INTERACTION OF ALPHA-CONOTOXIN PEPTIDES WITH NEURONAL NICOTINIC ACETYLCHOLINE RECEPTORS

Abstract: This invention relates to derivatives of the conopeptide MII, an alpha -4/7 conotoxin peptide, in which amino acid residues are substituted as described herein while maintaining the basic activity of MII. The present invention also relates to the discovery of the 3-dimensional structure of MII, and the relationship of its structure to its specificity to the alpha 3 beta 2 subtype of the neuronal nicotinic acetylcholine receptor (nAChR). The present invention also relates to computer based programs for the expression of the three-dimensional structure of MII and peptide analogs, peptide mimetics or non-peptide mimetics thereof. The structural characteristics may be correlated with biological activity to enable the design of alpha -4/7 conotoxin peptide analogs and peptide mimetics which demonstrate the same specificity to neuronal nAChR. Such analogs and peptide mimetics are useful as cardiovascular agents and for treating or detecting small-cell lung carcinoma (SCLC).

Description: TITLE OF THE INVENTION INTERACTION OF ALPHA-CONOTOXIN PEPTIDES WITH NEURONAL NICOTINIC ACETYLCHOLINE RECEPTORS This invention was made with Government support under Grant Nos. GM-54710, P01 48677 and MH-53631 awarded by the National Institutes of Health, Bethesda. Maryland. The United States Government has certain rights in the invention. BACKGROUND OF THE INVENTION The present invention relates to derivatives of the alpha conopeptide Mil. an α-4/7 conotoxin peptide. in which amino acid residues are substituted as described herein while maintaining activity substantially similar to Mil. The present invention is further directed to the discovery of the 3-dimensional structure of Mil and the relationship of its structure to its specificity for the α3β2 subtype of the neuronal nicotinic acetylcholine receptor (nAChR). The discovery of the 3-dimensional structure enables the design of α-4/7 conotoxin peptide analogs and peptide mimetics which will demonstrate the same specificity to neuronal nAChR. Such analogs and peptide mimetics are useful as cardiovascular agents and for treating or detecting small-cell lung carcinoma (SCLC). The present invention also relates to computer based programs for the expression of the three-dimensional structure of Mil and peptide analogs, peptide mimetics or non-peptide mimetics thereof. The publications and other materials used herein to illuminate the background of the invention and. in particular cases, to provide additional details respecting the practice, are incorporated by reference, and for convenience are numerically referenced in the following text and respectively grouped in the appended bibliography. The α-conopeptide Mil has the amino acid sequence: Gly-Cys-Cys-Ser-Asn-Pro-Val-Cys- His-Leu-Glu-His-Ser-Asn-Leu-Cys (SEQ ID NO: l). This peptide contains two disulfide bonds between the first and third cysteine residues and between the second and fourth cysteine residues. The C-terminal end may contain a carboxyl or amide group, preferably an amide group. The amino acid at position 6 may be proline or 4-trans-hydroxyproline. preferably proline. The identification of Mil is described in U.S. Patent No. 5,514.774, incoφorated herein by reference. A major challenge for neurobiology is to define the function of the multiple forms of nicotinic receptors and ion channels that have recently been discovered in the nervous system by molecular techniques. The use of gene knock-out organisms is one method for examining such function. A complementary approach is to use ligands that specifically inhibit a particular molecular form of receptor or ion channel. Such ligands must be able to discriminate between closely related members of receptor families. Nicotinic acetylcholine receptors (nAChR) are ligand-gated ion channels which are key components of nervous systems. The classical role of these receptors was defined at the neuromuscular junction, nicotinic receptors concentrated on the muscle end plate serve as the key macromolecule that detects release of neurotransmitter from the presynaptic terminus of the motor axon. However, in addition to these skeletal muscle nicotinic receptors, many other molecular forms of nicotinic receptors exist; these are generally referred to as neuronal nicotinic receptors. In the central nervous system (CNS), nAChRs play a prominent role in modulating the release of neurotransmitters including dopamine, norepinephrine, acetylcholine, GABA and glutamate. The small peptide toxins (conotoxins) from the venom of fish-hunting cone snail, Conus magus, are a natural source of ligands that discriminate between closely related molecular forms of a single receptor or ion channel family. Alpha conopeptide Mil is a small peptide with selective action on neuronal nicotinic receptors. In the autonomic nervous system, Mil was recently used