of the molecule.

The overall structure of the IL-8 dimer is similar to that of the AB dimer in the

recently determined 3 Å resolution crystal structure of the PF4 tetramer (St.

Charles et al. 1989); in particular, the arrangement of the ß-sheet and -helices

is essentially identical.

The orientation of the helix relative to the triple-stranded ß-sheet within each

monomer is stabilized by several hydrophobic interactions. The dimer interface

is stabilized principally by an antiparallel ß-sheet with six hydrogen bonds

between strand 1 from one subunit and strand 1’ of the second. In addition to

these backbone interactions, there are several other stabilizing forces involving

side chains. In particular, there are some hydrophobic contacts and an

electrostatic interaction between the two helices. These interactions further

serve to maintain the orientation of the C-terminal helices, with respect to each

other and to the ß-sheet below.

It is interesting to note that the structure of IL-8 is closely related to the fold of

the domains of the class I major histocompatibility (MHC) antigen HLAA2 determined by x-ray crystallography (Brown et al. 1988) where the sheet is

formed by eight ß-strands, four from each domain, with two helices separated

by ~18 Å running across them at an angle of ~-45°. Thus, the same kind of

general architecture is achieved with two different kinds of ß-pleated sheets in

which the strands run almost orthogonal to each other. In the case of HLA-A2,

the ß-sheet is formed by strands arising from two domains of a single subunit

(i.e., a pseudodimer), whereas in the case of IL-8 and putatively the class II

MHC molecules, it is formed by strands originating from two separate subunits

(i.e., an intermolecular dimer).

The views of the IL-8 structure presented in figure 13 clearly demonstrate the

prominent positioning of the two -helices. They sit on top of the rather flat ß98
sheet domain, with hydrophobic amino acid side chains forming the central

features in the interface; indeed, this -helix represents an almost idealized

amphophilic helix, with hydrophobic residues on the interior face and hydrophilic

residues on the solvent-exposed face.

In light of the structural similarities between the domains of HLA-A2 and

IL-8, it is tempting to speculate on the functional role of the long helix in IL-8. It

may well be that the two long -helices in IL-8 and other related proteins serve

as a major interaction site with the respective receptor. Specific recognition

then would be achieved primarily through the different combinations of polar

and charged residues on the outside of the helix, which would have their

counterparts on the surface of the cellular receptor.

PERSPECTIVE AND CONCLUDING REMARKS

It should be clear from the above discussion that NMR now stands side by side

with x-ray crystallography as a powerful method for 3D structure determination.

What are the limitations of this approach? At present, the NMR approach is

limited to proteins of MW<20,000. Indeed, the largest proteins whose 3D

structures have been determined to date are plastocyanin (99 residues) (Moore

et al. 1988) the globular domain of histone H5 (79 residues) (Clore et al.

1987a), -amylases inhibitor (74 residues) (Kline et al. 1986, 1988) and IL-8 (a

dimer of 72 residues per monomer) (Clore et al. 1990). Virtually complete

assignments, however, have been made for a variety of larger systems, in

particular, hen egg white lysozyme (129 residues) (Redfield and Dobson 1988)

and the lac repressor headpiece-operator complex (MW~15,000) (Boelens et al.

1987) Staphylococcal nuclease (148 residues) (Torchia et al. 1988), and

interleukin-1ß (153 residues) (Driscoll et al. 1990). Further development of

novel techniques based on multidimensional NMR in combination with isotopic

labeling and the introduction of yet more powerful magnet may make it possible

to extend the molecular weight range up to proteins of MW~40,000 in the future.

This, however, probably will present a fundamental limit, as the large linewidths

of such proteins significantly reduce even the sensitivity of 1H-detected

heteronuclear correlation experiments.

At this point, it is appropriate to add a word of caution concerning the practical

limits of structure determination by NMR. It is not always the size or the number

of residues in a particular protein that determines the feasibility of an NMR

structure determination. Other factors play equally important roles, such that

the protein is soluble up to millimolar concentrations, nonaggregating, and

preferably stable up to at least 40°C, particularly for large proteins. A further

consideration is the chemical shift dispersion of the 1H-NMR spectrum. This

depends largely on the structure of the protein under investigation. Proteins

99
that are made up only of -helices, loops, and turns invariably exhibit a fairly

poor proton chemical shift dispersion, while the chemical shift dispersion in ßsheet proteins is usually good. To a certain degree, such problems associated

with chemical shift degeneracy can be overcome by heteronuclear 3D

experiments.

Another potential problem may arise from the fact that different regions or

domains of a protein may be well defined and, therefore, amenable to an NMR

structure determination, while other parts of the same protein may not. This is

reflected in the absence of long-range tertiary NOES for the ill-defined regions

and leads to the inability to position these regions with respect to the rest of the

protein satisfactorily (e.g., the case of hirudin discussed above). We therefore

believe that it is necessary to calculate a reasonable number of structures (ca.

20) with the same experimental data set to obtain a good representation of the

NMR structure. Only by analyzing such a family of structures can the local and

global definition of a structure be assessed.

X-ray crystallography, of course, also has its limitations, the most obvious being

the requirement for a protein to crystallize. Thus, suitable crystals that diffract

to high resolution have to be grown, and a successful search for heavy-atom

derivatives to solve the phase problem is necessary. Therefore, not every

protein will be amenable to NMR and x-ray crystallography. In those cases

where this is feasible, the information afforded by NMR and crystallography is

clearly complementary and may lead to a deeper understanding of the

differences between the solution and crystalline state of the protein.

Finally, it should be stressed that, in addition to being able to determine 3D

structures of proteins, NMR has the potential to address other questions, in

particular, those concerning the dynamics of the system. This opens the

possibility for a variety of different NMR studies, initiated on the basis of an

NMR structure, such as the investigation of the dynamics of conformational

changes upon ligand binding, unfolding kinetics, conformational equilibria

between different conformational states, fast internal dynamics on the

nanosecond time scale and below, and slow internal motions on the second

and millisecond time scales. The results obtained from these kinetic studies

can then be interpreted in the light of the previously determined structure, thus

bringing together structure and dynamics of proteins in a unified picture.

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Wüthrich, K.; Billeter, M.; and Braun, W. Polypeptide secondary structure

determination by nuclear magnetic resonance observation of short protonproton distances. J Mol Biol 180:715-740, 1984.

Wüthrich, K.; Wider, G.; Wagner, G.; and Braun, W. Sequential resonance

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1982.

104
Zuiderweg, E.R.P., and Fesik, S.W. Heteronuclear three-dimensional NMR

spectroscopy of the inflammatory protein C5a. Biochemistry 28:2387-2391,

1989.

ACKNOWLEDGMENT

The work in the authors’ laboratory was supported in part by the AIDS-targeted

Anti-Viral Program of the Office of the Director of the National Institutes of

Health.

AUTHORS

Angela M. Gronenborn, Ph.D.

Senior Scientist

G. Marius Clore, M.D., Ph.D.

Senior Scientist

Laboratory of Chemical Physics

National Institute of Diabetes and Digestive and Kidney Diseases

National Institutes of Health

Bethesda, MD 20892

105
Combined Use of Solid-State Nuclear

Magnetic Resonance Spectroscopy,

Small-Angle X-Ray Diffraction, and

Differential Scanning Calorimetry in

Studies of Cannabinoid: Membrane

Interactions

Alexandros Makriyannis, De-Ping Yang, and Thomas

Mavromoustakos

INTRODUCTION

Because of their complexity and inherent instability, membranes do not lend

themselves to a detailed analysis of their structure and dynamics by means of a

single physicochemical method. It is, therefore, preferable to combine several

experimental methods when seeking to obtain molecular information on the

interactions of drugs with membranes. This chapter describes how three

biophysical techniques—differential scanning calorimetry (DSC), small-angle xray diffraction, and solid-state nuclear magnetic resonance (NMR)

spectroscopy—can be combined for such studies. For example, this chapter

includes some results from our work with cannabinoids, which appear to induce

their physiological effects, in part, by interacting with cellular membranes. Our

studies have shown that cannabinoid analogs, which are closely related to each

other in structure, can produce strikingly different effects on membrane

preparations. These differences are used to explain the respectively large

differences in pharmacological potencies among the analogs.

DRUG: MEMBRANE INTERACTIONS

The interactions of many drug molecules with cellular membranes play an

important role in determining drug activity. This role can be dual: (1) The drug

may induce changes in membrane function through the perturbation of one or

more membrane components; and (2) lipophilic drugs may diffuse through the

membrane lipid bilayer to reach some specific site(s) of action on a

106
membrane-associated protein. Thus, it has been argued (Herbette et al. 1986)

that for some groups of drugs the location and orientation of the drug molecule

in the membrane are critical in determining its ability to reach its site(s) of action

in the proper orientation and/or conformation so that it can interact productively

with that site.

Evidence indicates that many of the biological properties of cannabinoids can

be attributed to their effects on biological membranes (Lawrence and Gill 1975;

Bach et al. 1976). These effects may involve amphipathic interactions either

with the membrane lipids or with noncatalytic sites in membrane-associated

proteins leading to conformational changes at the catalytic sites of those

proteins whose functions are affected. Our studies sought to determine the

structural requirements for cannabinoid activity by comparing the effects

produced on membranes by a group of analogs that are closely related in

structure but have different pharmacological potencies (Makriyannis et al. 1986;

Kriwacki and Makriyannis 1989). For a more complete understanding of

cannabinoid: membrane interactions at the molecular level, we also studied the

orientation, conformation, and location of the cannabinoids in the membrane.

This chapter compares the psychotropically active (—) tetrahydrocannabinol

-THC) with its inactive O-methyl-ether analog (Me- THC) (Edery et al.

1971; Razdan 1986) and examines the role of the phenolic hydroxyl group in

cannabinoid activity.

DSC (Jain and Wu 1977), small-angle x-ray diffraction (Franks and Lieb 1979;

Herbette et al. 1983), and solid-state 2H-NMR (Dufourc et al. 1984; Makriyannis

et al. 1985, 1986, 1989; Auger et al. 1988) all have been used to study the

effects of drugs on membranes. Each method has distinct advantages and

limitations and when used independently can give only partial information.

However, the three methods can be complementary when combined and can

lead to a more detailed understanding of the molecular features of the drug/

membrane interaction. DSC is a relatively inexpensive technique that allows

quantitative study of the thermotropic properties of membranes and the

effects of drugs on these properties. Small-angle x-ray diffraction provides

information on the unit cell repeat distance and packing of the membrane

bilayer. Solid-state NMR gives the most detailed molecular information on

membrane conformation and dynamics and on the effects of drugs on each.

NMR also can be used to identify the orientation and conformation of the drug

molecule in the membrane.

The first part of this chapter outlines the basic principles for each of the three

biophysical methods and presents appropriate examples; the second part

demonstrates how these methods can be combined to yield detailed information

on drug: membrane interactions.

107
DIFFERENTIAL SCANNING CALORIMETRY

DSC is a thermodynamic technique suitable for studying phase transitions of

various materials. It has been used extensively to investigate the thermotropic

properties of membranes and obtain information on the effects of drugs on

membranes. In a DSC experiment, a sample and a reference “inert” material

are heated simultaneously at identical rates. If there is no phase transition, the

differential heat flow between the sample and the reference is zero. During the

phase transition, when the sample undergoes a thermally induced event, the

control system senses the resulting temperature differential between the sample

and reference cells and supplies heat to the sample cell to hold its temperature

equal to that of the reference. The term “scanning” signifies that the

temperatures of both the sample and the reference are varied in the same

programed rate and that the excess specific or differential heat is recorded as a

function of temperature. The area under the peak during the thermal event

permits calculation of the enthalpy of transition (Ladbrooke and Chapman

1969; Jürgen and Sturtevant 1972; Melchior and Steim 1976).

Certain hydrated phospholipids spontaneously form bilayers that share many

conformational and dynamical properties with the natural membranes. Studies

with these fully hydrated phospholipids are, therefore, useful because they

allow insight into the physical chemistry of lipid interactions in natural

membranes in which phospholipids are believed to exist, largely as liquid

crystalline bilayers (Steim et al. 1969).

Among membrane phospholipids, phosphatidylcholines are a major component

whose phase properties have received much attention. An example for L

dipalmitoylphosphatidylcholine (DPPC) is given in figure 1. The thermograms

for a fully hydrated DPPC preparation show two endothermic transitions in the

temperature range usually used to study membranes: a broad low-enthalpy

pretransition (T’c=35.3°C) and a main transition (Tc=41.3°C). Below the

pretransition, the phospholipid molecules are arranged in a one-dimensional

lamellar gel phase (Lß’); above the main transition they exist in the liquid

crystalline phase (La

). At temperatures between T’c and Tc, there is a ripple

phase (Pß’), which, on the basis of solid-state NMR evidence, has been shown

to be composed of coexisting gel and liquid crystalline components. These

phase transitions also can be detected by small-angle x-ray diffraction and

solid-state NMR. However, DSC is a simple and accurate method that can be

used to study the gel-to-liquid crystalline phase transitions in phospholipid

bilayers and biological membranes (McElhaney 1982).

The effects of more than 100 compounds on the thermotropic behavior of DPPC

were investigated by Jain and Wu (1977), who stated that lipophilicity of a

108
FIGURE 1. Thermogram of hydrated DPPC bilayers (50 percent w/w) using a

scanning rate of 2.5°C/min

molecule cannot always explain its localization in the membrane. In contrast,

the localization of a molecule in a lipid bilayer is determined by the presence of

the polar and apolar groups in the compound and by the geometric

arrangements of these groups within the molecule.

SMALL-ANGLE X-RAY DIFFRACTION

X-ray diffraction is a useful and direct method for characterizing materials

having periodicity in their structures. Lipid bilayers can be packed into a stack

of lamellae that give coherent Bragg-like reflections. Thus, information can be

obtained about bilayer structures and about the effects of drugs on them

(Franks and Levine 1981).

109
X-rays are produced by bombarding a metal target (almost always copper) with

electrons that have been accelerated through a voltage of about 30 to 40 kV.

These x-rays consist mainly of a Cu Ka spectral line at 1.54 Å, Kß at 1.34 Å, and

a broad background whose wavelength distribution is determined by the

accelerating voltage. Nickel foils are used to eliminate the Cu Kß line and cause

only a tolerable reduction in the intensity of the Cu Ka

 radiation. The x-rays then

are collimated into either a fine line or a point by a system of pinholes or by a

combination of reflecting mirrors and crystal monochromators. In the specimento-detector path, hellum is used to prevent intensity loss due to air scattering.

X-ray diffraction data then can be collected by using either a stack of films or a

position-sensitive detector. To prevent overexposure of the films or damage of

the detector by the intense main beam, a small beam-stop is required.

Regularly stacked lipid bilayers give various diffraction orders that are

approximately equally spaced and follow Bragg’s law—2d sin —where d is

the unit cell repeat distance (d-spacing), is called the Bragg angle (<15°), h is

the order number, and is the wavelength of the Ka radiation. Bragg’s law

reveals the d-spacing from the known wavelength and measurable angle

To obtain finer details on membrane structure, diffractions at larger angles must

be used (Shipley 1973; Silver 1985).

From the diffraction pattern, the electron density profile structure of the

membrane can be derived by assuming that the electron density profile is

centrosymmetric and the membrane stack has a characteristic time-averaged

electron density distribution only in the dimension perpendicular to the

membrane plane. This one-dimensional projection is considered as a

continuous distribution of electron density that repeats periodically (Franks and

Levine 1981). Figure 2 shows examples of diffraction patterns of partially

hydrated dimyristoylphosphatidylcholine (DMPC) bilayers at temperatures

below and above the phase transition and the corresponding derived electron

density profile structures.

The x-ray diffraction pattern shows that the d-spacing of the bilayer decreases

when going from the gel to the liquid crystalline state. This is due to an

increased gauche: trans conformer ratio in the methylene segments of the

bilayer chains in the liquid crystalline phase. On this basis, x-ray diffraction

experiments can be used to obtain information on the conformational properties

of the bilayer chains. On the other hand, d-spacing measurements as a

function of temperature provide information about the phase transition of the

membrane, including phase transition temperatures and the sharpness of these

transitions. In this aspect, x-ray diffraction is complementary to DSC.

110
FIGURE 2. Diffraction patterns of DMPC bilayers at a relative humidity (RH)

of 98 percent below and above its phase transition and their

corresponding derived electron density profile structures

111
Small-angle x-ray diffraction in drug research is useful in obtaining information

on the location of a drug molecule in the membrane. This method is based on

comparing the electron density profile from a membrane preparation serving as

a control with that from an identical membrane preparation into which the drug

molecule is incorporated. The observed differences allow determination of the

approximate location of the drug in the bilayer (Franks and Lieb 1979; Herbette

et al. 1986).

SOLID-STATE NUCLEAR MAGNETIC RESONANCE

Since the early 1960s NMR has found many useful applications in biochemistry

and other related fields of research. It is the method of choice for obtaining

detailed molecular and dynamic information on the interaction of ligands with

functional biopolymers. In this regard, it has been used to study drug: activesite interactions and provide information for rational drug design.

To date, most of this work has made use of high-resolution NMR, which is most

successful if both ligand and biopolymer are present in solution. However, in

spite of its wide applicability in the study of biological systems, high-resolution

NMR suffers from serious limitations. Principal among these is the inability to

obtain well-resolved spectra from relatively large biopolymers (molecular

weight>25,000) because of severe line broadening. These difficulties can be

circumvented with the use of solid-state NMR techniques. During the past

decade these methods have led to previously unavailable detailed molecular

information on the conformational and dynamic properties of proteins and

membranes (Griffin 1981).

The solid-state NMR experiment can be carried out by observing the wide-line

spectrum obtained from one or a small number of nuclei in the system under

investigation. In such experiments, the sample is stationary and the nucleus

under observation either is introduced by isotopic labeling (e.g., 2H, 13C) or is

already present in natural abundance in the system (e.g., 31P, 14N). Information

from the spectra then is obtained by lineshape analysis, including spectral

simulations based on specific conformational and motional models,

Alternatively, the spectrum from the solid or semisolid sample can be obtained

in high-resolution mode using the magic angle sample spinning experiment

(Groot et al. 1988). Such spectra resemble those obtained from solution and

can be analyzed using analogous principles.

Stationary solid-state 2H-NMR has been used to obtain information on the

conformational and dynamic properties of model and biological membranes

(Fyfe 1983; Davis 1983; Smith and Oldfield 1984). The use of solid-state 2HNMR also has been extended successfully to study drug: membrane

112
interactions (Smith 1983; Makriyannis et al. 1985, 1986; Auger et al. 1988).

This method finds application in systems undergoing anisotropic motions such

as with phospholipid multilamellar bilayers or biological membranes

(semisolids). In such systems the deuterium nuclei give rise to a “powder

spectrum” in which the doublet with the maximum intensity is the 2H

quadrupolar splitting and is equal to (Davis 1983)

where e

2

qQ/h is the static quadrupolar coupling constant, which for paraffinic

C—D bonds is approximately 170 kHz. SCD is the order parameter, which can

be used to describe the amount of motional averaging of the C—D bond vector

with respect to a fixed symmetry axis and has been used as a measure of

membrane “fluidity.”

Figure 3 is an example of solid-state 2H-NMR spectra of aqueous dispersions of

DPPC, 2H-labeled in the 7’-methylene group of the sn-2 chain, at a temperature

range covering three phases. At 42°C, the hydrated 2[7’, 7’-2H2

]-DPPC

(Makriyannis et al. 1986) is in the liquid crystalline phase and gives rise to a

powder pattern similar to that observed in the 2H spectrum of a solid. However,

the quadrupolar splitting is drastically reduced due to motional averaging,

including axial diffusion of the chains and gauche: trans isomerization in the

methylene chain segments. Its spectrum is axially symmetric with sharp parallel

and perpendicular edges and has a residual quadrupolar splitting of =28.1

kHz. As the temperature is raised, the values decrease, indicating an

increase in the gauche: trans conformer ratio in the chains. When the

preparation exists in the Pß’ phase (36°C), the spectrum is broadened, but it has

a flattop appearance and only its perpendicular edges are discernible. This

spectral appearance is compatible with the existence of two exchanging

components, a gel component and a liquid crystalline-like one. At 17°C, the

preparation exists in the gel phase and gives a broadened spectrum having a

conical shape with a round top.

Solid-state 2H-NMR also can be used to study the orientation of drug molecules

in membrane bilayers. The study requires the strategic introduction of 2H labels

in different positions of the rigid part of the molecule. The spectra due to the 2H

labels on the drug molecule in the liquid crystalline phospholipid bilayer have

quadrupolar splittings that depend on the angle between the individual C—D

bonds and the director axis. If, as expected, the drug molecule undergoes

anisotropic motions in the bilayer, then each deuteron attached to the rigid part

will be expected to have an 2H quadrupolar splitting described by the following

equation:

113
where is the angle between the C-2H bond in question and the director axis.

The last term, which is known as the molecular order parameter (Smol),

describes the anisotropic motion of the rigid component. Because Smol is

FIGURE 3. Solid state 2H-NMR spectra representing the three phases for

DPPC aqueous dispersions within the temperature range at which

studies were conducted

NOTE: The solid state 2H-NMR spectra due to the 2[7’, 7’-2H2

] segment of

DPPC was obtained using a 90° 90° quadrupolar echo pulse

sequence at 45.3 MHz with a 90° pulse width of 2.1 μs; 8,000 echoes

were signal averaged.

114
expected to be identical for all 2H atoms attached to the rigid part of the

molecule, the value of the observed quadrupolar splitting thus can be directly

related to lf the DvQ values for a set of deuterons are available, one can then

obtain a value for Smol and a set of values for which give the orientation of the

director axis. Because this axis is assumed to be parallel to the bilayer chains,

the orientation of the drug molecule in the bilayer can be determined.

This method was initially introduced for molecules undergoing symmetric axial

rotation in the bilayer (Taylor et al. 1981; Ekiel et al. 1988). Recently, we

modified this method to include molecules undergoing asymmetric axial motions

and, thus, expanded its scope significantly (Makriyannis et al. 1989).

CANNABINOID: MEMBRANE INTERACTIONS

Extensive studies on the structure-function correlation of cannabinoids have

shown that removal of the phenolic hydroxyl group or methylation to give the

corresponding O-methyl ether results in an analog devoid of biological activity

(Edery et al. 1971; Razdan 1986). In this example, the effects of THC on

membranes are compared with those of Me THC.

Differential Scanning Calorimetry

Normalized thermograms of fully hydrated DPPC preparations containing

increasing concentrations of THC and Me THC are shown in figure 4. A

low THC: DPPC molar ratio (5:95, or x=0.05) produces elimination of the

pretransition and broadening of the main transition. At a higher drug

concentration (x=0.10), the main transition broadens and moves down in

temperature, while two new broad peaks appear in the thermogram at lower

temperatures. When the drug concentration is increased to x=0.20, the middle

peak intensifies and becomes the dominant one in the thermogram (table 1).

The DSC results of THC: DPPC data closely correspond to those of another

active THC isomer, the naturally occurring (—) tetrahydrocannabinol

THC) (Van der Schyf et al. 1988). In all of the above thermograms, the phase

transition enthalpy remains essentially unchanged.

The thermotropic effects of Me THC on DPPC bilayers are different from

those of THC. At x=0.05 the pretransition is still observable, although

broadened. The main transition has the same halfwidth as that of the pure

hydrated lipid, with only a small decrease in Tc

. At higher drug concentrations

(x=0.10, x=0.20), there is still no appreciable change in the onset of the main

transition; only a progressive broadening of the transition is observed, and a

shoulder appears at the low temperature end when x=0.20.

115
FIGURE 4. Normalized thermograms of DPPC preparations containing

increasing concentrations of THC and Me THC

KEY: (A) x=0.00; (B) x=0.05; (C) x=0.10; (D) x=0.20

The experiments show that only the active cannabinoid associates or

complexes with the phospholipids in the bilayer, in contrast with the inactive

one, which does not appear to participate in such interactions. These results

indicate that the presence of a free phenolic OH seems to be a necessary

requirement for the formation of the THC: DPPC complex.

116
TABLE 1. Effect of (—) THC and (—)-O-methyl THC on the onset

temperature, midpoint transition temperature (Tc), and enthalpy

change of hydrated DPPC obtained by DSC

Concentration Onset Temperature Tc DH

Cannabinoid (x) (C) (C) (cal/g)

0.05 37.9 39.6 10.5

(—) THC 0.10 32.1 27.5,35.0,38.0 9.7

0.20 27.5 26.5,29.2,35.5 10.9

0.05 38.2 39.9 10.3

(—)-O-mathyl THC 0.10 37.5 39.6 9.9

0.20 38.4 35.2 10.0

X-Ray Diffraction

Small-angle x-ray diffraction was used to study the location of the biologically

active -THC in a partially hydrated model membrane and obtain direct

evidence on the topography of the drug in the bilayer. We compared the

electron density profiles of DMPC bilayers containing -THC and those with

(—)-5’-iodo tetrahydrocannabinol (5’-I -THC), a molecule that contains the

heavy atom iodine at the end of the alkyl chain, and obtained an estimate of the

position of the iodine atom in the bilayer. To describe the differences in electron

density profiles, the centrosymmetric bilayer profile was divided into three

regions (figure 5). Region I (from 0 to±9Å) covers the terminal methyl groups

and the last 5 to 6 methylene segments of the acyl chains. Region II (from ±9Å

to ±20Å) covers the remaining methylene segments and the interface, up to the

headgroup region. Region Ill (from±20Å to ±d/2) covers the rest of the

headgroup and the water region between the bilayers. The electron density is

the number of electrons per unit volume and is denoted by e/v.

Some representative electron density profiles of pure DMPC, DMPC+ -THC,

and DMPC+5’-I THC at RH 98 percent are shown in figure 6. A careful

comparison shows that the presence of the cannabinoid always enhances the

e/v in region II. This enhancement is centered in a region approximately 13Å

from the center of the bilayer and strongly suggests that the drug molecule is

located in region II (i.e., at or near the amphipathic interface of the bilayer).

Thus, it appears that the cannabinoid may anchor itself to the bilayer interface

through its phenolic hydroxyl group, probably by hydrogen bonding with the

ether or the carbonyl oxygens of the lipid molecule. When comparing the

electron density profiles of DMPC+ -THC and DMPC+5’-I THC at RH 98

percent, we observed that the e/v difference was in region I (below and above

117
FIGURE 5. Schematic correlation between an electron density profile and a

space filling model of a phospholipid bilayer, with the

centrosymmetric bilayer divided into regions I, II, and III

Tc). This enhancement is centered at approximately 6Å from the center of the

bilayer and is due to a contribution from the iodine atom of 5’-I THC (figure

7). This is evidence that the cannabinoid side chain exists in an extended

conformation in the bilayer and runs parallel with the bilayer chains.

Also, the temperature dependence of the d-spacing of DMPC bilayers was

compared with those containing THC (figure 8). The results show again that

118
FIGURE 6. Comparisons of the electron density profiles of DMPC (solid line),

DMPC+D6-THC (x=0.15, short dashed line), and DMPC+5’-I-D6-

THC (x=0.15, long dashed line) at RH 98 percent

-THC induces significant changes in the d-spacing of DMPC, whereas the

profile of DMPC+Me -THC differs only slightly from that of DMPC. As with

DSC, these data provide evidence that the active cannabinoid THC induces

severe changes in the conformational and phase properties of the membrane

bilayer, whereas the inactive O-methyl analog alters the membrane properties

significantly less.

119
FIGURE 7. Representation of 5’-I THC molecule (two different

perspectives) in a DMPC bilayer based on results from x-ray

diffraction and solid-state 2H-NMR experimental data

120
FIGURE 8. D-spacing as a function of temperature for bilayers of DMPC

(circles and solid lines) and DMPC+ -THC (x=0.15, triangles and

dashed lines) at RH 98 percent

Solid-State Nuclear Magnetic Resonance

The phase properties of hydrated DPPC preparations as described earlier are

reflected in the respective solid-state 2H-NMR spectra from 1,2[2’, 2’-2H2]-DPPC.

Figure 9 shows representative spectra obtained from the model membrane

preparation in the absence and presence of THC (x=0.20) or Me THC

(x=0.20).

In the liquid crystalline phase (45°C), the 2H spectrum of DPPC shows three

components represented by three quadrupolar splittings. According to Seelig

(1977), the largest splitting corresponds to the two deuterons at the C-2’

position of the sn-1 chain and the other two splittings to the corresponding

deuterons on the sn-2 chain. This inequivalence of the spectra due to the sn-1

and sn-2 C

2H2

 segments has been attributed to the different average

conformations of the chains in the region of the glycerol backbone. At 39°C the

121
FIGURE 9. Temperature dependence of solid-state 2H-NMR spectra due to the 1,2[2’, 2’-2H2

] segment of DPPC

KEY: (A) DPPC; (B) DPPC+ THC (x=0.20); (C) DPPC+Me -THC (x=0.20)
spectrum from pure DPPC exhibits the flattop lineshape characteristic of the Pß,

phase. THC produces significant changes in the spectra of 1,2[2’, 2’-2H2]-

DPPC, whereas its O-methyl ether analog has little effect. The -THC/DPPC

preparation gives a three-component La-type spectrum, and Me THC/DPPC

gives a spectrum in which the gel and liquid crystalline phases are discernible.

At 33°C the spectra from pure DPPC and Me -THC/DPPC are virtually

identical with no sharp features in their lineshapes. On the other hand, the

THC/DPPC spectra show the characteristic features described earlier, with

sharp perpendicular edges but no parallel edges. Only two of the three

components observed in the La

 spectrum can be seen. The third intermediate

component is invisible, probably due to broadening in the other two. This type

of spectrum is evidence for the presence of a mix of gel and liquid crystalline

components undergoing intermolecular exchange at an intermediate rate.

As already observed in the DSC and x-ray diffraction experiments, THC

decreases the main phase transition by 6°C, while Me THC produces a

decrease of less than 2°C. The phase transition of DPPC/ THC is more

gradual than that of pure DPPC, and the spectra retain more liquid crystalline

features. Although the presence of -THC produces no qualitative changes in

the La bilayer lineshapes of DPPC, it does increase the quadrupolar splittings in

all three spectral components (table 2). The increase is more significant with

the two components representing the sn-2 chain. This effect may be interpreted

to indicate a closer interaction of the drug molecule with the sn-2 chain in the

bilayer and could be the result of a slight increase in the trans: gauche

methylene conformer ratio. Alternatively, the increased values may be

associated with small drug-induced changes in the orientation of the C

2H2

segment with respect to the bilayer surface. The methyl ether analog produces

no significant changes in the quadrupolar splittings of the DPPC preparation.

The data point to the significance of the phenolic hydroxyl group in

cannabinoids during their interactions with membranes. These effects are

almost entirely reversed when hydroxyl hydrogen is substituted with the

hydrophobic methyl group.

The above conclusion is further strengthened by results from experiments

aimed at determining the orientation of THC and Me THC in DPPC

multilamellar bilayers. This study required the introduction of 2H labels in

different positions of the tricyclic cannabinoid system. For this experiment, we

synthesized THC and Me- -THC with specific deuterium labels in the 2, 4,

8, 10 , 10ß, and 10a positions. 2H-NMR spectra were obtained for preparations

containing one or more 2H labels that could be unambiguously assigned in the

solid-state spectra. Calculations (Makriyannis et al. 1989) showed that -THC

orients with the long axis of its tricyclic structure perpendicular to the bilayer

chains (figure 10). Presumably, this “awkward” orientation optimizes the

123
TABLE 2. Solid-state 2H-NMR quadrupolar splittings for 1,2[2’, 2’-2H2

] DPPC

preparations in the absence and presence of drug molecule

(x=0.20) at 45°C

(kHz)

Chain DPPC DPPC+ THC DPPC+Me- THC

sn-1 26.8 7.4 26.5

17.8 9.3 17.7

sn-2 12.0 14.1 12.1

interaction of the cannabinoid OH group with the polar membrane groups. On

the other hand, calculations showed that Me- -THC assumes an orientation in

which the long axis of the tricyclic structure is parallel to the lipid chains (figure

10). From geometrical and mechanical points of view, that the drug’s rotation

axis coincides with its natural long axis points to the absence of hydrogen

bonding between Me- THC and the lipid bilayer. This may explain the inability

of this molecule to effectively perturb the membrane at the interface.

The striking difference between the orientations of -THC and its O-methyl

ether analog in DPPC provides evidence that the anchoring effect by the THC

phenolic OH on the membrane determines its orientation in the bilayer. The

results also suggest that the orientation of cannabinoids in the amphipathic

membrane may play an important role in determining the nature of the drug:

membrane interaction and the drug’s ability to induce productive membrane

perturbations. The above conclusions on the location and orientation of the

biologically active (—)- -THC also may have some bearing on those

cannabinoid effects that may be produced through interactions with specific

sites on one or more membrane-associated proteins. Assuming that the

cannabinoid preferentially partitions in the membrane bilayer then reaches the

protein sites through lateral diffusion, its ability to reach these sites is

determined to a large extent by its location and conformation in the bilayer. It is

tempting to speculate that the cannabinoid sites on the protein(s) are present

at the level of the bilayer interface and that the conformation of (—)- -THC

in the membrane, as described here, allows it to engage in the productive

drug: active-site interactions.

124
FIGURE 10. The orientations of -THC (A) and Me- -THC (B) in hydrated

DPPC bilayers as determined by solid-state 2H-NMR

NOTE: Dashed lines indicate the direction of the lipid chains.

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AUTHORS

Alexandros Makriyannis, Ph.D.

Professor

De-Ping Yang, Ph.D.

Assistant Professor

Thomas Mavromoustakos, Ph.D.

Postdoctoral Fellow

127
Section of Medicinal Chemistry and Pharmacognosy

Institute of Materials Science

University of Connecticut School of Pharmacy

U92

Storrs, CT 06269

Francis Bitter National Magnet Laboratory

Massachusetts Institute of Technology

Cambridge, MA 02139

128
Characterization and Localization of

Cannabinoid Receptors in Brain: An In

Vitro Technique Using Slide-Mounted

Tissue Sections

Miles Herkenham

INTRODUCTION

Marijuana (Cannabis sativa) is one of the oldest and most widely used drugs in

the world, with a history of use dating back over 4,000 years (Harris et al. 1977;

Mechoulam 1986). It was not until about 20 years ago that the principal

psychoactive ingredient of the marijuana plant was isolated and found to be

tetrahydrocannabinol -THC) (Gaoni and Mechoulam 1964; Mechoulam 1973;

Mechoulam et al. 1970). -THC and other natural and synthetic cannabinoids

produce characteristic behavioral and cognitive effects (Dewey 1986; Hollister

1986), most of which can be attributed to actions on the central nervous system

(Martin 1986). However, until recently, very little was known about the cellular

mechanisms through which cannabinoids act. The unique spectrum of

cannabinoid effects, coupled with evidence of stereoselectivity of action of

cannabinoid isomers (see below), strongly suggested the existence of a specific

cannabinoid receptor in brain, but attempts to identify and characterize such a

recognition site were not successful. As discussed by Devane and colleagues

(1988), cannabinoids are extremely hydrophobic and adhere to fitters and other

surfaces (Garrett and Hunt 1974). Other obstacles in the early attempts to

characterize the receptor were (1) the use of [3H] -THC (Harris et al. 1978) or

[

3H] -THC (Roth and Williams 1979), which bind with low affinity and have low

specific activities, and (2) the use of [

3H]5’-trimethylammonium- -THC (Nye et

al. 1985), which is water-soluble but does not act like a cannabinoid in animal

tests.

Without evidence that cannabinoids act through a specific receptor coupled to a

functional effector system, researchers were prone to study the effects of

cannabinoids on membrane properties (Hilliard et al. 1985), second

messengers, metabolism, and other neurotransmitter systems in vitro (Pertwee

1988). Most of the biochemical studies employed concentrations of -THC that

129
were far in excess of physiologically meaningful concentrations that might be

found in brain (for a review, see Martin 1986; Pertwee 1988).

In many of these studies, the criterion of structure-activity correlation was not

met—that is, the potencies of various cannabinoids in the in vitro assays bore

no resemblance to their relative potencies in eliciting characteristic behavioral

effects. Particularly damaging to the relevance of these in vitro studies was the

absence of stereoselectivity or enantioselectivity. In contrast, Martin’s group

had found that the potencies of (-) and (+) forms of each of the cis and trans

isomers of -THC differ by 10- to 100-fold in producing static ataxia in dogs,

depressing schedule-controlled responding in monkeys, and producing

hypothermia and inhibiting spontaneous activity in mice (Martin et al. 1981).

Similarly, Hollister and coworkers (1987) had shown cannabinoid

enantioselectivity in human studies using indices of the subjective experience,

or “high.”

May’s group had found enantioselectivity of a series of synthetic compounds in

tests of motor depression and analgesia (Wilson and May 1975; Wilson et al.

1976, 1979). One of these compounds, (-)9-nor-9ß-hydroxyhexahydrocannabinol (ß-HHC), was used as a starting compound by Johnson and Melvin

(1986) for the synthesis of a rather large series of structurally novel

cannabinoids for studies of their potential use as analgesics (figure 1). The

synthetic cannabinoids shared physicochemical properties with the natural

cannabinoids and produced many behavioral and physiological effects

characteristic of -THC, but were 5 to 1,000 times more potent and showed

high enantioselectivity.

The availability of these Central Pfizer (CP) compounds revolutionized the study

of the biochemical basis of cannabinoid activity. Hewlett’s group used them in

neuroblastoma cell lines to show inhibition of adenylate cyclase activity (Howlett

et al. 1988). Such inhibition was enantioselective, and the pharmacological

profile correlated well with that observed by Martin’s group, which showed

similar orders of potencies for the CP compounds in tests of mouse

spontaneous activity, catalepsy, body temperature, and analgesia (Little et al.

1988).

One of the compounds, CP55,940, was tritiated and used to identify and fully

characterize a unique cannabinoid receptor in membranes from rat brain

(Devane et al. 1988). The centrifugation assay showed that the [

3H]CP55,940

binding site is saturable, has high affinity and enantioselectivity, and exhibits

characteristics expected for a neuromodulator receptor associated with a G

protein. The slide-mounted section assay, described in this chapter, is used to

130
FIGURE 1. Chemical structures of -THC and three synthetic cannabinoids

NOTE: According to the nomenclature of Johnson and Melvin (1986), -THC

and ß-HHC are defined as members of the ABC-tricyclic cannabinoid

class. CP55,940 is a hydroxypropyl analog of a 2-(3-hydroxycyclohexyl)phenol, defined as an AC-bicyclic cannabinoid. CP55,244 is

an ACD-tricyclic cannabinoid with a rigidly positioned hydroxypropyl

moiety.

SOURCE: Herkenham et al. 1990.

131
characterize and validate the binding of [

3H]CP55,940, and the same assay is

used to autoradiographically visualize the distribution of cannabinoid receptors.

MATERIALS AND METHODS

To perform exhaustive optimization and characterization studies before

autoradiographic analysis, many brain sections of uniform composition and size

are required. For these kinetics studies, bound radioactivity is determined by

liquid scintillation counting; therefore, heterogeneity of receptor distribution from

section to section must be avoided. Relative uniformity of receptor content was

created by preparing rat brain “sausage” sections. These sections were

prepared by placing three whole rat brains (removed fresh after decapitation) in

a petri dish on ice, combining and mincing them with a razor blade (thoroughly,

for about 5 minutes), then placing the paste into a tube, briefly spinning at low

speed in a centrifuge (1,000 rpm for 1 minute), and freezing it to produce a

cylindrical sausage that can be removed from the tube, mounted on a pedestal

with embedding matrix, and cryostat-cut to make sections of uniform

composition and size (Rothman et al. 1983). Sections (30 μm thick) were thawmounted onto gelatin-coated (“subbed”) slides, dried briefly on a hot plate at

30°C and stored in airtight boxes at -35°C prior to use (Herkenham 1988).

Cannabinoid and noncannabinoid drugs were stored at -70°C either in solid

form or dissolved in absolute ethanol. Cannabinoids were kept under argon to

prevent oxidation. Some drugs were dissolved in dimethyl sulfoxide and stored

frozen at -70°C. Stock solutions of drugs were kept at 10 mM concentration or

lower, depending on their potencies in the assay. [

3H]CP55,940 (specific

activity 76-79 Ci/mmole after custom preparation [Herkenham et al. 1990]) was

found to be unstable unless kept at low concentrations in absolute ethanol. To

prevent conversion to a nonradioactive form, it was stored at -80°C in a stock

concentration of 1 mCi per 5 mL ethanol under argon.

The assay procedures used were described previously (Herkenham 1988;

Herkenham et al. 1990). All optimization, kinetic, and competition studies were

carried out using slide-mounted rat brain sausage sections. Incubations were in

polyethylene cytomailers, each containing eight sections on four slides in 5 mL

of solution. During incubations, cytomailers were held in test tube racks in a

water bath. For washes, slides were transferred to cytomailers placed in ice. At

the end of the wash period, slides were transferred to stainless steel slide racks

(30 slides/rack) and blown dry with slightly warm air from a hair dryer. Slides

were scored and broken; the section-laden slide fragments were placed into

vials to which 10 mL of detergent-fluor were added. After equilibrating

overnight, the radioactivity was counted.

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Solutions were prepared in large glass beakers; Tris-HCI and bovine serum

albumin (BSA) were added while stirring. [

3H]CP55,940 and other drugs were

delivered to the source solution and/or individual cytomailers with micropipettes

and disposable polyethylene tips. Cannabinoids were drawn up and expelled

from the tips several times to saturate binding sites on the plastic tips.