to help pharmacologically dissect the nAChRs which mediate synaptic transmission in the parasympathetic ciliary ganglion. In frog sympathetic ganglia, Mil discriminates between nAChRs in B versus C neurons. In the CNS, the specificity of Mil enables identification of subunits of nAChRs which modulate nicotine-stimulated dopamine release. In retina, Mil's selective block was used to confirm the role of nAChRs in the development of visual circuitry. The use of Mil for detecting the presence and location of small-cell lung carcinoma (SCLC) tumors, treating a patient having SCLC and inhibiting proliferation of SCLC tumors is described in U.S. Patent 5,595,972, incorporated herein by reference. The use of Mil for treating disorders resulting from nicotine stimulated dopamine release is described in U.S. Patent 5,780,433, incoφorated herein by reference. The use of Mil as a cardiovascular agent is described in copending provisional application Serial No. 60/031,141, filed 18 November 1996, incoφorated herein by reference. To date, there have been no reports of the tliree-dimensional structure of Mil and no systematic studies of the relationship of the three-dimensional structure and function of the molecule, studies which are essential to the systematic design of Mil analogs and mimetics. It is desired to identify derivatives of Mil, peptide analogs and peptide mimetics of α- conotoxins, generally, which are selective for specific subtypes of nAChRs and which have the uses described herein. SUMMARY OF THE INVENTION The present invention relates to derivatives of the alpha conopeptide Mil, an α-4/7 conotoxin peptide, in which amino acid residues are substituted as described herein while maintaining activity substantially similar to MIL More specifically, the present invention is directed to the derivatives having the general formula (SEQ ID NO:2): Xaa-Cys-Cys-Xaa-Xaa,-Xaa 2 -Xaa-Cys-Xaa 3 -Xaa-Xaa 4 -Xaa 5 -Xaa-Xaa-Xaa-Cys, wherein Xaa represents an amino acid selected from the group consisting of natural, modified or non-natural amino acids. The modifications may be by addition substitution or deletion of one or more amino acid residues. The modification may also include the addition or substitution of analogs of the amino acid themselves, such as peptidomimetics, or amino acids with altered side groups, or mimetics, e.g., organic molecules with similar space/structure/function relationships. Individual residue Xaa, is any amino acid, preferably Asn or His; Xaa 2 is any amino acid, preferably Pro or hydroxy-Pro; Xaa 3 is any amino acid, preferably His or Asn; Xaa 4 is any amino acid, preferably Glu; and Xaa 5 is any amino acid, preferably His or Asn. It is most preferred that Xaa, is Asn; Xaa, is Pro or hydroxy-Pro; and Xaa 5 is His. The C-terminal end may contain a carboxyl or amide group, preferably an amide group. A second aspect of the present invention is directed to the discovery of the 3 -dimensional structure of Mil and the relationship of its structure to its specificity for the α3β2 subtype of the neuronal nicotinic acetylcholine receptor (nAChR). Based on the correlation of structure to biological activity, the discovery of the 3-dimensional structure enables the design of α-4/7 conotoxin peptide analog, peptide mimetics and non-peptide mimetics which demonstrate specificity to different subtypes of neuronal nAChRs In one embodiment, compounds are developed which demonstrate higher specificity to the α3β2 subtype of neuronal nAChR than the α3β4 subtype, such as evidence by MIL In a second embodiment, compounds are developed which demonstrate higher specificity to the α3β4 subtype of neuronal nAChR than the α3β2 subtype, such as evidence by several of the Mil derivatives described herein. The derivatives, peptide analogs, peptide mimetics and non-peptide mimetics of the present invention are useful as cardiovascular agents, gastric motility agents, urinary incontinence agents, anti-smoking agents and for treating or detecting small-cell lung carcinoma (SCLC) . A third aspect of the present invention is directed to the synthesis of mimetics, e.g., organic molecules based on the three-dimensional structure of Mil which demonstrates the same or different specificity to neuronal nAChRs. A fourth aspect of the present invention is directed to the synthesis of peptide analogs and peptide mimetics of Mil with altered nicotinic AChR subtype specificity based on the identification of peptide fragments which define the activity and selectivity of the conopeptide Mil and on its three-dimensional structure. A fifth aspect of the present invention is directed to synthesis of mimetics, e.g., organic molecules based upon the overall structural activity information relating to MIL A sixth aspect of the present invention also provides for computer programs for the expression (such as visual display) of the three-dimensional structure of Mil or a peptide analog or peptide