Concentration of [

3H]CP55,940 was checked by scintillation counting of 100 μL

of the solution. For inhibition studies requiring dilutions of unlabeled drug, serial

dilutions were achieved by mixing drug in the first cytomailer containing 15 mL

of solution and then removing 6 mL for addition to the next in the line, which

was prefilled with 9 mL, achieving a 2.5-fold dilution. After thorough mixing by

using a 5 mL disposable tip to draw up and expel the solution five to six times,

the sequence was repeated. Similar strategies were used to achieve 2-fold and

10-fold dilutions in some assays.

Cannabinoids are extremely hydrophobic (Garrett and Hunt 1974), so

preliminary studies were performed to determine how to avoid ligand adherence

to glass and plastic surfaces. The disposition of iigand during pipetting and

dilution steps was checked in mock assays in which either [

3H]CP55,940 or

[

3H] -THC (provided by NIDA) was substituted for cold drug, and the solutions

were assayed for radioactivity by scintillation counting. Tests were performed

using subbed pipette tips and subbed cytomailers and using plain glass or

sialyzed glass test tubes in place of cytomailers. Using solutions prepared

according to the optimized assay conditions (see below), no differences were

found between calculated and observed radioactivity in the initial pipetting from

source vials or throughout the cascade of mock dilutions when using the

untreated polyethylene tips and cytomailers; therefore, protective coatings were

deemed unnecessary.

RESULTS

Preliminary binding studies were carried out to determine appropriate buffer

type and pH, effects of salts and preincubation in various media, optimal

incubation time and temperature, and optimal postincubation wash time. Early

experiments, carried out in incubations with 2 to 3 nM [

3H]CP55,940 at 24°C for

2 hours, revealed that the best binding (around 70 percent specific) was

produced by incubation in 50 mM Tris-HCI buffer, pH 7.4, with 5 percent BSA

(reagent grade, Sigma, worked as well as fatty acid-free BSA) and by washing

at 0°C for 4 hours in Tris buffer with 1 percent BSA. Nonspecific (NS) binding

was determined by addition of 10 μM CP55,244. Incubations without BSA gave

no specific binding—counts were actually lower in the total than in the NS

condition (total=8,900 cpms/section; NS=10,700 cpms/section).

133
Binding was relatively unaffected by preincubation in Tris buffer with 100 mM

NaCl for 30 minutes, at either 0°C or 24°C or by the inclusion of 100 mM NaCl

in the incubation medium. Incubations in 10 percent BSA gave lower total and

specific binding. Binding was reduced by use of other buffers (KPO4, HEPES,

MOPS) or by increases or decreases in pH or Tris buffer concentration. Binding

was eliminated by heat (preincubation for 30 minutes at 60°C in buffer). The

optimal postincubation wash condition, to remove nonspecifically bound label,

was 4 hours in Tris buffer with 1 percent BSA at 0°C. Longer wash times or

wash at 24°C for 1 hour gave lower percent specific binding. Specific binding

was reduced by wash with 0.1 percent BSA (higher nonspecific), whereas 1

percent and 5 percent BSA in the wash gave similar results.

The next set of variables to be examined were temperature and time of

incubation, optimal concentrations of BSA and [

3H]CP55,940 in the incubation,

and their interactions. As shown in figure 2, virtually no binding occurred at

0°C; binding at 24°C reached equilibrium at 16 hours of incubation; and binding

at 37°C was greater and reached equilibrium faster than at 24°C. Therefore,

the next set of parameters was examined at 37°C. As shown in figure 3,

incubations in 10 nM [3H]CP55,940 gave much greater binding than at 2.5 nM,

and reduction of BSA concentration elevated binding still more. However, a

plateau of binding was reached more quickly with 5 percent BSA than with 1

percent BSA (3 hours vs. 4 hours); in all experiments at 37°C, binding fell off at

longer incubation times, probably due to degradation of the ligand and/or

receptors. Binding of 1 to 20 nM [

3H]CP55,940 at 37°C for 2 hours was typically

80 percent to 90 percent specific.

Binding surface analysis (McGonigle et al. 1986; Rothman 1986; Rothman et al.

1988) was next used to determine kinetics of binding using optimized conditions

with either 1 percent or 5 percent BSA in the incubation medium (figure 4). To

determine binding kinetics, each of two concentrations of [

3H]CP55,940 (1 and

10 nM) was competitively inhibited by 6 to 12 concentrations of unlabeled drug.

Competitive inhibition curves were subjected to a computerized iterative curvefitting program for determining best-fit parameter estimates (Kd

, KI, Bmax)

according to one- or two-site competitive binding models. The competitive

inhibition curves were best fit by a single-site kinetic model: The affinity (Kd

) of

CP55,940 in 1 percent BSA was 2.6 nM, and the binding capacity (Bmax) was

528 fmoles/section (1,158 fmoles/mg protein, since sausage section has

456±26 mg protein/section). With 5 percent BSA, the Kd was 15 nM and the

Bmax was 415 fmoles/section (910 fmoles/mg protein).

A large series of cannabinoid and noncannabinoid drugs was assayed to test

for competitive displacement of [

3H]CP55,940 (table 1). To ensure that the

lipophilic drugs would dissolve at the high concentrations required (at least for

134
FIGURE 2. Time course of association of 2.5 nM [

3H]CP55,940 at three

different temperatures (°C)

NOTE: Total and NS binding are shown.

the drugs with low potency), all competition studies were performed in the

assay with 5 percent BSA. Drug concentrations of 10-4 M were achieved, which

are well higher than the limit of solubility of cannabinoids in water or buffer

without a carrier, such as BSA; -THC solubility limit in water at 23°C is

6.8 μM and 1.9 μM in physiological saline (Garrett and Hunt 1974). Solubility of

other cannabinoids is similar (Bach et al. 1976). It also was found that

variability of binding was reduced in the 5 percent BSA condition as opposed to

the 1 percent BSA condition (data not shown).

The competition curves (figure 5) and derived inhibition constants (KI’s) for the

natural and synthetic cannabinoids (table 1) provided a test for validation of

binding. It was found that highly significant (p<0.0001) correlations exist

between the KI‘s and potencies of the drugs in tests of dog ataxia and human

subjective experience, the two most reliable markers of cannabinoid activity

135
FIGURE 3. Time course of association of [

3H]CP55,940 as a function of its

concentration and the concentration of BSA in the incubation

medium

(Dewey 1986; Hollister 1986). The KI

’s also correlate very closely with relative

potencies in tests of motor function (ataxia, hypokinesia, catalepsy), analgesia,

and inhibition of contractions of guinea pig ileum and adenylate cyclase in

neuroblastoma cell lines in vitro (Herkenham et al. 1990). Enantioselectivity

was striking (figure 5; table 1); the (-) and (+) forms of CP55,244 differ by more

than 10,000-fold in vitro, a separation predicted by the rigid structure of the

molecule (figure 1) (Johnson and Melvin 1986) and by potencies in vivo.

Natural cannabinoids that lack psychoactive properties, such as cannabidiol,

showed extremely low potency at the receptor, and all tested noncannabinoid

drugs had no potency (table 1).

Because the validation of binding had been performed using the 5 percent BSA

condition, and because we believed that this concentration might support

preservation of tissue quality, the following binding conditions for

autoradiographic visualization of receptor distributions were selected:

incubation at 37°C for 2 to 3 hours in 50 mM Tris-HCI buffer, pH 7.4, with 5

percent BSA and 10 nM [3H]CP 55,940, and washing at 0°C for 4 hours in the

136
FIGURE 4. Binding surface analysis of unlabeled CP55,940 displacement of

two concentrations (1 and 10 nM) of [3H]CP55,940, with either 1

percent or 5 percent BSA in the incubation

NOTE: Horizontal and vertical lines mark the concentrations at which 50

percent of the binding of 1 nM [3H]CP55,940 is inhibited (IC50).

Compare with Kd’s, described in test.

same buffer with 1 percent BSA. Sections were blown dry; slides were placed

in x-ray cassettes and exposed to tritium-sensitive film for 3 to 4 weeks before

developing.

Autoradiography showed great heterogeneity of binding, with patterns of

receptor distribution that correlated closely with cytoarchitecture. Very dense

binding was found in the globus pallidus, the substantia nigra pars reticulata,

and the molecular layers of the cerebellum and hippocampal dentate gyrus

(figure 6). Dense binding also was found in the cerebral cortex, in other parts of

the hippocampal formation, and in the striatum. Neocortex had similar levels of

137
TABLE 1. Potencies of several cannabinoids in the section-binding assay

Compound KI

 (nM)

CP55,940 (-AC)

CP56,667 (+AC)

CP55,244 (-ACD)

CP55,243 (+ACD)

CP50,556 (levonantradol)

CP53,870 (dextronantradol)

CP54,939 (desacetyl levonantradol)

Nabilone

ß-HHC

-HHC

(-) -THC

(+) -THC

-THC

11-OH- -THC

Trimethylammonium- -THC (TMA)

8ß-OH- -THC

8 -OH- -THC

11-OH-cannabinol

Cannabinol

Cannabidiol

Cannabigerol

9-COOH-11-nor- -THC

9-COOH-11-nor- -THC

15±3 (Kd)

470 ± 57

1.4 ± 0.3

18,000 ± 1,100

14 ± 2

26,000 ± 3,500

14 ± 2

120 ± 13

124 ± 17

2,590 ± 360

420 ± 51

7,700 ± 2,100

498 ± 52

210 ± 56

2,300 ± 1,000

4,200 ± 700

8,700 ± 1,800

800 ± 150

3,200 ± 450

53,000 ± 6,700

275,000

75,000

Inactive

NOTE: Structures of CP analogs have been reported by Johnson and Melvin

(1986). The first six analogs are enantiomeric pairs, as are (-) and

(+) -THC. The last two are 9-TCH metabolites. KI’s ±standard

deviations are derived from binding surface analysis. Each represents

the results from a single experiment. In a separate set of “prediction”

experiments (Rothman et al. 1988), each drug was tested for inhibition

at the calculated KI

. For CP55,940 itself, the Kd shown represents the

mean and standard deviation of three separate determinations. Drugs

that at 10 μM concentration show no inhibition of [

3H]CP55,940 binding

are amphetamine, ß-estradiol, cis-flupenthixol (dopamine receptor

ligand), cocaine, corticosterone, cyclohexyl-adenosine,

dexamethasone, etorphine (opiate receptor ligand), -amino butyric

acid, glutamate, leukotriene B4 and D4 (both at 1 μM), lysergic acid

diethylamide (LSD), phencyclidine (PCP), prostaglandin E2, and Ro 15-

1788 (benzodiazepine receptor ligand).

SOURCE: Herkenham et al. 1990.

138
FIGURE 5. Competition curves for several enantiomers of the CP series of

synthetic cannabinoids

NOTE: Competitive inhibition of 1 nM [3H]CP55,940 binding in whole rat brain

sausage sections by various synthetic and natural cannabinoids at the

concentrations indicated. The data are normalized to specific binding

(total minus nonspecific) in absence of competitors. Nonspecific

binding was determined by addition of the 10 μM CP55,244 (the most

potent cannabinoid in the CP series) (Johnson and Melvin 1986) and

typically represented 10 to 20 percent of total binding at both 1 and 10

nM [

3H]CP 55,940. Data points represent means of eight

determinations.

SOURCE: Herkenham et al. 1990.

139
FIGURE 6. Autoradiography of 10 nM [

3H]CP55,940 binding in sagittal section of brain

NOTE: From left to right, the most densely labeled areas are the globus pallidus (GP), entopeduncular nucleus (EP),

substantia nigra pars reticulata (SNr), and cerebellar molecular layer (Cer). The GP, EP, and SNr are all

components of the basal ganglia. The basal ganglia and cerebellum are critical centers for the control of

movement. In addition, the cerebral cortex (Cx) and caudate-putamen (CP) are well labeled. Within the

cerebral cortex, the hippocampus (Hipp) has the densest labeling. The hippocampus is a critical center for

the laying down of permanent memory traces and is specifically involved in spatial and temporal aspects of

memory. The brain stem (Br St) has very few receptors.

SOURCE: Herkenham et al. 1990.
binding across fields, with peaks in superficial and deep layers. Very low and

homogeneous binding characterized the thalamus and most of the brain stem,

including all of the monoamine-containing cell groups, as well as the reticular

formation; the primary sensory, visceromotor, and cranial motor nuclei; and the

area postrema. The exceptions—hypothalamus, basal amygdala, central gray,

nucleus of the solitary tract, and laminae I-III and X of the spinal cord—showed

slightly higher but still sparse binding (Herkenham et al. 1990).

DISCUSSION

Binding parameters are dependent on the assay used to characterize them.

For this reason, optimization, kinetics, and validation must be done on slidemounted brain sections of the type that will be used for autoradiographic

visualization. In the case of cannabinoids, this requirement delivered an

additional major dividend when it was discovered that the section assay, by its

nature, obviates many of the technical problems associated with membrane

binding. The section-binding assay is easy to perform, does not require

expensive equipment other than a cryostat, gives highly reproducible data, and

shows high sensitivity to manipulations of binding conditions such as the

addition of guanine nucleotides (Herkenham et al. 1990). The assay

circumvents technical problems inherent in membrane assays, such as

adherence of ligand to glass and plastic surfaces and to filters; Devane and

colleagues (1988) were unsuccessful at developing an assay based on filtration

techniques. In addition, BSA appears to act as a carrier to keep cannabinoids

in solution without appreciably affecting binding kinetics. The low nonspecific

binding and absence of binding in white matter indicate that the

autoradiographic patterns are not affected by ligand lipophilia. The inclusion of

BSA in the incubation medium actually may mimic the disposition of

cannabinoids administered in vivo, as they would quickly complex with serum

albumin or other carriers in the blood.

The structure-activity profile suggests that the receptor defined by the binding of

[

3H]CP55,940 is the same receptor that mediates many of the behavioral and

pharmacological effects of cannabinoids (table 1), including the subjective

experience termed the human “high.” All other tested psychoactive drugs,

neurotransmitters, steroids, and eicosanoids at 10 μM concentrations failed to

bind to this receptor, There was no compelling evidence for receptor subtypes

from that analysis.

Autoradiography of cannabinoid receptors reveals a heterogeneous distribution

pattern that conforms to cytoarchitectural and functional subdivisions in the

brain. The distribution is unique—no other pattern of receptors is similar; and it

is similar across several mammalian species, including human, suggesting that

141
cannabinoid receptors are phylogenetically stable and conserved in evolution.

Knowing the locations of cannabinoid receptors increases understanding of

cannabinoid pharmacology. Generally high densities in forebrain and

cerebellum implicate roles for cannabinoids in cognition and movement. Sparse

densities in lower brain stem areas that control cardiovascular and respiratory

functions may explain why high doses of -THC are not lethal.

Accounts of cannabis use in humans stress the loosening of associations,

fragmentation of thought, and confusion on attempting to remember recent

occurrences (Hollister 1986; Miller 1984). These cognitive effects may be

mediated by receptors in the cerebral cortex, especially the receptor-dense

hippocampal cortex. The hippocampus “gates” information during memory

consolidation and codes spatial and temporal relations among stimuli and

responses (Douglas 1967; Eichenbaum and Cohen 1988). -THC causes

memory “intrusions” (Hooker and Jones 1987), impairs temporal aspects of

performance (Schulze et al. 1988), and suppresses hippocampal electrical

activity (Campbell et al. 1986).

The localization of cannabinoid receptors in motor areas suggests therapeutic

applications. Cannabinoids exacerbate hypokinesia in Parkinson’s disease but

are beneficial for some forms of dystonia, tremor, and spasticity (Clifford 1983;

Dewey 1986; Hollister 1986; Marsden 1981; Petro and Ellenberger 1981). The

development of an antagonist could provide additional therapeutic uses of

value. The section-binding assay will be helpful in this regard and can be used

also to screen novel drugs that have greater potency or that bind irreversibly to

aid in the identification of the receptor gene and the putative endogenous

ligand.

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19:1165-1167, 1976.

AUTHOR

Miles Herkenham, Ph.D.

Research Psychologist

Section on Functional Neuroanatomy

Clinical Neuroendocrinology Branch

National Institute of Mental Health

National Institutes of Health

Building 36, Room 2D-15

9000 Rockville Pike

Bethesda, MD 20892

145
New Developments in Radiotracers for

Positron Emission Tomography

Joanna S. Fowler and Alfred P. Wolf

INTRODUCTION

Organic molecules labeled with short-lived positron emitters are utilized in tracer

kinetic experiments to study complex biochemical processes in living kinetic

experiments allowing the study of complex biochemical processes in living

animals and humans. A positron emission tomograph is used to determine the

absolute amount of radioactivity in small volumes of tissue. Thus, the uptake

and retention of labeled organic molecules, which are used as probes, can

reflect a particular biochemical process. The development and application of

positron emission tomography (PET) is a multidisciplinary and interdisciplinary

effort involving the overlap of four major areas (figure 1).

It is the purpose of this chapter to place one of these areas, chemistry, in the

perspective of its use in radiotracer design and development and to describe

some of the special challenges associated with applying isotopes of short halflives to problems in biology and medicine.

To understand the PET method, some comment is appropriate on the basic

technology that makes the measurement on in vivo biochemical processes

possible. The following four elements constitute the PET method.

1. Cyclotron or other suitable accelerator for isotope production

2. Chemistry laboratory for the synthesis of labeled tracers and the study of

their biodistribution and metabolism

3. Positron emission tomograph for the quantitative measurement of

radioactivity concentration in vivo

4. Computational facilities for data reconstruction and manipulation

146
FIGURE 1. Four major areas of PET research

ACCELERATORS FOR ISOTOPE PRODUCTION

The four most commonly used radionuclides in PET and some of their

properties are listed in table 1. For comparison, the properties of carbon-14 and

tritium, the two most commonly used tracers in biochemical research, also are

listed. They are not positron emitters.

There are several other positron emitters used in PET work, but they are rarely

used in labeling procedures. Generator-produced radionuclides also are used

in PET, although these are typically metal ions, which do not have the synthetic

flexibility of the four short-lived positron emitters listed in table 1 (Guillaume and

Brihaye 1986).

The positron emitters are produced by nuclear reactions most commonly

brought about by bombarding appropriate targets with either protons or

deuterons. These nuclear reactions are listed in table 2.

147
The accelerators used to bring about these reactions are most often cyclotrons

with proton energies in the 10- to 17-million electron volt (MeV) range (Wolf

1988). The most widely used machines are listed in table 3.

TABLE 1. Properties of the short-lived positron emitters and carbon-14 and

tritium

Isotope Half-Life

Carbon-11 20.4 min

Fluorine-18 109.8 min

Nitrogen-13 10 min

Oxygen-15 2.07 min

Carbon-14 5,730 y

Tritium 12.4 y

Specific Activitya

9.2x106

1.7x106

1.9x107

9.1x107

0.0624

29

Decay Product

Boron-11

Oxygen-18

Carbon-13

Nitrogen-15

Nitrogen-14

Helium-3

aSpecific activities are in curies/mmol. These specific activities are never

achieved because of unavoidable contamination with the corresponding stable

isotopes. Dilutions with the stable isotope are usually from 100 to 100,000.

TABLE 2. Nuclear reactions for the production of positron emitters

Isotope Nuclear Reaction

Carbon-11 1 4N(p, )

11C

Fluorine-18 18O(p,n)18F

20Ne(d, 1 8F

Nitrogen-13 13C(p,n)13N

16O(p, )13N, 12C(d,n)13N

Oxygen-15 15N(p,n)15O

14N(d,n)15O

TABLE 3. Cyclotrons for PET

Proton Energy Deuteron Energy Beam Current

Companya

(MeV) (MeV) (μA)

JSW 1710 17 10 10

MC 17F 17.2 8.5 65

CTI-RDS 11 — 50

CGR-MeV 18 10 70

a

JSW 1710, Japan Steel Works; MC 17F, Scanditronix Corporation; CTI-RDS,

Siemens Corporation; CGR-MeV, Sumitomo and the CGR Corporations

148
The beam currents listed allow a more than adequate supply of the isotope to

be made. Because of the recent increase in interest in this field, several new

companies are involved with the research and development of small cyclotrons

and other accelerators. These so-called “medical cyclotrons” are designed to

be relatively simple to operate and serve as a convenient onsite source of the

needed isotope.

SYNTHESIS OF LABELED TRACERS

Some of the precursors needed for labeling procedures are produced online in

the cyclotron target or are prepared synthetically within a few minutes following

the delivery of the isotope from the cyclotron. The major precursors are listed in

table 4. Descriptions of methods for preparation of these precursor molecules

can be found in Fowler and Wolf (1986), Wolf (1981) and Wolf and Fowler

(1985).

TABLE 4. Precursor molecules

Isotope Precursor

Carbon-11 [

11C]O2 H[11C]N [

11C]H3

I

Nitrogen-13 [

13N]H3

Oxygen-15 H2

[

15O] [15O]CO2 [

15O]O2

Fluorine-18 [

18F]F2 H[18F]

Utilization of these precursors will become more evident in the subsequent

sections on a variety of labeled compounds used as biochemical or

physiological probes. Some of the more common reactions include

carboxylation or reductive carboxylation with [

11C]O2

, alkylation via [

11C]H3

I,

nucleophilic substitution via 11CN, aliphatic and aromatic nucleophilic

substitution with 18F or the use of reactions such as the Schiemann or triazine

decomposition, and electrophilic addition and substitution with [

18F]F2

 (Fowler

and Wolf 1982, 1986 and references therein).

One of the key requirements is rapid incorporation into the tracer molecule, a

rule of thumb being a maximum of the half-life of the isotope used for synthesis

multiplied by three. This time relates to the end of cyclotron bombardment for

isotope production. Thus, carbon-11 compounds need to be prepared in less

than 1 hour, whereas fluorine-18 compounds require a maximum of about 5

hours for preparation. Of the approximately 900 syntheses reported to date, the

average preparation time is reported to be between 20 minutes and 1 hour.

149
Only a few of these tracers have proven to be useful for in vivo PET studies of a

specific biochemical process due to factors such as in vivo transport to the

region of interest, localization rate, metabolism, binding to plasma proteins,

nonspecific binding, excess lipophilicity, inability to cross the blood-brain barrier,

or entry into metabolic pathways other than the one of interest. The selection of

a compound for study of a definable biochemical process usually is made with

guidance from the literature of pharmacology and biochemistry, and the

validation of the tracer typically is carried out on small animals and nonhuman

primates.

Another important factor in studies with positron emitters is the achievable

specific activity, which varies with the nature of the study. In receptor-ligand

work a true tracer should have a high specific activity so that the animal or

human under study will not show a physiology response. However, when

tracing the activity of relatively abundant endogenous substances such as

glucose, there is greater latitude in choice of specific activity.

As can be seen from table 1, three of the positron emitters are elements that

can be found in every natural biomolecule and in drugs that are used to treat

disease. Fluorine, although rarely found in nature in organic combination,

frequently is a good substitute for hydrogen when placed in a nonreactive

position in the molecule. Thus, PET tracers can be contrasted with other

tracers such as iodine or technetium used in single-photon emission computed

tomography studies where the molecules used do not always accurately mimic

the process being studied because of the gross steric and electronic

perturbation of the labeled molecule by the “unnatural” isotope.

Once a synthesis has been developed and the compound has undergone the

required analytical control for chemical, radiochemical, and radionuclidic purity

in addition to testing of sterility and apyrogenicity, it is ready for testing animals

and ultimately for human studies with PET.

The tracer can be used to determine the following parameters: regional

distribution in a tissue element, pharmacokinetics of the uptake and clearance

of radioactivity, response of the tracer to sensory or pharmacological challenge,

mechanism of a biochemical process in vivo, and tissue response in

pathological conditions and other processes that can shed light on the nature of

biochemical processes in the complex milieu of a living organism. Once the

uptake and kinetic behavior of a tracer has been determined, a tracer kinetic

model may be required to extract more detail from the observations. Good

examples of this can be found in such diverse processes as regional glucose

metabolism, brain blood flow, and some properties of neurotransmitter

receptors (Huang and Phelps 1986 and references therein).

150
POSITRON EMISSION TOMOGRAPHY

The annihilation radiation (see below) produced on decay of the tracer labeled

with a positron emitter (or its labeled metabolites) can be detected in animals

and humans using a positron emission tomograph. The unique capability of

PET to allow absolute measurement of the concentration of radioactivity in a

tissue element—and thus provide quantitative data rather than relative values—

stems from the nature of the positron decay process. A nucleus such as that of

fluorine-18 emits a positron (figure 2) that travels a finite distance until it collides

with an electron, resulting in an annihilation process that yields two photons of

equal energy (511 keV) traveling in opposite directions at an angle nearly equal

to 180°. Because the positrons are not monoenergetic, a distribution of

distances from origin to the point of annihilation is seen from any element

undergoing this decay process. The distance of travel before annihilation and

slight deviation from the 180° angle of movement limit the ultimate resolution of

any positron emission tomograph.

2 Photons at 511 keV at 180°

Maximum distance of travel for 18F positron=2.4 mm

FIGURE 2. Positron annihilation using the decay of fluorine-18 as an

example. Two photons of equal energy (511 keV are produced

at an approximate 180° angle when the positron is annihilated

with an electron.

If two radioactivity detectors are directly opposite each other, it can be seen that

any set of events detected simultaneously must have occurred in the volume

element of space seen by the two detectors (figure 3a). If an array of detectors

surrounds the object being measured, the lines of coincidence drawn between

each detector will determine the position in space of the decay events (figure

3b). The coincidence detection also allows quantitative measurement of

radioactivity coming from any volume element.

151
FIGURE 3a. Coincidence detection of the two photons produced when the

positron annihilates with an electron allows the decay event to

be positioned in the volume between the detectors.

FIGURE 3b. An array of detectors in coincidence surrounds a source of

positron emitters and allows the position in space of the source

to be determined.

PET cannot achieve the ultimate resolution possible with tritium

autoradiography; however, as the resolution of positron emission tomographs

increases, exceedingly small tissue volume elements can be studied. Table 5

lists the situation as it exists today and indicates what the future holds. In

general, however, practical considerations lead to quantitation of a volume

152
element that is about twice the volume element listed in table 5. Thus, with a

current tomograph, the volume element is closer to 0.5 to 0.7 cm3

 rather than

0.25 cm3.

TABLE 5. Positron emission tomograph resolutiona

Instrument X Y Z Volume Element

PET Ill (circa 1974)

PET VI and NeuroEcat II

Commercial Devices (1989)

Ultimate Device (1995)b

2.0x2.0x2.5 cm 10 cm3

0.8x0.8x1.5 cm 1 cm3

0.6x0.6x0.7 cm 0.25 cm3

0.1x0.1x0.1 cm 0.001 cm3

aAlthough resolution in PET is more complex than this simple table implies (see

also Hoffman and Phelps 1986), the values are for full-width, half-maximum

resolution commonly quoted.

bResolution below 0.1 cm, although theoretically possible, is of no practical

value because of the range of the positron, which results in smearing of the

image seen if there were a “true” point source. The annihilation event occurs

at a finite distance from the tracer molecule undergoing decay, hence the

limitation in what ultimately can be seen with PET.

A PET experiment on a human (e.g., a brain study of the corpus striatum)

involves the usual medical requirement of informed consent before the study.

The patient receives a medical checkup followed by preparation of a head

holder or mask molded individually for each patient so that there is no

movement during data acquisition. Arterial and venous catheters then are

inserted for blood sampling (assay of blood constituents and metabolites) and

tracer injection, and the patient is positioned in the positron emission

tomograph. Depending on the isotope used, duration and nature of the study,

and other factors, acquisition of data by the positron emission tomograph may

involve durations that vary from 1 to 20 minutes. An automated blood sampler

for arterial blood usually is used to obtain the blood input function so that the

uptake curve can be adjusted for the instantaneous blood concentration of the

tracer corrected for the presence of labeled metabolites. At the end of the

experiment the data are reconstructed and image analysis takes place.

Examples of PET studies follow in the text.

The technology of PET requires the cooperation of diverse professional and

technical personnel. Currently, its major power is as a research tool, but

increasing interest in clinically useful procedures also is apparent from the

153
increasing number of hospitals that are setting up cyclotron-PET facilities.

Some procedures—for example, measurement of brain glucose metabolism

with 2-deoxy-2-[18F]fluoro-D-glucose (

18FDG)—have been converted to

technician-operated procedures that can be used in daily routine clinical

diagnosis. This chapter, however, provides examples of the many areas of

biomedical and fundamental biochemical research that can be carried out. The

following sections delineate several major areas that are probed with positronemitting radiotracers. The radiotracer is the key element served by the

technology just described.

RADIOTRACERS FOR PET STUDIES OF THE BRAIN

To date, PET research and the development of new radiopharmaceuticals have

focused primarily on the brain. This was stimulated, in large part, by the early

development of radiotracers and tracer kinetic models for measuring regional

brain glucose metabolism (Fowler and Wolf 1986 and references therein:

Reivich et al. 1979) and blood flow (Ter-Pogossian and Herscovitch 1985 and

references therein). The 18FDG method for measuring regional brain glucose

metabolism was developed in the mid-1970s and is now the most widely used

radiotracer in PET research. The synthesis of 18FDG has improved continually

since it was first developed in 1976 (Ido et al. 1978; Fowler and Wolf 1986 and

references therein). Currently, this tracer is prepared in high yield via a

displacement reaction (Hamacher et al. 1986). In addition, fully automated

synthesis systems are now commercially available.

The development of 18FDG is a classic example of radiotracer design based on

a knowledge of the biochemistry of the molecule and the principles of tracer

kinetics. The 18FDG method is based on the metabolic trapping of 18FDG-6-

phosphate, the product of hexokinase-catalyzed phosphorylation of 18FDG.

Because glucose derivatives missing the hydroxyl group on C-2 do not undergo

further steps in glycolysis, the radioactivity in tissue after the injection consists

only of free 18FDG and 18FDG-6-phosphate, allowing the measurement of

glucose metabolism via a tracer kinetic model.

The primary application of 18FDG has been in the measurement of regional

glucose metabolism in normal and diseased brain and heart, although it also

has been used to measure the effects of drugs and other substances of abuse,

cognitive processing, and somatosensory stimulation on brain glucose

metabolism (Pheips and Mazziotta 1985). Carbon-11-labeled 2-deoxy-Dglucose has been used in several protocols because its short half-life permits

serial studies to be carried out on a single subject on the same day (Reivich et

al. 1982). Although carbon-11-labeled glucose also has been developed along

with a tracer kinetic model (Raichle et al. 1975), it has neither been applied

widely nor validated for the measurement of regional brain glucose metabolism.

154
Brain blood flow and oxygen utilization are measured most conveniently using

oxygen-15-labeled tracers (Ter-Pogossian and Herscovitch 1985). In spite of

the 2-minute half-life of oxygen-15, online methods have been developed for its

production in the chemical forms required for the measurement of blood flow

and oxygen utilization. Its short half-life allows multiple serial studies in a single

individual, and there are many examples of its use to study cognitive

psychology (Petersen et al. 1990). As in the case of 18FDG, the success of the

oxygen-15 methods can be traced to the early development and validation of

tracer kinetic models, which allow the quantitative measurement of important

biochemical parameters.

Following the early successful use of PET to measure regional brain glucose

metabolism and blood flow, an interest developed in applying in vivo tracer

methodology to the study of neurotransmitters and their receptors. A key

development in the application of PET to neurotransmitter studies has been the

discovery of synthetic methods for producing high specific activity tracers that

also have high affinity and selectivity for the receptor. High specific activity,

where the dilution of radioisotope by the naturally occurring element can be in

the range of factors from 100 to 10,000, is required to avoid saturation and

measurable physiological reactions to the labeled compound.

Radiotracers are under development for studying many neurotransmitters and

their receptors: dopamine (Fowler and Wolf 1991 and references therein),

opiate (Frost et al. 1985; Luthra et al. 1985), serotonin (Wong et al. 1987; Blin

et al. 1988), acetylcholine-muscarine (Mulholland et al. 1988; Mulholland et al.

1989; Dewey et al. 1990; Dannals et al. 1988), benzodiazepine (Persson et al.

1985; Pappata et al. 1988), and N-methyl-D-aspartate (Brady et al. 1989;

Wieland et al. 1988; Burns et al. 1989; Monn and Rice 1989). However, the

major focus has been on the dopaminergic system stimulated by the importance

of dopamine in Parkinson’s disease and in schizophrenia.

The dopaminergic system has been studied from several neurochemical

perspectives. For example, dopamine metabolism has been probed with 6-

[

18F]fluoro-DOPA, which crosses the blood-brain barrier and is converted into 6-

[

18F]fluoro-dopamine, which traces dopamine metabolism in the striatum (Firnau

et al. 1986). More recently, fluorine-18-labeled derivatives of metatyrosine (a

good substrate for amino acid decarboxylase) have been developed (DeJesus

et al. 1989; Gildersleeve et al. 1989; Melega et al. 1989). This tracer does not

exhibit some of the metabolic complexities of 6-[18F]fluoro-DOPA and may prove

to be superior for PET studies.

Dopamine (D2) receptor activity also has been examined with PET using

positron emitter-labeled antagonists of the D2 receptor. For example,

155
N-methylspiroperidol has been labeled with carbon-11 and fluorine-18 and used

to study D2

 receptors in normal and diseased brain and to probe D2 receptor

occupancy by antipsychotic drugs (Wagner et al. 1983; Arnett et al. 1986;

Wolkin et al. 1989a; Smith et al. 1988b). The benzamide, [

11C]raclopride, also

has been used in human studies (Farde et al. 1985; Farde et al. 1988). Of

current interest are two studies, one reporting the use of [11C]Nmethylspiroperidol and the other reporting use of [

11C]raclopride to measure D2

receptor density in schizophrenic patients (Wong et al. 1986; Farde et al. 1987).

With [

11C]N-methylspiroperidol, a significant elevation in D2

 receptor density was

found, a result consistent with in vitro measurements made with postmortem

human brain tissue (Seeman et al. 1984). In contrast, with [

11C]raclopride, no

differences were found between the schizophrenic subjects and the normal

control population. The factors that may have contributed to this apparent

contradiction have been enumerated by a recent panel (Andreasen et al. 1988).

Several tracers that bind to the dopamine reuptake system have been

developed, including 11C-nomifensine (Aquilonius et al. 1987), [

18F]GBR 13119

(Kilbourn 1988), and [

11C]cocaine (Fowler et al. 1989). These tracers are of

potential interest in mapping drug-binding sites and probing the loss of

dopaminergic neurons in neurodegenerative diseases such as Parkinson’s

disease.

Protein synthesis and turnover in brain are important biochemical features of

brain metabolism, and several positron emitter-labeled amino acids have been

investigated as tracers for the quantitative measurement of the regional

incorporation of amino acids into protein. The carboxyl-labeled amino acid [

11Ccarboxyl]L-leucine has been studied (Phelps et al. 1984). The important design

feature of this molecule is the position of the label in the carboxyl group so that

the products of amino acid metabolism (loss of [11C]O2

) are not labeled, but

proteins of interest are labeled. Despite the rational approach to designing this

tracer so that the label in in vivo tissue could be quantitatively interpreted in

terms of protein synthesis, a recent detailed examination of the carbon-14-

labeled analog showed that recycling of unlabeled amino acids derived from

protein degradation complicated the estimation of precursor pool-specific

activity (Smith et al. 1988a). [11C-S-methyl]L-methionine and [1-11C]Lmethionine also have been examined as substrates for protein synthesis

(Bustany et al. 1982; lshiwata et al. 1988). A promising new development in the

use of PET to measure regional brain protein synthesis is the report that 2-

[

18F]fluorotyrosine is rapidly incorporated into protein to the exclusion of other

metabolic pathways (Coenen et al. 1989).

156
RADIOTRACERS FOR STUDYING THE BINDING OF THERAPEUTIC

DRUGSANDOTHERSUBSTANCESOFABUSE

The use of PET to better understand drug behavior can be approached in the

following two ways or by applying a combination of these two approaches: (1)

A radiotracer that selectively probes a biochemical transformation (e.g., 18FDG)

can be used in serial studies with drug intervention to examine the effect of the

drug on a particular biochemical reaction; or (2) the labeled drug can be used to

map its binding sites and kinetics.

Among the important parameters that can be measured by PET are the effect of

a drug on metabolism and neurotransmitter properties, binding sites and target

organs for the drug, absolute brain uptake of the drug, pharmacokinetics,

binding mechanisms, drug interactions, duration of action, effect of route of

administration on target uptake, and relationship between drug-binding to target

receptors and plasma drug concentration.

There are an increasing number of examples of the use of PET to probe the

effects of drugs on glucose metabolism and D2 receptor availability as

measured by 18FDG or [

11C]2-deoxy-D-glucose or carbon-11- or fluorine-18-

labeled neuroleptics (Fowler and Wolf 1991 and references therein).

The use of PET to map drug-binding sites and kinetics is exemplified by studies

with [

11C]cocaine in human and baboon brains (Fowler et al. 1989). Details on

the results of these studies are included in the chapter by Volkow and

colleagues (this volume).

In vivo PET studies of the stereoselectivity of cocaine-binding in baboon brain

with the behaviorally active- and inactive-labeled enantiomers of cocaine (-)-

and (+)- [11C]cocaine with PET (Gatley et al. 1990) provided an important new

perspective on the previously observed lack of behavioral activity of the (+)-

enantiomer (Spealman et al. 1983). Carbon-11-labeled (-)-cocaine was taken

up rapidly and cleared from brain tissue after intravenous (IV) injection. In

contrast, carbon-11-labeled (+)-cocaine was excluded from the brain (figure 4).

On examination of this unexpected result, it was found that the (+)-enantiomer

is metabolized so rapidly in plasma (by butyrylcholinesterase) that there is

essentially no tracer left a few seconds after injection (figure 5). Thus, the

biological activity of the (+)-enantiomer could be assessed only if the compound

could be administered directly and then would be available only if brain

enzymatic activity relative to the (+)-enantiomer is slow.

The regional distribution of binding sites for the most widely used antipsychotic

drug, haloperidol, also has been determined using [

18F]haloperidol and PET

157
(Wolf et al. 1988). It is known that haloperidol binds to D2

 receptors. Although

the structure of haloperidol is similar to N-methylspiroperidol, which is

selectively taken up in the striatum, the brain uptake of haloperidol is

widespread. This indicates that nonspecific binding or binding to other receptor

sites, in addition to D2

 receptors, is operative and may be partially responsible

for the therapeutic characteristics of the drug.

FIGURE 4. Comparative uptake of [

11C]-(-)-cocaine and [11C]-(+)-cocaine in

baboon brain showing that the (+)-enantiomer does not penetrate

the brain after intravenous injection

SOURCE: Gatley et al. 1990, copyright 1990, Raven Press.

The question of whether receptor occupancy by haloperidol parallels the

concentration of drug in the plasma also was addressed using PET to

determine whether plasma drug levels are a good measure of receptor

occupancy by antipsychotic drugs (Wolkin et al. 1989a; Smith et al. 1988b)

using [

18F]N-methylspiroperidol to probe receptor occupancy. Plasma drug

levels were measured at the time of each PET study. It was found that receptor

occupancy by haloperidol increased with increasing plasma concentrations of

158
the drug, leveling off at 5 to 15 ng/mL. Interestingly, clinical studies show this to

be the initial phase of therapeutic levels for haloperidol. However, at the higher

plasma drug concentrations achieved by high haloperidol doses, there was no

increase in receptor occupancy. This supports a growing clinical consensus

that there is little added benefit in increasing plasma haloperidol levels above 20

ng/mL.

FIGURE 5. Residual unchanged tracer in baboon plasma after the injection of

carbon-11-labeled (-)-cocaine and (+)-cocaine showing the rapid

metabolism of the (+)-enantiomer

SOURCE: Gatley et al. 1990, copyright 1990, Raven Press.

[

18F]N-methylspiroperidol also was used to address the question of whether

schizophrenic subjects who respond positively to antipsychotic drug therapy

have a different receptor occupancy by the drug than those who do not respond

159
(Wolkin et al. 1989b). The conclusion of this study was that receptor blockade

by haloperidol occurs to the same extent in responders and nonresponders and

that the treatment of nonresponders with high neuroleptic doses to increase

receptor occupancy is not warranted.

The duration of action of drugs directly at their target sites has been measured

with PET. One study examined the duration of action of a single dose of (-)-

deprenyl, the suicide enzyme inactivator of monoamine oxidase B (MAO B)

(Arnett et al. 1987), which is currently used in the therapy of Parkinson’s

disease. (-)-Deprenyl acts by suicide inactivation with covalent attachment of

the activated inhibitor to MAO B. This results in the destruction of the enzyme.

The distribution of [

11C]L-deprenyl in brain has been shown to parallel MAO B

(Fowler et al. 1987) distribution, and its trapping in brain appears to reflect MAO

B activity (Fowler et al. 1988). Tracer doses of [

11C]L(-) deprenyl were used to

probe MAO B activity in baboon brain before and 34 minutes after a single dose

of 1 mg/kg of (-)-deprenyl and then at 1, 5, 22, 34, 61, and 111 days following

the dose. With PET, it was found that the recovery of the enzyme activity is

surprisingly slow, with a half-life of 30 days. This information is important in

designing a drug dosage regimen, especially in the case of drugs that act by

irreversibly inhibiting a biological substrate such as an enzyme.

Another report addressed the duration of occupancy of μ-opiate receptors by

naltrexone, an orally administered opiate antagonist (Lee et al. 1988).

Occupancy was probed by the μ-specific ligand [

11C]carfentanil and an external

detector before naltrexone and at 1, 48, 72, 120, and 168 hours after the oral

administration of 50 mg of naltrexone. The half-life of blockade by naltrexone in

the brain ranged from 72 to 108 hours, which corresponds to the half-life of the

terminal plasma phase of naltrexone clearance. Both studies illustrate the

advantage of in vivo imaging and detection—to probe not only the target sites

for a drug but also the duration of its pharmacological action and to provide a

direct assessment of the relevance of measurements of drug concentration in

plasma to receptor occupancy by the drug.