mimetic thereof, and further, a computer program which expresses the identity of each constituent of Mil and the precise location within the overall structure of that constituent, down to the atomic level. There are many currently available computer programs for the expression of the three-dimensional structure of a molecule. Generally, these programs provide for inputting of the coordinates for the three-dimensional structure of a molecule; means to express (such as visually display) such coordinates, means to alter such coordinates and means to express an image of a molecule having such altered coordinates. In a further aspect, one may program NMR coordinates of the location of the atoms of an Mil molecule in three dimension space, wherein such coordinates have been obtained from NMR analysis of said Mil molecule, into such programs to perform comparative protein modeling of Mil or a portion thereof, as described herein. Also provided, therefore, is a computer program for the expression of the three-dimensional structure of a peptide analog or peptide mimetic of MIL Preferred is the computer program CAVEAT, available from Molecular Simulations, Inc. (Waltham, MA) with the coordinates as set forth in Figure 8 input. BRIEF DESCRIPTION OF THE FIGURES The file of this patent contains at least one drawing executed in color. Copies of this patent with color drawing(s) will be provided by the Patent and Trademark Office upon request and payment of the necessary fee. Figure 1 shows the effect of alanine substitutions in the conopeptide Mil on the ability of the analogs to block acetylcholine-gated currents in voltage-clamped Xenopus oocytes expressing cloned rat α3 and β2 subunits. Figure 2 shows the NOESY spectrum (250-ms mixing time) of α-CT x Mil in H 2 O illustrating sequential NOE connectives between neighboring α and amide protons. The d aN NOE cross peaks are connected by lines and are labeled by residue number. Two traces between residues Cys 2 - Asn 5 and Val 7 - Cys 16 are shown with their contiguous connectives broken at Pro 6 . Figure 3 shows an amino acid sequence of α-CT x Mil with its disulfide bridges drawn to show its disulfide bridge pattern and a summary of short- to medium-range sequential NOE cross peaks as well as experimentally measured 3 J NH.CαH coupling constants. Arrows pointing down are those with 3 J constants <5.0 Hz, and those pointing up are those with 3 J constants >8.0 Hz. Filled bars represent the NOE cross peaks with the thickness classifying NOE intensities from strong (thick) to weak (thin) and the width indicating short- to medium-range separation along the linear sequence. *** represents overlapped NOE cross peaks. Figure 4 shows α proton chemical shift differences (ppm), between observed values from α-CT x Mil in H 2 0 and random-coil values, plotted versus the residue. Figures 5A-B show superimposition of the 14 lowest energy structures of α-CT x Mil calculated from simulated annealing. Figure 6A-C show the angular order parameters for the backbone obtained from the 14 minimum energy structures, plotted versus the residue number. Figure 6A shows parameters for ψ, Figure 6B for ψ; and Figure 6C for χ. Figure 7 shows surface (A,B) and backbone (C, D, E) representations of α-CT xs Mil, PnIA, and GI. Space-filling models of the X-ray crystal structure of α-CT x PnIA (A) and the lowest energy structure of α-CT Mil (B) are displayed in puφle for hydrophobic residues, in yellow for polar side chains and in red (positive) and blue (negative) for charged side chains. Backbone conformations of α-CT x PnIA (C), α-CT x Mil (D), and α-CT GI (E) are displayed in ribbons and surface distributions in dots with the same color codes to illustrate their similarity and difference. Arrows indicate terminal residues, blue for carboxyl and yellow for amino. Figure 8 lists the coordinates of α-conotoxin MIL These coordinates have been deposited in the Brookhaven Protein Data Bank, Upton, NY 19973, under accession code lm2c. Figure 9 shows selective block by α-Conotoxin Mil of α3β2 nAChRs. Oocytes expressing various nAChR subunit combinations were voltage-clamped and the response to ACh was measured at various α-Conotoxin Mil concentrations. Data represent the mean ± S.E. for at least three oocytes at each concentration. Figure 10 shows that block of α3β2 nAChRs by α-Conotoxin Mil is independent of the membrane potential. Oocytes expressing α3β2 nAChRs were voltage-clamped and the response to ACh was measured over a range of membrane potentials. Peak-amplitude currents in the absence (o) and presence (*■) of 500 pM α-Conotoxin Mil are plotted against the membrane potential. Scaled toxin responses ( τ ) are also shown. Figure 11A-C show that the competitive antagonist, Dihydro-β-Erythroidine (DHβE), protects α3β2 nAChRs from blockade by α-Conotoxin MIL Oocytes expressing α3β2 nAChRs were voltage-clamped and the response to ACh was measured. In Figure 11 A, 500 μM DHβE was applied for 5 min. The oocyte was then continuously perfused with buffer without DHβE. In Figure 1 IB, 500 μM DHβE was applied for 5 min. followed by coapplication of 500 μM DHβE and 20nM α-Conotoxin Mil for 2 min. The oocyte was then continuously perfused with buffer without toxins. In Figure 1 IC, 20 nM α-Conotoxin Mil was applied for 2 min. The oocyte was then continuously perfused with buffer without toxin. Figure 12A and B show the kinetics of block of α3β2 and α3β4 nAChRs by α-Conotoxin MIL Figure 12A shows the response of voltage-clamped oocytes expressing α3β2 nAChRs to ACh measured during application of 500 pM α-Conotoxin Mil (first graph) and following washout from toxin (second graph). Figure 12B shows the response of voltage-clamped oocytes expressing α3β4 nAChRs to ACh measured during application of 1 μM α-Conotoxin Mil (first graph) and following washout from toxin (second graph). Figure 13A and B show the recovery kinetics of α3β2 and α3β4 nAChRs from block by saturating concentrations of α-Conotoxin MIL Figure 13A shows voltage-clamped oocytes expressing α3β2 nAChRs and their response to ACh. 2 μM α-conotoxin Mil was applied for 5 min. The oocyte was then continuously perfused with buffer without toxin. Figure 13B shows oocytes expressing α3β4 nAChRs, which were voltage-clamped and their response to ACh. 2.5 mM α- Conotoxin Mil was applied for 5 min. The oocyte was then continuously perfused with buffer without toxin. Data were fit to a 2-site model (solid lines). Dashed lines represent the expected single-exponential recovery kinetics. Figures 14A-C show the Mil "Dock & Lock" model of ligand/receptor interation. In this illustration, Mil binds at the interface between the α and β subunits. Mil interacts with the β subunit with a very fast k on and k otf and thus moderate affinity. Conversly, Mil interacts with the α subunit with a very slow k on and k ott and thus moderate affinity. As shown in Fig. 14A and 14B, Mil approaches the receptor and very rapidly binds to the β subunit (docking interaction). However, this rapid binding to the β subunit in close proximity to the α subunit binding site leads to enhancement of the rate of Mil's interaction with the α subunit and subsequent blockage of the receptor. Fig. 14C shows that once Mil is bound to the α subunit, it has a very slow k otf (locking interaction). Thus, by targeting the subunit interface of the nicotinic receptor. Mil is able to convert two relatively moderate binding interactions into a very potent and specific interaction with one molecular form of neuronal nAChR. SUMMARY OF SEQUENCE LISTING SEQ ID NO: 1 is the amino acid sequence for α-CT x Mil peptide. SEQ ID NO:2 is the amino acid sequence for derivatives of the alpha conopeptide MIL SEQ ID NO:3 is the amino acid sequence for the FATN chimera of MIL DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS I. Derivatives of Mil The present invention relates to derivatives of Mil, an α-4/7 conotoxinpeptide, in which amino acid residues are substituted as described herein while maintaining the basic activity of MIL More specifically, the present invention is directed to the derivatives having the general formula (SEQ ID NO:2): Xaa-Cys-Cys-Xaa-Xaa 1 -Xaa 2 -Xaa-Cys-Xaa 3 -Xaa-Xaa 4 -Xaa<;-Xaa-Xaa-Xaa-Cys, wherein Xaa represents an amino acid selected from the group consisting of natural, modified or non-natural amino acids. The modifications may be by addition substitution or deletion of one or more amino acid residues. The modification may also include the addition or substitution of analogs of the amino acid themselves, such as peptidomimetics, or amino acids with altered side groups, or mimetics, e.g., organic molecules with similar space/structure/function relationships. Individual residue Xaa, is any amino acid, preferably Asn or His: Xaa 2 is any amino acid, preferably Pro or hydroxy-Pro; Xaa 3 is any amino acid, preferably His or Asn; Xaa 4 is any amino acid, preferably Glu; and Xaa 5 is preferably His or Asn. It is most preferred that Xaa, is Asn; Xaa-, is Pro or hydroxy-Pro; and Xaa 5 is His. The derivatives contain two disulfide bonds between the first and third cysteine residues and between the second and fourth cysteine residues. The C-terminal end may contain a carboxyl or amide group, preferably an amide group. The amino acid is an α-amino acid, which includes natural amino acids, including unusual amino acids such as γ-carboxyglutamic acid, as well as modified or non-natural amino acids, such as those described in, for example, Roberts et al. (1983). The derivatives of the present invention are highly selective for either the α3β2 or α3β4 subtype of neuronal nAChRs which are present in the autonomic and central nervous systems. Thus, they are useful as cardiovascular agents, gastric motility agents, urinary incontinence agents and anti-smoking agents, as well as being useful against