PET also has been used to examine the effect of intra-arterial vs. IV

administration of the chemotherapeutic drug N,N-bif(2-chlorethyl)-N-nitrosourea (BCNU) on tumor (Tyler et al. 1988). Intra-arterial administration of BCNU

resulted in a 50-fold greater concentration in tumor than IV administration and

suggested that the early metabolic trapping of BCNU in tumor correlates with

clinical response.

OUTLOOK

As a tool for investigating in vivo biochemistry and physiology in normal and

pathological states, PET has made great strides since the early 1970s,

180
especially in the past 10 years (Phelps et al. 1986). This is attributable to the

increased sophistication in radiopharmaceutical probes and to rapid advanced

in PET instrumentation. The coming years will see increasing clinical

application (Coleman et al. 1988; Jacobson 1988a-d), establishment of PET in

drug research, and a greater understanding of the biochemistry and functioning

of the human brain.

It must be kept in mind that the basis for the PET method is the use of tracer

kinetics in the study of human biochemistry and physiology in vivo. Thus, any

PET study involves a multiplicity of processes, which together result in the PET

image and the pharmacokinetics that define that image. PET cannot be used to

define a biochemical pathway in a single cell and does not compete with the

elegant basic work on the structure and function of single cells or small groups

of cells. However, one of the unique capabilities of PET is in the quantitative

assessment of the behavior, including the interactions of aggregates of cells in

a volume element of tissue in vivo, especially in the human brain.

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ACKNOWLEDGMENT

This research was carried out at Brookhaven National Laboratory under

Department of Energy (DOE) contract DE-AC02-76CH00016 and supported by

the DOE Office of Health and Environmental Research.

AUTHORS

Joanna S. Fowler, Ph.D.

Senior Chemist

Alfred P. Wolf, Ph.D.

Director

Cyclotron-PET Program

Senior Chemist

Department of Chemistry

Brookhaven National Laboratory

Building 555

Lewis Road

Upton, NY 11973

167
Use of Positron Emission Tomography

To Study Cocaine in the Human Brain

Nora D. Volkow, Joanna S. Fowler, and Alfred P. Wolf

INTRODUCTION

Positron emission tomography (PET) is a nuclear imaging method that can be

used to measure receptor concentration, neurotransmitter activity, brain glucose

metabolism, cerebral blood flow, and pharmacokinetics in the living brain

(Phelps and Mazziotta 1985). PET is a unique technique to investigate the

neurochemical and physiological processes underlying drug reinforcement and

addiction. This chapter reviews the different experimental strategies used with

PET to investigate the pharmacological actions of cocaine in the human brain.

These same experimental strategies can be applied to investigate other drugs

of abuse.

THE DRUG

Cocaine is a complex pharmacological agent with local anesthetic properties as

well as sympathomimetic effects (Johanson and Fischman 1989), which have

been related to its reinforcing and addicting properties (Koob and Bloom 1988;

Wise and Bozarth 1984; Dackis and Gold 1985). Cocaine’s sympathomimetic

effects are due to its ability to inhibit the reuptake of monoamines into the

presynaptic terminal, which produces a transient increase in the concentration

of the monoamine at the synapse (Hurd and Ungerstedt 1989). Although it has

been shown that cocaine can inhibit transport of serotonin (Cunningham et al.

1987), norepinephrine (Banerjee et al. 1979) and dopamine (Ritz et al. 1987)

into the presynaptic neuron, it is the drug’s ability to block the reuptake of

dopamine that has been associated with its reinforcing properties (Ritz et al.

1987). In this respect, it has been shown that destruction of dopamine cells

with the neurotoxin 6-hydroxydopamine (Roberts et al. 1977), and blockade of

postsynaptic dopamine receptors with neuroleptic (Goeders and Smith 1986)

reduces the reinforcing properties of cocaine. Similarly, the addicting properties

of cocaine have been related to its effect on the dopamine system (Dackis and

Gold 1985). It has been postulated that chronic cocaine use leads to dopamine

depletion in the brain, which in turn generates dependence on cocaine. Several

168
pharmacological treatments that increase the concentration of dopamine in the

brain have been explored in the treatment of cocaine abusers (Dackis et al.

1987; Extein et al. 1986; Tennant and Sagherian 1987; Berger et al. 1989).

In the past 10 years the abuse of cocaine has reached epidemiological

proportions (Adams 1982; Schnoll et al. 1984; Turner 1988) resulting in

increased morbidity and mortality (Gawin and Ellinwood 1988; Lowenstein et al.

1987). Medical complications from cocaine include cardiac, pulmonary,

cerebral, renal, gastrointestinal, and gynecobstetrical problems (Johanson and

Fischman 1989), and many have been related to the sympathomimetic actions

of cocaine. This chapter reviews cocaine studies done with PET in the areas of

brain toxicity, addiction, and reinforcement.

TOXICITY OF COCAINE IN THE BRAIN

Measurement of brain dysfunction can be achieved with PET with tracers that

monitor glucose metabolism (Reivich et al. 1985) such as 2-deoxy-2[18F] fluoro18 D-glucose (

18FDG) or [1-11C] deoxyglucose (11CDG) or with tracers that

monitor cerebral blood flow (CBF) such as H2

15O (Raichle et al. 1983).

The effects of chronic cocaine use on brain function have been evaluated with

glucose metabolism and with CBF. The study that investigated CBF used H2

15O

and PET in a group of 24 chronic cocaine abusers (Volkow 1988). The patients

for this study had taken cocaine for at least 6 months, with an average dose of 4

g per week. All the subjects came from an inpatient unit for drug detoxification

and rehabilitation. Measurement of CBF was performed twice during the

hospitalization; the first measurement was done within 1 week of entering the

hospital, and the second was done 10 days after the first study. During this 10-

day period patients were kept free of any medication; routine urine samples were

obtained to ensure that patients did not take any drug during the detoxification

period. The measurement of CBF revealed evidence of defective CBF,

suggestive of cerebrovascular pathology. Although the defects in isotope

accumulation occurred throughout most of the cortical brain areas, they were

seen predominantly in the frontal cortex, left temporal cortex, and left parietal

cortex (figure 1) (Volkow et al. 1988). The defects in CBF remained after 10 days

of cocaine detoxification and were interpreted as reflecting the vasoconstricting

actions of cocaine. In vitro studies had demonstrated that cocaine can induce

vasospasm in cerebral blood vessels (Altura et al. 1985), which in turn decreases

CBF. Although the pharmacological half-life of cocaine is short (40 to 60

minutes) (Javaid et al. 1983) the pattern of utilization of cocaine by the cocaine

abuser involves repeated administration for periods of 48 to 72 hours (binge),

which can lead to prolonged periods of cerebral blood vessel vasospasm. This

continuous vasospasm could induce ischemia and necrosis of brain tissue.

169
FIGURE 1. Images obtained using H2

150 to measure CBF in a chronic

cocaine abuser. Note the marked disruptions in uptake of the

tracer in the anterior areas of the brain (arrows) suggestive of

decreases in regional CBF.

Under normal physiological conditions CBF and brain glucose metabolism are

tightly coupled (Siesjo 1978) and reflect brain function (Sokoloff 1978).

However, under certain circumstances, CBF and metabolism can be uncoupled

as could be hypothesized to happen when administering a vasoactive agent. In

the case of cocaine this is a complex issue because cocaine has vasoactive

effects as well as neurochemical effects on brain tissue activity (Pitts and

Marwah 1988). To assess whether decreases in CBF secondary to chronic

170
cocaine use were due to decreased brain metabolism, a subgroup of 10 chronic

cocaine abusers were investigated using H2

15O for CBF and 18FDG to measure

regional brain glucose metabolism. Only four of these patients showed

evidence of metabolic defects similar to the flow deficiencies seen using H2

15O.

For the six remaining patients, the metabolic defects were smaller than the CBF

effects, suggesting that, for most of the cases, the decrease in CBF had not led

to comparable changes in brain metabolism. Nevertheless, most of the patients

showed evidence of decreased metabolic activity in the frontal cortex (Volkow et

al. 1988). These preliminary studies support the notion that the widespread

decreases in CBF in cocaine abusers are due to the vasoactive properties and

not to the actions of cocaine on brain tissue activity. However, it is difficult to

assess whether the decreased metabolic activity in the frontal cortex is

secondary to changes in perfusion or whether it reflects changes directly

associated with the actions of cocaine in the dopamine system.

COCAINE ADDICTION

The addicting properties of cocaine have been related to its effect on the

dopamine system (Dackis and Gold 1985). The “dopamine depletion

hypothesis” suggests that chronic cocaine abuse leads to a depletion of

dopamine in the presynaptic neuron. Although there have been several animal

experiments designed to document decreases in dopamine function as

assessed by measurements of dopamine synthesis, metabolism, and receptor

concentrations, the results are controversial, with different groups showing

decreases, no change, or increases in dopamine activity (Post et al. 1987;

Galloway 1988).

With PET it is feasible to directly evaluate dopamine function in the living human

brain. The following different parameters of the dopamine system can be

measured:

Postsynaptic dopamine D-2 receptors using compounds such as 11C- or

18F-labeled N-methylspiroperidol (NMS) (Wagner et al. 1983; Arnett et al.

1985) or 11C-raclopride (Farde et al. 1985).

Postsynaptic dopamine D-1 receptors using a compound such as 11Clabeled SCH 23390 (Halldin et al. 1986).

The presynaptic dopamine transporter using compounds such as 11Cnomifensine (Aquilonius et al. 1987), 18F-GBR (Kilbourn 1988) and 11Ccocaine (Fowler et al. 1989).

171
Regional brain activity of those areas that either have a high concentration

of dopamine receptors or receive afferents from the dopamine system.

This can be achieved using 18FDG and/or 11CDG (Reivich et al. 1985).

Dopamine neurotransmitter synthesis using compounds such as [

18F]fluoroL-Dopa (Baxter et al. 1988).

Preliminary work has been done with PET in measuring the concentration of

postsynaptic dopamine receptors in the human brain to assess if chronic

cocaine use leads to dopamine depletion. If there is depletion of dopamine,

there should be an upregulation of postsynaptic dopamine receptors, which

then could be measured with 18F-NMS or 11C-raclopride and PET. A study of 10

chronic cocaine abusers—7 were studied within 1 week of the last

administration of the drug, and 3 were studied after 4 weeks of detoxification—

showed that the short-term detoxified cocaine abusers had a decrease in

binding of 18F-NMS suggestive of a decrease in the number of postsynaptic

dopamine receptors (Volkow et al. 1990). In contrast, the patients who had

been detoxified for 4 weeks before the study showed values of uptake of 18FNMS similar to those of normal individuals. This study showed that the changes

in postsynaptic dopamine receptors are not fixed and appear to be related to

the amount of time that has elapsed after cocaine discontinuation. During

active cocaine administration or shortly after its withdrawal, there is

downregulation of postsynaptic dopamine receptors to compensate for

dopamine overstimulation from cocaine. With protracted cocaine withdrawal,

dopamine overstimulation is discontinued with a consequent increase in

postsynaptic dopamine receptors.

Effects of chronic cocaine use on dopamine synthesis also have been

investigated in humans using PET and [

18F]fluoro-L-Dopa. A preliminary study

reported that shortly after detoxification from cocaine, there was an overall

decrease in uptake of [

18F]fluoro-L-Dopa in the brain consistent with decreased

dopamine synthesis (Baxter et al. 1988). After 30 days of cocaine

detoxification, the uptake of [

18F]fluoro-L-Dopa was similar to that seen in

normals, suggesting a normalization of dopamine synthesis after

discontinuation of the drug.

Studies evaluating the effects of chronic cocaine on glucose metabolism are

controversial, with one study reporting a decrease in prefrontal cortical activity

in the chronic cocaine abuser (Volkow et al. 1988) and another failing to report

abnormalities in glucose metabolism in these patients (Baxter et al. 1988). The

study documenting decreased metabolism in the frontal cortex related these

effects to the action of cocaine in the dopamine system, which sends

projections into the prefrontal cortex.

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With PET it is feasible to monitor not only the postsynaptic receptor but also the

presynaptic dopamine terminal. Currently, labeling of the dopamine presynaptic

terminal can be accomplished using compounds that bind to the dopamine

transporter. There have not been any human studies investigating the effects

of chronic cocaine on the dopamine transporter or on dopamine D-1 receptors.

COCAINE REINFORCEMENT

Mechanisms of reinforcement of cocaine can be assessed with PET using

different experimental strategies.

1. Acute administration of cocaine to monitor sensitivity of different brain

areas to actions of cocaine. This in turn can provide information on the

brain areas that are responsible for the behavioral actions of cocaine and

the neurotransmitters that may be involved with the function of these

regions.

2. Measurement of pharmacokinetics of cocaine within the brain. This can be

achieved using 11C-cocaine and monitoring its distribution and kinetics in

the human brain.

The effects of acute cocaine administration on regional brain glucose

metabolism have been investigated with PET and 18FDG. The study was done

on a group of chronic cocaine abusers who were given an acute dose of 40 mg

of cocaine hydrochloride intravenously. Two minutes after cocaine injection,

these patients were injected with 18FDG to monitor for the effects of the drug on

regional brain glucose metabolism (London et al. 1990). This study reported an

overall decrease in glucose metabolism in the cortex and in the extrapyramidal

system after acute cocaine administration. In contrast, the cerebellum failed to

show any response to cocaine. The decrease in cortical metabolism after acute

cocaine administration was interpreted as reflecting the actions of cocaine on

dopamine, because other dopamine agents such as amphetamines also have

been shown to decrease cortical glucose metabolism (Wolkin et al. 1987);

dopamine antagonists have been shown to increase glucose metabolism

(Volkow et al. 1986).

With PET, it is also feasible to directly monitor the pharmacokinetics of a given

drug at its site of action. 11C-cocaine was used to monitor the distribution and

kinetics of cocaine in the human brain. This study was done in baboons and in

humans and demonstrated that cocaine rapidly enters the brain. Maximal

accumulation of cocaine in the brain occurred between 4 and 8 minutes after

injection. Clearance of 11C-cocaine was rapid; by 20 minutes postinjection, only

50 percent of the radioactivity remained in the brain. The accumulation of

173
cocaine in the brain was heterogenous, with the basal ganglia showing the

highest concentration of 11C-cocaine (figure 2). Binding of cocaine into the

basal ganglia appeared to be related to the dopamine transporter because

pretreatment with nomifensin (a dopamine transporter inhibitor) decreased

binding of 11C-cocaine in the basal ganglia, whereas desipramine (a blocker of

FIGURE 2. Images obtained 15 minutes after administration of 11C-cocaine in

a normal human volunteer. The images represent an axial (upper

left), a sagittal (upper right), and a coronal (lower left) plane at the

level where the basal ganglia are located. Note that maximal

binding of 11C-cocaine occurs in the basal ganglia.

174
the serotonin and norepinephrine transporter) failed to affect the binding of

cocaine in the basal ganglia (Fowler et al. 1989). Rapid uptake and clearance

of cocaine from the brain were compared with the time response to the

euphorigenic actions of cocaine when administered intravenously. The data for

the euphorigenic effects of cocaine were obtained from Cook and colleagues

(1985). In this study cocaine abusers were injected intravenously with 20 mg of

cocaine, and their subjective response to the “high” from cocaine was monitored

every minute during the first 5 minutes and at 2-minute intervals thereafter for

30 minutes (Perez-Reyes et al. 1982). The values for the time-related response

to the euphorigenic actions of cocaine were compared with the kinetics of 11Ccocaine in the striatum in a group of eight normal subjects. Although the two

populations of subjects were different, there was a close parallel between the

time activity curves of these two groups (figure 3).

FIGURE 3. Panel A shows the time course of the mean subjective high after

intravenous cocaine (data from Cook et al. 1985). Panel B shows

the time course of 11C-cocaine in the human basal ganglia

measured by PET (Fowler et al. 1989). Note that the curves

parallel one another, suggesting an association between

behavioral elevation and cocaine binding in the basal ganglia.

The parallel between the two time curves suggests that the euphorigenic

actions of cocaine are associated with the rapid binding of cocaine into the

dopamine transporter and that the short duration of cocaine action also is

related to the release of cocaine from its binding site.

175
SUMMARY

It is feasible to directly image and measure the concentration of different drugs

of abuse and their consequences on regional brain function and

neurotransmitter activity with PET. Although PET is a relatively new technique,

it already is proving to be useful in disclosing the mechanisms of toxicity

reinforcement and addiction of drugs of abuse.

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ACKNOWLEDGMENT

This research was performed under U.S. Department of Energy contract DEAC02-76CH00016.

AUTHORS

Nora D. Volkow, M.D.

Associate Scientist

Medical Department

Joanna S. Fowler, Ph.D.

Senior Chemist

Alfred P. Wolf, Ph.D.

Director

Cyclotron-PET Program

Senior Chemist

Chemistry Department

Brookhaven National Laboratory

Building 490

Bell Avenue

Upton, NY 11973

179
Development of Opioid Peptide

Analogs as Pharmacologic Tools

and as Potential Drugs: Current

Status and Future Directions

Peter W. Schiller

INTRODUCTION

It is generally recognized that opiates and opioid peptides exert their various

biological effects through interaction with either central or peripheral receptors,

and the existence of at least three different classes of opioid receptors (μ,

also generally is accepted (Paterson et al. 1984). More recently, several

investigators obtained evidence indicating that subtypes of the three major

opioid receptor classes may exist; however, the issue of opioid receptor

subtypes still remains somewhat controversial and needs to be clarified further.

It has not yet been possible to establish clear-cut relationships linking specific

opioid receptor types or subtypes to distinct opioid effects. This is mainly due to

the fact that, until recently, potent stable opioid agonists and antagonists with

high specificity for the various receptor types or subtypes have not been

available. Unfortunately, the various endogenous opioid peptides resulting from

processing of the three precursor molecules display only limited selectivity

toward the various receptor types (HölIt 1986). On the other hand, various

peptides of the (ß-casomorphin family show high μ-receptor selectivity but

relatively low receptor affinity (Brantl et al. 1981). The most selective naturally

occurring opioid peptides discovered to date are the dermorphins (μ-selective)

(Montecucchi et al. 1981) and the deltorphins ( -selective) (Erspamer et al.

1989). Because of their already high-receptor selectivity, the dermorphins and

deltorphins represent excellent starting points for the development of ligands

with even higher μ- or -receptor specificity.

Numerous efforts have been made to obtain more selective opioid receptor

ligands through synthesis of opioid peptide analogs that were developed on the

basis of the following three design principles:

180
1. Substitution, deletion, or addition of natural or artificial (nonproteinogenic)

amino acids

2. Concept of conformational restriction of opioid peptides through various

appropriate cyclizations

3. Design of bivalent compounds containing two opioid receptor ligands

separated by a spacer of appropriate length and able to interact

simultaneously with two receptor binding sites

The applications of these three design strategies in the opioid peptide field are

described in the following sections.

LINEAR ANALOGS OF OPIOID PEPTIDES

Many efforts have been made to develop more selective opioid receptor ligands

through synthesis of linear opioid peptide analogs. Hundreds of enkephalin

analogs have been prepared, mostly by the classical approach of substituting

one or several natural or artificial amino acids in various positions of the peptide

sequence. These efforts resulted in several selective compounds, such as HTyr-D-Ala-Gly-Phe(NMe)-Gly-ol (DAGO; μ-selective) (Handa et al. 1981) and HTyr-D-Ser(OtBu)- Gly-Phe-Leu-Thr-OH (DSTBULET; -selective) (FourniéZaluski et al. 1988). The substituted tripeptide enkephalin analog MeTyr-D-AlaGly-N(Et)-CH(CH2

-Phe)CH2-N(CH3)2 (LY164929) also shows high μ-selectivity

(Rothman et al. 1988). The enkephalin analog (N-allyI)2

-Tyr-Gly- [CH2S]PheLeu-OH is a fairly selective but not very potent -antagonist (Shaw et al. 1982).

Among various analogs derived from peptides of the ß-casomorphin family, the

potent agonist PL017 (H-Tyr-Pro-Phe(NMe)- D-Pro-NH2) is the most μ-selective

(Chang et al. 1983).

The most selective μ-agonist developed to date is the dermorphin tetrapeptide

analog H-Tyr-D-Arg-Phe-Lys-NH2 (DALDA) (Schiller et al. 1989a). DALDA

displays high affinity for μ-receptors, and its extraordinary μ-selectivity is a

consequence of extremely poor -receptor affinity (table 1). The tetrapeptide

amide is about 60 times more μ-selective than the parent peptide, dermorphin.

Furthermore, the μ-selectivity displayed by DALDA is 11 times higher than that

of DAGO and 8 times higher than that of PL017. Its affinity for -opioid

receptors is negligible 1,000 nM). In the guinea pig ileum (GPI) and mouse

vas deferens (MVD) assays, DALDA was shown to be a full agonist. As

expected, this compound showed extremely low potency (IC50~40 μM) in the

bioassay based on inhibition of electrically evoked contractions of the hamster

vas deferens, a tissue containing opioid receptors exclusively of the -type.

Because of its high positive net charge (3+), DALDA most likely will not be able

181
to cross the blood-brain barrier to any significant extent. Thus, it may be that,

aside from its high μ-receptor preference, this analog also may show

pronounced selectivity for peripheral vs. central receptors. Therefore, DALDA

may be particularly useful as a specific agonist for studying peripheral

μ-receptor interactions (see below).

TABLE 1. Receptor affinities and μ-selectivity of opioid peptide analogsa

Compound [nM]b

[nM]b

DALDA 1.69 ± 0.25 19,200 ± 2,000 11,400

Dermorphin 0.839 ± 0.013 160 ± 56 191

DAGO 1.22 ± 0.12 1,280 ± 90 1,050

PLO17 2.89 ± 0.30 4,250 ± 540 1,470

aBinding assays based on displacement of [3H]DAGO (μ-selective) and

[

3H]DSLET ( -selective) from rat brain membrane preparations

(DSLET=H-Tyr-D-Ser-Gly-Phe-Leu-Thr-OH).

bMean of three determinations±SEM.

Because peptides with the phenylalanine residue in the 3-position (ßcasomorphins, dermorphins, deltorphins) and peptides with the Phe residue in

the 4-position of the peptide sequence (enkephalins, dynorphins, ß-endorphin)

are potent opioid agonists, it was of interest to prepare dermorphin-enkephalin

hybrids containing a Phe residue in the 3- and 4-positions. The prototype

analog H-Tyr-D-Ala-Phe-Phe-NH2 (TAPP) showed high μ-receptor affinity and

selectivity in the rat brain membrane receptor binding assays (table 2) (Schiller

et al. 1989a). Introduction of a nitro substituent in para position of the Phe

aromatic rings produced a potency drop in position 3 and a potency increase in

position 4, as it had been observed in the case of opioid peptides with a single

Phe residue in either the 3- or 4-position (Schiller et al. 1983), indicating that the

two Phe residues in TAPP do interact with the two distinct receptor subsites

previously proposed. Unlike the polar analog DALDA, TAPP is a relatively

lipophilic molecule. In an effort to obtain even more lipophilic opioid peptide

analogs, we substituted bulky, hydrophobic amino acids, such as tryptophan or

1 (or 2)-naphthylalanine (Nap), in positions 3 and 4 of TAPP. The resulting

analogs still showed high μ-receptor selectivity and, because of their quite high

lipophilicity, may be able to cross the blood-brain barrier to some extent after

peripheral administration.

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TABLE 2. Opioid receptor affinities of dermorphin-enkephalin hybrid analogsa

Compound [nM]b

[nM]b

H-Tyr-D-Ala-Phe-Phe-NH2 1.53 ± 0.59 626 ± 162 409

H-Tyr-D-Ala-Phe(pNO2)-Phe-NH2 56.80 ± 12.70 1,380 ± 276 24.3

H-Tyr-D-Ala-Phe-Phe(pNO2)-NH2 0.509 ± 0.022 65.5 ± 14.0 129

H-Tyr-D-Ala-Trp-Trp-NH2 0.833 ± 0.071 652 ± 49 783

H-Tyr-D-Ala-1-Nap-1-Nap-NH2 2.88 ± 0.43 1,180 ± 230 410

H-Tyr-D-Ala-2-Nap-1-Nap-NH2 5.61 ± 0.60 575 ± 13 102

aBinding assays were performed as indicated in table 1.

bMean of three determinations±SEM.

The most selective -agonists known to date are the deltorphins, three opioid

peptides that have recently been isolated from frog skin (Erspamer et al. 1989).

No consensus regarding nomenclature seems to have been reached as yet, but

referring to them as deitorphin, [D-Ala2

]deltorphin I, and [D-Ala2]deltorphin II, as

suggested by the discoverers, seems reasonable:

H-Tyr-D-Met-Phe-His-Leu-Met-Asp-NH2 (deltorphin)

H-Tyr-D-Ala-Phe-Glu-Val-Val-Gly-NH2 ([D-Ala2]deltorphin I)

H-Tyr-D-Ala-Phe-Asp-Val-Val-Gly-NH2 ([D-Ala2]deltorphin II)

Among these three peptides, [D-Ala2]deltorphin II shows highest selectivity with

a reported selectivity ratio of 21,000 (Erspamer et al. 1989), thus

apparently being nearly 100 times more -selective than the cyclic enkephalin

analog [D-Pen2,D-Pens]enkephalin (DPDPE) (Mosberg et al. 1983).

Among the various endogenous opioid peptides, dynorphin A is the most potent

at the -receptor; but it also interacts with μ- and receptors and, therefore,

displays only moderate -selectivity. A relatively limited number of analogs have

been prepared in attempts to improve the -selectivity and the stability of

dynorphin A. The dynorphin analog with highest -selectivity reported to date is

(D-Pro10]dynorphin A-(1-11), showing a ratio of 60 and a ratio of 230

(Gairin et al. 1985). Efforts will have to be made to develop dynorphin analogs

with further improved general -selectivity. Such analogs also may be useful for

the elucidation of the still controversial issue of -receptor heterogeneity and may

be selective for distinct -receptor subtypes.

183
CYCLIC OPIOID PEPTIDE ANALOGS

Small linear opioid peptides, such as the enkephalins, are flexible molecules, as

indicated by numerous conformational studies (Schiller 1984). This structural

flexibility may be one of the reasons for the lack of receptor selectivity of these

peptides, because conformational adaptation to the various receptor binding

sites is possible. Because of this, a different approach of analog design based

on conformational restriction through peptide cyclization via side chains of

appropriately substituted amino acids was taken in the author’s laboratory a

decade ago (DiMaio and Schiller 1980). The first cyclic enkephalin analog, HTyr-cyclo[-D-A2bu-Gly-Phe-Leu-] (A2bu= -diaminobutyric acid), showed high

potency in the GPI assay and moderate μ-receptor selectivity (Schiller and

DiMaio 1982). Variation of the side-chain length in the 2-position of this

prototype analog through substitution of A2pr ( ,ß-diaminopropionic acid), Orn,

or Lys resulted in a series of cyclic homologs that were also moderately μselective (DiMaio et al. 1982). The cystine-containing cyclic peptides H-Tyr-DCys-Gly-Phe-D(or L)-Cys-X are examples of side-chain-to-side-chain cyclized

analogs. [D-Cys2, D(or L)-Cys5]Enkephalinamides (X=NH2) were highly potent

in the GPI assay but nonselective (Schiller et al. 1981), whereas the

corresponding analogs with a free C-terminal carboxyl group (X=OH) were

about as moderately -receptor selective as the natural enkephalins (Schiller et

al. 1985a). Replacement of the two half-cystine residues in these peptides with

penicillamine residues resulted in compounds with considerably improved

-selectivity (H-Tyr-D-Pen-Gly-Phe-Pen-OH [DPLPE] and H-Tyr-D-Pen-GlyPhe-D-Pen-OH[DPDPE]) (Mosberg et al. 1983).

The receptor selectivities of the cyclic enkephalin analogs described above

have been further improved through additional structural modifications. For

example, the reversal of two peptide bonds in the ring structure of H-Tyrcyclo[-D-A2bu-Gly-Phe-Leu-] led to a compound, H-Tyr-cyclo[-D-Glu-Gly-gPheD-Leu-], which is three times more μ-selective than the cyclic parent peptide

(Berman et al. 1983). Furthermore, thioamide [CSNH] peptide bond

replacements in H-Tyr-cyclo[-D-Lys-Gly-Phe-Leu-](selectivity ratio =13.7)

produced two compounds, H-Tyr-cyclo[-D-Lys-Gly (CSNH]Phe-Leu-]

=144) and H-Tyr-cyclo[-D-Lys-Gly [CSNH]Phe-Leu [CSN’H]] =107),

showing an approximate tenfold improvement in μ-selectivity (Sherman et al.

1989). Finally, substitution of (S,S)ß-methyl-p-nitrophenylalanine for Phe in

position 4 of H-Tyr-D-Pen-Gly-Phe-D-Pen-OH resulted in a compound showing

vs. μ-selectivity five times higher than that of the DPDPE parent peptide, as

assessed in the GPI and MVD assays (Hruby et al. 1989).

The dermorphin tetrapeptide analog H-Tyr-D-Orn-Phe-Asp-NH2 is the most

selective cyclic opioid peptide analog with μ-agonist properties reported to date

184
=213) (Schiller et al. 1985b). Interestingly, the cyclic tetrapeptide analog

H-Tyr-D-Cys-Phe-D-Pen-OH displayed -receptor selectivity similar to that of

DPDPE, but had about 3.5 times higher receptor affinity than DPDPE

(Mosberg et al. 1988). In contrast to most of the cyclic enkephalin analogs

described above, these two cyclic opioid peptides with Phe in the 3-position of

the peptide sequence contain highly constrained 13- and 11 -membered ring

structures, respectively.

In an effort to reduce the conformational flexibility of the -receptor-selective

opiold peptide dynorphin A, the cyclic analogs [D-Orn2, Asp5]dynorphin A-(1-8),

[Orn5, Asp5]dynorphin A-(1-13), [Orn5, Asp10]dynorphin A-(1-13), and [Orn5,

Asp13]dynorphin A-(1-13) were recently synthesized (Schiller et al. 1988). All

four analogs showed Ko

 values for naloxone as antagonist below 5 nM in the

GPI assay, indicating that they no longer interact significantly with -receptors.

In the receptor binding assays, [D-Orn2, Asp5]dynorphin A-(1-8) displayed

extraordinarily high affinity for the μ-receptor, and the determined ratios of the

binding inhibition constants indicated that all four analogs are μselective. It was concluded that the performed cyclizations resulted in overall

folded conformations that are incompatible with the conformational

requirements of the -receptor. Further attempts will have to be made to

develop cyclic dynorphin analogs that retain the -characteristics of the native

peptide.

Recently, a cyclic somatostatin-related peptide analog, H-D-Phe-Cys-Phe-DTrp-Lys-Thr-Cys-Thr-ol (SMS 201-995), was shown to possess antagonist

properties at μ-opioid receptors (Maurer et al. 1982). Similar somatostatin

analogs characterized by additional constraints in the ring structure, such as

TCTOP (H-D-Tic-Cys-Tyr-D-Trp-Orn-Thr-Pen-Thr-NH2 (Kazmierski et al. 1988),

were subsequently prepared. The latter analogs are the most selective μantagonists reported to date and, unlike SMS 201-995, no longer display

significant affinity for somatostatin receptors. Aside from representing valuable

tools in opioid pharmacology, the various receptor-selective cyclic opioid

peptide analogs are of great interest for conformational studies aimed at

determining the bioactive conformation of opioid peptides at the μ- or

receptor. The conformation(s) of some of the cyclic analogs have been studied

by various techniques, including theoretical studies based on the molecular

mechanics or molecular dynamics approach, nuclear magnetic resonance

(NMR) spectroscopy, and fluorescence spectroscopy (Schiller and Wilkes

1988). These conformational studies have not yet led to a consensus

concerning a possible unique bioactive conformation at the receptor. An

important finding of these endeavors was the realization that the ring structures

in the cyclic enkephalin analogs still retain some flexibility and that the various

intramolecular hydrogen bonds observed are constantly formed, broken, and

185
reformed again, as shown most conclusively in molecular dynamics studies

(Mammi et al. 1985). In the case of H-Tyr-c[-D-A2bu-Gly-Phe-Leu-] and H-Tyrc[-D-Orn-Gly-Phe-Leu-] (Kessler et al. 1985), the results of NMR studies

indicated the existence of a hydrogen bond that defines a -turn centered on

Phe4

 (figure 1). Computer simulations revealed that this hydrogen bond occurs

with relatively high frequency on the picosecond time scale (Mammi et al.

1985). In a molecular mechanics study, extensive energy minimization was

performed with 10 cyclic tetrapeptides structurally related to H-Tyr-D-Orn-PheAsp-NH2

 and displaying considerable diversity in μ-receptor affinity (Wilkes and

Schiller 1990). The results of this study suggested that a tilted stacking

arrangement of the Tyr1 and Phe3 aromatic rings may represent a structural

requirement for high μ-receptor affinity of the examined cyclic dermorphin

analogs. However, this study also revealed that the exocyclic Tyr1 residue and

the Phe3

 side-chain still enjoy considerable orientational freedom. To obtain

more definitive insight into the receptor-bound conformation of the various cyclic

opioid peptides described above, it will be necessary to develop analogs in

which the Tyr residue and the Phe side-chain also are restricted

conformationally.

OPIOID PEPTIDE MIMETICS

In efforts to develop peptide-derived drugs, it often would be desirable to

replace parts of the peptide backbone with other appropriate structural elements

to eliminate susceptibility to enzymatic degradation and to reduce the relatively

polar character of peptide molecules that may prevent them from being well

absorbed and from crossing certain barriers, such as the blood-brain barrier.

Such compounds generally are referred to as peptide mimetics. It is imperative

that the spatial disposition of side chains that are crucial for the interaction of

the native peptide with the receptor be retained in the peptide mimetic.

Whereas the various modifications of individual peptide bonds described above

represent a first step in the direction of developing peptide mimetics, the

substitution of structural elements mimicking larger portions of the peptide

backbone also has been attempted. The latter approach is particularly

applicable to peptides with a relatively well-defined conformation such as the

semirigid cyclic analogs discussed above. An example is the peptide mimetic

derived from the cyclic enkephalin analog H-Tyr-cyclo[-D-Orn-Gly-Phe-Leu-]

(Huffman et al. 1989), shown in figure 1. In this compound, the -turn structure

detected in the cyclic parent peptide (see above) is replaced by a -turn mimic.

One of the peptide bonds in the -turn mimic is replaced with a trans olefin, and

the oxygen and hydrogen atoms of the hydrogen bond (C=O H-N) are

replaced with an ethylene moiety. Diastereomers of the bicyclic compound with

either R or S configuration at the chiral center of the -turn mimic were obtained

separately. Both diastereomers essentially were inactive in the GPI and MVD

186
assays and showed weak affinity for μ- and -opioid receptors in the rat brain

membrane binding assay. The lack of activity of these peptide mimetics can be

explained in several ways. First, it is possible that the -turn detected in the

NMR and computer simulation studies of the monocyclic parent peptide may not

be a structural feature of the receptor-bound conformation. Second, the Gly3

carbonyl group that is no longer present in the -turn mimic may be important

for the interaction with the receptor. Third, the ethylene bridge introduced in the

mimic may interfere with the receptor binding process either due to unfavorable

steric interactions or due to the fact that it produces too much rigidity in the

molecule.

FIGURE 1. Structural formulas of the cyclic enkephalin analog H-Tyrcyclo[-D-Orn-Gly-Phe-Leu-] (left) and of a bicyclic enkephalin

analog containing -turn mimic (right)

In contrast to the rational design of peptide mimetics just described, large-scale

screening of substances from various sources by means of a receptor binding

assay recently also led to the discovery and development of most useful

peptide mimetics. The best known example is the discovery of the novel

benzodiazepine natural product asperlicin, which is an antagonist of

cholecystokinin (CCK) (Freidinger 1989). Using asperlicin as a starting point, a

series of structurally related methylbenzodiazepines then was developed by the

Merck group. One of these compounds, MK-329, became a potent competitive

CCK antagonist with high preference for CCKA over CCKB receptors; whereas

another, L-365260, was a potent, competitive, and orally active CCK antagonist

showing CCKB receptor selectivity. Another screening discovery is the recently

described nonpeptide angiotensin II receptor antagonists, such as the imidazole

acetic acid derivative S-8307 (Wong et al. 1988). Even though these

compounds have relatively weak receptor affinity (K1~10-5M), they represent

187
excellent starting points for the development of angiotensin antagonists with

therapeutic potential.

BIVALENT OPIOID RECEPTOR LIGANDS

In attempts to bridge two opioid receptor binding sites, various bivalent ligands

containing two enkephalin-related peptides linked via their C-terminal carboxyl

group through flexible spacers of varying length have been synthesized and

pharmacologically tested. It has been observed that, at a certain spacer length,

the affinity and selectivity for -receptors increased drastically (Shimohigashi et

al. 1982). This result was interpreted to indicate that a bivalent ligand with the

right spacer length is capable of bridging two -binding sites. Analogous

dimerization of the tripeptide H-Tyr-D-Ala-Gly-OH via a short spacer resulted in

a highly μ-selective compound (Lutz et al. 1985a), which apparently is able to

simultaneously bind to two μ-binding sites. These studies with bivalent opioid

peptide ligands had been initiated based on the hypothesis that opioid receptors

of the or the μ-type might be clustered together and that the distance

between two -receptors in such clusters might be different from that between

two μ-receptors. Therefore, it was thought that variation of the spacer length

might produce either or μ-selective ligands, as turned out to be the case.

However, on the basis of data obtained from binding experiments in which the

opioid receptor density was altered through irreversible labeling with the

selective ligand FIT (Lutz et al. 1985b) as well as on the basis of structural

considerations, it now seems more likely that these bivalent ligands are able to

bridge binding sites on two putative subunits of either the or μ-receptor rather

than interacting with two separate receptors. The best bivalent μ-ligand is

about three times less selective than morphiceptin, and the most selective

bivalent -ligand shows vs. μ-selectivity comparable to that of DPDPE.

These bivalent opioid peptide ligands represent valuable tools for basic opioid

receptor research, but are perhaps less attractive as candidates for peptide

drug development because of their increased molecular size.

OPIOID PEPTIDE ANALOGS AS POTENTIAL DRUGS

The two best known enkephalin analogs that have undergone fairly extensive

clinical testing so far are the Sandoz compound FK33-824(H-Tyr-D-Ala-GlyPhe(NMe)-Met(O)-ol) (Von Graffenried et al. 1978) and the Eli Lilly compound

metkephamid (H-Tyr-D-Ala-Gly-Phe-Met(NMe)-NH2

) (Frederickson 1986).

FK33-824 shows only moderate preference for μ-receptors over -receptors,

and metkephamid is essentially nonselective toward μ- and -receptors (table

3); neither analog has significant affinity for -receptors. Both FK33-824 and

metkephamid exert a potent centrally mediated analgesic effect after systemic

administration. However, FK33-824 also produced a number of quite serious

188
side effects (table 3) and is no longer pursued clinically as an analgesic

candidate. Relatively fewer side effects were observed with metkephamid.

Some evidence was obtained to indicate that metkephamid may exert its central

analgesic effect through interaction with -receptors and that it may produce

less physical dependence than morphine. Of particular interest was the

observation that this analog does not cross the placental barrier to a significant

extent in the pregnant sheep model (Frederickson 1986). This finding

suggested that metkephamid might be of interest for use in obstetric analgesia.

However, metkephamid finally was abandoned as a candidate for obstetric

analgesia because it also produced a transient hypotensive effect in the

particular obstetric population that had been subjected to a clinical trial. The

various side effects observed with FK33-824 and metkephamid led to a certain

discouragement with regard to the potential of opioid peptides as viable

analgesics. However, it should be realized that the lack of receptor selectivity of

these two enkephalin analogs may be responsible for some of the observed

side effects. Progress recently made in the development of opioid peptide

analogs now permits the preparation of compounds showing greatly improved

receptor selectivity and, therefore, showing better potential for application in

various types of analgesia.

In recent years, increasing evidence has been obtained to indicate that opioids

are able to produce peripherally mediated analgesic effects. Although data on

peripheral antinociceptive effects in normal noninflamed tissue are still

controversial, effects in hyperalgesic and inflammatory conditions have been

well documented (Ferreira and Nakamura 1979; Smith et al. 1982; Stein et al.

1988). The mechanism underlying peripherally mediated, opioid-induced

antinociceptive effects is not entirely clear, but they appear to be mediated by

inhibition of sensory neurons that would prevent information about noxious

events from reaching the spinal cord. The most convincing evidence for the

occurrence of peripherally mediated analgesic effects has been obtained from

studies with opioid agonists and antagonists that are unable to cross the bloodbrain barrier. Thus, it has been demonstrated that N-methylmorphine was able

to produce an analgesic effect in the mouse writhing test that could be

antagonized with N-methylnalorphine (Smith et al. 1982). Because these

quaternized opiates do not have access to the brain, it is obvious that

antinociception was induced through interaction with peripheral opioid

receptors. Obviously, peripherally acting opioid agonists have potential for

clinical applications, because they will not produce centrally mediated side

effects such as dependence and respiratory depression. For example, such

compounds could be used for the treatment of painful inflammatory conditions.

Recently, a relatively polar enkephalin analog, H-Tyr-D-Arg-Gly-Phe(pNO2

)-ProNH2

 (BW443C), also has been shown to produce peripherally mediated

antinociception in the mouse writhing test at a dose of about 5 mg/kg (Hardy et

189
TABLE 3. Clinical testing of enkephalin analogs

Compound Selectivity Analgesia Side Effects

Tyr-DAla-Qly-Phe(NMe)-Met(O)-ol

(FK33-824)

Centrally mediated

(systemic

administration)

Muscle heaviness

Chest oppression

Anxiety

Bowel sound

Increase

Chemosis

Whole body flush

Tyr-DAla-Gly-Phe-Met(NMe)-NH2

(metkephamid)

Heavy sensation

in extremities

Nasal congestion

Emotional

detachment

Conjunctival

infection

Hypotension

Tyr-DArg-Qly-Phe(pNO2

)-Pro-NH2

(BW443c)

Nonselective Centrally mediated

(systemic

administration)

Does not cross

placental barrier

Somewhat

μ-selective

Peripherally

mediated

(S.C.

administration)

Nasal stuffiness

Dry mouth

Postural

hypotension

No central effects

(such as sedation,

mood change,

respiratory

depression)

al. 1988). Preliminary clinical studies indicated that side effects of this

moderately μ-selective compound given by intravenous (IV) infusions (10 μgkg-1

min-1 for 20 minutes) were relatively minor (table 3); and there was no evidence

for central activity such as sedation, respiratory depression, and mood changes

(Posner et al. 1988).

The analgesic activity of the highly μ-selective dermorphin tetrapeptide analog

DALDA was compared with that of morphine in the mouse writhing test (table 4)

(Schiller et al. 1989b). In this assay, DALDA showed an ED50 comparable to

that of morphine 5 minutes after administration (s.c.). The effect of DALDA

seems to be of somewhat shorter duration than that of morphine; but

nevertheless, it is remarkable that this peptide analog showed a still relatively

low ED50 (2.80 mg/kg) when given 60 minutes before the administration of

phenyl-1, 4-benzoquinone. The antinociceptive effect of DALDA in the writhing

assay could be antagonized with the quaternary opiate antagonist Nmethyllevallorphan (10 mg/kg intraperitoneal [IP]), which increased the ED50

190
(20 minutes) from 0.65 mg/kg to 2.98 mg/kg (figure 2). Because Nmethyllevallorphan is unable to cross the blood-brain barrier, this observation

suggests that DALDA produces antinociception through interaction with

peripheral μ-receptors. On the other hand, the antinociceptive effect of

morphine (s.c.) was unchanged after IP administration of the same dose of Nmethyllevallorphan, as expected in the case of a centrally acting compound.

DALDA also showed high potency in the writhing assay after IV administration.

On the other hand, in the mouse hot plate test, peripheral administration of

DALDA produced an analgesic effect only at high doses (ED50>20 mg/kg),

indicating that access of this compound to the central nervous system is limited.

In comparison with the peripherally acting enkephalin analog BW443C

discussed above, DALDA is more polar, more potent, and much more μselective. DALDA also shows considerably higher μ-selectivity than do the

dermorphin analogs H-Tyr-D-Arg-Phe-Sar-OH (Sasaki et al. 1985) and H-Tyr-DMet(O)- Phe-D-Ala-OH (Marastoni et al. 1987), which have been shown to be

highly active in various analgesic tests.

TABLE 4. Mouse writhing test of DALDA and morphine

Compound

Timea ED50

(min) (mg/kg)

DALDA 5 0.48

20 0.65

60 2.80

Morphine 5 0.31

20 0.43

80 0.60

a

Time interval between administration of test compound (s.c.) and phenyl-1,4-

benzoquinone (2.5 mg/kg IP).

Aside from peripherally induced analgesia, other peripheral effects of opioid

peptides might be exploited for the development of potential drugs. Of

particular interest are the various effects of opioid peptides in the

gastrointestinal tract. Recently, the enkephalin analog H-Tyr-D-Met(O)-GlyPhe(pNO2

)-Pro-NH2 (BW942C) was shown to be a safe and effective agent for

controlling diarrhea after cisplatin administration in cancer patients (Kris et al.

1988). Another study performed with the μ-selective enkephalin analog H-TyrD-Lys-Gly-Phe-homocysteine-thiolactone (Hoe 825) revealed that this

191
FIGURE 2. Analgesic effect of DALDA in the mouse writhing test in absence

(•) and presence of N-methyllevallorphan (10 mg/kg IP)

compound has a powerful gut-stimulating effect and may have therapeutic

potential for the management of paralytic ileus or other gut dysfunctions

requiring stimulation of motor activity (Bickel et al. 1985).

CONCLUSION

In recent years, substantial progress has been made toward the development of

opioid peptide analogs showing high selectivity for μ- or -opioid receptors.

Further efforts are required to obtain peptide ligands with high preference for

receptors. Another future goal of great importance is the development of opioid

peptide analogs showing selectivity for the putative μ-, and -receptor

subtypes. Early clinical trials with relatively nonselective enkephalin analogs led

192
to a certain disappointment because of several serious side effects that were

observed with these compounds. Peptide analogs with high specificity for

distinct opioid receptor types or subtypes can be expected to produce fewer

side effects and should be examined in future clinical trials. Peptides offer the

possibility of developing analogs that display great diversity in the relative

lipophilicity/hydrophilicity of their structures, such that they may or may not

cross certain barriers (blood-brain barrier, placental barrier, etc.). Therefore,

analogs can be designed that may act at either central or distinct peripheral

sites and that may have potential as selective therapeutic agents in various

clinical situations.

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Bickel, M.; Alpermann, H.-G.; Roche, M.; Schemann, M.; and Ehrlein, H.-J.

Pharmacology of a gut motility stimulating enkephalin analogue. Drug Res

35(II):1417-1426, 1985.

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ACKNOWLEDGMENTS

The author’s work described in this chapter was supported by operating grants

from the Medical Research Council of Canada (MT-5655), the Quebec Heart

Foundation, and the National Institute on Drug Abuse (DA-04443).

AUTHOR

Peter W. Schiller, Ph.D.

Director

Laboratory of Chemical Biology and Peptide Research

Clinical Research Institute of Montreal

110 Pine Avenue West

Montreal, Quebec H2W 1R7

CANADA

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Conformational Analysis of Opioid

Receptor-Selective Peptides Using

Nuclear Magnetic Resonance and

Theoretical Calculations

Victor J. Hruby, Om Prakash, Wieslaw Kazmierski, Catherine

Gehrig, and Terry O. Matsunaga

INTRODUCTION

It is now generally accepted that there are four different types of opioid receptor:

(Rapaka et al. 1986; Udenfriend and Meienhofer 1984); and there

is increasing evidence for subtypes of these receptors. Efforts to determine the

physiological roles of this multiple receptor system and the individual receptors

have been difficult owing to the lack of highly selective ligands (>1,000-fold) for

these receptors. Recently, our laboratory (Mosberg et al. 1982, 1983; Hruby

1986) developed a class of cyclic disulfide-containing enkephalin analogs that

possess exceptional -opioid receptor selectivities as measured in the classical

mouse vas deference (MVD)/guinea pig ileum (GPI) bioassays and in binding

studies using the plasma membranes from brain tissue and selective

radioligands (Akiyama et al. 1985; Vaughn et aI. 1989). The prototypical

peptide with high -receptor selectivity is [D-Pen2, D-Pen5]enkephalin (DPDPE,

H-Tyr-D-Pen-Gly-Phe-D-Pen-OH). In parallel studies using a different

approach, researchers have succeeded in converting somatostatin, a

tetradecapeptide with high potency in inhibition of release of glucagon, growth

hormone, and insulin among other activities, into a highly μ-opioid receptorselective ligand (Pelton et al. 1985a, 1986; Kazmierski et al. 1988). It has

virtually no somatostatin-like biological activities, as measured by bioassays

and binding studies similar to those used in the evaluation of -ligands.

This chapter discusses some of the considerations applied in the design of

these compounds and the evaluation of their conformational properties using

nuclear magnetic resonance (NMR) and other biophysical methods. Special

emphasis is given to the use of conformational constraints and topographical

considerations in the design of the peptide ligands the authors have developed.

198
GENERAL DESIGN PRINCIPLES

Most peptide hormones and neurotransmitters are flexible molecules with

multiple conformations accessible under physiological conditions. As such, it

perhaps is not surprising that these peptides can adopt multiple conformations

and interact with multiple receptors. A basic hypothesis of this approach, which

uses conformational (Hruby 1982; Hruby et al. 1990) and topographical (Hruby

et al. 1987, 1990; Kezmierski and Hruby 1988) constraints, is that different

receptor subtypes will utilize different structural, conformational, and

topographical features of the peptide ligand. Imposition of proper

conformational and topographical constraints should result in more highly

receptor-selective ligands. From this perspective, morphine—a highly

constrained ligand (figure 1) with only modest opioid-receptor selectivity—is not

a suitable ligand to model the bioactive conformations of opioid-receptor

ligands. Rather, one should design conformationally and topographically

constrained opioid analogs and then utilize the most selective ones for

exploring the differential conformational and topographical requirements of the

opioid receptors. In this regard, this research group has been involved primarily

in the design of opioid peptides, and some of these efforts are discussed here.

Methionine enkephalin (figure 1)—a natural endogenous opioid-receptor ligand

possessing modest -opioid receptor selectivity (Hruby and Gehrig 1989)—is a

particularly suitable starting point. The use of somatostatin-14 (H-Ala-Gly-CysLys-Asn-Phe-Phe-Trp-Lys-Thr-Phe-Thr-Ser-Cys-OH) as the starting point for a

μ-opioid receptor-selective ligand design begins from a different premise

(discussed later in this chapter).

The initial design principles for DPDPE were twofold: (1) pseudoisosteric

cyclization (Sawyer et al. 1982) in which the Gly2 and Met5 residues and sidechain moieties are replaced by residues D-Cys2

 and D- or L-Cys5 to give a

cyclic 14-membered macrocyclic ring structure and (2) geminai dimethyl

substitution on the ß-carbons of the Cys residues (penicillamine=ß,ßdimethylcysteine). The use of penicillamine in cyclic peptides previously had

been shown to have both local conformational and more global topographical

effects in peptide disulfide rings (Meraldi et al. 1977). Both of these

modifications are necessary for high -opfoid receptor selectivity. For example,

the authors have found that [D-Cys2, D-Cys5]enkephalin, though 10 to 20 times

more potent than DPDPE in the MVD and rat brain binding assays, has only

modest -receptor selectivity as measured by the MVD compared with the GPI

bioassays and by rat brain binding studies (unpublished). These studies

suggest that conformational and stereostructural properties were of critical

importance for the high -opioid receptor selectivity of DPDPE.

199
FIGURE 1. Structure of [Met5

]-enkephalin (top) and of morphine (bottom)

The redesign of somatostatin-related peptides to be opioid peptides with little or

no somatostatin-like activities had different origins. In this case, both biological

and conformational considerations were critical. On the biological side, it was

observed that somatostatin, albeit at high concentration, had analgesic

activities (Terenius 1976; Rezek et al. 1981). Subsequent studies with a series

of cyclic octapeptide analogs of somatostatin, especially H-D-Phe-Cys-Phe-DTrp-Lys-Thr-Cys-Thr(ol), which was found to be superpotent in the release of

growth hormone and to have antagonist activities on enkephalin-mediated

electrophysiological actions (Maurer et al. 1982) gave further evidence of the

interaction of somatostatin analogs with opioid receptors. This led to

examination of the possibility that appropriately modified analogs of the cyclic

octapeptide might lose most of their somatostatin-like activities but, at the same

200
time, have highly selective and potent opioid-receptor bioactivity. Structureactivity studies (Pelton et al. 1985a, 1985b, 1986) led to the development of the

peptide D-Phe-Cys-Tyr-D-Trp-Lys-Thr-Pen-Thr-NH2(CTP), which was found to

have selective and potent binding at the μ-opioid receptor and to only weakly

interact with the somatostatin receptor.

CONFORMATION: TOPOGRAPHlCAL/BlOLOGlCAL ACTIVITY

RELATIONSHIPS OF DPDPE AT THE -OPIOID RECEPTOR

The highly -opioid receptor selectivity of DPDPE has led to its extensive use by

many laboratories to explore the biological properties of this receptor. A

summary of some of the biological properties of DPDPE is given in table 1.

These properties suggest that highly -opioid receptor-selective ligands, such

as DPDPE, have exceptional potential for the treatment of a variety of diseases

related to opioid receptors. In addition, these ligands may provide a central

analgesic that does not have many of the severe side effects of drugs such as

morphine and heroin, which have many of their biological effects through

interaction with μ-opioid receptors. These findings have led the authors and

other researchers to continue developing approaches to obtain more potent and

selective -opioid peptides.

TABLE 1. Some biological properties of DPDPE

1. vs. μ-receptor—100- to 5,000-fold selective for -receptor, depending on

system

2. vs. -receptor—>50,000-fold selective for -receptor

3. Potent and prolonged analgesic action

4. Does not inhibit gut transit

5. Greatly reduced addiction potential relative to μ-opioids

6. Potent antidiarrheal effects

7. Positive interaction with μ-ligands

As part of our efforts to develop a more rational approach to the design of

biologically active peptide ligands (Hruby 1981a, 1981b, 1982, 1984, 1985,

1990; Hruby and Hadley 1986; Hruby et al. 1990), we have been developing a

201
topographical approach to peptide design. This approach requires a careful

analysis of the conformational properties of DPDPE and its analogs to

determine what structural changes can maintain the same backbone template

conformation. Careful use of two-dimensional (2D) NMR spectroscopy is an

important aspect of such an approach. The authors have prepared more than

50 analogs of DPDPE, some of which are more potent and -opioid receptor

selective than DPDPE (Toth et al. 1990).

Previously, Hruby and colleagues (1988) reported a comprehensive study on

the NMR of DPDPE in aqueous solution. The authors have repeated many of

these studies in dimethyl sulfoxide (DMSO)-d6 (e.g., see figure 2, the COSY

spectrum of [pCI-Phe4

]DPDPE). The chemical shifts and coupling constants for

DPDPE in DMSO-d6 are given in table 2, and the results are compared with

those previously reported for DPDPE in aqueous solution. Although there are

chemical shift differences as a result of the solvent change, the chemical shift

parameters remain basically the same. The changes in CaH-CßH coupling

constants for the Tyr1 and Phe4 residues indicate that, in DMSO, these residues

are even more strongly biased to the trans and/or gauche(-) side-chain

rotamers. These studies, coupled with molecular mechanics calculations

similar to those previously reported (Hruby et al. 1988), indicate that, overall,

DPDPE analogs modified in the Phe4 aromatic ring and in the ß-carbon of Phe4

maintain the same overall conformation. Particularly interesting is [ß,ßdimethyl-Phe4

]DPDPE, because molecular dynamics calculations indicate that

the Phe4 side-chain conformation is “frozen” in the trans conformation, as

shown in figure 3 (Kao and Hruby, unpublished results). Since this compound

is about 500 times less potent than DPDPE, but appears to retain -receptor

selectivity and agonist activity, it might be suggested that the topography

associated with the Phe4 aromatic side-chain group in the x1 trans conformation

is not highly compatible with -opioid receptor recognition (binding) but is

consistent with transduction. Previous studies (Hruby et al. 1985) have shown

that the Tic4 analog of DPDPE (in which the aromatic side-chain group is

exclusively in the gauche(+) conformation) is even less potent at the -receptor

than is the ß,ß-dimethylPhe4

 analog, but it also is an agonist. It might be

suggested, therefore, that -opioid receptor recognition prefers the gauche(-)

side-chain conformation for receptor recognition, but that any one of the sidechain conformations of that residue may be compatible with transduction of

activity at the -opioid receptor. Further studies under way are examining these

topographical aspects of structure-activity relationships, as are similar studies

examining the topographical requirements of the Tyr1

 side-chain group for

interaction with the -opioid receptor.

202
FIGURE 2. 1H-1H COSY spectrum at 500 MHz of [pCI-Phe4

]DPDPE in

DMSO-d6 solution

Based on studies to date, the following tentative conclusions regarding the

structural and topographical requirements of the -opioid receptor can be made:

1. DPDPE can serve as a relatively conformationally stable template for

examining the stereostructural and topographical requirements for vs. μ-

(and opioid receptors.

2. The overall conformation of the cyclic 14-membered ring of DPDPE can be

retained within a closely related conformational family with substitution at

the ß-carbon and further removed carbons in residues of DPDPE (table 3)

and, possibly at the -carbons of the D-Pen5 and Phe4 residues as well.

203
TABLE 2. Proton chemical shifts (ppm) and coupling constants (Hz) for

DPDPE in DMSO-d6

Residue

Tyr14.28 (m)

Pen24.54 (d; 9.1

Hz)

—

Gly34.38 (dd; —

14.3, 9.5 Hz)

3.21 (dd; 14.3,

3.1 Hz)

—

Phe44.30 (ddd; 8.0,

3.8, 11.1 Hz)

Pen54.33 (d; 8.5 Hz)

2.95 (dd; 13.5, —

6.4 Hz)

2.76 (dd; 13.5,

8.1 Hz)

8.64 (d;

9.1 Hz)

8.58 (dd;

9.5, 3.1 Hz)

3.08 (dd; 14.3, 8.85 (d; 8.0 Hz)

3.8 Hz) 2.79 (dd; 14.3,

11.1 Hz)

— 7.24 (d; 8.5 Hz)

7.10 (d; 8.4

Hz)

6.9 (d;

8.4 Hz)

1.35 (s)

0.98 (s)

7.26 (m)

—

FIGURE 3. Superimposed molecular dynamics structures of DPDPE (left)

and [ß-ß-dimethylphenylalanine4

]DPDPE (right) at 1000° C

showing the relatively rigid conformation of the ßß-Me2

-Phe

residue in a trans rotamer conformation

204
3.

4.

5.

6.

For maximal agonist activity and selectivity, topographical relationships of

the aromatic residues are preferred in which the aromatic rings are on the

same surface.

The paraposition in the aromatic ring of Phe4 has specific stereoelectronic

requirements at the -opioid receptor but not at the μ-opioid receptor (Toth

et al. 1990).

The selectivity of DPDPE for the -opioid receptor lies primarily in the

topographical relationships of residues 1, 2, and 4.

Topographical changes without any large changes in backbone

conformation can dramatically affect receptor potency and especially

specificity. The approach of topographical constraints is likely to provide a

general approach to the design of peptide ligands for a variety of receptor

and acceptor molecules, including enzymes, surface receptors, nucleic

acids, and other biologically important macromolecules.

TABLE 3. Proton chemical shifts (ppm) of Ca-H and of the peptide backbone

in DPDPE analogs

Peptide

D-Pen2

(ppm)

Ca-H NH

Gly3 Phe4 D-Pen5

(ppm) (ppm)

Ca-H Ca-H1 NH Ca

-H NH Ca-H NH

(ppm)

1. DPDPE

2. p-F-Phe4-DP

3. p-Cl-Phe4-DP

4. p-Br-Phe4-DP

5. p-l-Phe4-DP

6. p-NO2-Phe4-DP

7. p-NH2-Phe4-DP

8. [(S,S)ß-MePhe4]-

DPDPE

4.54 8.64 4.38 3.21 8.58 4.30 8.85 4.33 7.24

4.54 8.63 4.38 3.21 8.58 4.27 8.86 4.31 7.22

4.51 8.54 4.38 3.21 8.54 4.28 8.87 4.29 7.22

4.52 8.55 4.38 3.22 8.55 4.28 8.85 4.29 7.21

4.53 8.63 4.34 3.24 8.61 4.28 8.86 4.29 7.23

4.55 8.63 4.38 3.21 8.60 4.40 8.93 4.31 7.30

4.54 8.64 4.39 3.21 8.58 4.32 8.76 4.29 7.20

4.47 8.40 4.15 3.10 8.42 4.20 8.30 4.18 7.38

CONFORMATION: BIOLOGICAL ACTIVITY RELATIONSHIPS OF HIGHLY

μ-OPIOID RECEPTOR-SELECTIVE PEPTIDE ANTAGONISTS

Somatostatin is a tetradecapeptide with the structure H-Ala1-Gly-Cys-Lys-Asn5-

Phe-Phe-Trp-Lys-Thr10-Phe-Thr-Ser-Cys14-OH. Its primary physical role

appears to be in controlling the release of several key hormones, enzymes, and

neurotransmitters—especially growth hormone, insulin, and glucagon; as such,

205
it is widely distributed throughout peripheral tissues and the central nervous

system (CNS). These biological activities have been shown to be related to

specific structural and conformational properties of the hormone (Veber and

Saperstein 1979; Hruby et al. 1984). In particular, via a series of

conformational, structural, and structure-activity studies, it has been found that

the sequence -Phe-Trp-Lys-Thr- (residues 7-10) in somatostatin, when

stabilized In a ß-turn conformation, provides the key structural and

conformational properties of the hormone at the receptors related to

somatostatin inhibition of growth hormone, glucagon, and insulin release

(Freidinger and Veber 1984).

On the other hand, though much higher concentrations were required than were

needed to inhibit growth hormone release, it was demonstrated early that

somatostatin could interact with the opioid receptor system and, among other

effects, stimulate analgesia (Terenius 1976; Rezek et al. 1981). These effects

were largely ignored, presumably because they were thought to be of no

interest because of the high concentrations required for analgesia. However, in

conjunction with appropriate conformational constraints (Hruby 1982, 1984,

1985) and structural considerations, it might be possible to modify the

somatostatin structure in such a way as to select for its opioid-like properties

while diminishing or even eliminating its classical “somatostatin” effects.

Particularly intriguing was the prospect of utilizing the ß-turn structure of

somatostatin -Phe-Trp-Lys-Thr- as a “template” on which to design an opioid

ligand with high opioid-receptor selectivity. It was anticipated that such studies

might be successful for several reasons. First, because somatostatin was

only weakly active as an opioid-receptor ligand but had very potent activity as a

somatostatin receptor ligand, it seemed reasonable to conclude that the

structure-activity relationships at the two different receptor types would be

different. Second, analysis of structure-function studies for many peptide

hormones and neurotransmitters that have both peripheral and central

receptors indicates that, in general, receptors found in the CNS compared with

those in the periphery have uniquely different structure-activity relationships,

Third, it was observed by Maurer and coworkers (1982) that the cyclic analog

D-Phe-Cys-Phe-D-Trp-Lys-Thr-Cis-Thr(ol), a highly potent somatostatin analog

at inhibiting growth hormone release, also interacted with brain receptors

related to the opioid receptors. These later findings also indicated that

truncated somatostatin octapeptide analogs, utilizing the modified somatostatin

5-12 sequence, would be sufficient to explore the design of potent and selective

opioid peptides.

The examination began with the synthesis of several of C-terminal carboxylate

analogs of somatostatin 5-12 of the type H-D-Phe1-Cys-Phe-D-Trp4-Lys-ThrCys-Thr8

-OH in which the Cys2 and 7 residues were replaced with L-Pen (Pelton

206
et al. 1985b). It was found that the Pen substitution significantly reduced

somatostatin-like binding; if, in addition, L-Pen was substituted for the Cys7

residue, it increased potency at opioid receptor sites. Interestingly, this

modification resulted in a significant increase in μ- vs. -opioid receptor

selectivity. Subsequently, it was found that substitution of Phe3

 by Tyr, and

especially modification of the carboxylate terminal to a carboxamide group,

resulted in a profound increase in μ-receptor selectivity with a concomitant

decrease in -receptor binding. In addition, the somatostatin receptor affinity

diminished dramatically (Pelton et al. 1985b). The most favored ligand was DPhe1

-Cys-Tyr-D-Trp-Lys5-The-Pen-Thr6-NH2 (referred to as CTP for the

substitution Cys2, Tyr3, and Pen7) in the basic somatostatin structure. (It was

found that a D-Pen7 substituted analog has weak interaction with the opioid

receptor.) Furthermore, it was shown that CTP was highly selective for the μvs. opioid receptor (Pelton et al. 1985b).

CONFORMATION: TOPOGRAPHICAL/BIOLOGICAL ACTIVITY

RELATIONSHIPS OF CTP AT THE μ-OPIOID RECEPTOR

The highly μ-opioid receptor selectivities that were observed in the binding

studies of CTP raised several questions related to its biological and biophysical

properties and their relationships to one another. On the biological side, an

immediate question was whether CTP was an agonist or antagonist as an

opioid receptor ligand. This was examined using classical oploid assays in

collaborative biological studies at the University of Arizona (Thomas F. Burks,

Henry I. Yamamura, and their coworkers). It was determined that in the in vitro

GPI assay, the classical preceptor assay, CTP was a potent and selective μreceptor antagonist; similar results were found for its other μ-opioid receptor

activities (Shook et al. 1987a, 1986; Gulya et al. 1986). In vivo, CTP also was

found to be a potent and selective inhibitor of a variety of actions mediated by

μ-opioid receptor ligands such as morphine; by the highly μ-opioid receptorselective agonists [D-Ala2

, N-MePhe4, Gly(ol)s]enkephalin (DAGO); and by [NMePhe3

, D-Pro4]morphiceptin (PLO17). For example, it was shown that CTP

could block against morphine-induced analgesia and μ-opioid-mediated

inhibition of transit and could precipitate withdrawal in morphine-dependent

mice (Shook et al. 1987a, 1987b, 1987c, 1987d; Porreca et al. 1987; Wire et al.

1987; Ayers et al. 1988). Interestingly, it was found that, whereas CTP was a

highly potent μ-opioid receptor antagonist, it was a weak agonist at the -opioid

receptor. In addition, the in vitro and, especially, the in vivo studies uncovered

bioactivities of CTP that were not opioid-like and, thus, were assumed to be due

to some residual somatostatin-like activities. It was found later that appropriate

modification of the structural features of CTP can eliminate this putative

somatostatin-like activity. In particular, substitution of the Lys5 by Arg5 (but not

Orn5) gave the analog H-D-Phe-Cys-Tyr-D-Trp-Arg-Thr-Pen-Thr-NH2 (CTAP)

207
(Pelton et al. 1986), which was found to have essentially none of the

undesirable side actions of CTP (Kramer et al. 1989). Furthermore, CTAP was

found to be more selective than CTP, not only compared with other opioid

receptors but also, and especially, compared with the somatostatin receptor.

Thus, we recommend CTAP or the D-TiC analog (see below) as the ligand of

choice for a prolonged acting, potent, highly μ-oploid receptor-selective

antagonist.

From the beginning of these studies we have tried to determine whether it is a

valid, initial goat to utilize the ß-turn in somatostatin as a reasonably stable

conformational template on which to build an opioid-receptor Iigand. This

problem has been addressed by extensive 2D NMR spectroscopy studies in

conjunction with molecular mechanics and molecular dynamics calculations.

Extensive NMR investigations of CTP and related analogs in which the L-Pen7

is replaced by D-Pen7 or L-Cys7 were made in aqueous and DMSO solutions.

These studies (Pelton et al. 1988; Sugg et al. 1988; Kazmierski and Hruby

1988) led to several tentative conclusions.

1.

2.

3.

The presence of a ß-turn for the sequence -Tyr-D-Trp-Lys-Thr- in the

various μ-opioid receptor-selective ligands examined, although in some

cases a -turn also would be compatible with the NMR data obtained.

Strong support for this was seen especially in the nuclear Overhauser

effect (NOE) pattern for most of these compounds; for example, the

NOESY (NOE spectroscopy) spectrum of [D-Pgl1

]CTP (figure 4), is that

expected of a molecule with a reverse-turn structure for the residues -TyrD-Trp-Lys-Thr- (this reverse-turn conformation also is retained when the

Lys residue is replaced by Arg, Orn, and related amino acid residues).

The disulfide bridge appears to prefer a negative helicity as determined by

NMR (Sugg et al. 1988). When a right-handed helicity was observed as in

the D-Pen7

 analog, the compound was found to have low potency at

μ-opioid receptors (Kazmierski et al., unpublished results). These results

suggest that interaction of the terminal Thr8

-NH2 and D-Phe1 residues with

the μ-opioid receptor requires a specific topographical orientation of these

residues for strong interaction with the m-opioid receptor to occur.

The ß-turn conformation thus obtained obligated the placement of the 3-

aromatic side-chain groups (D-Phe1

, Tyr3, and D-Trp4) to the same

topographical face. The highly lipophilic surface thus obtained would

appear to suggest that this arrangement is critical for interaction of these

molecules with the μ-opioid receptor in the antagonist conformation of that

receptor. These observations and model building studies led to the

development of a new approach in the conformational design of peptide

208
FIGURE 4. The 1H-1H NOESY spectrum at 500 MHz of [D-Pgl4

]CTP in

DMSO-d6 solution

FIGURE 5. Low-energy side-chain conformations of phenylalanine-gauche(-),

trans, and gauche(+)

209
ligands. This approach sought to establish the specific topographical properties

of the side-chain groups within the context of the same conformational

(backbone) template and the ways in which the side-chain conformations might

specifically be constrained or biased to one specific side-chain topography

(figure 5). Thus, peptide analogs with specific topographical features could be

obtained.

DISCUSSION

The authors began this approach by carefully examining the topographical

requirements for the D-Phe1 residue in the CTP-related structures. An

important consideration in this approach is the necessity to retain the specific

backbone conformation of the original analogs so that any changes in biological

activity as the result of a particular substitution will be due to different

topographical structural features and not due to changes in the backbone

conformation of the peptide. In this approach, it is critical that the basic

assumption with regard to conformation be carefully checked. Thus, the

investigations began by examining the use of the phenylalanine analogs Dphenylglycine (D-Pgl), D-N-methylphenylalanine (D-N-MePhe), and Dtetrahydroisoquinoline carboxylate (D-Tic) (figure 6) as replacements for the DPhe1

 residue in CTAP or D-Phe-Cys-Tyr-D-Trp-Orn-Thr-Pen-Thr-NH2(CTOP).

It is expected that the N-methyl substitution on D-Phe will bias the side-chain

conformation of D-Phe to the trans x1 angle. On the other hand, D-Tic is so

constrained by the cyclization of the N-methyl to the 2’ carbon of the aromatic

ring in D-Phe that it now can exist only in a gauche(-) or a gauche(+)

conformation (figure 7). The D-phenylglycine residue, on the other hand,

primarily would be expected to place the aromatic residue as close to the 20-

membered disulfide-containing ring to maximize nonbonded van der Waals

stabilization.

Preparation of analogs containing these various amino acids led to interesting

and important results. In fact, the D-N-MePhe1 and D-Pgl1 analogs of CTP and

CTOP, respectively, we found to be about 250 times less potent than their

parent analogs at the μ-opioid receptor (Kazmierski and Hruby 1988;

Kazmierski et al. 1988). Extensive 2D NMR investigations (Kazmierski et al.

1989, 1991) firmly establish that these analogs have the same overall backbone

conformation; the only differences are their topographic structures. In both the

D-N-MePhe1 and the D-Pgl1 analogs, the aromatic ring at position 1 is on the

same surface and directed toward the Tyr3

 aromatic ring, whereas in the D-Tic1

analog, the observed side-chain conformation [gauche(-)] placed the aromatic

ring on the same face as the Tyr3

 aromatic ring, but a maximum distance apart

(figure 8). These results further support the idea that a maximal separation of

the D-Phe1 and Tyr3 side-chain groups favors interactions of these analogs with

210
the μ-opioid receptor in its antagonist conformation. These compounds are the

most selective opioid-receptor ligands known and should be of great use in

examining the physiological and pharmacological roles of μ-opioid receptors.

Furthermore, these results establish the importance of the topographical

properties of a peptide ligand for its interactions with its receptor(s). It is

believed that the use of topographical considerations in conjunction with

topographical constraints provides a new and highly important approach to the

design of peptide hormone and neurotransmitter ligands. Several other amino

acid derivatives and analogs are being examined that may be utilized for

topographical design and constraint and for devising asymmetric syntheses to

obtain these compounds. It is anticipated that important new ligands for a

variety of hormone and neurotransmitter receptors will emerge from these

studies.

FIGURE 6. Structures of D-phenylalanine analogs D-Tic, N-Me-D-Phe, D-Pgl,

and D-2-MePhe

211
FIGURE 7. Conformations possible for D-tetrahydroisoquinoline carboxylate

(D-Tic)

FIGURE 8. Conformation (stereoview) of [D-Tic1

]CTP (D-Tic-Cys-Tyr-D-TrpLys-Thr-Pen-Thr-NH2

)

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ACKNOWLEDGMENTS

This research was supported by grant NS-19972 from the U.S. Public Health

Service, grant DA-06284 from the National Institute on Drug Abuse, and a grant

from the National Science Foundation. Our biological collaborators, Drs.

Thomas F. Burks and Henry I. Yamamura and their coworkers, performed most

of the assay studies discussed herein.

AUTHORS

Victor J. Hruby, Ph.D.

Regents Professor

Om Prakash, Ph.D.

Research Associate

Wieslaw Kazmierski, Ph.D.

Research Scientist

Catherine Gehrig, Ph.D.

Research Assistant

Terry O. Matsunaga, Ph.D.

Research Associate

Department of Chemistry

University of Arizona

Tucson, AZ 85721

217
Peptidomimetic Opioids—Synthesis,

Spectroscopy, and Computer

Simulations

Murray Goodman, Odlle E. Said-Nejad, Eduard Felder, Dale F.

Mierke, Toshimasa Yamaraki, and Peter W. Schiller

INTRODUCTION

Over the past several years, the authors have synthesized many retro-inverso

modified enkephalin analogs structurally related to Tyr-c(D-A2bu-Gly-Phe-Leu],

originally designed and synthesized by Schiller and associates (DiMaio et al.

1982). Results from the in vitro activities emphasize that the peptide bonds

between residues Phe4

-Leu5 and Leu5-X2 (side-chain) can be reversed with

maintenance of high activity (Berman and Goodman 1984). The retro-inverso

modifications at all the other positions greatly reduced the activities of the

analogs in the guinea pig ileum (GPI) and the mouse vas deferens (MVD)

assays.

The conformational analysis of four of the stereoisomeric enkephalin analogs,

Tyr-c[D-A2bu-Gly-Phe-(L and D)-Leu] and Tyr-c[D-A2bu-Gly-gPhe-(S and R)-

mLeu], was carried out by using nuclear magnetic resonance (NMR) and

computational techniques employing flexible geometry energy minimization and

molecular dynamic simulations (Mierke et al. 1987). The results obtained

demonstrated that the orientation of the aromatic residues Tyr1

 and Phe4 and

the conformational flexibility of the 14-membered backbone ring are important

factors that govern the selective activity of opioid peptides. It was found that,

for a specific ligand to be recognized at the μ-opiate receptor, the molecule

must adopt a conformation in which a large distance between the aromatic rings

at positions 1 and 4 is maintained. The constrained 14-membered backbone

rings in Tyr-c[D-A2bu-Gly-Phe-Leu] and Tyr-c[D-A2bu-Gly-gPhe-S-mLeu]

stabilized by intramolecular hydrogen bonds help maintain this desired

conformation. For activity at the μ- and -opiate receptors, as observed in Tyrc[D-A2bu-Gly-Phe-D-Leu] and Tyr-c[D-A2bu-Gly-gPhe-R-mLeu], the molecules

undergo greater conformational flexibility. This flexibility allows the peptide to

adapt to various opioid receptor surfaces (Goodman and Mierke 1987).

218
Other examples in the literature are in agreement with the authors’ findings.

The constrained 13-membered ring analog Tyr-c[D-Orn-Phe-Asp]-NH2,

synthesized by Schiller, turned out to be highly active and μ-receptor selective

(Schiller et al. 1985; Schiller and Nguyen 1984). The high selectivity of this

compound toward the μ-receptor was the result of its complete inactivity at the

-opioid receptor. Conformational studies of this analog have been carried out

in our laboratories (Mierke 1988). The NMR analysis revealed two

intramolecular hydrogen bonds between D-Orn NH (side-chain)-D-Orn CO and

Asp NH-D-Orn CO. The hydrogen bonds also were present for a large fraction

of the molecular dynamic simulations. No significant backbone mobilities in this

analog were detected from the dynamics.

The effect of varying the length of the side-chain at position 2 on opiate activity

and selectivity also has been examined by altering the size of the backbone ring

from 13 to 15 members by the substitution of different combinations of Asp, Glu,

A2bu, Orn, and Lys at positions 2 and 4. Complete loss of selectivity was

observed in the less constrained 15-membered ring dermorphin analog Tyr-c[DLys-Phe-Glu]-NH2

 (Goodman and Mierke 1987; Schiller and Nguyen 1984). In

the series of cyclic enkephaiins Tyr-c[D-Xxx-Gly-Phe-Leu], the selectivity for the

μ-opioid receptor increased with the length of the side-chain of the second

residue. The D-Lys containing analog was the most selective, followed by the

D-Orn and D-A2bu analogs (DiMaio et al. 1982). Increasing the size of the ring

further to 18-membered, as shown in the synthesis of Tyr-c[D-Lys-Gly-PheGlu]-NH2

, yielded a highly potent but nonselective analog (Schiller et al. 1986).

These findings indicated that the degree of flexibility of the backbone ring can

have a major effect on the selective activity of the various analogs.

To characterize the effect of the phenylalanine residue at position 3 of

dermorphins and at position 4 of enkephalins on biological activity, a series of

14-membered cyclic opiate analogs were synthesized that contain

phenylalanine at positions 3 and 4 (figure 1). Four of these analogs, Tyr-c[DA2bu-Phe-gPhe-(S and R)-mLeu] and Tyr-c[D-Glu-Phe-gPhe-(L and D)-rLeu],

incorporate retro-inverso modifications between residues 4 and 5 and residues

5 and 2 (side-chain). Few substitutions in the third position of the linear

enkephalin have been reported to date. Replacement of Gly with an Ala or Pro

resulted in weakly active compounds (Morley 1980). Tetrapeptides containing

phenylalanine residues in the 3 and 4 positions, however, have been reported.

Among these, H-Tyr-D-Ala-Phe-Phe-NH2 showed high preference for the μreceptor over the -receptor (Schiller 1988). Compared to Leu-enkephalin, this

compound was 75 times more potent in the GPI assay and 70 times less potent

in the MVD assay.

219
FIGURE 1. Structure of a series of cyclic molecules related to dermorphin

220
This chapter reports the synthesis, biological activities, and preliminary

conformational analysis of the six cyclic dermorphin analogs completed to date.

SYNTHESIS

Solid-Phase Synthesis of Tyr-c[D-A2bu-Phe-Phe-(L and D)-Leu]

The synthesis of the two cyclic parent dermorphin analogs was achieved by a

combination of the solid-phase technique and peptide synthesis in solution.

The partially protected linear peptides Z-Tyr(Bzl)-D-A2bu-Phe-Phe-(L and D)-

Leu-OH were assembled separately from the C-terminus on the palkyloxybenzyl alcohol resin, commonly known as the Wang resin (Wang and

Merrifield 1969). The cleavage of the peptides from the resin was followed by

cyclization in solution (figure 2).

All couplings were accomplished by preformed N-hydroxybenzotriazole (HOBt)

active esters, obtained by allowing the appropriate protected amino acids to

react with dicyclohexylcarbodiimide (DCC) and HOBt in CH2Cl2 for 30 minutes.

After the removal of the insoluble N,N’-dicyclohexylurea (DCU), the filtrate

containing the activated form of the urethane protected amino acid derivative

was added directly to the reaction vessel. Except for the Tyr residue, the 9-

fluorenylmethyloxycarbonyl (Fmoc) group was used for the N

a

-protection of all

amino acids. Each coupling step gave quantitative yields as measured by

spectrophotometric Fmoc-amino acyl resin analysis (Kaiser et al. 1970; Stewart

and Young 1984).

To prevent branching in the growing peptide chain the amino group of the

D-diaminobutyric acid (D-A2bu) side-chain also was protected with the acid

labile tert-butyloxycarbonyl (Boc) group. This protecting group was expected to

remain in place during the chain elongation process and to resist the reagent

used for the deprotection of -amino Fmoc groups.

The cleavage of the peptide from the resin and the removal of the side-chain

Boc protecting group of the D-A2bu residue was achieved in one step using a

mixture of trifluoroacetic acid (TFA) in CH2Cl2

 solution in the presence of anisole

and thioanisole scavengers for tert-butyl carbocation, which could lead to

undesired alkylation of the tyrosine ring.

After recrystallization, the partially protected linear pentapeptides were cyclized

using diphenylphosphoryi azide (DPPA) in dimethylformamide (DMF) to

generate the fully protected products N

a

-(Z)-Tyr(Bzl)-c[D-A2bu-Phe-Phe-(L and

D)-Leu] (Brady et al. 1983). At this stage, the peptides were purified on a mixed

bed ion exchange resin to remove any unreacted starting materials or any

221
FIGURE 2. Solid synthesis of parent dermorphin analogs Tyr-c[D-A2bu-PhePhe-(L and D)-Leu]

undesired dimers formed during the cyclization step. The homogeneous white

powders obtained in both cases were subjected to catalytic hydrogenation in

the presence of Pd/C in methanol/acetic acid mixture to yield the crude final

products. Each peptide was subjected to reverse-phase (RP)/high-pressure

liquid chromatography (HPLC) purification in a mixture of acetonitrile/water/TFA

using isocratic conditions.

222
Synthesis of Tyr-c[D-A2bu-Phe-gPhe-(S and R)-mLeu]

A representative synthetic scheme for the preparation of the diastereomeric

pairs Tyr-c[D-A2bu-Phe-gPhe-(S and R)-mLeu] carried out in solution is shown

in figure 3. The synthesis of the Tyr-c[D-Glu-Phe-gPhe-(L and D)-rLeu] follows

a similar route and therefore is not included. The gem-diaminoalkyl residue

Boc-Phe-gPhe-H•TFA was obtained by the conversion of dipeptide

carboxamide Boc-Phe-Phe-NH2

 to the corresponding gem-diaminoalkyl

dipeptide salt using bis[(trifluoroacetoxy)iodo]benzene (IBTFA). This

rearrangement is known to proceed without racemization (Pallai et al. 1983;

Pallai and Goodman 1982).