SCLC. The conopeptides can be produced by recombinant DNA techniques well known in the art. Also, these conopeptide derivatives are sufficiently small to be chemically synthesized. General chemical syntheses for preparing the foregoing conopeptide derivatives are described hereinafter, along with specific chemical synthesis of conopeptide derivatives and indications of biological activities of these synthetic products. The conopeptides of the present invention may be synthesized and/or substantially pure. By "substantially pure" is meant that the peptide is present in the substantial absence of other biological molecules of the same type; it is preferably present in an amount of at least about 85% purity and preferably at least about 95% purity. II. Preparation of recombinant and chemically synthesized derivatives. The conopeptides of the present invention can be produced by recombinant DNA techniques well known in the art , such as those described in, for example, Sambrook et al. (1979). The peptides produced in this manner are isolated, reduced if necessary, and oxidized to form the correct disulfide bonds, if present in the final molecule. One method of forming disulfide bonds in the conopeptides of the present invention is the air oxidation of the linear peptides for prolonged periods under cold room temperatures or at room temperature. This procedure results in the creation of a substantial amount of the bioactive, disulfide-linked peptides. The oxidized peptides are fractionated using reverse-phase high performance liquid chromatography (HPLC) or the like, to separate peptides having different linked configurations. Thereafter, either by comparing these fractions with the elution of the native material or by using a simple assay, the particular fraction having the correct linkage for maximum biological potency is easily determined. It is also found that the linear peptide. or the oxidized product having more than one fraction, can sometimes be used for in vivo administration because the cross-linking and/or rearrangement which occurs in vivo has been found to create the biologically potent conopeptide molecule. However, because of the dilution resulting from the presence of other fractions of less biopotency, a somewhat higher dosage may be required. It should be possible to prepare many, or even all, of these peptides using recombinant DNA technology. However, when peptides are not so prepared, they can be chemically synthesized by a suitable method, such as by exclusively solid-phase techniques, by partial solid-phase techniques, by fragment condensation or by classical solution couplings. In conventional solution phase peptide synthesis, the peptide chain can be prepared by a series of coupling reactions in which constituent amino acids are added to the growing peptide chain in the desired sequence. Use of various coupling reagents, e.g., dicyclohexylcarbodiimide or diisopropylcarbonyldimidazole, various active esters, e.g., esters of N-hydroxyphthalimide or N- hydroxy-succinimide, and the various cleavage reagents, to carry out reaction in solution, with subsequent isolation and purification of intermediates, is well known classical peptide methodology. Classical solution synthesis is described in detail in the treatise, "Methoden der Organischen Chemie (Houben-Weyl): Synthese von Peptiden," (1974). Techniques of exclusively solid-phase synthesis are set forth in the textbook, "Solid-Phase Peptide Synthesis." (Stewart and Young, 1969), and are exemplified by the disclosure of U.S. Patent 4,105,603 (Vale et al. 1978). The fragment condensation method of synthesis is exemplified in U.S. Patent 3,972,859 (1976). Other available syntheses are exemplified by U.S. Patents No. 3,842,067 (1974) and 3,862,925 (1975). The synthesis of peptides containing γ-carboxyglutamic acid residues is exemplified by Rivier et al. (1987), Nishiuchi et al. (1993) and Zhou et al. (1996). Common to such chemical syntheses is the protection of the labile side chain groups of the various amino acid moieties with suitable protecting groups which will prevent a chemical reaction from occurring at that site until the group is ultimately removed. Usually also common is the protection of an a-amino group on an amino acid or a fragment while that entity reacts at the carboxyl group, followed by the selective removal of the a-amino protecting group to allow subsequent reaction to take place at that location. Accordingly, it is common that, as a step in such a synthesis, an intermediate compound is produced which includes each of the amino acid residues located in its desired sequence in the peptide chain with appropriate side-chain protecting groups linked to various ones of the residues having labile side chains. As far as the selection of a side chain amino protecting group is concerned, generally one is chosen which is not removed during deprotection of the a-amino groups during