FIGURE 3. Synthesis of retro-inverso analogs Tyr-c[D-A2bu-Phe-gPhe-(S and

R)-mLeu]

223
The commercially available 2-isobutylmalonic acid diethyl ester was converted

to R,S-isobutylmalonic acid monobenzyl ester in one step involving

saponification and transesterification. The R,S-isobutylmalonic acid was

incorporated into the peptide chain as a racemate, thereby generating a pair of

diastereomers.

Stepwise elongation of the peptide chain led to the fully protected pentapeptide

N

a

-Boc-Tyr(tBu)-Ny(Z)-D-A2bu-Phe-gPhe-R,S-mLeu-OBzl. Catalytic

hydrogenation of this compound simultaneously removed the -benzyl ester

and the N

y

-benzyloxycarbonyl (Z) protecting groups to yield the partially

protected zwitterionic pentapeptide Na-Boc-Tyr(tBu)-D-A2bu-Phe-gPhe-R,SmLeu-OH. Activation of the malonyl leucine carboxyl group was chosen for ring

closure, because the attacking amine, from the side-chain of D-A2bu was a

good nucleophile. In addition, no chirality concerns are involved with the amide

formation.

Cyclization was achieved using DPPA as described above. A second

technique using the BOP reagent also was employed (Castro et al. 1975; LeNguyen et al. 1981). In this case, the linear peptide Boc-Tyr(tBu)-D-A2bu-PhegPhe-(R and S)-mLeu-OH was dissolved in DMF in the presence of

diisopropylethylamine and was stirred for 1 day at room temperature. The

cyclic protected peptide obtained from each route, Boc-Tyr(tBu)-c[D-A2bu-PhegPhe-(R and S)-mLeu], was purified by treatment with a mixed bed ion

exchange resin to remove any starting materials or dimeric linear peptides

formed during the cyclization step.

The final diastereomeric mixture was obtained by acidolytic cleavage of the

protecting groups on the tyrosine in the presence of anisole and thioanisole,

scavengers used to trap the tert-butyl carbocation. It was possible to separate

the diastereomeric mixture by RP-HPLC, as shown in figure 4. The chirality at

the maionyl leucine center was assigned by carrying out two-dimensional (2D)

NMR techniques.

BIOLOGICAL ACTIVITY

All the in vitro biological activities were measured in Schiller’s laboratories. The

observed in vitro biological activities of the dermorphin analogs measured

against the GPI and the MVD assays are shown in table 1 along with biological

activities of selected enkephaiin analogs for comparison.

224
Column: VYDAC C18 10μ (1.0x25 cm)

Eluent: 68 percent A (95 percent H2O, 5 percent CH3CN, 0.1 percent TFA)

32 percent B (95 percent CH3CN, 5 percent H2O, 0.1 percent TFA)

Flow rate: 4 mL/min

FIGURE 4. RP-HPLC profile of the final diastereomeric mixture of Tyr-c[DA2bu-Phe-gPhe-(S and R)-mLeu]

As can be seen in table 1, all the dermorphin analogs were effective at inhibiting

the electrically induced contractions in the GPI and MVD assays. All the

modified analogs are more potent (relative to Leu5

-enkephalin) in the GPI

assay. With the exception of the two analogs Tyr-c[D-A2bu-Phe-gPhe-R-mLeu]

and Tyr-c[D-Glu-Phe-gPhe-D-rLeu], which display reduced activity at the

-opioid receptor, the remaining analogs display equal or higher potencies in

the MVD bioassay than does Leu5-enkephalin. The greatly reduced activity of

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] provides important information about the

requirement for selective opiate receptor interactions and is discussed below in

conjunction with the results obtained from computer simulations.

All the dermorphin analogs display higher potencies in the GPI and the MVD

bioassays than do the enkephalin analogs incorporating a Gly residue at

position 3, although the activity profiles of the two analogs Tyr-c[D-A2bu-GlygPhe-S-mLeu] and Tyr-c[D-A2bu-Phe-gPhe-S-mLeu] are similar. The reason

for the increased potencies of the dermorphin analogs containing a Phe at

position 3 is not well understood. It can be speculated that the hydrophobic

225
TABLE 1. GPI and MVD assays of dermorphin analog in comparison with

analogous enkephalin analogsa

Compound GPI

IC50[nM]

MVD

IC50[nM]

MVD/GPI

IC50-ratio

Tyr-c[D-A2bu-Phe-Phe-Leu]

Tyr-c[D-A2bu-Phe-Phe-D-Leu]

Tyr-c[D-A2bu-Phe-gPhe-S-mLeu]

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu]

Tyr-c[D-Glu-Phe-gPhe-rLeu]

Tyr-c[D-Glu-Phe-gPhe-rDLeu]

Tyr-c[D-A2bu-Gly-Phe-Leu] 14.1 ± 2.9

Tyr-c[D-A2bu-Gly-Phe-D-Leu] 66.1 ± 8.4

Tyr-c[D-A2bu-Gly-gPhe-S-mLeu] 1.51 ± 0.19

Tyr-c[D-A2bu-Gly-gPhe-R-mLeu] 25.5 ± 2.0

Tyr-c[D-Glu-Gly-gPhe-rDLeu] 19.4 ± 3.4

[Leu5]-Enk 246 ± 39

1.08 ± 0.10

1.14 ± 0.12

0.518 ± 0.099

17.6 ± 2.8

39.0 ± 9.3

2.75 ± 0.63

4.70 ± 0.92

13.9 ± 0.9

6.30 ± 1.11

117 ± 31

3.64 ± 0.10

49.1 ± 9.9

81.4 ± 5.8 5.77

27.1 ± 1.6 0.409

7.76 ± 3.17 5.14

14.9 ± 5.0 0.584

313 ± 102 16.1

11.4 ± 1.1

4.35

12.2

12.2

10.1

0.09

17.9

0.0463

aMean of three determinations±SEM.

side-chain of the Phe3 interacts favorably with a hydrophobic site at the opiate

receptor surfaces. The preferred interaction of the opiate receptor with the

hydrophobic side-chain of the Phe at position 3 may result in higher ligandreceptor recognition and, consequently, lead to the increased potencies

observed.

All the modified dermorphin analogs were found to be highly resistant to

proteolytic degradation by rat brain membrane preparations measured in our

laboratories (table 2), which rapidly hydrolyzes Leu5-enkephalin (t1⁄2 7 minutes).

With the exception of Tyr-c[D-A2bu-Phe-Phe-(L and D)-Leu], all the modified

analogs show no appreciable degradation and prove more enzyme resistant

than the enzyme-stable [D-Ala2

-Leu5]-enkephalinamide.

These results are in full agreement with the authors’ previous results obtained

with the retro-inverso modified analogs containing a Gly at position 3. It was

demonstrated that application of the partial retro-inverso modifications to

dermorphins gives rise to opioid peptides that exhibit higher potency and

selectivity than their corresponding enkephalin counterparts.

226
TABLE 2. Half-lives determined from degradation of peptides against rat

brain homogenate

Analog

Time1⁄2

(min)

Tyr-c[D-A2bu-Phe-Phe-Leu] 35

Tyr-c[D-A2bu-Phe-Phe-D-Leu] 53

Tyr-c[D-A2bu-Phe-gPhe-S-mLeu] 227

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] 265

Tyrc[D-Glu-Phe-gPhe-rLeu] 137

Tyr-c[D-Glu-Phe-gPhe-D-rLeu] 338

[Leu5]-Enk 7

[D-Ala2-Leu5]-Enkephalinamide 62

CONFORMATIONAL ANALYSIS

It is clearly important to understand the conformational consequences of the

phenylalanine substitution in partial retro-inverso modified analogs and,

ultimately, to relate these to the pharmacological profile of the analogs. The

conformational characterization of the molecules was carried out by 1H NMR

and nuclear Overhauser effect (NOE)-restrained molecular dynamics and

flexible geometry energy minimizations. The proton resonances were assigned

using 2D COSY and HOHAHA techniques. The NOES were measured in the

rotating frame (ROESY experiments) at various mixing times, from 75 to 500

ms. The computer simulations were carried out at the San Diego

Supercomputer Center using the DISCOVER program.

Nuclear Magnetic Resonance

The temperature coefficients obtained for all six cyclic analogs are shown in

table 3. The NOES obtained from the ROESY experiments are shown in figure

5 for compounds Tyr-c[D-A2bu-Phe-gPhe-(S and R)-mLeu]. These NOES were

useful in unambiguously assigning the chirality at the malonyl leucine center (as

described below).

Temperature coefficients obtained from one of the two diastereomeric pairs,

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu], show one intramolecular hydrogen bond

involving the D-A2bu side-chain NH. The acceptor of the hydrogen bond was

deduced from the NOES. The amide proton of the D-A2bu side-chain is directed

227
TABLE 3. Temperature coefficients in -ppb/K) of amide protons of

cyclic dermorphin analogs containing intramolecular hydrogen

bonds

Amide Protons [L-Leu5

] [D-Leu5] [S-mLeu5] [R-mLeu5] [L-rLeu5] [D-rLeu5]

D-A2bu

D-A2bu (side-chain)

D-Glu

Phe3

Phe4

gPhe4 (normal)*

gPhe4 (new)*

Leu

3.1 3.3 3.6 2.6 — —

1.5 3.5 3.3 -0.6 — —

— — — — -0.2 3.9

4.4 2.9 3.3 3.2 3.4 8.7

4.3 5.3 — — — —

— — 5.1 7.1 3.3 5.4

— — 2.8 7.1 4.1 1.9

-0.3 1.1 — — 4.1 3.4

* The amino precursors of the normal and the new amide protons are the

amino group present in Phe and the amino group generated from the Hofmann

rearrangement, respectively.

toward the ring, forming a 7-membered hydrogen bond with the D-A2bu CO and

accounting for a relatively small temperature coefficient of the D-A2bu NH (sidechain) amide proton. The chirality at the fifth position was assigned in the

following way: The analog Tyr-c[D-A2bu-Phe-gPhe-S-mLeu], which lacks

intramolecular hydrogen bonds, shows a weak NOE between Phe NH and Phe

C

aH and a weak NOE between Phe CaH and gPhe NH. For these NOES to be

fulfilled, the Phe NH and gPhe NH must be projecting downward with respect to

the plane of the ring. Medium NOES between gPhe NH, gPhe C

aH and a strong

NOE between gPhe C

aH-gPhe N*H require that the gPhe N*H and gPhe CaH

be pointing downward (figure 6). The strong NOE between gPhe N*H-mLeu

C

aH protons is possible if the residue at position 5 has an S configuration,

The hydrogen bond between the D-A2bu CO and the D-A2bu NH (side-chain) in

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] requires that the D-A2bu CO be directed in the

plane of the ring. The Phe NH, which should be trans to the D-A2bu CO, must

project out of the plane of the ring. A medium NOE between Phe NH-Phe C

aH,

a strong NOE between Phe C

aH-gPhe NH, and a strong NOE between gPhe

NH-gPhe C

aH are consistent with a geometry in which the Phe CaH, the gPhe

NH, and the gPhe CaH are pointing downward with respect to the plane of the

14-membered ring. A weak NOE between gPhe C

aH and gPhe N*H requires

that the N*H be projecting upward, as shown in figure 6. A strong NOE

between gPhe N*H and mLeu C

aH at this position requires an R configuration at

the mLeu C

aH center.

228
FIGURE 5. NOE data obtained for Tyr-c[D-A2bu-Phe-gPhe-(S and R)-mLeu]

229
FIGURE 6. Configurational assignment of the malonyl leucyl center in Tyrc[D-A2bu-Phe-gPhe-S-mLeu] (top) and Tyr-c[D-A2bu-Phe-gPheR-mLeu] (bottom)

Observation of Cis-Trans lsomerization In the Dermorphin Analogs

Multiple resonances were observed in the proton spectra of two of the six

compounds shown in figure 1. The Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] consists

of predominantly trans conformer and two minor cis conformers accounting for

21 and 13 percent, respectively. The analog Tyr-c[D-Glu-Phe-gPhe-D-retroLeu] is composed of only 28 percent of all trans structure, with two cis amide

containing isomers accounting for 51 and 21 percent, respectively. We have

been able to show with ROESY experiments that the additional resonances

arise from cis/trans isomerization about unsubstituted amide linkages. Using

one-dimensional saturation transfer techniques, the rate of isomerization was

measured at various temperatures (Forsen and Hoffman 1964; Grathwohl and

Wüthrich 1981; Sanders and Mersh 1982). The results are shown in table 4.

230
The rates of interconversion are similar to the values reported by Grathwohl and

Wüthrich (1981) for proline containing linear peptide sequences, which may be

indicative of similar energy barriers for cis/trans transitions.

TABLE 4. Rate constants and free energies of activation for the cis/trans

isomerization measured in DMSO at 30°C

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu]

Tyr-c[D-Glu-Phe-gPhe-D-rLeu]

Analog cis Rate (sec-1) DG (kJ mol-1)

Bond Fraction

Phe-gPhe 0.21 2.0±0.1 1.6±0.1 72 74

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu]

mLeu-D-A2bu 0.13 — — — —

Tyr-c[D-Glu-Phe-gPhe-D-rLeu]

D-Glu-Phe 0.51 1.6±0.2 1.4±0.2 74 72

Phe-gPhe 0.21 — — — —

The assignment of the resonances was carried out with HOHAHA and ROESY

experiments (Davis and Bax 1985; Bothner-By et al. 1984; Bax and Davis

1985). From the ROESY spectra, chemical exchange between the different

sets of resonances was observed (Mierke et al. 1989). The two cis isomers of

Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] contain cis amide bonds between Phe-gPhe

and mleu-D-A2bu side-chain, accounting for 21 and 13 percent of the

population, respectively. The major isomer of Tyr-c[D-Glu-Phe-gPhe-DretroLeu], accounting for 51 percent of the population, has a cis amide linkage

about the D-Glu-Phe amide bond. The other cis isomer, accounting for 21

percent, has a cis arrangement between Phe-gPhe.

The observation of cis and trans isomers within the series is unexpected. The

results from the NMR analysis of the series of enkephalin analogs with a glycine

at the third position, Tyr-c[D-A2bu-Gly-gPhe-(R and S)-mLeu and Tyr-c[D-GluGly-gPhe-rDLeu], containing analogous retro-inverso modifications have been

reported (Mammi and Goodman 1986). There was no evidence of multiple

resonances or configurational isomers. It therefore must be concluded that the

additional constraint from the replacement of phenylalanine is the source of the

observed configurational isomers.

231
Computer Simulations

The molecular dynamic simulations of five of the six dermorphin analogs have

been completed. These simulations were carried out for 20 picoseconds with

the measured NOES as restraints. A superposition of the structures obtained

from the molecular dynamic simulations for the molecules under consideration

provided qualitative information about the mobility of the side-chains and

backbone in each peptide. These structures are shown in figures 7, 8, and 9.

These results indicate that the mobilities of the side-chains of Tyr1,

Phe3, and Phe4 are similar in all compounds, with the Tyr side-chain exhibiting

the greatest degree of freedom. With the exception of Tyr-c[D-A2bu-Gly-gPheR-mLeu], which displays superactivity at the μ-receptor only, the remaining

molecules are superactive at the μ- and the -opioid receptors. All the

molecules that display activity at both opioid receptors contain flexible

backbones. The Tyr-c[D-A2bu-Gly-gPhe-R-mLeu] analog consisting of two cis

conformers and one trans conformer has a more constrained backbone and

displays activity at the μ-receptor only.

The conformational analysis of the dermorphin analogs presented here indicate

that the interaction between the side-chains of Tyr1

 and Leu5 or mLeu5 residues

may be important to elicit a proper biological response at the -opiate receptor.

A strong hydrophobic interaction between the side-chains of Tyr1 and Leu5 and

Tyr1

 and mLeu5 in Tyr-c[D-A2bu-Phe-Phe-Leu], Tyr-c[D-A2bu-Phe-Phe-D-Leu],

Tyr-c[D-A2bu-Phe-gPhe-S-mLeu], and Tyr-c[D-Glu-Phe-gPhe-rLeu] dominate

the structures obtained from molecular dynamic simulations and is believed to

be important for ligand-receptor interactions at the -opiate receptor. On the

other hand, the two analogs Tyr-c[D-A2bu-Phe-gPhe-R-mL/eu] and

Tyr-c[D-Glu-Phe-gPhe-D-rLeu] display superactivity at the μ-opioid receptor.

The conformational analysis of Tyr-c[D-A2bu-Phe-gPhe-R-mLeu] carried out to

date indicates that there is no interaction between the Tyr1

 and the mLeu5 sidechains.

Although all the 14-membered ring dermorphin analogs in this study are more

active than their 14-membered enkephalin counterparts, the exact role of the

Phe side-chain at position 3 is not well understood. Future research in the

authors’ laboratories is aimed at unraveling the mysterious role of the Phe at

position 3 on biological activity in the cyclic dermorphin series of analogs.

Toward this goal, cyclic enkephalin and dermorphin analogs are being

synthesized, incorporating different substitutions at the third position. Some of

these target molecules will incorporate a D-Phe at position 3 to study the

chirality effect at position 3 on biological activity. Others will incorporate

nonaromatic hydrophobic residues such as Ala and cyclohexylalanine at

position 3 to understand which of the two interactions—hydrophobic or

232
FIGURE 7. Superposition of structures obtained from the molecular dynamic

simulations of Tyr-c[D-A2bu-Phe-gPhe-(L and D)-Leu]

233
FIGURE 8. Superposition of structures obtained from the molecular dynamic

simulations of Tyr-c[D-A2bu-Phe-gPhe-(S and R)-mLeu]

234
FIGURE 9. Superposition of structures obtained from the molecular dynamic

simulations of Tyr-c[D-Glu-Phe-gPhe-L-Reu]

electronic—have a greater influence on potency. Novel analogs also will be

synthesized that will incorporate side-chain modifications at position 5 to alter

the nature of the hydrophobic interactions between Tyr1 and Leu5, believed to

be necessary for recognition and activity at the -opiate receptor.

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pharmacological characterization in vitro of cyclic enkephalin analogues:

Effect of conformational constraints on opiate receptor selectivity. J Med

Chem 25:1432-1438, 1982.

Forsen, S., and Hoffman, R.J. Exchange rates by nuclear magnetic multiple

resonance. III. Exchange reactions in systems with several nonequivalent

sites. J Chem Phys 40:1189-1196, 1964.

Goodman, M., and Mierke, D.F. Conformational comparison of four constrained

stereoisomeric cyclic enkephalin analogues by 1H-NMR and computer

simulations. In: Peeters, H., ed. Protides of the Biological Fluids:

Proceedings of Colloquium XXXV. Oxford: Pergamon Press, 1987. pp.

457-460.

Grathwohl, C., and Wüthrich, K. NMR studies of the rates of proline cis-trans

isomerization in oligopeptides. Biopolymers 20:2623-2633, 1981.

Kaiser, E.; Colescott, R.L.; Bossinger, C.D.; and Cook, P.I. Color test for

detection of free terminal amino groups in the solid-phase synthesis of

peptides. Anal Biochem 34:595-598, 1970.

Le-Nguyen, D.; Dormoy, J.R.; and Castro, B. Segment coupling in peptide

synthesis. II. A simple predictive equation correlating racemization and

primary structure. Tetrahedron 37:4229-4238, 1981.

Mammi, N.J., and Goodman, M. Conformational analysis of cyclic partially

modified retro-inverso enkephalin analogues by proton NMR. Biochemistry

25:7607-7614, 1986.

Mierke, D.F. “Nuclear Magnetic Resonance Studies and Computer Simulations

of Biologically Active Peptides.” Unpublished Ph.D. dissertation, University

of California, San Diego, San Diego, CA, 1988.

236
Mierke, D.F.; Lucietto, P.; Schiller, P.W.; and Goodman, M. Synthesis and

conformational analysis of a cyclic enkephalin analogue. A conformational

comparison of two diastereomers by 1H NMR and computer simulations.

Biopolymers 26:1573-1586, 1987.

Mierke, D.F.; Yamazaki, T.; Said-Nejad, O.E.; Felder, E.R.; and Goodman, M.

Cis/trans isomers in cyclic peptides without N-substituted amides. J Am

Chem Soc 111(17):6847-6848, 1989.

Morley, J. Structure-activity relationships of enkephalin-like peptides. Annu

Rev Pharmacol Toxicol 20:81-110, 1980.

Pallai, P., and Goodman, M. Preparation of optically pure monoacyl 2-alkyl

gem-diamines from peptide amides. Chem Commun 280-281, 1982.

Pallai, P.; Richman, S.; Struthers, R.S.; and Goodman, M. Approaches to the

synthesis of retro-inverso peptides. Int J Peptide Protein Res 21:84-92,

1983.

Sanders, J.K.M., and Mersh, J.D. Nuclear magnetic double resonance: the use

of difference spectroscopy. Prog Nucl Magn Reson Spectroscopy 15:353-

400, 1982.

Schiller, P.W. New strategies in the development of receptor-selective peptide

analogs. In: Dhawan, B.N., and Rapaka, R.S., eds. Recent Progress in

Chemistry and Biology of Centrally Acting Peptides. Lucknow, India: Central

Drug Research Institute, 1988. pp. 11-24.

Schiller, P.W.; Maziak, L.A.; Lemieux, C.; and Nguyen, T.M.-D. Side-chain to

side-chain cyclization of an enkephalin analog results in loss of opioid

receptor selectivity. Int J Pept Protein Res 28:493-497, 1986.

Schiller, P.W., and Nguyen, T.M.-D. Activity profiles of novel side-chain to sidechain cyclized opioid peptide analogs. Neuropeptides 5:165-168, 1984.

Schiller, P.W.; Nguyen, T-M.-D,; Maziak, L.; and Lemieux, C. A novel cyclic

opioid peptide analog showing high preference for μ-receptors. Biochem

Biophys Res Commun 127:558-564, 1985.

Stewart, J.M., and Young, J.D. Solid Phase Peptide Synthesis. 2d ed.

Rockford, IL: Pierce Chemical Company, 1984. p. 107.

Wang, S.-S., and Merrifield, R.B. Preparation of a t-alkyloxycarbonylhydrazide

resin and its application to solid-phase peptide synthesis. J Am Chem Soc

91:6488-6491, 1969.

ACKNOWLEDGMENTS

This project was supported in part by the National Institutes of Health grant DK15410 and by the San Diego Supercomputer Center.

237
AUTHORS

Murray Goodman, Ph.D.

Professor

Toshimasa Yamazaki, Ph.D.

Postdoctoral Research Scientist

Department of Chemistry

University of California, San Diego

9500 Gilman Drive

La Jolla, CA 92093-0343

Odile E. Said-Nejad, Ph.D.

Research Scientist

Salk Institute of Biotechnology Industrial Associates

505 Coast Boulevard

La Jolla, CA 92037

Eduard Felder, Ph.D.

Research Scientist

CIBA-GEIGY Corporation

Basel

SWITZERLAND

Dale F. Mierke, Ph.D.

Postdoctoral Researcher

Munich Technical University

Munich

FEDERAL REPUBLIC OF GERMANY

Peter W. Schiller, Ph.D.

Director

Laboratory of Chemical Biology and Peptide Research

Clinical Research Institute of Montreal

110 Pine Avenue West

Montreal, Quebec H2W 1R7

CANADA

238
Modified Solid-Phase Methods for the

Rapid Synthesis of Opioid Peptides

Richard A. Houghten, John M. Ostresh, and Suzanne M. Pratt

INTRODUCTION

Since the discovery of endogenous peptides having opiate activity in 1975 by

Hughes and Kosterlitz (Hughes et al. 1975) the opioid peptide system has

been shown to involve at least a dozen different naturally occurring peptide

sequences (Holaday et al. 1987). The resulting investigations have involved

not only the preparation of these naturally occurring peptides but also, in almost

all cases, the tritiated and 125I-labeled analogs as well. In the course of

investigations, the natural opioid peptides have been compared and contrasted

to at least a thousand different analogs, using in vivo and in vitro assays.

These have been directed toward the development of analogs having increased

potency, length of action, resistance to degradation, and selectivity toward

receptor subclasses.

The continually escalating need for synthetic peptides in the neurosciences has

far exceeded the supply available to most laboratories. This is also true in

molecular biology and immunology in which synthetic peptides are being used

for vaccine development (Lerner 1982; Bittle et al. 1982; Wilson et al. 1984;

Geysen et al. 1984) and for the detailed study of peptide antigen-antibody

interactions (Appel et al. 1990), for the determination of antigens having clinical

diagnostic utility (Chen et al. 1984), and for the mapping of protein products of

brain-specific genes (Sutcliffe et al. 1983). Researchers in pharmacology,

biochemistry, and biology also need numerous peptides in the study of

biologically active peptides (Yamashiro and Li 1984) and the investigation of

peptide and protein conformation (Hruby 1984) and folding (Shoemaker et al.

1985). In the majority of these studies, in which hundreds to thousands of

peptides are needed, the limiting factor has remained the availability and cost of

the desired peptides in the necessary amounts and purity. It is possible to

produce large numbers of peptides (i.e., hundreds) by conventional manual and

automated methods, but the effort is so time-consuming and costly that to carry

out this number of syntheses is normally impractical, even in especially wellequipped laboratories. In smaller research facilities or individual laboratories,

239
the preparation of this number of peptides is virtually impossible.

Straightforward synthesis methodologies, which now enable the preparation of

large numbers of specific synthetic peptides in milligram to multigram quantities

more efficiently and in a much shorter timeframe, will aid all fields utilizing

peptides.

MATERIALS AND METHODS

Protected N Boc amino acids were purchased from BACHEM (Torrance, CA).

The accuracy of quality control sheets for each amino acid concerning melting

point, optical purity, and thin-layer chromatographic behavior was confirmed for

each lot received. Major solvents (CHC12, DMF, and isopropanol) were

purchased in bulk (50-gallon drums) from Fisher Scientific. For the past 5

years, these reagent-grade quality solvents have proved acceptable in the

author’s laboratory. Trifluoracetic acid was purchased from Halocarbon in 5-

gallon lots—a quantity that was cost-effective and safe to handle. All resins

were purchased from BACHEM. The 4-(oxymethyl)phenylacetamidomethyl

resins (Pam resins) were significantly more costly than benzyl ester resins but,

in many instances, yielded a higher quality peptide. All peptides needing a Cterminal carboxyl were prepared using Pam resins. C-terminal amides were

prepared using p-methyl benzhydrylamine resin.

The technique of simultaneous multiple peptide synthesis (SMPS) (Houghten

1985; Houghten et al. 1968) was used throughout this work for small-scale (50

to 100 mg) and large-scale (50 g) synthesis and is described below. The

differences between a standard solid-phase protocol and one involving SMPS,

as well as an illustration of a compartmentalized resin packet used in SMPS,

are shown in figures 1, 2, and 3.

Standard t-Boc (tertiary butoxycarbonyl) amino acid resin (50 to 100 mg, 100 to

200 mesh, 0.2 to 0.8 meq/g) was contained in tared polypropylene mesh

packets (74 u), having approximate dimensions of 20x20 mm. These

dimensions were selected after trying various resin sizes (20 to 400 mesh) and

mesh materials (polyethylene, teflon, nylon, etc.). Although the example

described below uses 100 mg of resin, it was found that at least 5.0 g of resin

can be readily accommodated by adjusting the dimensions of the packet size.

After placing a number at the top of each unsealed bag with a black graphitebased marking pen, the packet was dosed and the number permanently sealed

into the polypropylene, giving an easily readable label for each bag (figure 2).

With the appropriate preliminary sieving, no resin was lost from the packet. The

resin-filled packets have excellent mechanical stability, and even with violent

shaking or stirring, the resin beads are not broken. These resin packets can be

used for SMPS—that is, syntheses in which many different peptides are

240
Action Achieved/Reagents Used Condition of Resin

FIGURE 1. Solid-phase peptide synthesis

241
Front Side

FlGURE 2. Resin packet

produced concurrently—or multiple analog peptide synthesis—syntheses in

which many analogs of a particular peptide are produced concurrently.

Standard deprotecting, neutralization, coupling, and wash protocols used in this

laboratory are variations of Merrifield’s original solid-phase procedures (1963).

Using completely manual methods, from 1 to as many as 400 individual packets

containing the desired starting resin can be carried through their common N

Boc removal, washing, and neutralization steps (figure 3). It was determined

that vigorous agitation of the resin packets was required to ensure successful

completion of the various steps in the synthesis protocol. Three washes were

found sufficient for effective removal of the total solvent retained in the resin and

polypropylene mesh for packets containing 100 mg of resin. Because the total

solvent retained after pouring off the residual wash solvent was approximately

242
FIGURE 3. Simultaneous multiple peptide synthesis

0.50 mL per bag, three 400 mL washes would be expected to remove greater

than 99.8 percent of the previous solvent when using 100 resin packets.

While routinely using 100 mg of resin per 20x20 mm packet, it was determined

that a range of resin quantities could be successfully accommodated in this size

packet. Approximately 250 to 300 mg appears to be the upper limit for this

243
packet size, although the simple solution of using larger packets enables 10 g

or more of resin to be readily utilized.

Following the dichloromethane washes for the removal of excess base (figure 3,

step II 6), the packets that contained the neutralized peptide resins were

removed from the reaction vessel and added to solutions of the desired

activated amino acid. Routinely, either preformed symmetrical anhydrides of

the protected amino acids or coupling procedures in which the protected amino

acid and activator are added in situ are used. The individual coupling steps

were carried out for 60 minutes at room temperature while shaking on an

Eberbach reciprocating shaker. Each coupling step can be checked for

completion by Gisin’s picric acid procedure (1972), which was easily carried out

on all the resin packets simultaneously. Incompletely coupled resins can be

treated again with activated amino acid or they also can be intentionally

terminated with acetylimidazole to form the N-acetyl derivative (Markley and

Dorman 1970). After completion of the coupling step, the resin packets were

returned to the common reaction vessel, and the synthesis was continued

through additional cycles of common wash, deprotection, neutralization, and

individualized couplings until the syntheses were completed.

Computer programs are necessary to assist in keeping track of the various

coupling steps when large numbers (i.e., >50) of individual peptides are being

synthesized simultaneously. The programs calculate the amounts and volumes

of reagents to be used for each coupling step as well as provide organized

checklists for the amino acids being added at each coupling step of the

synthesis. Specific variations of analogous peptides, such as residue

replacement, omission analogs, or chain-lengthened or -shortened analogs,

were easily accomplished by removing the individual, coded packets at the

point of variation during the synthesis, carrying out the desired coupling

separately, and if appropriate, returning the packet to the common reaction

vessel for completion. Using 14C-labeled t-Boc-alanine, cross-contamination

was determined to be less than 0.01 percent when recombining all the packets

following their coupling.

Following the synthesis of a set of protected peptide resins, the resin-filled

packets were washed thoroughly, dried, and weighed to give an initial indication

of yield based on the tared weight of starting resin and packet. It is important to

note that no resin is lost from the bag if the resin used has been thoroughly

sieved before its use. This enables an accurate weight determination of the

resulting protected peptide resin to be made at the end of the synthesis. The

protected peptide resins, still contained within their packets, were then cleaved

using the multivessel apparatus for hydrogen fluoride/anisole described below

(Houghten el al. 1986a).

244
The multivessel hydrogen fluoride (HF) cleavage apparatus (figure 4) consists

of three polypropylene plates with a polypropylene-threaded chamber

separating the top and middle plates. The bottom plate (not shown) serves as a

support for the 24 individual reaction vessels (made from either polypropylene

or Kel-F) and is attached through threaded post (point “A”) on the middle plate.

Alternate configurations having 10 to 80 mL vessels, 4 to 250 mL vessels, or

one large 2,000 mL vessel are also available for use. The top plate has two

threaded ports, the first of which serves as a vent, whereas the second leads to

a polypropylene radial distribution manifold having 24 outlets. Hollow

polypropylene tubes are connected to the radial manifold in the central chamber

leading through the middle plate and terminating 8 cm from the bottom of each

reaction vessel. The bottom safety plate ensures the security of the tubes. Into

each of the 24 reaction vessels was added either a free resin (100 to 500 mg)

or, more conveniently, a resin contained in its original polypropylene synthesis

packet. An amount of anisole equaling 7.5 percent of the expected volume of

HF along with a small teflon-coated magnetic stir bar was added to each

reaction vessel. After cooling in a dry ice/acetone solution, the vessels were

purged with N2

 for 15 minutes, and HF (5 to 10mL) was condensed

simultaneously and equally into all 24 reaction chambers. After 1.0 hour at 4°C,

the HF was removed rapidly (<15 minutes) with a strong flow of N2

. Nitrogen

purging was continued for another 15 minutes; the apparatus then was

subjected to an aspirator or mechanical pump vacuum for 15 minutes. The

vesseIs then were removed from the apparatus; the residual anisole was

removed with ethyl ether or ethyl acetate, and the peptide was extracted with

aqueous acetic acid (5 to 25 percent, depending on the solubility of the

peptide).

Initial analytical reverse phase-high-performance liquid chromatography (RPHPLC), to determine the homogeneity and approximate elution conditions of the

peptides produced, was carried out using (1) a Beckman 338 Gradient HPLC

system equipped with a Biorad AS-100 autosampler and (2) a Shimadzu CR4A

integrator. This system is used routinely to ascertain the homogeneity of all

peptides produced using standard pH 3.5 or pH 7.0 buffer systems. The

peptides then were purified using a Waters Milliprep 300 preparative HPLC

modified with a Gilson Model 232 preparative autosampler and preparative

Foxy Fraction collector with a Waters Prep Pak 5 cmx46 cm column. The

preliminary RP-HPLC information determined for each peptide enabled an

optimized eluting system to be used for each peptide. Fifty percent of these

peptides required a second pass through the preparative HPLC to obtain 95

percent or greater purity. The peptides were collected in 3 to 5 fractions.

Analytical HPLC chromatograms of each fraction then were run, and finally,

fractions of acceptable purity were combined and lyophilized. The average

yield of 200 mg of a 15-mer peptide that is 70 percent pure by analytical RP245
FIGURE 4. Simultaneous multiple HF cleavage apparatus

HPLC was approximately 100 mg of purified material after two passes through

the preparative HPLC. The losses of desired peptide were mainly from the

leading and trailing edge “cuts.” Each purified peptide then was characterized

by two analytical RP-HPLC systems, three thin-layer chromatography (TLC)

systems, mass spectroscopy, amino acid analysis, and sequencing.

246
DISCUSSION

Although there are several protocols for the preparation of peptides, the most

direct is Merrifield’s solid-phase method (1963). This approach toward the

solid-phase synthesis of peptides has changed little, conceptually, from

Merrifield’s original presentation in 1963. Synthesis is typically carried out in a

reservoir containing a single polymeric solid support to which the initial carboxyterminal amino acid of the desired peptide is covalently attached. The addition

of successive amino acids is a process that uses repetitive washing,

deprotection, neutralization, and coupling steps (figure 1). Although all steps

except the coupling reaction are identical, only a single peptide is typically

prepared at a given time. Thus, if multiple peptides that differ only in their

carboxy-terminal amino acid are desired, a separate synthesis for each would

be required, even though all the individual steps are identical except the initial

coupling of the first amino acid to the resin. Based on this fact, the author and

colleagues have developed the SMPS method (Houghten 1985, 1986;

Houghten et al. 1968) for use in the rapid production of large numbers of

peptides. In this patented procedure (U.S. Patent No. 4,631,211), the individual

starting resins for the solid-phase peptide synthesis of various peptides are

placed in separate solvent permeable packets (figure 2) which, when used in

conjunction with standard solid-phase peptide synthesis protocols, enable the

multiple repetitive steps involved to be carried out simultaneously (figure 3).

This procedure enables large numbers of discrete protected peptide resins to

be prepared rapidly. However, one still would face the formidable task of

cleavage and deprotection of many individual resins, one at a time, to generate

the desired free peptides. Therefore, we also have developed an apparatus

capable of cleaving 24 peptide resins simultaneously with hydrogen fluoride

(figure 4) (Houghten et al. 1986a). As a result, we are able to produce useful

quantities of large numbers of peptides, as pure as those produced by

conventional methods. The overall rate of synthesis is much faster and the use

of materials and personnel is more cost-effective. With SMPS, it is possible to

accomplish at least two couplings per day in the preparation of 150 peptides

having entirely different sequences. This is equivalent to the preparation of 20

different 15-residue peptides per day per technician. SMPS has been used to

prepare large numbers of peptides for use in various research areas, including

the study of antibody/antigen interactions (Houghten 1985; Houghten et al.

1986b), development of potential synthetic vaccines (Parry et al. 1985), and

optimal analog development for biologically relevant peptides (Ruggeri et al.

1986). We are using these methods to prepare 10-g quantities, and specific

tritiated analogs, of the peptides listed in table 1. The majority of these are now

available from the NIDA Drug Supply System.

247
TABLE 1. List of peptides prepared

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

DPDPE

3H-DPDPE

DSLET

3H-DSLET

DTLET

DADLE

3H-DADLE

ICI 174,864

PLO17

3H2

-PLO17

DAGO

3H-DAGO

CTAP

3H-CTAP

Dynotphin A 1-17, porcine

Dynorphin A 1-13, porcine

Dynorphin A 1-13 amide, porcine

3H-Dynorphin A 1-13 amide porcine

Dynorphin A 1-11, porcine

3H-Dynorphin A 1-11, porcine

Dynorphin A 1-9, porcine

3H-Dynorphin A 1-9. porcine

Dynorphin B

ß-Endorphin

25. 3H-ß-Endorphin

26. 125I-ß-Endorphin

27. DALDA

H-Tyr-D-Pen-Gly-Phe-D-Pen-OH

H-Tyr(3H2)-D-Pen-Gly-Phe-D-Pen-OH

H-Tyr-D-Ser-Gly-Phe-Leu-Thr-OH

H-Tyr(3H2)-D-Ser-Gly-Phe-Leu-Thr-OH

H-Tyr-D-Thr-Gly-Phe-Leu-Thr-OH

H-Tyr-D-Ala-Gly-Phe-D-Leu-OH

H-Tyr(3H2)-D-Ala-Gly-Phe-D-Leu-OH

H-Diallyl-Tyr-Aib-Aib-Gly-Phe-Leu-OH

H-Tyr-Pro-N-Me-Phe-D-Pro-NH2

H-Tyr(3H2)-Pro-N-Me-Phe-D-Pro-NH2

H-Tyr-D-Ala-Gly-N-Me-Phe-Gly-ol

H-Tyr(3H2)-D-Ala-Gly-N-Me-Phe-Gly-ol

H-D-Phe-Cys-Tyr-D-Trp-Arg-Thr-Pen-Thr-NH2

H-D-Phe-Cys-Tyr(3H2)-D-Trp-Arg-Thr-Pen-Thr-NHz

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-Pro-Lys-Leu-Lys-Trp-Asp-Asn-Gln-OH

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-Pro-Lys-Leu-Lys-OH

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-Pro-Lys-Leu-Lys-NH2

H-Tyr(3H2)-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-Pro-Lys-Leu-Lys-NH2

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-Pro-Lys-OH

H-Tyr(3H2)-Gly-Gly-Phe-Leu-Arg-Ile-Arg-Pm-Lys-OH

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-OH

H-Tyr(3H2)-Gly-Gly-Phe-Leu-Arg-Arg-lle-Arg-OH

H-Tyr-Gly-Gly-Phe-Leu-Arg-Arg-Gln-Phe-Lys-Val-Vai-Thr-OH

H-Tyr-Gly-Gly-Phe-Met-Thr-Ser-Glu-Lys-Ser-Gln-Thr-Pro-Leu-Val-Thr-Leu-Phe-LysAsn-Ala-lle-lIe-Lys-Asn-Ala-Tyr-Lys-Lys-Gly-Glu-OH

H-Tyr(3H2)-Gly-Gly-Phe-Met-Thr-Ser-Glu-Lys-Ser-Gln-Thr-Pro-Leu-Val-Thr-Leu-Phe

Lys-Asn-Ala-lle-Ile-Lys-Asn-Ala-Tyr-Lys-Lys-Gly-Glu-OH

H-Tyr(125l)-Gly-Gly-Phe-Met-Thr-Ser-Glu-Lys-Ser-GIn-Thr-Pro-Leu-Val-Thr-Leu-PheLys-Asn-Ala-lle-lle-Lys-Asn-Ala-Tyr-Lys-Lys-Gly-GIu-OH

H-Tyr-D-Arg-Phe-Lys-NH2
The difficulties in peptide synthesis typically occur at the purification stage, not

in the assembly of the peptide. Although the two stages are intimately linked,

the assembly process always must be carried out with the ultimate necessary

purification in mind. Several obvious but essential precautions must be followed

to avoid later problems when preparing synthetic peptides. The highest quality

starting materials (protected amino acids, solvents, etc.) prevent later difficulty

in characterization and purification. All solvents used must be freshly distilled

as needed and all the protected amino acids must be of the highest quality

available. Currently, several suppliers are available for N t-butoxycarbonyl

amino acids. The highest quality in terms of level of impurities, and the least

amount of racemate (typically, <0.05 percent), must be used; and every lot must

be checked against each manufacturers specifications.

The use of Merrifield’s solid-phase method often has been criticized as unable

to generate peptides of extremely high quality. We have found that the solidphase method, in conjunction with SMPS and standard purification and analysis

procedures, permits the preparation of 99+ percent pure peptides. An example

of the protocol and results found for dynorphin (1-13) amide are shown in

figures 5 and 6. As illustrated, this peptide can be prepared in >99 percent

purity multigram quantities in a final overall yield of approximately 53 percent

with no detectable impurity, as determined using two different RP-HPLC

systems, three TLC systems, amino acid analysis, mass spectral analysis, and

sequencing. The largest losses came at the extraction step following the final

HF cleavage of the peptide. Further evidence for the overall purity of the

peptide was found following the preparation of all the single position omission

analogs of the sequence and their examination by RP-HPLC (pH 3.5). As

shown in figure 7, all these analogs separate from the desired sequence on

analytical RP-HPLC. During preparative runs, the two glycine omission analogs

and the proline omission at positions 2, 3, and 10, respectively, would not have

been successfully separated. However, the presence of these peptides would

be detectable by analytical HPLC. Although clearly the successful separability

of individual omission analogs of specific peptides will vary greatly, the majority

of the opioid peptides shown in table 1 can be separated successfully from their

expected major contaminants.

The ability to prepare synthetic peptides conveniently and rapidly is essential to

many areas of biomedical research, including the investigation of the causative

mechanisms of drug abuse. The methods utilized in the preparation of the

opioid peptides presented here enable large numbers of totally different

sequences, or large numbers of analogs of a given sequence, to be prepared

quickly and cost-effectively.

249
FIGURE 5. Flow chart—compound 17: dynorphin A (1-13) amide, porcine

250
FIGURE 6. Data sheet

251
FIGURE 7. Omission analogs of dynorphin (1-13) amide

Y1G2G3F4L5R6R7I8R9P10K11L12K13 amide (pH 2.1)

NOTE

lnquiries about the availability of these peptides for research studies should be

addressed to Drug Supply System-NIDA, Research Technology Branch,

National Institute on Drug Abuse, Room 10A-13, 5600 Fishers Lane, Rockville,

MD 20857; the telephone number is (301) 443-5280.

REFERENCES

Appel, J.R.; Pinilla, C.; Niman, H.; and Houghten, R.A. Elucidation of

discontinuous linear determinants in peptides. J lmmunol 144(3):976-983,

1990.

Bittle, J.L.; Houghten, R.A.; Alexander, H.; Shinnick, T.M.; Sutcliffe, J.G.;

Lerner, R.A.; Rowlands, D.J.; and Brown, F. Protection against foot and

mouth disease by immunization with a chemically synthesized peptide

predicted from the viral nucleotide sequence. Nature 298:30-33, 1982.

252
Chen, P.P.; Houghten, R.A.; Fong, S.; Karras, J.G.; Lerner, R.A.; Vaughan,

J.H.; and Carson, D.A. Delineation of a cross-reactive idotype on human

autoantibodies with antibody against a synthetic peptide. J Exp Med

159:1502-1511, 1984.

Geysen, H.M.; Meloen, R.H.; and Barteling, S.J. Use of peptide synthesis to

probe viral antigens for epitopes to a resolution of a single amino acid. Proc

Natl Acad Sci USA 81:3998-4002, 1984.

Gisin, B.F. The monitoring of reactions in solid-phase peptide synthesis with

picric acid. Anal Chem Acta 58:248-249, 1972.

Holaday, J.W.; Law, P.-Y.; and Herz, A., eds. Progress in Opioid Research:

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National Institute on Drug Abuse Research Monograph 75. DHHS Pub. No.

(ADM)87-1507. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off.,

1986.

Houghten, R.A. General method for the rapid solid-phase synthesis of large

numbers of peptides: Specificity of antigen-antibody interaction at the level

of individual amino acids. Proc Natl Acad Sci USA 82:5131-5135, 1985.

Houghten, R.A. Simultaneous multiple peptide synthesis: The rapid

preparation of large numbers of discrete peptides. In: Peeters, H., ed.

Protides of the Biological Fluids, Proceedings of the Thirty-Fourth Colloquium

1986. Vol. 34. Oxford, England: Pergamon Press, 1986. pp. 95-98.

Houghten, R.A.; Bray, M.K.; DeGraw, S.T.; and Kirby, C.J. A simplified

procedure for carrying out simultaneous multiple hydrogen fluoride cleavages

of protected peptide resins. Infer J Pept Prot Res 27:673-678, 1986a.

Houghten, R.A.; DeGraw, S.T.; Bray, M.K.; Hoffman, S.R.; and Frizzell, N.D.

Simultaneous multiple peptide synthesis: The rapid preparation of large

numbers of discrete peptides for biological, immunological, and

methodological studies. Biotechniques 4:522-529, 1968.

Houghten, R.A.; Hoffman, S.R.; and Niman, H.L. Relative importance of

position and individual amino acid residues in peptide antigen-antibody

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ACKNOWLEDGMENT

This work was supported by National Institute on Drug Abuse contract

271-87-8122.

AUTHORS

Richard A. Houghten, Ph.D.

Director of Research

Multiple Peptide Systems

Torrey Pines Institute for Molecular Studies

3550 General Atomics Court

San Diego, CA 92121

254
John M. Ostresh, M.S.

Vice President

Research and Development

Suzanne M. Pratt, B.S.

Chief Operating Officer

Multiple Peptide Systems

3550 General Atomics Court

San Diego, CA 92121

255
Irreversible Ligands as Probes for

Drug Receptors

Amy Hauck Newman

INTRODUCTION

The design and synthesis of highly selective chemical probes are critical for

progress in the area of drug receptor pharmacology. Drugs of abuse mediate

their pharmacological actions and abuse liability via interactions with specific

receptor system(s). The preparation and use of selective probes, referred to as

irreversible or affinity labels, have proven to be extremely useful in the isolation,

purification, and characterization of many receptor systems. By definition,

irreversible ligands first recognize a specific binding site and then form a

covalent bond on or near that recognition site, resulting in irreversible

attachment (Baker 1967; Takemori and Portoghese 1985; Portoghese and

Takemori 1986). For the purpose of this review, all ligands discussed possess

a reactive chemical moiety that is capable of forming a covalent bond. These

groups may be intrinsically active and are generally electrophilic in nature, or

they may require a photoactivation step that leads to a reactive species

(Takemori and Portoghese 1985). The compounds are classified according to

the receptor system they interact with and are further categorized into specific

functionalities, beginning with electrophiles and ending with the photoactivated

agents.

The successful design of highly receptor-selective irreversible ligands,

containing an electrophilic moiety, has been described as being dependent on

receptor affinity and selectivity of the ligand, location of the electrophile on the

ligand, and the reactivity of the electrophile (Takemori and Portoghese 1985;

Portoghese and Takemori 1986). Electrophilic moieties most commonly used

include isothiocyanates, Michael acceptors, haloacetamides, aldol esters, and

nitrogen mustards. Placement of the electrophilic moiety within the parent

ligand generally takes into account ease of chemical synthesis and avoidance

of a known site of ligand receptor interaction. Ideally, when the ligand binds to

the receptor site, a nucleophile on or near that site will be in a position to

covalently bond. Because biological tissues possess a multitude of reactive

nucleophiles, the probability is high for nonspecific covalent attachment. This

256
must be taken into account when analyzing results of experiments with these

agents.

Photoaffinity labels are ligands that have an inherent affinity for a binding site,

may function as agonists or antagonists, and also contain a photosensitive

functional group that, when photoactivated with light, is capable of forming a

covalent bond at or near the binding site (Fedan et al. 1984). Unlike

electrophilic affinity labels, the photoaffinity labels’ association with the

recognition site is reversible until photolysis is initiated (Fedan et al. 1984). Due

to the high reactivity of the photoactivated intermediate relative to electrophiles,

it is generally easier to design a photoaffinity label, since the location of the

photoactivated group is not crucial for covalent attachment to the binding site

(Takemori and Portoghese 1985). The chemical mechanism for photoaffinity

labeling has been reviewed (Cavalla and Neff 1985). Caution must be taken to

assess the possible effects of irradiation on the tissue being studied (Fedan et

al. 1984). For example, UV-radiation damage to the opioid receptor has been

reported (Capponi and Catt 1980; Glasel and Venn 1981; Smolarsky and

Koshland 1980). Another limitation of the photoaffinity labels is that they are

only useful under conditions that support photolysis, which, at the very least,

eliminates in vivo work. Eiectrophilic agents need not be activated and, hence,

are amenable to both in vitro and in vivo pharmacology (Takemori and

Portoghese 1985).

OPIOID RECEPTORS

The central nervous system (CNS) opioid receptor subtypes μ, have

been characterized with several structurally diverse, irreversible ligands (for

review, see Takemori and Portoghese 1985; Portoghese and Takemorl 1986;

Zimmerman and Leander 1990). Ligands that bind selectively and irreversibly

to particular opioid receptor subtypes can provide insight into the relationship of

these subtypes to one another and their physiological roles. A nitrogen mustard

derivative of naltrexone, ß-CNA, 1, was the first successful irreversible

antagonist for opioid receptors. ß-CNA proved to be a potent affinity label

selective for all three opioid receptors, both in vitro and in vivo (Portoghese et

al. 1978, 1979). The lack of selectivity of 1 for a particular opioid receptor

appears to be due to the high reactivity and low selectivity of the reactive

species, the aziridinium ion (Takemori and Portoghese 1985). Michael

acceptors react preferentially with sulfhydryl groups, which are thought to be

present on opioid receptors (Simon et al. 1973). These considerations led to

the discovery of ß-FNA, 2, having a fumaramate methyl ester function

(Portoghese et al. 1980; Takemori et al. 1981). This compound has been

reported to interact reversibly with receptors and irreversibly with μreceptors (Ward et al. 1985). ß-FNA displays reversible agonlst activity that

257
appears to be -receptor mediated (Takemori et al. 1981). However, selective

antagonism of μ-activities has been observed after systemic administration of 2,

increasing its usefulness in studying these receptors in vivo (for review, see

Zimmerman and Leander 1990). The N-methyl-derivatives of ß-CNA and ßFNA are irreversible ligands with long-lasting agonist properties (Takemori and

Portoghese 1985; Larson and Armstrong 1980). Structure-activity relationships

have been described for a series of ester and fumaramate morphinan and

endoethenooripavine analogs (Burke et al. 1984a; Jacobson et al. 1983; Lessor

et al. 1984, 1986; Schoenecker et al. 1986; Portoghese et al. 1986).

Halogenated amide derivatives of endoethenooripavine, 3 (Lessor et al. 1986),

and -naltrexamine, 4 (Archer et al. 1985), have also been described as potent

irreversible ligands of opioid receptors. CAN, 5, and BAM, 6, are C-14-position

derivatives of naltrexone and have been described as covalently bonding to a

high-affinity μ-site (Reichman et al. 1986).

The isothiocyanate function has proven to be highly versatile as an electrophilic

moiety for irreversible ligands. The ease of synthesis from primary amines

(Assony 1961), the known rapid reactivity with amino and sulfhydryl groups, and

the low reactivity toward water and hydroxyl functions (Williams et al. 1980a)

have led to successful application of this functionality to affinity ligand

preparation and use. Fentanyl isothiocyanate (FIT, 7 is a highly selective

acylator of -receptors (Rice et al. 1983; Burke et al. 1984a). [

3H]FIT (Burke et

al. 1984b) was first used to identify and partially purify a glycoprotein subunit,

Mr 58,000, from NG-108 neuroblastoma x glioma hybrid cells, which was

acylated by this ligand in the presence of dextromethorphan, but not

levorphanol, and was presumed to be a component of the opioid receptor (Klee

et al. 1982). The (+)- and (-)-cis-3-methyl derivatives of FIT were the first

enantiomeric pair of irreversible ligands to be described (Burke et al. 1986).

The (+)-enantiomer, SUPERFIT, 8, was found to be 10 times more potent than

7 in acyiation of -receptors and 50 times more potent than its (-)-enantiomer

(Burke et al. 1986). [

3H]SUPERFIT labeled the same 58,000-dalton subunit of

the opioid receptor as 8 (Burke et al. 1986) and was used to purify this subunit

to homogeneity (Simonds et al. 1985). This ligand subsequently has been used

to characterize functional coupling of opioid receptors to GTPase (Clark and

Medzihradsky 1987). An antibody was generated to the opioid receptor

complex from NG-108 cells, and [

3H]SUPERFIT was employed to characterize

the 58,000-dalton subunit of the immunoaffinity purified receptor (Carr et al.

1987). The trans-isomers of 8 were prepared to obtain further insight into the

steric requirements of the -receptor (Kim et al. 1989). The (+)-cis- and (+)-

trans-isomers demonstrated similar affinity to the high-affinity -sites, which was

considerably greater than for either of the (-)-isomers, suggesting that optical

isomerism plays a more important role than the cis:trans configuration. In vivo,

the (+)-trans-isomer was only weakly active (Kim et al. 1989).

258
The benzimidazole isothiocyanate (BIT, 9), related to the extremely potent opioid

agonist etonitazene, is a high-affinity irreversible ligand for μ-receptors (Rice et

al. 1983; Burke et al. 1984a). Several endoethenooripavine-isothiocyanates

10, 11) also have been reported to have μ- or -receptor selectivity (Jacobson

et al. 1983; Lessor et al. 1984, 1986). Another new -selective ligand,

naitrindoie-isothiocyanate, 12, has been preliminarily described (Sultana et al.

1989). Recently, the first -receptor selective irreversible ligand was prepared

(de Costa et al. 1989a). Compound 13 is an isothiocyanate-derivative of the

most active (1S,2S) enantiomer of the -selective compound U-50, 488 (14). At

1 μM concentration in guinea pig membranes (completely depleted of functional

259
μ- and -receptors with 9 and 7, respectively), compound 13 enantiospecifically

and irreversibly reduced the binding of [

3H]U-69,593 to 11.2 percent of control

without affecting [

3H]bremazocine binding, thus providing an independent line of

evidence for x-receptor heterogeneity (de Costa et al. 1989a). The racemic

mixture UPHIT, 15, and its 1S,2S- and 1R,2R-trans-enantiomers, more closely

related derivatives of U-50,488, have been reported to be potent displacers of

[

3H]U-69,593 and weak displacers of [3H]bremazocine, possibly identifying

receptor subtypes (de Costa et al. 1989b). A 300-fold enantioselectivity was

demonstrated, and the 1S,2S enantiomer of 15 was marginally more potent than

13 in vitro. Racemic 15 was a potent and selective -acylator in vivo compared

to an inactive 13 in this assay, perhaps because of increased reactivity of 15

toward nucleophiles (de Costa et al. 1989b; Band et al. 1989).

Substitution of the C-6 carbonyl of naloxone and naltrexone by a group that has

similar spatial configuration to that of a carbonyl group and is electrophilic in

nature led to the discovery of naioxazone, 16 and naltrexazone, 17 (Pasternak

and Hahn 1980). Both compounds were selective, high-affinity ligands for

opioid receptors and caused long-term inhibition of morphine analgesia

(Pasternak and Hahn 1980; Pasternak et al. 1980). The irreversible inhibition

was characterized as selectively occurring at the high-affinity μ1-subtype

(Pasternak et al. 1980; Hahn et al. 1982). It was later discovered that these

hydrazones could be converted to more active azines such as naioxonazine,

18 This compound is a more potent μ1-ligand, whose mechanism of

irreversible binding is not well understood and may not occur through covalent

attachment (Hahn et al. 1982; Johnson and Pasternak 1984). Subsequently, a

series of phenyl hydrazones were developed to further investigate the

mechanism of action of these agents; however, none of these compounds was

as subtype selective as 16 (Hahn et al. 1985; Luke et al. 1988; Williams et al.

1988). Comparison of μ1-selectivity between naloxonazine, 16 and ß-FNA, 2,

revealed that ß-FNA is also μ1-selective in vitro but interacts with μ1 and μ2in

vivo (Recht and Pasternak 1987).

260
Photoaffinity ligands have not proven to be as successful as electrophilic-type

irreversible agents in opioid receptor research, primarily due to the reported UVinactivation of the receptor (Capponi and Catt 1980; Glasel and Venn 1981;

Smoiarsky and Koshiand 1980). The opioid analgesic azido-levorphanol, 19,

caused irreversible incorporation of radioactivity into biological material upon

photolysis (Winter and Goldstein 1972). However, extensive nonspecific

binding resulted, diminishing the usefulness of this compound (Winter and

Goldstein 1972). Photoaffinity labels based on fentanyl, (+)-cis-3-

methylfentanyl, lofentanyl, and sufentanyl were similarly unsuccessful;

photodecomposition of opioid receptors was reported (Maryanoff et al. 1982).

Azido-derivatives of the opioid peptides DAGO and DTLET have been

described as binding to μ- and -receptors, respectively (Garbay-Jaureguiberry

et al. 1983, 1986). Recently, azido-derivatives of the -selective peptide

DPDPE and μ-selective peptide CTP have been synthesized (Landis et al.

1989).

NMDA RECEPTORS/PCP BINDING SITES

The bizarre behavioral actions induced by PCP, the abuse liability, and the

neuroprotective effects produced by this drug have generated considerable

interest in its biochemical and behavioral pharmacology. Saturable and

stereoselective PCP binding sites in the brain have been described (Vincent et

al. 1979; Zukin and Zukin 1979; Quirion et al. 1981; Hampton et al. 1982).

These sites appear to be allosterically coupled to the N-methyl-D-aspartate

(NMDA)/L-glutamate macromolecular complex, and PCP and related

compounds have been shown to block the increases in neuronal discharges

induced by NMDA (Lodge and Anis 1982; Quirion et al. 1987). The probability

of interaction between PCP and NMDA receptors is further supported by the

striking similarity in distribution of these receptors in the brain (Maragos et al.

1986).

The meta-isothiocyanate derivative of PCP, metaphit, 20, was the first

electrophilic irreversible ligand to selectively label PCP sites in rat brain

261
(Rafferty et al. 1985). The metaphit isomer with the isothiocyanate function in

the 4-position of the piperidine ring did not irreversibly inhibit [3H]PCP binding,

indicating structural specificity for the acylation of these receptors (Rafferty et al.

1985). Metaphit demonstrated long-term inhibition of PCP-induced stereotypy

in rats (Contreras et al. 1985) but did not antagonize stereotyped behavior

induced by the -ligands (-)-cyclazocine or (+)-SKF-10,047, suggesting

selective acylation of only the PCP sites (Contreras et al. 1986). However, it

has been proposed that 20 prevents PCP-induced locomotor behavior through

mechanisms not related to the PCP recognition site (French et al. 1987). In

addition, in pigeons and monkeys, 20 induced PCP-like catalepsy, ataxia, and

convulsions and did not inhibit these PCP-induced behaviors (Koek et al. 1985,

1986). In vitro studies showed 20 caused a concentration-dependent inhibition

of acetylcholine release evoked by NMDA, which paralleled loss of [

3H]TCP

binding in striatal tissue, indicating metaphit as having long-term PCP-like

effects (Snell et al. 1987). Furthermore, 20 has been described as a tool for the

study of the molecular basis of stimulant action (Schweri et al. 1987) and has

been shown to inactivate cocaine binding sites as well as antagonize cocaineinduced locomotor stimulation in rats (Berger et al. 1986). Finally,

autoradiographic studies have revealed that metaphit inhibits most of the PCPinduced increases in glucose metabolism in selected areas of the rat cortex

(Tamminga et al. 1987); microelectrophoresis studies in rat spinal neurones

showed a decrease in NMDA-induced excitation by 20 (Davies et al. 1986).

Etoxadrol-meta-isothiocyanate, 21, has been synthesized and characterized as

an irreversible ligand for PCP receptors (Thurkauf et al. 1988). It is the first

chiral electrophilic affinity ligand to be described for this site and displaces

[

3H]TCP, from PCP sites in rat brain, with four times higher affinity than 20

(Thurkauf et al. 1988).

Photoaffinity labeling of rat brain PCP receptors with [

3H]azido-PCP, 22,

revealed five polypeptides with Mr’s 90,000, 62,000, 49,000, 40,000, and

33,000, which were unevenly distributed in the brain (Haring et al. 1985, 1986).

262
Competition studies with [

3H]PCP and dexoxadrol suggest that the high-affinity

PCP site correlated best with the 90,000-dalton peptide (Haring et al. 1985,

1986); the 33,000-dalton peptide is suggested to be a low-affinity PCP site

(Haring et al. 1986, 1987).

MK 801 potently and selectively inhibits binding of [3H]TCP from PCP sites and

weakly inhibits binding of [

3H]SKF-10,047 from -sites (Loo et al. 1987). (+)-

[

3H]-7-Azido-MK 801, 23, was preliminarily reported to display reversible binding

to PCP sites and a pharmacological profile identical to the parent compound,

MK 801 (Sonders et al. 1989). Photoactivation in guinea pig membranes

resulted in the labeling of a single radioactive band of 115,000 daltons. This

band was absent from lanes that had been preincubated with PCP, suggesting

a PCP component of the NMDA-receptor complex (Sonders et al. 1989).

SIGMA RECEPTORS

The benzomorphans, such as SKF-10,047, represent a class of

psychotomimetic drugs that were once believed to interact at a -opioid site

(Martin et al. 1976). Further studies demonstrated that many actions of these

agents could not be blocked by the opioid antagonist naloxone; thus, they were

not interacting at an opioid receptor subtype (Tam and Cook 1984). Many

compounds that bind with high affinity to -sites exert similar behavioral effects

to PCP, and there is an overlap in the binding of these agents to both receptor

sites (Contreras et al. 1987). The striking similarities between the actions of the

PCP and -drug classes led to the concept that there was only one receptor

system involved. However, radioreceptor binding studies and different rank

order of potencies of drugs that interact at both sites implicate two distinct drug

recognition sites (Manallack et al. 1986). In addition, autoradiography studies

show that the anatomical distribution of these sites is very different in rodent

brain (Sonders et al. 1988). Recently, [

3H]-(+)-pentazocine has been introduced

as a ligand with high specificity for -receptors and insignificant affinity for PCP

sites, further demonstrating that these receptor sites are not the same (de

263
Costa et al. 1989c). -Receptors now have been defined as nondopaminergic,

nonopioid receptors that are distinct from PCP receptors (de Costa et al. 1990).

Metaphit (20) was shown to displace [3H]DTG and [3H]3-PPP from -sites in

guinea pig brain, in an irreversible and competitive manner (Bluth et al. 1989).

An isothiocyanato-derivative of the selective -receptor ligand 1,3-di-ortho-tolyl

guanidine (DTG) has been prepared (DIGIT, 24) (Adams et al. 1987).

-Receptors are selectively and irreversibly modified by 24, whereas PCP

receptors are not affected. A radiolabeled azido-derivative of DTG, 25, recently

was used to isolate a 29,000-dalton polypeptide that may represent the intact

-receptor complex (Kavanaugh et al. 1988).

BENZODIAZEPINE RECEPTORS—CENTRAL/GABA AND PERIPHERAL

TYPES

The benzodiazepine receptors in the CNS are associated with GABA receptors

and a chloride ion channel and are responsible for the mediation of anxiolytic,

anticonvulsant, and muscle relaxant properties of this class of drugs (Haefly et

al. 1985). Abuse liability and physical dependence have been demonstrated for

many of the centrally acting benzodiazepines. The first isothiocyanatobenzodiazepine to demonstrate noncompetitive, irreversible binding to central

benzodiazepine sites was irazepine, 26 (Rice et al. 1979). Irazepine, 26,

demonstrated long-term protection against pentylenetetrazol-induced seizures

when administered intracerebroventricularly, which was accompanied by a

decrease in [3H]-diazepam binding in forebrain of treated mice (Williams et al.

1980b). The primary amino-precursor of 26 was used to prepare an affinity

column for the purification of anti-benzodiazepine antibodies (Goldman et al.

1986). A related bromoacetamide derivative, kenazepine, 27, demonstrated

similar irreversible properties to 26 but, in addition, appeared to interact

reversibly with one population of benzodiazepine receptors and irreversibly with

another (Williams et al. 1980a, 1980b). More recently, an isothiocyanatoanalog of the inverse agonist ß-CCE (28) has been prepared, 29 (Allen et al.

1988).

When irradiated, the potent centrally active benzodiazepine flunitrazepam, 30,

irreversibly binds to the benzodiazepine receptor (Mohler et al. 1980). The

receptor component labeled by 30 is a protein with Mr 50,000; its locations in

cerebral and cerebellar cortical slices were visualized with electron microscopic

autoradiography (Mohler et al. 1980). In contrast to opioid receptors, the

benzodiezepine receptors are not damaged by irradiation (Mohler et al. 1980).

Heterogeneity of the benzodiazepine receptors has been reported in

subsequent studies using 30, with Mr 51,000 in cerebellum and Mr’s 55,000

and 51,000 in hippocampus (Sieghart and Karobath 1980; Eichinger and

264
Sieghart 1984). Shortwave ultraviolet irradiation has been reported to improve

the photoaffinity labeling of the benzodiazepine receptors by 30 (Herblin and

Mechem 1984). [

3H]Clonazepam, 31, can also be photoactivated and binds to

benzodiazepine receptors irreversibly, but with fivefold lower specific activity

compared to 30 (Sieghart and Mohler 1982; Bowling and DeLorenzo 1987).

Another photoaffinity ligand, the partial inverse agonist [

3H]Ro 15-4513, 32,

ligands the same proteins as flunitrazepam; however, instead of only labeling

25 percent of the benzodiazepine sites, as with 30, compound 32 is reported to

photolabel all binding sites (Sieghart et al. 1987; Mohler et al. 1984). The first

ß-carboline photoaffinity label, 33, has recently been described as producing a

42-percent decrease in maximal binding of ß-carboline carboxylic propyl ester

(ß-CCP) sites, with essentially no effect on flunitrazepam sites (DellouveLourillon et al. 1989). These results provide evidence that the ß-carbolines and

the benzodiazepines bind to discrete sites on the central benzodiazepine

receptor (Dellouve-Lourillon et al. 1989).

The related GABA-regulated chloride ionophore has been treated with two

isothiocyanates, 34 and 35, derived from the cage convulsant TBOB (Lewin et

al. 1989). These compounds are specific, site-directed acylating agents for

sites on or near GABA-gated chloride channels labeled by [

3H]TBOB and

[35S]TBPS (Lewin et al. 1989). Compound 34 inhibited binding of the above

265
radioligands with an affinity comparable to the parent ligand, whereas 35 was

more than one order of magnitude less potent (Lewin et al. 1989).

[

3H]Muscimol has been described as photolabeling 86 percent of the GABAA

receptors in rat cerebellar synaptosomal membranes (Cavalla and Neff 1985).

Ultraviolet irradiation did not adversely affect the GABA receptor, and the two

components isolated were proteins with Mr’s of more than 250,000 and 52,000

(Cavalla and Neff 1985). [

3H]Muscimol and [3H]flunitrazepam have been used

in a large-scale purification of the GABA-benzodiazepine receptor protein from

rat brain, by affinity chromatography (Stauber et al. 1987). The material

recovered was used for structural and immunochemical studies, including the

production of antisera against the purified receptor complex protein (Stauber et

al. 1987). A series of aryl-diazo compounds based on muscimol also have

been described as potential photoaffinity ligands for the GABA receptor

(Bouchet et al. 1987).

In comparison to the central-type benzodiazepine receptors, very little is known

about the function and molecular organization of recognition sites for

benzodiazepines found outside the CNS. The benzodiazepine Ro 5-4864 (36)

and the isoquinoline PK 11195 (37) have been used to characterize the

peripheral-type benzodiazepine receptors because they have high affinity and

selectivity for these sites and do not possess any of the pharmacological

characteristics of classical centrally acting benzodiazepines. The

ethylisothiocyanato-derivatives of these compounds, AHN 086, 38, and AHN

070, 39, respectively, have proven to be potent, selective, and irreversible

ligands for these receptors (Lueddens et al. 1986; Newman et al. 1987).

Compound 38 has been used to characterize the association between

peripheral benzodiazepine receptors and the calcium channels in guinea pig

atria and ileal longitudinal smooth muscle (Bolger et al. 1989), and [

3H]AHN 086

has been used to label the peripheral benzodiazepine receptor protein, Mr

30,000, in rat pineal gland (McCabe et al. 1989).

Although the peripheral benzodiazepine receptor sites recognize flunitrazepam,

30, they cannot be photoaffinity-labeled by it (Thomas and Tallman 1981).

However, photoaffinity labeling of the peripheral benzodiazepine receptors has

been achieved with PK 14105, 40 (Doble et al. 1987a, 1987b; Skowronski et al.

1988; Antkiewicz-Michaluk et al. 1988a, 1988b; Benavides et al. 1989).

Photoactivation of 40 results in the covalent coupling of this ligand to an

approximately 18,000-dalton protein in cardiac, adrenal, brain, and kidney

membranes (Doble et al. 1987a, 1987b; Skowronski et al. 1988). Additional

characterization and subcellular distribution studies of the peripheral

benzodiazepine sites in rat adrenal mitochondria revealed a protein of

approximately 17,000 daltons (Antkiewicz-Michaluk et al. 1988a, 1988b).

266
Recently, 40 has been employed to study the peripheral benzodiazepine sites

in immune system organs of rats (Benavides et al. 1989). The distribution of

these sites in the immune system organs suggests a preferential labeling of

T-cells and monocytic cells consistent with a proposed immunomodulatory role

for some peripheral benzodiazepine receptor ligands (Benavides et al. 1989).

DOPAMINE RECEPTORS

Central dopamine receptors have been implicated in the mechanism of action of

several drugs of abuse, including LSD and cocaine. As in many of the other

receptor systems described, N-chloroethyl-substituted monoamine agonists

have been prepared as irreversible ligands for studying dopamine receptors.

An early example of this is the N-chloroethyl-derivative of apomorphine, 41

(Neumeyer et al. 1980; Costall et al. 1980). Tritiated 41 has been used to

characterize dopamine receptors and, furthermore, has been suggested to bind

selectively to the D2

-sites (Guan et al. 1984). The N-chloroethyl derivative, 42,

of 3-PPP (described in the -receptor section of this chapter) was prepared as

another potential alkylating agent for dopamine receptors but was not a good

irreversible agent due to its reduced affinity and inability to covalently bond to

the receptor as evidenced by facile washout (Williams et al. 1983).

LSD is reported to be a “naturally photoreactive agent” that needs no chemical

modification and whose receptor-binding properties already have been well

characterized (Mahon and Hartig 1982). LSD covalently binds to bovine

caudate membranes, but the fact that this compound binds with high affinity to

serotonin and adrenergic receptors in addition to dopamine receptors limits its

usefulness as a photoaffinity label (Mahon and Hartig 1982). More selective

photoaffinity ligands have since been introduced that bind selectively to either

D1

 or D2 receptors. The D2 dopamine receptor has many functional correlates

with such dopaminergic behaviors as rotation, locomotion, emesis, and

267
stereotypy (Seeman 1980). The first selective striatal D2

-photoaffinity label was

an azido-derivative of clebopride, 43 (Niznik et al. 1984, 1985a). Compound 43

also was found to inhibit [

3H]spiperone binding in human striatal membranes

irreversibly and with high affinity (Wouters et al. 1984). Replacing the 5-chloro

group of 43 with 125l resulted in a D2

-selective photoaffinity label with high

specific radioactivity (Neumeyer et al. 1985; Niznik et al. 1985a, 1985b). The

[

125I]azidoaryl-derivative of spiroperidol, 44, covalently labels a peptide of Mr

94,000 in rat striatal membranes, which has been suggested to be the D2

-

receptor (Amlaiky and Caron 1985). An azidomethyl-derivative of spiperone,

45, covalently labels a peptide of Mr 92,000 in canine striatal membranes,

although several minor lower molecular weight proteins also were labeled and

this agent had a much lower specific activity than 44 (Niznik et al. 1986).

Azidosulpride, 46, was used to photolabel D2

-receptors in rat striatal, anterior

pituitary, and olfactory bulb tissues (Redouane et al. 1985). The radiolabeled

receptors from the three tissues were concentrated in a single band at Mr

85,000, with low nonspecific incorporation (Redouane et al. 1985).

Azidohaloperidol, 47, selectively photolabels D2

-receptors in bovine striatum

and has been used to identify the photolabled D2-receptor binding subunit (Mr

94,000) by antibodies specific for haloperidol (Kanety and Fuchs 1988).

Selective tools for the identification of the D1-receptor protein more recently

have become available. After radioiodination of an amino-derivative of the D1

-

selective antagonist SCH 23390, 48 a radioactive probe that binds selectively

and with high affinity to D1-receptors resulted (Amlaiky et al. 1987). By

crosslinking 48 with the heterobifunctional reagent SANPAH, this compound

was covalently incorporated into a peptide of Mr 72,000, representing the D1-

receptor subtype (Amlaiky et al. 1987). A closely related azido-analog, 49, was

effectively used to photolabel D1-receptors in canine, bovine, and porcine

striatal membranes and covalently incorporated into a peptide with Mr 75,000,

as well as minor bands at Mr’s 62,000 and 51,000 (Baindur et al. 1988; Niznik

et al. 1988).

SEROTONIN RECEPTORS

Serotonin receptors have been identified in various areas of the brain and have

been classified into three major subtypes: 5-HT1, 5-HT2, and 5-HT3. These

subtypes have been further divided into subclassifications but, thus far,

irreversible ligands only have been developed for the 5-HT2

 and 5-HT1A

subtypes. The 5-HT2 site has been associated with the mediation of the

hallucinogenic action of phenylisopropylamine drugs, such as DOM (Glennon et

al. 1984; Glennon and Hauck 1985). The 6- and 7-azido derivatives 50 and 51,

respectively, of the 5-HT2 receptor selective antagonist ketanserin, have been

prepared as photoaffinity probes for these and the histamine receptors

268
(Wouters et al. 1985a, 1985b). Incorporation of an azido-moiety in either the 6-

or 7-position of ketanserin increased the affinity of both compounds for the

histamine receptors while retaining equal affinity for the 5-HT2

 receptors;

however, compound 51 photolabels both receptors, whereas 50 did not

(Wouters et al. 1985b). The 8-[125I]-analog of 51 was recently used to

photolabel a 73,000-dalton component of the monoamine transporter of bovine

chromaffin granule membranes (Isambert et al. 1989). The previously

described metaphit, 20, has also been reported to deplete 5-HT2 sites as well as

PCP binding sites (Nabeshima et al. 1989).

The bromoacetyl derivative of TFMPP, 52, was designed as a 5-HT1

 receptor

alkylating agent (Ransom et al. 1985). This compound distinguishes the same

two subpopulations of [

3H]5-HT binding sites as spiperone, in rat cortex, but

receptor alkylation was not achieved (Ransom et al. 1985). However, the paraazido derivative of TFMPP, 53, photolabeled a single class of sites in rat

hippocampal membranes with high affinity (Ransom et al. 1986). A polypeptide

of Mr 55,000 was irreversibly labeled with 53, which is suggested to be the 5-

HT1A receptor or a subunit thereof (Ransom et al. 1986). An electrophilic

chloroamino-derivative of the 5-HT1A selective agonist, 8-hydroxy-DPAT,

269
displayed irreversible but low-affinity binding to 5-HT1

 sites (Hamon et al. 1984;

Emerit et al. 1985). The arylazido-derivative of this agent, 54, displayed

selective, irreversible blockade of 5HT1A sites in rat hippocampal membranes,

in the nanomolar range (Emerit et al. 1986). Tritiated 54 photolabels a P1

protein in hippocampal microsomal membranes with Mr 63,000, which is

believed to be the 5-HT1A site (Emerit et al. 1987). A protein of similar

molecular weight also has been isolated from human hippocampus and frontal

cortex using photoaffinity labeling and immunoprecipitation techniques with the

azido-spiperone derivative, 49, previously described (Raymond et al. 1989).

SUMMARY

Electrophilic and photoactivated agents have proven to be useful as receptorselective irreversible probes. These compounds are generally derivatives of

selected ligands that may be chemically modified in such a way as to retain high

receptor affinity and selectivity while permitting covalent bonding to the receptor

protein. The receptor systems described in this chapter are associated with a

variety of classes of abused drugs. These irreversible agents are allowing the

isolation and purification of these drug receptors to improve our understanding

of their physiological and pharmacological properties and to aid us in better

design of agents with therapeutic value without abuse or physical dependence

liability. In the opioid field, ß-FNA and SUPERFIT have been successfully used

to elucidate structure and function of the μ-, -receptors, respectively.

Recently, the -subtype selective irreversible ligands naltrindol and

UPHIT have been introduced for receptor subtype studies that are designed to

further clarify the physiological function of these sites. The PCP recognition site

on the NMDA receptor complex and the sigma receptors have been

characterized in part by the use of irreversible agents. These receptors,

although sharing similar pharmacological properties, are clearly different

systems and the irreversible agents described will allow their further

270
characterization. The central-type benzodiazepine receptors have been labeled

with irreversible agents; and, now, receptor subsites that differentially recognize

ß-carbolines and benzodiazepines have been discovered through studies using

a ß-carboline photoaffinity probe. The associated chloride ionophore has been

studied with electrophilic irreversible ligands, as well as the pharmacologically

distinct peripheral-type benzodiazepine receptors. Physiological function of the

latter receptor system has been implicated through the photoaffinity ligand PK

14105, which is highly selective for these sites. Receptor subtype selective

irreversible ligands also have been prepared for both the dopamine and

serotonin receptors systems in hopes of clarifying their physiological roles in the

CNS.

It is clear that more selective irreversible compounds with higher affinity will

continue to be in demand for further receptor characterization. In addition,

radioligands with higher specific activity will continue to be important for

molecular weight determination of receptor proteins and autoradiographic

studies key to neuroanatomical localization of these sites.

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AUTHOR

Amy Hauck Newman, Ph.D.

Research Chemist

Department of Applied Biochemistry

Division of Biochemistry

Walter Reed Army Institute of Research

282
Senior Staff Fellow

Drug Development Group

Psychobiology Laboratory

Addiction Research Center

National Institute on Drug Abuse

P.O. Box 5180

Baltimore, MD 21224

283
Important Compounds in the Cocaine

Class: A Synthesis Overview

F.I. Carroll and Anita H. Lewin

INTRODUCTION

Previous reviews on tropane alkaloids have addressed the occurrence,

chemistry, and pharmacology of cocaine and its analogs (Lounasmaa 1988;

Clarke 1977; Fodor 1960; Holmes 1950). Another review was devoted solely to

the chemistry of cocaine and its derivatives (Archer and Hawks 1976). An

annotated bibliography of cocaine also has been published (Turner et al. 1988).

This chapter presents an overview of the synthesis of cocaine and some of the

more important cocaine derivatives and analogs that have been used for

biochemical, pharmacological, and analytical studies. The chapter is restricted

to compounds possessing the azabicyclo-[3•2•1]octane ring system, even

though there is interest, from a biological standpoint, in other structural types.

The chapter includes mass-labeled, radiolabeled, and nonlabeled compounds

(figure 1).

The Chemical Abstracts name for natural (-)-cocaine is methyl [1R-(exo,exo)]-3-

benzoyloxy-8-methyl-8-azabicyclo[3•2•1]octane-2-carboxylate; the 1R

designation refers to the configuration of the natural cocaine ring structure

following the convention of Cahn and colleagues (1966). For simplicity, the

more familiar traditional names are used in this review. However, all structures

derivable from the natural cocaine ring system are designated by an “R” prefix.

Thus, natural cocaine and its three possible stereoisomers are designated (R)-

cocaine (1), (R)-pseudococaine (2), (R)-allococaine (3), and (R)-

allopseudococaine (4). These isomers differ by the relative configurations of

the carbomethoxy and benzoyloxy substituents at C2 and C3, respectively, of

the azabicyclo[3•2•1]octane skeleton. There was some confusion in the early

literature with regard to the nomenclature of structures 3 and 4 (Findlay 1956;

Bainova et al. 1960). Specifically, structure 4 originally was named allococaine

and structure 3, identified subsequently, was named allopseudococaine

(Findlay 1956). The opposite nomenclature since has been proposed (Bainova

et al. 1960, 1964; Sinnema et al. 1968) and now is generally accepted. Table 1

helps to clarify this situation by listing the names and summarizing the

284
FIGURE 1. Important compounds in the cocaine class

285
FIGURE 1. Important compounds in the cocaine class (continued)

286
FIGURE 1. Important compounds in the cocaine class (continued)

stereochemical positions of the substituents in all eight cocaine isomers,

assuming a chairlike conformation for the piperidine ring portion of the

molecule. Thus, the prefix “pseudo” identifies equatorial carbomethoxy groups,

and the prefix “allo” means that the benzoyloxy group is axial. The converse is

true in the absence of a prefix.

COMPOUNDS PREPARED FROM (R)-COCAINE

Many of the (R)-cocaine analogs shown in figure 1 can be derived from

commercially available natural (R)-cocaine using the reactions outlined in figure

2. Hydrolysis of (R)-cocaine in 3N hydrochloric acid gives (R)-ecgonine (9) (Bell

and Archer 1960). Fisher esteriflcation of 9 using methanol and hydrochloric

acid yields (R)-ecgonine methyl ester (10). If cocaine is hydrolyzed in neutral

water, (R)-benzoylecgonine (11) is obtained (Findlay 1954). A modified

hydrolysis using a 1:1 dioxane:water mixture at 55 to 60°C gave a cleaner

reaction (unpublished work from the authors’ laboratory). Fisher esterification of

11 using ethanol and hydrochloric acid affords the ethyl ester analog of cocaine

12 (McCurdy 1980). The methiodlde 13 and N-oxide 14 of (R)-cocaine are

287
TABLE 1. Stereochemistry and nomenclature of the isomeric cocaines

Structure Position of Substituent Common Name

Carbomethoxy Benzoyloxy

1 (R)-Cocaine

2

Axial Equatorial

Equatorial Equatorial (R)-Pseudococaine

3 Axial Axial (R)-Allococaine

4

5 (S)-Cocaine

6

Equatorial Axial

Axial Equatorial

(R)-Allopseudococaine

Equatorial Equatorial (S)-Pseudococaine

7 Axial

8

Axial (S)-Allococaine

Equatorial Axial (S)-Allopseudococaine

prepared by treating (R)-cocaine with methyl iodide in the dark in acetone or

with m-chloroperoxybenzoic acid, respectively (Tessel et al. 1978; Misra et al.

1979).

Because the 2-carbomethoxy group in R-cocaine is in the less stable axial

orientation, subjection of (R)-cocaine to hydrolysis conditions using potassium

methoxide in anhydrous methanol gives (R)-pseudoecgonine methyl ester 15,

which has the 2-carbomethoxy group in the more stable equatorial position

(Findlay 1954). Benzoylation of 15 with benzoyl chloride in pyridine gives (R)-

pseudococaine (2) (Lewin et al. 1987).

The synthesis of several (R)-cocaine analogs starting with (R)-ecgonine methyl

ester (10) is shown in figure 3. Treatment of 10 with trans-cinnamoyl chloride in

pyridine gives the (R)-trans-cinnamoylcocaine 16, a cocaine analog that also is

found in the Erythroxylon coca plant (Turner et al. 1981). Acylation of 10 with pmethylbenzoyl chloride gives the cocaine analog 17, which has been referred to

as (R)-p-toluoylecgonine methyl ester, (R)-p-methylcocaine, or (R)-ptoluoylcocaine (Singh et al. 1979; Seyda and Chrupala 1986). Hydrolysis of 17

under conditions similar to those used for the preparation of 11 affords (R)-ptoluoylecgonine (18) (unpublished work from the authors’ laboratory). (R)-paminococaine (19) is prepared from 10 by acylation with p-nitrobenzoyl chloride

followed by catalytic reduction of the nitro function (Soffer and Schneider 1975).

Hydrolysis of 19 affords (R)-p-aminobenzoyl-ecgonine (20), which gives the

isothiocyanate derivative (21) on treatment with thiophosgene (Soffer and

Schneider 1975).

In addition to being a pyrolysis product of cocaine, anhydroecgonine methyl

ester (22) is a useful intermediate for the preparation of some important cocaine

analogs. These syntheses are outlined in figure 4. Treatment of (R)-ecgonine

with phosphorus oxychloride followed by methanol gives 22 (Clarke et al. 1973).

288
FIGURE 2. Syntheses starting from cocaine (14)

When 22 is treated with phenylmagnesium bromide in ether at -20°C a 1:3

mixture of (R)-WIN35,065-2 (23) and (R)-WIN35,140 (24) is obtained; these

compounds can be separated chromatographically. If p-flurophenylmagnesium

bromide is used in place of phenyimagnesium bromide, (R)-WIN35,428 (25)

and the -isomer 26 (Clarke et al. 1973) are obtained.

(R)-Norcocaine (27) has been prepared by several methods. The best method

(figure 5) involves treatment of (R)-cocaine (1) with 2,2,2-trichloroethyl

chloroformate to yield a carbamate that, when treated with zinc dust in acetic

acid, leads to the desired 27 (Baldwin et al. 1977; Borne et al. 1977).

Subjection of (R)-benzoylecgonine (11) and (R)-WIN35,065-2 (23) to a similar

sequence provides (R)-norbenzoylecgonine (28) and (R)-WIN35,981 (29),

289
FIGURE 3. Syntheses starting from ecgonine methyl ester (17)

290
FIGURE 4. Syntheses starting from ecgonine (9)

respectively (unpublished work from the authors’ laboratory). The latter also

has been prepared (Clarke et al. 1973) via the 2-chloroethylcarbamate

derivative of WIN35,065-2. Alkylation of 27-29 provides N-alkyl-N-nor

derivatives of (R)-cocaine, (R)-benzoylecgonine, and (R)-WIN35,065-2,

respectively. For example, alkylation of 27 and 29 with allyl bromide leads to

N-allyl-N-norcocaine (30) and the N-allyl derivatives of WIN35,065-2 (31),

respectively (Lazer et al. 1978; Kamien et al. 1989). The use of 27-29 for

preparing mass-labeled and radiolabeled derivatives is addressed in a later

section.

COMPOUNDS PREPARED FROM 3-TROPINONE

The facile condensation of 3-tropinone (32) with dimethyl carbonate using

sodium hydride as the base (figure 6) to yield 2-carbomethoxy-3-tropinone

(RS)-33 (Carroll et al. 1982) makes 32 a useful starting point for several of the

compounds shown in figure 1. The first synthesis of (RS)-33, reported by

Wilstatter and colleagues (1923), involved the condensation of acetonedicarboxylic acid monomethyl ester, methylamine, and succindialdehyde.

Several improvements of this synthesis have been reported, the latest by

Casale (1987). Resolution of (RS)-33 using (+)- and (-)-tartaric acid provides

(R)-2-carbomethoxy-3-tropinone [(R)-33] and (S)-2-carbomethoxy-3-tropinone

[(S)-33] (Findlay 1957; Clarke et al. 1973; Casale 1987). Sodium borohydride

291
FIGURE 5. Synthesis of N-norcocaine (27) and N-norcocaine-derived

compounds

reduction of (R)-33 in methanol at -20°C (as described for (RS)-33 in Carroll et al.

1982) provides (R)-allopseudoecgonine methyl ester (34), which on benzoylation

gives (R)-allopseudococaine (4) (unpublished work from the authors’ laboratory).

When 34 is heated in water, isomerization at the 2-position takes place along

with hydrolysis to give (R)-alloecgonine (35) (Sinnema et al. 1968). Fisher

esterification of 35 using methanol and hydrogen chloride gives (R)-alloecgonine

methyl ester (37), which is benzoylated to give (R)-allococaine (3).

(S)-cocaine was first prepared by reduction of (RS)-33 with sodium amalgam to

a mixture of (RS)-ecgonine methyl ester and (RS)-pseudoecgonine methyl

292
FIGURE 8. Synthesis of analogs in the alloseries and allopseudoseries

ester. The latter, being less soluble, was separated by crystallization: the

mother liquor yielded (RS)-ecgonine methyl ester, which was benzoylated to

give (RS)-cocaine. Resolution via the bitartrate salt gave (S)-cocaine (5)

(Wilstatter et al. 1923). A more practical synthesis of (S)-cocaine (5) starts with

(S)-33 and incorporates several reported improvements to the Wilstatter

synthesis (Lewin et al. 1987). The improved synthesis of (S)-cocaine (5) as well

as the synthesis of other (S)-cocaine isomers is outlined in figure 7. Reduction

of (S)-33 with sodium amalgam provided (S)-ecgonine methyl ester (37) and

(S)-pseudoecgonine methyl ester (38), which were separated by

chromatography and benzoylated with benzoyl chloride in pyridine to give (S)-

cocaine (5) and (S)-pseudococaine (6), respectively (Lewin et al. 1987). (S)-

Allococaine (7) and (S)-allopseudococaine (8) were prepared via intermediates

39-41 by procedures exactly analogous to those described for the (R)-isomer

(unpublished work from the authors’ laboratory).

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FIGURE 7. Synthesis of (S)-cocaine and analogs

Tufariello and coworkers (1979) reported an interesting multistep synthesis of

(RS)-cocaine that involved the preparation of hexahydropyrrolo[1,2-b]

isoxazole (42) as a key intermediate. When 42 was refluxed in xylene, methyl

acrylate was expelled; the resulting nitrone spontaneously cyclized to 43.

Methylation of 43 with methyl iodide gave the methiodide 44 that on treatment

with activated zinc in aqueous acetic acid provided, stereo-specifically, (RS)-

ecgonine methyl ester that could be benzoylated to afford (RS)-cocaine (figure

8).

294
FIGURE 8. Intermediates in the Tufariello and colleagues (1979) synthesis

ISOTOPICALLY LABELED COMPOUNDS

The preparation of isotopically labeled cocaine and derivatives has been

reviewed (Archer and Hawks 1976). Compounds prepared since then fall into

three categories: (1) N-methyl-labeled, (2) benzoyloxy-labeled, and (3) ringlabeled. The preparation of the isotopically labeled compounds in figure 1 uses

the synthetic intermediates and route described above.

N-Methyl-Labeled Compounds

Cocaine deuterated or tritiated in the N-methyl moiety (N-CD3-1 and N-CT3-1,

respectively) is obtained on treatment of N-norcocaine (27) (figure 5) with

labeled iodomethane in the presence of potassium carbonate. Although such

alkylation reactions usually are carried out in polar media, such as

dimethylformamide and with excess alkylating agent, this alkylation can be

performed successfully in toluene (the solvent in which high specific activity

tritiated iodomethane is supplied) and with excess substrate (unpublished work

from the authors’ laboratory). The analogously labeled WIN compound N-CT3

-

23 is prepared similarly from the N-nor compound 29 (Naseree et al., in press).

Saponification of the carbomethoxy group of N-CD3-1 under mild conditions

affords N-CD3

 benzoylecgonine (N-CP3-11) (unpublished work from the authors’

laboratory).

Benroyloxy-Labeled Compounds

Benzoylation of ecgonine methyl ester (10) with labeled benzoyl chloride in

excess pyridine affords the cocaines labeled in the benzoyl moiety, C6D5-1 and

Ph14C-1 (unpublished work from the authors’ laboratory). The required 14Cbenzoyl chloride is prepared by carbonation of phenylmagnesium bromide using

14C-barium carbonate as the source for 14C-carbon dioxide followed by

treatment of the isolated 14C-benzoic acid with excess oxalyl chloride

(unpublished work from the authors’ laboratory). Dilution of Ph14C-1 with

295
FIGURE 9. Synthesis of [4-3H]-2carbomethoxy-3-tropinone[4-T-(R)-33]

unlabeled 1 gives specific activity 5 mCi/mmol, suitable for autoradiography.

Mild saponification of the deuterated cocaine C6D5-1 gives pentadeutero

benzoylecgonine (C6D5-11).

Ring-Labeled Compounds

Synthesis of cocaine with an isotopic label at the nonlabile, nonexchangeable

4-position of the backbone makes use of 2-carbomethoxy-3-tropinone [(R)-33],

a key intermediate in the total synthesis of cocaine. The label is introduced at

the 4-position by quenching of the dianion 45. (figure 9), obtained by treatment

of (R)-33 with a single equivalent of sodium hydride followed by less than an

equivalent of n-butyl lithium, with tritium oxide. Processing the labeled 2-

carbomethoxy-3-tropinone 4-T-(R)-33, as described for the synthesis of (S)-

cocaine (5) (figure 7), affords 4-T-1 (Lewin et al. 1983). Use of 0.17

equivalents of tritium oxide gives 4-T-1 with specific activity 3.2 Ci/mmol.

REFERENCES

Archer, S., and Hawks, R.L. The chemistry of cocaine and its derivatives. In:

Mule, S.J., ed. Cocaine: Chemical, Biological, Clinical, Social, and

Treatment Aspect. Cleveland: CRC Press, 1976. pp. 15-32.

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Bainova, M.S.; Bazilevskaya, G.I.; Miroschnichenko, L.D.; and Preobrazhenskii,

N.A. Conformational study in the cocaine series. Dokl Akad Nauk SSSR

157:599-602, 1964.

Bainova, M.S.; Bazilevskaya, G.I.; and Preobrazhenskii, N.A. Preparation of

the racemic stereoisomeric alkaloids, cocaine, pseudococaine, allococaine,

and allopseudococaine. Zh Obshch Khim 30:3258-3261, 1960.

Baldwin, S.W.; Jeffs, P.W.; and Natarajan, S. Preparation of noroocaine. Syn

Commun 7:79-84, 1977.

Bell, M.R., and Archer, S. L(+)-2-tropinone. J Am Chem Soc 82:4642-4644,

1960.

Borne, R.F.; Bedford, J.A.; Buelke, J.L.; Craig, C.B.; Hardin, T.C.; Kibbe, A.H.;

and Wilson, M.C. Biological effects of cocaine derivatives. I: Improved

synthesis and pharmacological evaluation of norcocaine. J Pharm Sci

66:119-120, 1977.

Cahn, R.S.; Ingold, C.; and Prelog, V. Specification of molecular chirality.

Angew Chem Int Ed Engl 5:385-410, 1966.

Carroll, F.I.; Coleman, M.L.; and Lewin, A.H. Synthesis and conformational

analysis of isomeric cocaines: A proton and carbon-13 nuclear magnetic

resonance study. J Org Chem 47:13-19, 1982.

Casale, J.F. A practical total synthesis of cocaine’s enantiomers. Foren Sci Int

33:275-298, 1987.

Clarke, R.L. The tropane alkaloids. In: Manske, R.H.F., ed. The Alkaloids.

Vol. 16. New York: Academic Press, 1977. pp. 83-180.

Clarke, R.L.; Daum, S.J.; Gambino, A.J.; Aceto, M.D.; Pearl, J.; Levitt, M.;

Cumiskey, W.T.; and Bogado, E.F. Compounds affinity. The central nervous

system. 4. 3ß-phenyltropane-2-carboxylic esters and analogs. J Med Chem

16:1260-1267, 1973.

Findlay, S.P. The three-dimensional structure of the cocaines. Part I. Cocaine

and pseudococaine. J Am Chem Soc 76:2855-2862, 1954.

Findiay, S.P. The synthesis of racemic allococaine and racemic

aiiopseudococaine. J Org Chem 21:711, 1956.

Findiay, S.P. Concerning 2-carbomethoxytropinone. J Org Chem 22:1385-

1394, 1957.

Fodor, G. The tropane alkaloids. In: Manske, R.H.F., ed. The Alkaloids. Vol.

6. New York: Academic Press, 1960. pp. 145-177.

Holmes, H.L. The chemistry of the tropane alkaloids. In: Manske, R.H.F., ed.

The Alkaloids. Vol. 1. New York: Academic Press, 1950. pp. 271-374.

Kamien, J.B.; Madras, B.K.; Fahey, M.A.; Milius, R.A.; Saha, J.K.; Neumeyer,

J.L.; and Speaiman, R.D. Methyl 3ß-(4-fluorophenyl)-N-allyl-nortropane-2ßsigns-carboxyiate, a novel high affinity ligand for cocaine recognition sites.

Fed Proced Abstr 407, 1989. p. 18.

Lazer, E.S.; Aggarwal, N.D.; Hite, G.J.; Nieforth, K.A.; Kelleher, R.T.;

Spealman, R.D.; Schuster, C.R.; and Wolverton, W. Synthesis and biological

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activity of cocaine analogs. I: N-alkylated norcocaine derivatives. J Pharm

Sci 67:1656-1658, 1978.

Lewin, A.H.; Clanton, R.P.; and Pitt, C.G. Synthesis of high specific activity

ring-labeled cocaine. In: Duncan, W.P., and Susan, A.B., ed. Synthesis and

Applications of Isotopically Labeled Compounds, Proceedings of an

International Symposium. Amsterdam: Elsevier Scientific Publishers, 1983.

pp. 421-422.

Lewin, A.H.; Naseree, T.; and Carroll, F.I. A practical synthesis of (+)- cocaine.

J Heterocycl Chem 24:19-21, 1987.

Lounasmaa, M. The tropane alkaloids. in: Brossi, A., ed. The Alkaloids. Vol.

33. New York: Academic Press, 1988. pp. 2-81.

McCurdy, H.H. Quantitation of cocaine and benzoylecgonine after JETUBE-Tm

Extraction and Derivatization. J Anal Toxicol 4:82-85, 1980.

Misra, A.L.; Pontani, R.B.; and Vadlamani, N.L. Metabolism of norcocaine, Nhydroxynorcocaine and cocaine-N-oxide in the rat. Xenobiotica 9(3):189-

199, 1979.

Naseree, T.M.; Abraham, P.; Kepler, J.A.; Carroll, F.I.; Lewin, A.H.; and Kuhar,

M.J. Synthesis of [

3H]WIN 35,065-2: A new ligand for cocaine receptors.

J Label Comp Radiopharm 28(9):1011-1016, 1990.

Seyda, K., and Chrupala, W. Substituent effects on some properties of

cocaine. Pol J Chem 60:505-513, 1986.

Singh, S.P.; Kaufman, D.; and Stenberg, V.I. Nitrogen photochemistry.

Cocaine and its model compounds. J Heterocycl Chem 16:625-631, 1979.

Sinnema, A.; Maat, L.; Van der Gugten, A.J.; and Breyerman, H.C.

Configuration and conformation of all four cocaines from NMR spectra.

Recveil de Travoux Chimique Pays-Bas 87:1027-1041, 1968.

Soffer, M.J., and Schneider, R.S. lsothiocyanate and thiourea derivatives of

benzoylecgonine conjugated to polypeptides. Chem Abstr 84(13):85374g,

1975.

Tessel, R.E.; Smith, C.B.; Russ, D.N.; and Hough, B.L. The effects of cocaine

HCI and a quaternary derivative of cocaine, cocaine methiodide, on isolated

guinea-pig and rat atria. J Pharmacol Exp Ther 105(3):568-576, 1978.

Tufariello, J.J.; Mullen, G.B.; Tegeler, J.J.; Trybuiski, E.J.; Wong, S.C.; and Ali,

Sk.A. Synthesis in the tropane class of alkaloids. Pseudo-tropine and dlcocaine. J Am Chem Soc 101:2435-2442, 1979.

Turner, C.E.; Ma, C.Y.; and Elsohly, M.A. Constituents of Erythroxylon coca. II.

Gas-chromatographic analysis of cocaines and other alkaloids in coca

leaves. J Ethnopharmacol 3:293-298, 1981.

Turner, C.E.; Urbanek, B.S.; Wall, G.M.; and Walker, C.W. Cocaine, an

Annotated Bibliography. Jackson, MS: Research Institute of Pharmaceutical

Sciences, University Press of Mississippi, 1988.

Wilstatter, R.; Wolfes, O.; and Mader, H. Synthese des naturlichen cocains.

Annal en der Chemie 434:111-139, 1923.

298
AUTHORS

F.I. Carroll, Ph.D.

Director

Organic and Medicinal Chemistry

Anita H. Lewin, Ph.D.

Senior Research Chemist

Research Triangle Institute

P.O. Box 12194

Research Triangle Park, NC 27709

299
lmmunomodulatory Effects of Drugs

of Abuse and the Importance of

Structure-lmmunomodulatory

Activity Studies

Rae S. Rapaka and Charles P. Holberg

The discovery of endogenous ligands for the opioid receptors (Hughes et al.

1976) and the demonstration of receptors on the surface of the cells of the

immune system generated an explosive interest in the role of opioid peptides

and neuropeptides in the regulation of the immune system. Because of the

acquired immunodeficiency syndrome (AIDS) epidemic, interest in the effects of

drugs of abuse has increased recently. Even in the absence of AIDS,

understanding the mechanisms of modulation of the immune system by

neuropeptides, opioid peptides, and drugs of abuse is an important topic (Kind

1988). Clearly, a compromised immune system predisposes the individual to

infectious diseases and complicates treatment procedures considerably.

Treatment of addictive disorders usually involves long-term treatment; hence, it

is imperative that their effects on the immune system be understood. If new

medications are developed, it is conceivable that the new compounds will be

structurally related to the drugs of abuse and may be immunologically active. It

is particularly important to avoid using immunosuppressive drugs in a patient

population that is already immunocompromised. Hence, the immunomodulatory

effects of new drugs must be investigated before embarking on extensive

studies for the drug approval process. Immune effects of new treatment drugs

must be determined; the chemical classes of drugs of abuse to be investigated

include neuropeptides, opiates, opioid peptides, marijuana and cannabinoids,

phencyclidine and its analogs, cocaine and its analogs, and inhalants.

There are several studies on the use of opiates in animals, particularly

morphine (Fuchs et al. 1987; Louria et al. 1967; for reviews, see Donahoe

1988; Kreek 1988; Pham and Rice 1990; Weber 1988; Yahya and Watson

1987). Chronic administration of morphine to mice depressed the

responsiveness of lymphocytes to concanavalin A (Con A) stimulation when

compared to lymphocytes of nonaddicted mice; this suppressive effect was

300
somewhat reversible if naloxone was coadministered with morphine. Morphine

administration to mice resulted in an enhanced susceptibility to bacterial and

fungal infections; this increased susceptibility was due to a decrease in

reticuloendothelial system activity and a reduction in the number of phagocytes.

Morphine administration reduces the capacity to produce superoxide anion (a

parameter to measure macrophage activation), primary antibody response to

sheep red blood cell (SRBC), and the ratio of spleen to body weight. Some of

the above effects were again naloxone-reversible, suggesting these effects may

be mediated via the opiate receptor. Morphine also was shown to reduce

natural killer (NK) activity, lymphoid organ weight, and mitogenic response to

Con A and interferon titers. In rats chronically treated with morphine, cellmediated immunity (CMI) is altered, as evidenced by the animals’ inability to

produce a tuberculin reaction and a lowered ability to produce an inflammatory

response to carrageenan.

Studies by Tubaro and colleagues (1983, 1985) showed a severe depression of

phagocytosis, NK cell activity, and superoxide anion generation in opiate

addicts. McDonough and coworkers (1980) reported a decrease in absolute

number of T lymphocytes in the peripheral blood of opiate addicts as measured

by the ability to form rosettes with SRBC. Naloxone was able to reverse some

of the above effects. Heroin produced similar immunosuppressive effects to

morphine. Nair and coworkers (1986) and others (Novick et al. 1986; for

reviews, see Donahoe 1988; Weber 1988) reported that NK cell activity is

significantly reduced in street heroin addicts. Medical status of heroin addicts

entering clinics was studied by Kreek (1988), whose observations included

absolute lymphocytosis and elevated serum levels of IgM and IgG. Brown and

coworkers (1974) observed abnormalities in T-cell rosette formation and

diminished response to mitogens. Several investigators (for a review, see

Morley et al. 1987) reported that in heroin addicts the ratio of T-helper to Tsuppressor cells was depressed. Evidently, the depressed immune function by

the opiates makes the animals more susceptible to bacterial and fungal

infections. Several other studies supported the above results. Thus, most of

the human studies indicate the immunosuppressive action of opiates.

A few other opiates also were studied. Neither (+) nor (-) naloxone have

significant effect on NK cell activity (Ochshorn et al. 1988a). Similarly, (+) and

(-) methadone do not appear to have any significant effect on NK activity

(Ochshorn et al. 1988b); however, at higher doses a significant reduction of NK

cell activity was observed (Kreek 1990).

At present, a preferred treatment modality for opiate addicts is treatment with

methadone. Brown and coworkers (1974) evaluated heroin addicts entering

clinics and found elevated levels of IgM and IgG. After methadone

maintenance treatment, these abnormalities lessened. Cushman and Grieco

301
(1973), Cushman and coworkers (1977), and several other groups (Kreek 1988;

for reviews and references, see Pham and Rice 1990) showed that abnormal T

rosetting found in most heroin addicts decreased with time following methadone

treatment. Methadone treatment still is not the ideal mode of treatment due to

some of its immunomodulatory effects. Donahoe (1988) and other groups

(Kreek 1988) reported that the effects of methadone may be dose-dependent

and that immunoenhancing effects predominate in the low doses of methadone

used for treatment. Thus, new and more efficient treatment modalities are

needed not only for the treatment of opiate addiction, but also for problems

arising out of usage of other drugs of abuse.

Wybran and coworkers (1979) were the first to provide evidence for the

presence of receptors specific for morphine on normal human T lymphocytes,

and this observation was confirmed by several other investigators.

Opioid receptors later were demonstrated to be present on human

polymorphonucleocytes and monocytes and platelets (for a review, see

Sibinga and Goldstein 1988). Presently, receptors have been shown to be

present on the cells of the immune system for opiates, opioid peptides,

phencyclidine, benzodiazepine, and dopamine. Another exciting development

in this area is the report by Donahoe (1990) suggesting that opiates modulate

the expression of HIV-1 viroreceptor, the CD4 molecule. The presence of

receptors for chemical agents on the immune cells presents possibilities for

modulation of specific immune function by exogenousiy administered drugs.

However, a factor that complicates the in vivo studies is the necessity to

discriminate carefully the observed effects as either direct or indirect. The

situation is made even more complex because opioid peptides are involved with

the modulation of the immune system via the autonomic nervous system and

the endocrine system, as well as within the central nervous system.

Several reports from animal studies indicate that opioid peptides enhance the

immune function (for a review, see Morley et al. 1987). Several investigators

reported that beta-endorphin-enhanced NK activity in in vitro and in vivo studies

(Faith et al. 1984; Mathews et al. 1983). Other studies in animals have shown

that opiates are involved with the modulation of tumor growth. Beta-endorphin

potentiates Con A and phytohemagglutinin-induced proliferation of T

lymphocytes but had no effect on the response to the B-cell mitogen

lipopolysaccharide/dextran sulfate (Gilman et al. 1982). On the other hand,

McCain and coworkers (1982) reported the beta-endorphin is a potent

suppressor of phytohemagglutinin-induced blastogenesis in cultured human T

cells. The effect of beta-endorphin on the lymphocyte function appears to be

due to the fragment beta-endorphin 10-16 peptide fragment. Studies by Kay

and colleagues (1987) indicate that the ability of the endorphins to stimulate NK

302
cell activity resides in 6-9 sequence peptide fragment, which is part of the

helical portion. It is further speculated that the alpha-helical portion is involved

in the interaction with the receptor. Beta-endorphin enhances in vitro antibody

production, NK function, and mitogenesis, while alpha-endorphin, which is a

slightly modified analog, is a potent suppressor of in vitro antibody response.

Recently, Shah and coworkers (1989) reported on the conformational features

for interaction at the viroreceptor. Beta-bend conformations of several

tetrapeptides related to peptide T were correlated with their activities in CD4-

receptor binding assays. It is to be especially noted that enkephalins (for

reviews, see Schiller 1984; Rapaka et al. 1986) and dermorphins were shown to

exist with beta-turn conformations. It may be speculated that the therapeutic

effects of enkephalins in general and Met-enkephalin in particular may be due

to beta-bend conformation that might serve as a conformational recognition site

for interaction with the CD4 receptor. Research into the conformational analysis

only has begun in these peptides, and it is unfortunate that extensive and

systematic structure-immunological activity studies have not been undertaken

by any research group. Only a few studies have been conducted to date on

some of the opioid peptides, and these studies are inadequate to formulate any

meaningful structure-activity correlations. Several other studies (Kay et al.

1984; Faith et al. 1984; Mathews et al. 1983; Morley et al. 1987) reported that

endogenousopioid peptides are immunoenhancers and Met-enkephalin and

beta-endorphin enhance NK cell activity. Several investigators also have

reported that opioids are mildly chemotactic. Mandler and coworkers (1986) and

Brown (1986) reported that beta-endorphin and Met-enkephalin augment

interferon production. It also was reported that beta-endorphin modulates the

expression of cell surface antigens. Miller and colleagues (1984) showed that

beta-endorphin enhances the expression of HLA-DR antigen in mononuclear

cells and reduces expression of T3 and T4 antigen in T lymphocyte.

The subtle differences in structure resulting in alteration of immunomodulatory

properties merit further investigation because several such observations cannot

yet be explained on structure-activity relationships (SAR) alone. Metenkephalin increased the percentage of active T-cell rosettes formed by

lymphocytes, an effect that is naloxone reversible, whereas the other naturally

occurring analog, Leu-enkephalin, lacks the rosette-forming activity. Betaendorphin and another opioid peptide, dynorphin, stimulate superoxide radical

formation (Sharp et al. 1985), and this effect probably is not mediated through

the opioid receptor. Met-enkephaiin and Leu-enkephalin significantly increase

NK cell activity in isolated human peripheral blood lymphocytes, and Metenkephalin and beta-endorphin enhance interferon production. An interesting

report by Sinha and coworkers (1988) indicates that immunologically active

components of IMREG-1 (a low molecular weight subfraction derived from

human leukocyte dialysate) are Tyr-Gly and Tyr-Gly-Gly. As these sequences

303
are present in enkephalins and endorphins, they may function as molecular

links between the neuroendocrine and immune systems. Note especially that

Tyr-Gly and Tyr-Gly-Gly are metabolites of enkephalins and are devoid of

analgesic activity; however, they are active immunologically. Thus, there are

only a few observations reported on the SAR of these compounds.

Due to the immunoenhanclng properties of Met-enkephalin, this peptide was

tried clinically. Met-enkephalin appears to enhance the immunostatus of the

patients with AIDS and AIDS-related complex (Wybran et al. 1987; Bhargava

1990). In Met-enkephalin-treated patients, there was a significant increase in

the absolute number of blood CD3 and CD4 lymphocytes without an increase in

the absolute number of lymphocytes and a significant increase in NK cell

activity, interleukin production, and the phytohemagglutinin response. Although

these are only preliminary studies, they provide optimism on the potential use of

this compound or its analogs in future and encourage SAR studies and rational

drug design.

There are significant differences between the opiates and the opioid peptides in

their immunomodulatory properties. For example, morphine depresses Erosette formation, whereas beta-endorphin and Met-enkephalin enhance it.

Morphine decreases superoxide formation, whereas Met-enkephalin and

dynorphin increase the formation. Opiates, in general, appear to be

suppressive, whereas opioid peptides are immunoenhancers. These

contrasting effects are not particularly discouraging because they pave the way

for extensive SAR studies to enable medicinal chemists to design new

immunoenhancing drugs.

lmmunomodulatory effects of marijuana were reviewed recently by Yahya and

Watson (1987). Due to the widespread abuse of marijuana, several

investigators focused their attention on the effects of marijuana on cardiac,

psychomotor, genetic, and immune functions. Most studies on the immune

function were performed with delta-9-tetrahydrocannabinol (THC), the major

psychoactive ingredient of marijuana. THC exhibits a wide spectrum of effects

in human and animal studies. Studies in animals revealed the

immunosuppressive effects of THC in such parameters as phagocytic function,

interferon production, and NK cell activity. Several investigators (Petersen et al.

1975; Lefkowitz and Chiang 1975; Zimmerman et al. 1977; Smith et al. 1978;

Yahya and Watson 1987) have demonstrated the in vivo immunosuppressive

effects of THC on humoral immune response of animals by such measurements

as plaque-forming cells in spleen and hemagglutinin titers after THC

administration.

304
In in vitro tests, THC was shown to produce a depressive response of mouse

splenocytes against SRBC and reduced blastogenic response of splenic

lymphocytes to E. coli lipopolysaccharide or pokeweed mitogen, and THC was

shown to reduce CMI in animals. The immunosuppressive effects of THC on

CMI were shown by in vitro and in vivo tests; the parameters investigated

included delayed-type hypersensitivity to SRBC, rosette-forming T-cell

numbers, blastogenic responses of lymphocytes to phytohemaggiutinin and

Con A, skin graft survival, mixed lymphocyte reaction, and migration inhibition

factor activity.

All these studies demonstrated the immunosuppressive effects of THC in

animals and showed that animals exposed to THC were more susceptible to

infections, both viral and bacterial.

The immunosuppressive effects of THC in humans are less convincing. Some

of the effects attributed to marijuana or THC (Armand et al. 1974; Gupta et al.

1974; Petersen et al. 1976; Schwartzfarb et al. 1974; Nahas et al. 1979;

Specter et al. 1986) include reduced serum IgG levels in chronic smokers,

inhibition of NK cell activity, phagocytic activity, and reduced T-cell numbers

and leucocyte migration. Studies from marijuana smokers showed that

response of the cells to PHA stimulation was depressed, and lymphocytes

isolated from marijuana smokers contained a reduced number of rosette

forming T lymphocytes. However, several other investigators have reported

that neither THC nor marijuana smoke are immunosuppressive, and only future

research might be able to clarify these inconsistencies.

Effects of cocaine and its analogs on the immune function were investigated by

a few investigators (Crary et al. 1983; Van Dyke et al. 1986; Harvas et al. 1987).

Crary and colleagues (1983) found that cocaine rapidly increases NK cell

activity in humans, and it was suggested that this effect might be due to an

increase in the number of circulating cells. The increase in NK cell activity after

in vivo administration probably is not due to metabolism of cocaine, because

benzylecgonine, a major cocaine metabolite, had no effect on NK cell numbers

or activity. It also is suggested that the in vivo effect of cocaine on NK cell

activity may be due to its ability to stimulate the release of catechoiamine Into

the bloodstream and to diminish the reuptake of norepinephrine by the

sympathetic nervous system.

Welch (1983) investigated the effect of cocaine on nonspecific human cellular

host defenses such as the oxidative microbicidal activity of polymorphonuclear

leukocytes and lymphocyte NK activity. Welch found that such activities were

found only at high concentrations (500 times those found in the blood of

cocaine users).

305
Harvas and coworkers (1987) studied the effect of cocaine on three parameters

of immune response: antibody production, resistance to infection, and

resistance to tumors. Their studies revealed that at low doses cocaine showed

no effect; in fact, at high doses it enhanced some immune responses. Finally,

note that opiates and some of the other drugs of abuse such as cocaine and

alcohol have a common ability to modulate surface molecules on T cells. With

opiates the effects are presumably mediated through receptor-ligand

interaction, whether it is the T cell acting directly with the opiate or some

hormonal product resulting from other systemic and centrally mediated points of

opiate-receptor stimulation. With cocaine, a key effect may relate to its

anesthetic properties of Na channel blockade that could alter surface-receptor

expression within the network in various ways (Donahoe et al. 1986; Donahoe

1990).

Few studies have been done on phencyclidine (PCP) or its analogs. PCP was

shown to interact with the cells of the immune system and cause suppression of

lymphocyte DNA synthesis in vitro, and PCP receptor sites were shown to be

present on membranes of lymphoid cells (Khansari and Whitten 1988; Singh

and Fudenberg 1988).

Histories from AIDS patients revealed a relatively high use of amyl and butyl

nitrites by inhalation (Marmor et al. 1982; for a review, see Haverkos and

Dougherty 1988). An evaluation of the immune status of the individuals would

be helpful to understand the effects of the inhalants on the immune system, if

any.

Laboratory results have shown various conflicting reports. For example, the

literature on the direct effects of opioids on NK activity is full of conflicting and

sometimes contradicting reports. This is also the case with several

immunochemical studies with opioids. For example, different reports suggest

that peptide ligands may enhance NK activity, have no effect on NK activity, or

may decrease NK activity. Opposite effects of opiates on immune function have

been observed among species, as well as varied responses between strains of

the same species.

There are obvious differences in the susceptibility of humans and animals to the

immunomodulatory effects of marijuana and THC. Animal studies clearly

demonstrate immunosuppressive effects, whereas in humans the effects are

less clear. These inconclusive results may be due to fewer studies conducted

and problems associated with dose.

The conflicting data also indicate how various parameters such as sex, stress,

hormonal balance, nutritional status, age, length of exposure to the drug,

306
species variation, and use of other drugs may influence the results. Although

on the surface these apparent complexities seem discouraging, the recognition

of the key variables involved in the mechanisms by which drugs of abuse

modulate immunological activity will help researchers to understand and

manipulate the immune system. It is anticipated that rational drug design

ultimately will yield potential therapeutic agents.

REFERENCES

Armand, J.P.; Hsu, J.T.; and Nahas, G.G. Inhibition of blastogenesis of T

lymphocytes by delta-9-THC. Fed Proc 33:539, 1974.

Bhargava, H.N. Opioid peptides, receptors, and Immune function. In: Pham,

P.T.K., and Rice, K., eds. Drugs of Abuse: Chemistry, Pharmacology,

Immunology, and AIDS. National institute on Drug Abuse Research

Monograph 96. DHHS Pub. No. (ADM)90-1676. Washington, DC: Supt. of

Docs., U.S. Govt. Print. Off., 1990. pp. 220-233.

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ACKNOWLEDGMENT

The authors wish to acknowledge Rani S. Rapaka for editorial assistance and

helpful discussions in the preparation of the manuscript.

AUTHORS

Rao S. Rapaka, Ph.D.

Medications Development Division

National Institute on Drug Abuse

Room 11A-55

5600 Fishers Lane

Rockville, MD 20857

Charles P. Hoiberg, Ph.D.

Supervisory Chemist

Center for Drug Research and Evaluation

Office of Drug Evaluation I

Division of Oncology and Pulmonary Drug Practice

Food and Drug Administration

HFD-150

5600 Fishers Lane

Rockville, MD 20857

312
FDA Regulatory Requirements for

Investigational New Drugs and New

Drug Applications: An Update

Charles P. Holberg and Rao S. Rapaka

INTRODUCTION

Since our previous article was published in the National Institute on Drug Abuse

Research Monograph Series (Hoiberg and Rapaka 1986), several significant

regulations have been promulgated by the Food and Drug Administration (FDA)

concerning the regulatory requirements for human drug products. This chapter

addresses these changes as they pertain to the requirements for the

submission of investigational new drug applications (INDs) and new drug

applications (NDAs). Other regulatory topics include orphan drug products, the

Center for Drug Evaluation and Research (CDER) guidelines, environmental

assessments, and two innovative procedures that have been implemented to

facilitate and improve the review process (i.e., computer-assisted new drug

applications [CANDA] and “NDA Days”).

INVESTIGATIONAL NEW DRUG APPLICATIONS

In the 1987 article only the proposed revisions to the IND Rewrite regulations

were discussed in detail. Since then, the following major rules or proposals

have been published pertaining to the IND process: (1) the final rule for the IND

Rewrite, (2) the treatment IND program, (3) subpart E of the IND provisions,

and (4) the proposed parallel track protocols. Together, these revisions have

altered or will alter significantly the development of investigational new drugs,

particularly those administered to patients with serious or life-threatening

diseases.

IND Rewrite

The final rule that revised the regulations governing the submission and review

of INDs was published in the Federal Register (52 FR 87988) on March 19,

1987. The intent of these new regulations, called the “IND Rewrite,” was to

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facilitate the development of new beneficial drug therapies while ensuring the

ability of FDA to monitor carefully the safety of patients participating in clinical

investigations. The objectives of the IND Rewrite were to focus FDA’s attention

on protecting the safety of human test subjects during the early phase of clinical

research and to give sponsors greater freedom to design, revise, and

implement clinical research studies. IND sponsors now are encouraged to

consult with FDA before submitting an IND to help ensure that the design of the

major clinical trials will be acceptable. Conferences are suggested at the “endof-Phase 2” and at the “pre-NDA” stage to facilitate dialog between the sponsor

and FDA personnel to expedite NDA approval. As with the “NDA Rewrite,” the

use of the CDER guidelines is encouraged to provide sponsors with assistance

in implementing the “IND Rewrite.”

The regulatory requirements for an IND are codified in the IND Rewrite under

part 312 of title 21 of the Code of Federal Regulations (CFR). The regulations

state that an IND must be filed for all drug products used in clinical investigation

that are subject to sections 505 and 507 of the Federal Food, Drug, and

Cosmetic (FD&C) Act. Exemptions to these filing requirements now are

permitted under 21 CFR 312.2(b), for example, when (1) the investigation of a

lawfully U.S.-marketed drug product is not intended to be reported to FDA as a

well-controlled study in support of a new indication for use nor is intended to be

used to support any other significant change in the labeling of the drug; (2) the

investigation does not involve a route of administration or dosage level or use in

a patient population or other factor that significantly increases the risk (or

decreases the acceptability of the risks) associated with the use of the drug

product; and (3) the investigation is conducted in compliance with the

requirements for institutional review set forth in 21 CFR 56 and with the

requirements for informed consent set forth in 21 CFR 50.

If the exemptions do not apply, the sponsor must file an IND with the agency

stating his or her intentions to conduct a clinical investigation with a specified

drug product. The investigation of this new drug may commence 30 days [21

CFR 312.40(b)(1)] after the FDA receives an IND, unless the sponsor has been

notified by FDA that the IND has been placed on clinical hold. Grounds for a

clinical hold are described in 21 CFR 312.42. Examples of a basis for a clinical

hold are as follows: (1) The human subjects are or would be exposed to an

unreasonable and significant risk of illness or injury and (2) the application does

not contain sufficient information required under 21 CFR 312.23 to assess the

risks to subjects in the proposed studies. The IND Rewrite also provided for

clinical holds during Phases 2 and 3 of the clinical investigation under 21 CFR

312.42(b)(2), for example, if the plan or protocol is clearly deficient in design to

meet its stated objectives. The imposition of a clinical hold may be made by

telephone or other means of rapid communication or in writing. The responsible

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FDA Division Director is to provide the sponsor a written explanation of the

basis of the hold in not more than 30 days after its imposition. Once the stated

corrections or modifications are made by the sponsor, the investigation may

proceed, but only after the FDA Division Director has notified the sponsor,

unless stated otherwise in the clinical hold order.

In the IND Rewrite, the recommended content and format for an IND application

are described in 21 CFR 312.23. The sponsor is required to submit an original

and two copies of the IND to the agency. Each copy of the IND is to contain in

the following order: (1) a cover sheet (Form FDA-1571); (2) a table of contents:

(3) an introductory statement and general investigational plan; (4) an

investigator’s brochure; (5) protocols; (6) chemistry, manufacturing, and control

information; (7) pharmacology and toxicology information; (8) previous human

experience with the investigational drug; and (9) any additional or relevant

information. If any of the required data have been submitted previously, the

sponsor generally is not required to resubmit this material, but must cite the

reference by name, reference number, volume, and page number.

Investigational Process

As described earlier (Hoiberg and Rapaka 1987), the clinical investigation of a

previously untested drug generally is divided into three stages (i.e., Phases 1, 2,

and 3). These phases (21 CFR 312.21) usually are conducted sequentially but

may overlap. In general, a protocol for a Phase 1 study may be less detailed

and more flexible than protocols for Phases 2 and 3. The Phase 1 protocol

should provide an outline of the investigation and should specify in detail only

those elements of the study that are critical to safety. In Phases 2 and 3,

detailed protocols describing all aspects of the study should be submitted. The

required contents of a protocol are described in 21 CFR 312.23(a)(6)(iii).

In general, the amount of chemistry, manufacturing, and control information

required is less in the clinical pharmacology stage (Phase 1) than in the later

stages of drug development. The chemistry material required under 21 CFR

312.23(a)(6) should be adequate to ensure the proper identification, quality,

purity, and strength of the investigational drug so that subject safety will not be

compromised. The application should include descriptions of the general

method of preparing the drug substance and of the method of manufacturing

and packaging of the drug product. A description of the composition and

methods of control of the drug substance and of the drug product should be

provided. FDA recognizes that modifications to the method of preparation of

the new drug substance and the dosage form may be necessitated as the

investigation progresses. Therefore, emphasis should be placed on the

identification and control of the raw materials and the new drug substance.

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Final specifications for all parameters for the drug substance and drug product

are not necessarily expected until the end of the investigational process. The

amount of information submitted depends on the scope of the proposed clinical

trial. For example, although stability data are required in all phases of the

investigation to demonstrate that the new drug substance and drug product are

within acceptable chemical and physical limits for the planned duration of the

proposed clinical trial, only limited stability data (e.g., accelerated studies)

should be submitted if very short-term tests are proposed.

An important guiding principle in the FDA review of INDs is that safety concerns

predominate at the beginning of the process to ensure that research subjects

are not exposed to unreasonable risks. In later phases, FDA evaluates the

scientific merit of the study protocols to ensure that planned clinical studies are

capable of producing the valid information on safety and effectiveness that is

necessary to obtain marketing approval.

The IND Rewrite also contains regulations (21 CFR 312.110) pertaining to

investigational drug products that may be imported or exported for clinical trials.

An investigational drug may be imported into the United States if it is subject to

an IND that is in effect under 21 CFR 312.40 and if (1) the consignee in the

United States is the sponsor of the IND, (2) the consignee is a qualified

investigator named in the IND, or (3) the consignee is the domestic agent of a

foreign sponsor. Regarding the export of investigational new drugs, the

following requirements must be met: (1) An IND is in effect for the drug under

21 CFR 312.40, and each person who receives the drug is an investigator

named in the application or (2) the FDA (International Affairs Staff) has

authorized shipment of the drug for use in clinical investigation. These

requirements do not apply to the export of new drugs approved for export under

section 802 of the FD&C Act. Section 802 of the Drug Export Amendment Act

of 1986 authorizes the commercial marketing of human drugs not approved for

marketing in the United States. One provision under section 802 allows the

export of unapproved drugs to 21 listed countries that have sophisticated health

care regulatory systems.

The emergency use of an investigational drug was codified in the IND Rewrite

under 21 CFR 312.36. These regulations provide for situations in which a

physician decides that the emergency use of an investigational drug is required

for a single patient and there is not adequate time for the submission of an IND

in accordance with 21 CFR 312.23 or 312.34. FDA may authorize shipment of

the drug; however, the physician’s flrst step should be to contact the

manufacturer of the drug and determine whether the physician may be added

as an investigator under the manufacturer’s IND. If the manufacturer elects not

to add the physician to its IND, the physician should contact FDA by telephone

316
or other rapid communication. Usually, the requesting physician will be placed

in contact with an FDA medical officer familiar with the drug who will review the

proposed circumstances for its use. If the medical officer is satisfied that the

emergency use of the drug is justified, he or she may authorize its shipment and

use in advance of any formal written submission to the Agency. Except in

extraordinary circumstances, such authorization will be conditional on the

sponsor making an appropriate IND submission (Forms FDA 1571 and 1572) as

soon as practicable after receiving authorization. If the sponsor fails to

complete and submit the requisite forms within 30 days, the “emergency” IND

will be deemed to have been canceled before use of the drug and any use of

the drug will not have been in compliance with the FD&C Act. The emergency

use “of a test article” also must be reported to the responsible Institutional

Review Board within 5 working days (21 CFR 56.104[c]), and written, informed

patient consent must be obtained.

Treatment IND Program

On May 22, 1987, FDA published a final rule (52 FR 19466) pertaining to

treatment use and sale of investigational new drugs. Known as the “treatment

IND program,” these procedures allow promising drugs to be available to

desperately ill patients as early in the drug development process as possible

(before general marketing begins) and permit FDA to obtain additional data on

the drug’s safety and effectiveness. These procedures apply to patients with

serious and immediately life-threatening diseases for which no comparable or

satisfactory alternative drug or other therapies exist. A treatment IND may be

permitted after sufficient data have been collected to show that the drug may be

effective and does not have unreasonable risks. In the notice, FDA defined

under 21 CFR 312.7 the conditions under which drug manufacturers may

charge for investigational new drug products. These procedures are intended

to provide sufficient incentives for drug manufacturers to make investigational

new drugs available to patients before general marketing begins, but under

sufficient safeguard so as to prevent commercialization of the product as well as

to ensure the integrity of clinical trials. The sponsor may not charge a price

larger than that necessary to recover costs of manufacture, research,

development, and handling of the investigational drug. The FDA Commissioner

may deny a request for treatment use if the available scientific evidence, taken

as a whole, fails to provide a reasonable basis for concluding that the drug (1)

may be effective for its intended use in its intended patient population or (2)

would not expose the patients to an unreasonable and significant additional risk

of illness or injury. To protect the integrity and timeliness of the clinical testing

process and to ensure that the distribution under a treatment IND does not

become a substitute for obtaining marketing approval, regulations were

promulgated so that treatment INDs and protocols may be placed on clinical

317
hold if the sponsor is not pursuing marketing approval with due diligence. As of

June 1, 1990, treatment IND status has been granted for 18 INDs, 6 of these for

AIDS-related conditions. Examples of drugs distributed under the treatment

IND provisions are (1) selegiline for Parkinson’s disease with incomplete

response to other agents, (2) pulmonary surfactants for preterm infants with risk

of respiratory distress syndrome, and (3) beta-glucocerebrosidase for Type I

Gaucher’s disease.

Subpart E

On October 21, 1988, an interim rule (53 FR 41516) was published to facilitate

the development, evaluation, and marketing of drugs intended to treat lifethreatening and severely debilitating illnesses, especially where no satisfactory

alternative therapies exist. These procedures, referred to as “Subpart E,” focus

on the entire drug development and evaluation process from early preclinical

and clinical testing, through FDA evaluation of controlled clinical trials and

marketing applications, to postmarketing surveillance. By treating the entire

process as a coherent whole, the overall efficiency of the process was believed

to be significantly increased. These new procedures were codified as part of

the IND regulations by adding a new subpart E (21 CFR 312.80 through

312.88) and by adding a conforming amendment to the NDA regulations under

a new paragraph, 21 CFR 314.25. A key component of the procedure is early

consultation (e.g., pre-IND conferences, end of Phase 1 meetings) between

FDA and the drug sponsor to seek agreement on the design of necessary

preclinical and clinical studies needed to gain marketing approval. If the

preliminary analysis of the test results during clinical investigation appears

promising, FDA may ask the sponsor to submit a treatment protocol to be

reviewed under the treatment regulations. Such a treatment protocol, if

submitted and granted, would serve as a bridge between completion of early

stages of clinical trials and the final marketing approval. Once the Phase 2

testing and analysis are completed by the sponsor and a marketing application

is submitted, FDA will evaluate the data utilizing a medical risk-benefit analysis.

As part of this evaluation, FDA will consider whether the benefits of the drug

outweigh the known and potential risks and the need to answer remaining

questions (Phase 3 clinical trials) about risks and benefits of the drug, taking

into consideration the severity of the disease and the absence of satisfactory

alternative therapy. If approval of a drug product is granted, the Agency may

seek agreement from the sponsor to conduct certain postmarketing (Phase 4)

studies to delineate additional information about the drug’s risk, benefit, and

optimal use. These procedures were modeled after the highly successful

development, evaluation, and approval of zidovudine, the first drug approved to

treat patients with AIDS. FDA believes that this program, taken as a whole,

establishes a new and innovative approach to stimulating the development of

318
particularly important drugs, while building on past practices that have proven to

be successful.

Parallel Track Protocols

The Public Health Service (PHS) proposed on May 21, 1990 (55 FR 20856), a

policy to make promising investigational drugs for AIDS and HIV-related

diseases more widely available under “parallel track” protocols, while ensuring

that the controlled clinical trials essential to establish the safety and

effectiveness of the new drug are carried out. Under the parallel track

mechanism, eligible physicians and patients would be able to participate in

open, nonconcurrently controlled studies and receive promising investigational

drugs at an early stage in the drug development process. In studies where all

patients receive the drug and there is no comparison group, the objective is not

to provide substantial evidence of effectiveness; rather, it is designed to provide

significant safety data, representing a wider patient experience than is usually

possible in other, more rigorously designed studies. It is possible under this

proposed procedure that investigational drugs being investigated for an HIVrelated condition may be made available in a large open study even earlier than

under the treatment IND mechanism. The process is referred to as a “parallel

track” because drugs will be made available through studies that lack

concurrent control groups to monitor drug safety and that are conducted in

parallel with the principal controlled clinical investigations. Although persons

with other life-threatening diseases also might desire to have investigational

drugs available through the parallel track mechanism, the current proposal is

limited to individuals with AIDS or HIV-related diseases. A similar mechanism

previously was implemented to provide investigational drugs to persons with

cancer. The FDA and the National Cancer Institute have described a special

category of investigational drugs, “Group C” drugs, which may be provided by

oncologists to appropriately chosen patients through protocols outside the

controlled clinical trials before the drug’s approval by FDA.

At the same time the parallel track protocols were announced, FDA proposed

on May 21, 1990 (55 FR 20802), that it plans to amend two provisions of its

regulations governing INDs. These provisions include additional grounds for

placing an investigation on “clinical hold” and for terminating an IND. If

adopted, FDA could require a sponsor to cease distributing an experimental

drug in an open, nonconcurrently controlled investigation if any of several

specified conditions exist. Two examples why FDA could place a proposed or

ongoing investigation on clinical hold are: (1) There is reasonable evidence that

the investigation that is not designed to be adequate and well controlled is

impeding enrollment in, or otherwise interfering with the conduct or completion

of, a study that is designed to be an adequate and well-controlled investigation

319
of the same or another Investigational drug or (2) insufficient quantities of the

investigational drug exist to adequately conduct both the investigation not

designed to be adequate and well controlled and the investigations that are so

designed. These amendments were proposed to help implement the proposed

PHS policy on expanded availability of promising investigational new drugs

through the parallel track mechanism for people with AIDS or HIV-related

diseases.

NEW DRUG APPLICATIONS

A comprehensive revision of the CFR pertaining to the procedures and

requirements for the submission, review, and approval of new drugs and

antibiotics for human use was published by FDA on February 22, 1985 (50 FR

7542). These regulations were fully discussed in a 1986 article (Hoiberg and

Rapaka 1986).

FDA has not proposed any significant changes to these regulations since the

CFR revision of 1985. Topics discussed later in this chapter that will impinge on

material that should be submitted in an NDA are environmental assessments,

CDER guidelines, and computer-assisted NDAs.

Orphan Drug Products

On January 4, 1983, the Orphan Drug Act was signed, which added four new

sections to the FD&C Act (sections 525 through 528) to facilitate the

development of drugs for rare diseases or conditions. This legislation was in

response to the plight of patients with rare diseases who could not obtain

potentially useful drugs and medical devices. These products have become

known as “orphans.” The purpose of this legislation was to overcome the

reluctance of applicants to become sponsors of orphan drugs and undertake

the expense of conducting clinical trials and obtaining FDA approval of these

drugs. This reluctance was based in part on the limited number of patients with

rare diseases, their geographic dispersion, and the nonpatentability of many of

these drugs. Section 525 requires FDA to give protocol assistance to sponsors

of drugs for rare diseases or conditions; section 526 defines orphan drugs and

requires FDA to publicize its designation of orphan drugs; section 527 describes

a 7-year period of granting exclusive approval to certain designated orphan

drugs; and section 528 facilitates the use of open protocols to permit patients to

use orphan drugs for treatment purposes while the drugs are being investigated

in clinical trials. The Orphan Drug Act also (1) amended the PHS Act by

establishing the Orphan Products Board whose role is to foster action within the

Government to expedite the development of orphan products, (2) amended the

lnternal Revenue Code to allow tax credits for qualified clinical testing

320
expenses, (3) provided for grants to defray costs of clinical testing, and (4)

provided patent term extension under certain conditions. On October 30, 1984,

the Health Promotion and Disease Prevention Amendments of 1984 were

signed, which, among other actions, amended section 526 to specify that a rare

disease or condition is one that (1) affects fewer than 200,000 persons in the

United States at the time of the date of the request for designation or (2) affects

more than 200,000 persons in the United States and for which there is no

reasonable expectation that the cost of developing and making it available in

this country will be recovered from sales. On August 15, 1985, the Orphan

Drug Amendments of 1985 became law. One provision of these amendments

provides marketing exclusivity for 7 years to the holder of the first approval of a

designated orphan drug whether it is patented or unpatented. The enactment

of the Orphan Drug Act has resulted in development and approval of numerous

drug products. Examples of drugs that received orphan designation are (1) 1-

alpha-acetylmethadol for the treatment of heroin addicts who are suitable for

maintenance on opiate agonists, (2) naltrexone HC1 for the blockade of the

pharmacological effects of exogenously administered opioids as an adjunct to

the maintenance of the opioid-free state in detoxified, formerly opioiddependent individuals, and (3) oxymorphone HC1 for the relief of severe

intractable pain in narcotic-tolerant patients. Copies of the list of current orphan

drug designations are available from the Food and Drug Administration,

Dockets Management Branch (HFA-305), Room 4-62, 5600 Fishers Lane,

Rockville, MD 20857 and from the National information Center for Orphan

Drugs and Rare Diseases, P.O. Box 1133, Washington, DC 20013-1133.

CDER GUIDELINES

To assist sponsors of INDs and those filing NDAs in complying with regulatory

requirements, FDA has made available guidelines under 21 CFR 10.90(b).

Draft guidelines are issued first so that comments from the regulated industry,

the medical community, and other members of the public may be obtained

before the guidelines are finalized. Guidelines do not impose mandatory

requirements; however, they offer guidance on acceptable approaches to

meeting regulatory requirements. Different approaches may be followed, but

the applicant is encouraged to discuss significant variations in advance with

FDA reviewers to preclude spending time and effort in preparing a submission

that the Agency later may determine to be unacceptable. The following

available guidelines apply to the regulations administered by CDER concerning

chemistry, manufacturing, and controls.

Guideline for the Format and Content of the Chemistry, Manufacturing, and

Controls Section of an Application

321
Guideline for Submitting Supporting Documentation in Drug Applications for

the Manufacture of Drug Substances

Guideline for Submitting Documentation for the Manufacture of and Controls

for Drug Products

Guideline for Submitting Documentation for Packaging for Human Drugs and

Biologics

Guideline for Submitting Documentation for the Stability of Human Drugs

and Biologics

Guideline for Submitting Samples and Analytical Data for Methods Validation

Guideline for Drug Master Files (September 1989)

In the notice published on October 7, 1988 (53 FR 39523), FDA announced the

availability of the final “Guideline for the Format and Content of the Clinical and

Statistical Sections of an Application” to market a new drug. The intent of this

guideline is to assist an applicant in presenting the clinical and statistical data

required as part of an application under 21 CFR 314.50. It describes an

acceptable format for organizing the clinical and statistical sections and

presenting the requisite information and documentation obtained in clinical

trials.

Additional CDER guidelines currently under development or under

consideration will address radiopharmaceutical drug products, sterilization/

sterility requirements, labeling issues, and stereochemistry considerations. The

last issue is becoming important because current technological advances now

permit the large-scale separation of isomeric mixtures and the synthesis of a

single enantiomer. FDA is assessing the clinical, pharmacology/toxicology,

chemistry, and other requirements for a drug product proposed for

development, which might be a single stereoisomer or several stereoisomers

derived from an approved racemic, diastereomeric, optically enriched, or

mixture of geometric stereoisomers.

ENVIRONMENTAL ASSESSMENTS

An area of increasing regulatory importance is environmental considerations.

On April 26, 1985, FDA published (50 FR 16636) regulations that set forth its

policies and supplemental procedures for compliance with the National

Environmental Policy Act of 1969 and the Council on Environmental Quality’s

regulations. IND [21 CFR 312.23(a)(7)(e)] and NDAs [21 CFR 314.50(d)(1)(iii)]

322
are required to contain either a claim for categorical exclusion under 21 CFR

25.24 or an environmental assessment (EA) under 21 CFR 25.31. An EA is a

public document that contains environmental and other pertinent information on

a proposed action, providing a basis for FDA’s determination whether to

prepare an Environmental Impact Statement or a Finding of No Significant

Impact. If an EA is required for approval of an FDA-regulated drug, it should be

prepared [21 CFR 25.31 (a)] in the following format: (1) date, (2) name of

applicant/petitioner, (3) address, (4) description of the proposed action, (5)

identification of chemical substances that are the subject of the proposed

action, (6) introduction of substances into the environment, (7) fate of the

emitted substances into the environment, (8) environmental effects of released

substances, (9) use of resources and energy, (10) mitigation measures, (11)

alternatives to the proposed action, (12) list of preparers, (13) certification, (14)

references, and (15) appendices. If an NDA is for a human drug intended (1)

for the prevention, treatment, or diagnosis of a rare disease or for a similarly

infrequent use; (2) for ophthalmic or topical application; or (3) for local or

general anesthesia, an abbreviated EA may be filed [21 CFR 25.31 a(b)].

Guidelines are being prepared to assist applicants in meeting the regulatory

requirements. The purpose of these regulations is to ensure that environmental

information is available to the public and the decisionmaker before decisions

are made that may significantly affect the quality of the human environment and

to ensure that FDA actions are supported by accurate scientific analysis.

CANDAS AND NDA DAYS

On September 15, 1988, FDA published (53 FR 35912) a notice titled

“Submission of Drug Applications to the Food and Drug Administration Using

Computer Technology.” The Agency believes that increased use of computer

technology may improve the efficiency of the drug application review process.

To facilitate the use of computers, FDA provided guidance on factors that it

considers when accepting CANDAs, which are defined as any method using

computer technology to improve the transmission, storage, retrieval, and

analysis of data submitted to FDA as part of the drug development and

marketing approval process. Computer technology may be applied to INDs,

NDAs, abbreviated new drug applications, and antibiotic applications. Use of

computers should enhance the speed and quality of the drug review program

because FDA must handle and evaluate large quantities of data concerning

safety and efficacy, which is often burdensome and involves nonessential hardcopy handling. An NDA may include thousands of pages of reports, analyses,

tabulations, and case reports. The filing of a CANDA, however, is conditional

on the reviewing Division’s willingness to accept the application in the CANDA

format used by the applicant. To ensure the acceptability of a proposed

CANDA, it is important that the applicant discuss with the appropriate FDA

323
personnel the proposed application well in advance of its filing. The submission

of a CANDA will not influence the priority given to an application. At this time,

the submission of a CANDA generally will not affect the required submission of

an application in paper form.

Another innovative approach being explored by the agency is the “NDA Day.” It

was introduced by Dr. John Harter and developed jointly with Dr. Temple, both

with FDA, to facilitate NDA approval by reducing the institutional review time at

the Office level and by coordinating all reviews at the same time. It is a

designated day in which a specific NDA is reviewed and evaluated by FDA

personnel at the Center, Office, and Division level. Typically, the assigned

reviewers make presentations of the submitted data and their interpretations

and conclusions. These results and recommendations are discussed

intensively by all participants. The NDA applicant, although not in the room, is

available in another conference room to handle inquiries. The applicant also

usually can communicate by telephone to his or her database to handle any

questions FDA may have. At the conclusion of the NDA Day review, there may

be extensive followup, and additional information or data may have to be

submitted subsequently. To date, few NDAs have been handled by this

experimental approach.

CONCLUSION

The involvement of FDA in the new drug development process is lengthy and

complex. The Agency’s requirements for drug approval are delineated and

explained in the CFR and its guidelines. Many previous requirements and

procedures have been eliminated or revised in subsequent rewrites to facilitate

drug review. Several studies have indicated that the length of time from

laboratory synthesis of a new molecular entity to NDA approval is 10 to 12

years at a cost of $125 million to $200 million. The mean total approval time for

the 23 new molecular entities approved by FDA in 1989 was 32.5 months. The

Agency is engaged in many new innovative programs to further improve the

review process.

REFERENCE

Hoiberg, C.P., and Rapaka, R.S. Opioid peptides as drug products: FDA

regulatory requirements. In: Rapaka, R.S., and Hawks, R.L., eds. Opioid

Peptides: Molecular Pharmacology, Biosynthesis, and Analysis. National

Institute on Drug Abuse Research Monograph 70. DHHS Pub. No. (ADM)87-

1455. Washington, DC: Supt. of Docs., US. Govt. Print. Off., 1986. pp.

385-404.

324
AUTHORS

Charles P. Hoiberg*, Ph.D.

Supervisory Chemist

Center for Drug Evaluation and Research

Office of Drug Evaluation I

Division of Oncology and Pulmonary Drug Products

Food and Drug Administration

HFD-150

5600 Fishers Lane

Rockville. MD 20857

*Please note that the interpretation of FDA’s policies represents the opinion of

the author and not necessarily that of FDA.

Rao S. Rapaka**, Ph.D.

Chemist

Research Technology Branch

Division of Preclinical Research

National Institute on Drug Abuse

Room 10A-13

5600 Fishers Lane

Rockville, MD 20857

**Please note that the views expressed are those of the author and not

necessarily those of NIDA.

325
While limited supplies last, single copies of the monographs may be obtained

free of charge from the National Clearinghouse for Alcohol and Drug

Information (NCADI). Please contact NCADI also for information about

availability of coming issues and other publications of the National Institute on

Drug Abuse relevant to drug abuse research.

Additional copies may be purchased from the U.S. Government Printing Office

(GPO) and/or the National Technical information Service (NTIS) as indicated.

NTIS prices are for paper copy; add $3 handling charge for each order.

Microfiche copies are also available from NTIS. Prices from either source are

subject to change.

Addresses are:

NCADI

National Clearinghouse for Alcohol and Drug Information

P.O. Box 2345

Rockville, MD 20852

(301) 468-2600

(800) 729-6686

GPO

Superintendent of Documents

U.S. Government Printing Office

Washington, DC 20402

(202) 275-2981

NTIS

National Technical information Service

U.S. Department of Commerce

Springfield, VA 22161

(703) 487-4650

For information on availability of NIDA Research Monographs 1 through 24

(1975-1979) and others not listed, write to NIDA, Community and Professional

Education Branch, Room 10A-54, 5600 Fishers Lane, Rockville, MD 20857.

326
25 BEHAVIORAL ANALYSIS AND TREATMENT OF SUBSTANCE ABUSE.

Norman A. Krasnegor, Ph.D., ed.

GPO out of stock NCADI out of stock

NTIS PB #80-112428/AS $31

26 THE BEHAVIORAL ASPECTS OF SMOKING. Norman A. Krasnegor,

Ph.D., ed. (reprint from 1979 Surgeon General’s Report on Smoking and

Health)

GPO out of stock NTIS PB #80-118755/AS $23

30 THEORIES ON DRUG ABUSE: SELECTED CONTEMPORARY

PERSPECTIVES. Dan J. Lettieri, Ph.D.; Mollie Sayers; and Helen W. Pearson,

eds.

GPO out of stock NCADI out of stock

Not available from NTIS

31 MARIJUANA RESEARCH FINDINGS: 1980. Robert C. Petersen, Ph.D.,

ed.

GPO out of stock NTIS PB #80-215171/AS $31

32 GC/MS ASSAYS FOR ABUSED DRUGS IN BODY FLUIDS. Rodger L.

Foltz, Ph.D.; Allison F. Fentiman, Jr., Ph.D.; and Ruth B. Foltz, eds.

GPO out of stock NCADI out of stock

NTIS PB #81-133746/AS $31

36 NEW APPROACHES TO TREATMENT OF CHRONIC PAIN: A REVIEW

OF MULTIDISCIPLINARY PAIN CLINICS AND PAIN CENTERS. Lorenz K.Y.

Ng, M.D., ed.

GPO out of stock NCADI out of stock

NTIS PB #81-240913/AS $31

37 BEHAVIORAL PHARMACOLOGY OF HUMAN DRUG DEPENDENCE.

Travis Thompson, Ph.D., and Chris E. Johanson, Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #82-136961/AS $39

38 DRUG ABUSE AND THE AMERICAN ADOLESCENT. Dan J. Lettieri,

Ph.D., and Jacqueline P. Ludford, M.S., eds. A RAUS Review Report.

GPO out of stock NCADI out of stock

NTIS PB #82-148198/AS $23

327
40 ADOLESCENT MARIJUANA ABUSERS AND THEIR FAMILIES. Herbert

Hendin, M.D; Ann Pollinger, Ph.D.; Richard Ulman, Ph.D.; and Arthur Carr,

Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #82-133117/AS $23

42 THE ANALYSIS OF CANNABINOIDS IN BIOLOGICAL FLUIDS. Richard

L. Hawks, Ph.D., ed.

GPO out of stock NTIS PB #83-136044/AS $23

44 MARIJUANA EFFECTS ON THE ENDOCRINE AND REPRODUCTIVE

SYSTEMS. Monique C. Braude, Ph.D., and Jacqueline P. Ludford, M.S., eds.

A RAUS Review Report.

GPO out of stock NCADI out of stock

NTIS PB #85-150563/AS $23

45 CONTEMPORARY RESEARCH IN PAIN AND ANALGESIA, 1983. Roger

M. Brown, Ph.D.; Theodore M. Pinkert, M.D., J.D.; and Jacqueline P. Ludford,

M.S. eds. A RAUS Review Report.

GPO out of stock NCADI out of stock

NTIS PB #84-184670/AS $17

46 BEHAVIORAL INTERVENTION TECHNIQUES IN DRUG ABUSE

TREATMENT. John Grabowski, Ph.D.; Maxine L. Stitzer, Ph.D.; and Jack E.

Henningfield, Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #84-184688/AS $23

47 PREVENTING ADOLESCENT DRUG ABUSE: INTERVENTION

STRATEGIES. Thomas J. Glynn, Ph.D.; Carl G. Leukefeld, D.S.W.; and

Jacqueline P. Ludford, M.S., eds. A RAUS Review Report.

GPO out of stock NCADI out of stock

NTIS PB #85-159663/AS $31

48 MEASUREMENT IN THE ANALYSIS AND TREATMENT OF SMOKING

BEHAVIOR. John Grabowski, Ph.D., and Catherine Bell, M.S., eds.

GPO out of stock NCADI out of stock

NTIS PB #84-145184/AS $23

50 COCAINE: PHARMACOLOGY, EFFECTS, AND TREATMENT OF

ABUSE. John Grabowski, Ph.D., ed.

GPO Stock #017-024-01214-9 $4 NTIS PB #85-150381/AS $23

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51 DRUG ABUSE TREATMENT EVALUATION: STRATEGIES, PROGRESS,

AND PROSPECTS. Frank M. Tims, Ph.D., ed.

GPO out of stock NTIS PB #85-150365/AS $23

52 TESTING DRUGS FOR PHYSICAL DEPENDENCE POTENTIAL AND

ABUSE LIABILITY. Joseph V. Brady, Ph.D., and Scott E. Lukas, Ph.D., eds.

GPO out of stock NTIS PB #85-150373/AS $23

53 PHARMACOLOGICAL ADJUNCTS IN SMOKING CESSATION. John

Grabowski, Ph.D., and Sharon M. Hall, Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #89-123186/AS $23

54 MECHANISMS OF TOLERANCE AND DEPENDENCE. Charles Wm.

Sharp, Ph.D., ed.

GPO out of stock NCADI out of stock

NTIS PB #89-103279/AS $39

55 PROBLEMS OF DRUG DEPENDENCE, 1984: PROCEEDINGS OF THE

46TH ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO out of stock NCADI out of stock

NTIS PB #89-123194/AS $45

56 ETIOLOGY OF DRUG ABUSE: IMPLICATIONS FOR PREVENTION.

Coryl LaRue Jones, Ph.D., and Robert J. Battjes, D.S.W., eds.

GPO Stock #017-024-01250-5 $6.50 NTIS PB #89-123160/AS $31

57 SELF-REPORT METHODS OF ESTIMATING DRUG USE: MEETING

CURRENT CHALLENGES TO VALIDITY. Beatrice A. Rouse, Ph.D.; Nicholas

J. Kozel, M.S.; and Louise G. Richards, Ph.D., eds.

GPO out of stock NTIS PB #88-248083/AS $23

58 PROGRESS IN THE DEVELOPMENT OF COST-EFFECTIVE

TREATMENT FOR DRUG ABUSERS. Rebecca S. Ashery, D.S.W., ed.

GPO out of stock NTIS PB #89-125017/AS $23

59 CURRENT RESEARCH ON THE CONSEQUENCES OF MATERNAL

DRUG ABUSE. Theodore M. Pinkert, M.D., J.D., ed.

GPO out of stock NTIS PB #89-125025/AS $23

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60 PRENATAL DRUG EXPOSURE: KINETICS AND DYNAMICS. C. Nora

Chiang, Ph.D., and Charles C. Lee, Ph.D., eds.

GPO out of stock NTIS PB #89-124564/AS $23

61 COCAINE USE IN AMREICA: EPIDEMIOLOGIC AND CLINICAL

PERSPECTIVES. Nicholas J. Kozel, M.S., and Edgar H. Adams, M.S., eds.

GPO out of stock NTIS PB #89-131866/AS $31

62 NEUROSCIENCE METHODS IN DRUG ABUSE RESEARCH. Roger M.

Brown, Ph.D.; David P. Friedman, Ph.D.; and Yuth Nimit, Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #89-130660/AS $23

63 PREVENTION RESEARCH: DETERRING DRUG ABUSE AMONG

CHILDREN AND ADOLESCENTS. Catherine S. Bell, M.S., and Robert Battjes,

D.S.W., eds.

GPO out of stock NTIS PB #89-103287/AS $31

64 PHENCYCLIDINE: AN UPDATE. Doris H. Clouet, Ph.D., ed.

GPO out of stock NTIS PB #89-131858/AS $31

65 WOMEN AND DRUGS: A NEW ERA FOR RESEARCH. Barbara A. Ray,

Ph.D., and Monique C. Braude, Ph.D., eds.

GPO Stock #017-024-01283-1 $3.50 NTIS PB #89-130637/AS $23

66 GENETIC AND BIOLOGICAL MARKERS IN DRUG ABUSE AND

ALCOHOLISM. Monique C. Braude, Ph.D., and Helen M. Chao, Ph.D., eds.

GPO out of stock NCADI out of stock

NTIS PB #89-134423/AS $23

68 STRATEGIES FOR RESEARCH ON THE INTERACTIONS OF DRUGS

OF ABUSE. Monique C. Braude, Ph.D., and Harold M. Ginzburg, M.D., J.D.,

M.P.H., eds.

GPO out of stock NCADI out of stock

NTIS PB #89-134936/AS $31

69 OPIOID PEPTIDES: MEDICINAL CHEMISTRY. Rao S. Rapaka, Ph.D.;

Gene Barnett, Ph.D.; and Richard L. Hawks, Ph.D., eds.

GPO out of stock NTIS PB #89-158422/AS $39

70 OPIOID PEPTIDES: MOLECULAR PHARMACOLOGY, BIOSYNTHESIS,

AND ANALYSIS. Rao S. Rapaka, Ph.D., and Richard L. Hawks, Ph.D., eds.

GPO out of stock NTIS PB #89-158430/AS $45

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71 OPIATE RECEPTOR SUBTYPES AND BRAIN FUNCTION. Roger M.

Brown, Ph.D.; Doris H. Clouet, Ph.D.; and David P. Friedman, Ph.D., eds.

GPO out of stock NTIS PB #89-151955/AS $31

72 RELAPSE AND RECOVERY IN DRUG ABUSE. Frank M. Tims, Ph.D.,

and Carl G. Leukefeld, D.S.W., eds.

GPO Stock #017-024-01302-1 $6 NTIS PB #89-151963/AS $31

73 URINE TESTING FOR DRUGS OF ABUSE. Richard L. Hawks, Ph.D., and

C. Nora Chiang, Ph.D., eds.

GPO Stock #017-024-01313-7 $3.75 NTIS PB #89-151971/AS $23

74 NEUROBIOLOGY OF BEHAVIORAL CONTROL IN DRUG ABUSE.

Stephen I. Szara, M.D., D.Sc., ed.

GPO Stock #017-024-01314-5 $3.75 NTIS PB #89-151989/AS $23

75 PROGRESS IN OPIOID RESEARCH. PROCEEDINGS OF THE 1986

INTERNATIONAL NARCOTICS RESEARCH CONFERENCE. John W.

Holaday, Ph.D.: Ping-Yee Law, Ph.D.; and Albert Herz, M.D., eds.

GPO out of stock NCADI out of stock

Not available from NTIS

76 PROBLEMS OF DRUG DEPENDENCE, 1986: PROCEEDINGS OF THE

48TH ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO out of stock NCADI out of stock

NTIS PB #88-208111/AS $53

77 ADOLESCENT DRUG ABUSE: ANALYSES OF TREATMENT

RESEARCH. Elizabeth R. Rahdert, Ph.D., and John Grabowski, Ph.D., eds.

GPO Stock #017-024-01348-0 $4 NCADI out of stock

NTIS PB #89-125488/AS $23

78 THE ROLE OF NEUROPLASTICITY IN THE RESPONSE TO DRUGS.

David P. Friedman, Ph.D., and Doris H. Clouet, Ph.D., eds.

GPO out of stock NTIS PB #88-245683/AS $31

79 STRUCTURE-ACTIVITY RELATIONSHIPS OF THE CANNABINOIDS.

Rao S. Rapaka, Ph.D., and Alexandros Makriyannis, Ph.D., eds.

GPO out of stock NTIS PB #89-109201/AS $31

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80 NEEDLE SHARING AMONG INTRAVENOUS DRUG ABUSERS:

NATIONAL AND INTERNATIONAL PERSPECTIVES. Robert J. Battjes,

D.S.W., and Roy W. Pickens, Ph.D., eds.

GPO out of stock NTIS PB #88-236138/AS $31

81 PROBLEMS OF DRUG DEPENDENCE, 1987: PROCEEDINGS OF THE

49TH ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01354-4 $17 NTIS PB #89-109227/AS

Contact NTIS for price

82 OPIOIDS IN THE HIPPOCAMPUS. Jacqueline F. McGinty, Ph.D., and

David P. Friedman, Ph.D., eds.

GPO out of stock NTIS PB #88-245691/AS $23

83 HEALTH HAZARDS OF NITRITE INHALANTS. Harry W. Haverkos, M.D.,

and John A. Dougherty, Ph.D., eds.

GPO out of stock NTIS PB #89-125496/AS $23

84 LEARNING FACTORS IN SUBSTANCE ABUSE. Barbara A. Ray, Ph.D.,

ed.

GPO Stock #017-024-01353-6 $6 NTIS PB #89-125504/AS $31

85 EPIDEMIOLOGY OF INHALANT ABUSE: AN UPDATE. Raquel A. Crider,

Ph.D., and Beatrice A. Rouse, Ph.D., eds.

GPO Stock #017-024-01360-9 $5.50 NTIS PB #89-123178/AS $31

86 COMPULSORY TREATMENT OF DRUG ABUSE: RESEARCH AND

CLINICAL PRACTICE. Carl G. Leukefeld, D.S.W., and Frank M. Tims, Ph.D.,

eds.

GPO Stock #017-024-01352-8 $7.50 NTIS PB #89-151997/AS $31

87 OPIOID PEPTIDES: AN UPDATE. Rao S. Rapaka, Ph.D., and Bhola N.

Dhawan, M.D., eds.

GPO Stock #017-024-01366-8 $7 NTIS PB #89-158430/AS $45

88 MECHANISMS OF COCAINE ABUSE AND TOXICITY. Doris H. Clouet,

Ph.D.; Khursheed Asghar, Ph.D.; and Roger M. Brown, Ph.D., eds.

GPO Stock #017-024-01359-5 $11 NTIS PB #89-125512/AS $39

89 BIOLOGICAL VULNERABILTY TO DRUG ABUSE. Roy W. Pickens,

Ph.D., and Dace S. Svikis, B.A., eds.

GPO Stock #017-022-01054-2 $5 NTIS PB #89-125520/AS $23

332
90 PROBLEMS OF DRUG DEPENDENCE, 1988: PROCEEDINGS OF THE

50TH ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01362-5 $17

91 DRUGS IN THE WORKPLACE: RESEARCH AND EVALUATION DATA.

Steven W. Gust, Ph.D., and J. Michael Walsh, Ph.D., eds.

GPO Stock #017-024-01384-6 $10 NTIS PB #90-147257/AS $39

92 TESTING FOR ABUSE LIABILITY OF DRUGS IN HUMANS, Marian W.

Fischman, Ph.D., and Nancy K. Mello, Ph.D., eds.

GPO Stock #017-024-01379-0 $12 NTIS PB #90-148933/AS $45

93 AIDS AND INTRAVENOUS DRUG USE: FUTURE DIRECTIONS FOR

COMMUNITY-BASED PREVENTION RESEARCH. C.G. Leukefeld, D.S.W.;

R.J. Battjes, D.S.W.; and Z. Amsel, D.Sc., eds.

GPO Stock #017-024-01388-9 $10 NTIS PB #90-148941/AS $39

94 PHARMACOLOGY AND TOXICOLOGY OF AMPHETAMINE AND

RELATED DESIGNER DRUGS. Khursheed Asghar, Ph.D., and Errol De

Souza, Ph.D., eds.

GPO Stock #017-024-01386-2 $11 NTIS PB #90-148958/AS $39

95 PROBLEMS OF DRUG DEPENDENCE, 1989: PROCEEDINGS OF THE

51ST ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01399-4 $21 NTIS PB #90-237660/AS $67

96 DRUGS OF ABUSE: CHEMISTRY, PHARMACOLOGY, IMMUNOLOGY,

AND AIDS. Phuong Thi Kim Pham, Ph.D., and Kenner Rice, Ph.D., eds.

GPO Stock #017-024-01403-6 $8 NTIS PB #90-237678/AS $31

97 NEUROBIOLOGY OF DRUG ABUSE: LEARNING AND MEMORY. Lynda

Erinoff, Ph.D., ed.

GPO Stock #017-024-01404-4 $8 NTIS PB #90-237686/AS $31

98 THE COLLECTION AND INTERPRETATION OF DATA FROM HIDDEN

POPULATIONS. Elizabeth Y. Lambert, M.S., ed.

GPO Stock #017-024-01407-9 $4.75 NTIS PB #90-237694/AS $23

99 RESEARCH FINDINGS ON SMOKING OF ABUSED SUBSTANCES.

C. Nora Chiang, Ph.D., and Richard L. Hawks, Ph.D., eds.

GPO Stock #017-024-01412-5 $5 NTIS PB #91-141119 $23

333
100 DRUGS IN THE WORKPLACE: RESEARCH AND EVALUATION DATA.

VOL. II. Steven W. Gust, Ph.D., and J. Michael Walsh, Ph.D., eds.

101 RESIDUAL EFFECTS OF ABUSED DRUGS ON BEHAVIOR. John W.

Spencer, Ph.D., and John J. Boren, Ph.D., eds.

GPO Stock #017-024-01426-7 $6 NTIS PB #91-172858/AS $31

102 ANABOLIC STEROID ABUSE. Geraline C. Lin, Ph.D., and Lynda Erinoff,

Ph.D., eds.

GPO Stock #017-024-01425-7 $8 NTIS PB #91-172866/AS $31

103 DRUGS AND VIOLENCE: CAUSES, CORRELATES, AND

CONSEQUENCES. Mario De La Rosa, Ph.D.; Elizabeth Y. Lambert, MS.;

and Bernard Gropper, Ph.D., eds.

GPO Stock #017-024-01427-3 $9 NTIS PB #91-172841/AS $31

104 PSYCHOTHERAPY AND COUNSELING IN THE TREATMENT OF

DRUG ABUSE. Lisa Simon Onken, Ph.D., and Jack D. Blaine, M.D., eds.

GPO Stock #017-024-01429-0 $4 NTIS PB #91-172874/AS $23

105 PROBLEMS OF DRUG DEPENDENCE, 1990: PROCEEDINGS OF THE

52ND ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS

OF DRUG DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

106 IMPROVING DRUG ABUSE TREATMENT. Roy W. Pickens, Ph.D.; Carl

G. Leukefeld, D.S.W.; and Charles R. Schuster, Ph.D., eds.

107 DRUG ABUSE PREVENTION INTERVENTION RESEARCH:

METHODOLOGICAL ISSUES. Carl G. Leukefeld, D.S.W., and William J.

Bukoski, Ph.D., eds.

108 CARDIOVASCULAR TOXICITY OF COCAINE: UNDERLYING

MECHANISMS. Pushpa V. Thadani, Ph.D., ed.

109 LONGITUDINAL STUDIES OF HIV INFECTION IN INTRAVENOUS

DRUG USERS: METHODOLOGICAL ISSUES IN NATURAL HISTORY

RESEARCH. Peter Hartsock, Dr.P.H., and Sander G. Genser, M.D., M.P.H.,

eds.

110 THE EPIDEMIOLOGY OF COCAINE USE AND ABUSE. Susan Schober,

Ph.D., and Charles Schade, M.D., M.P.H., eds.

334
111 MOLECULAR APPROACHES TO DRUG ABUSE RESEARCH:

VOLUME I. Theresa N.H. Lee, Ph.D., ed.

335
DHHS Publication No. [ADM] 91-1812

Alcohol Drug Abuse and Mental Health Administration

Printed 1991