the synthesis. However, for some amino acids, e.g., His, protection is not generally necessary. In selecting a particular side chain protecting group to be used in the synthesis of the peptides. the following general rules are followed: (a) the protecting group preferably retains its protecting properties and is not split off under coupling conditions, (b) the protecting group should be stable under the reaction conditions selected for removing the a-amino protecting group at each step of the synthesis, and © the side chain protecting group must be removable, upon the completion of the synthesis containing the desired amino acid sequence, under reaction conditions that will not undesirably alter the peptide chain. While solution phase synthesis may be used, peptides are preferably prepared using the Merrifield solid-phase synthesis, although other equivalent chemical syntheses known in the art can also be used as previously mentioned. Solid-phase synthesis is commenced from the C-terminus of the peptide by coupling a protected a-amino acid to a suitable resin. Such a starting material can be prepared by attaching an a-amino-protected amino acid by an ester linkage to a chloromethylated resin or a hydroxymethyl resin, or by an amide bond to a benzhydrylamine (BHA) resin or para- methylbenzhydrylamine (MBHA) resin. Preparation of the hydroxymethyl resin is described by Bodansky et al. (1966). Chloromethylated resins are commercially available from Bio Rad Laboratories (Richmond, CA) and from Lab. Systems, Inc. The preparation of such a resin is described by Stewart and Young (1969). BHA and MBHA resin supports are commercially available, and are generally used when the desired polypeptide being synthesized has an unsubstituted amide at the C-terminus. Thus, solid resin supports may be any of those known in the art, such as one having the formulae -O-CH 2 -resin support, -NH BHA resin support, or -NH-MBHA resin support. When the unsubstituted amide is desired, use of a BHA or MBHA resin is preferred, because cleavage directly gives the amide. In case the N-methyl amide is desired, it can be generated from an N-methyl BHA resin. Should other substituted amides be desired, the teaching of U.S. Patent No. 4,569,967 (Kornreich et al., 1986) can be used, or should still other groups than the free acid be desired at the C-terminus, it may be preferable to synthesize the peptide using classical methods as set forth in the Houben-Weyl text (1974). The C-terminal amino acid, protected by Boc or Fmoc and by a side-chain protecting group, if appropriate, can be first coupled to a chloromethylated resin according to the procedure set forth in Horiki et al. (1978), using KF in DMF at about 60° C for 24 hours with stirring, when a peptide having free acid at the C-terminus is to be synthesized. Following the coupling of the BOC- protected amino acid to the resin support, the a-amino protecting group is removed, as by using trifluoroacetic acid (TFA) in methylene chloride (CH 2 C1 2 ) or TFA alone. The deprotection is carried out at a temperature between about 0° C and room temperature. Other standard cleaving reagents, such as HC1 in dioxane, and conditions for removal of specific a-amino protecting groups may be used as described in Schroder and Lubke (1965). After removal of the a-amino-protecting group, the remaining a-amino- and side chain- protected amino acids are coupled step-wise in the desired order to obtain the intermediate compound defined hereinbefore, or as an alternative to adding each amino acid separately in the synthesis, some of them may be coupled to one another prior to addition to the solid phase reactor. Selection of an appropriate coupling reagent is within the skill of the art. Particularly suitable as a coupling reagent is N,N'-dicyclohexylcarbodiimide (DCC, DIC, HBTU, HATU, TBTU in the presence of HoBt or HoAt). The activating reagents used in the solid phase synthesis of the peptides are well known in the peptide art. Examples of suitable activating reagents are carbodiimides, such as N,N'- diisopropylcarbodiimide and N-ethyl-N'-(3-dimethylaminopropyl)carbodiimide. Other activating reagents and their use in peptide coupling are described by Schroder and Lubke (1965) and Kapoor (1970). Each protected amino acid or amino acid sequence is introduced into the solid-phase reactor in about a twofold or more excess, and the coupling may be carried out in a medium of dimethylformarnide (DMF):CH 2 C1 2 (1 :1) or in DMF or CH 2 C1 2 alone. In cases where intermediate coupling occurs, the coupling procedure is repeated before removal of the a-amino protecting group prior to the coupling of the next amino acid. The success of the coupling reaction at each stage of the synthesis, if performed manually, is preferably monitored by the ninhydrin reaction, as described by Kaiser et al. (1970). Coupling reactions can be performed automatically, as on a Beckman 990 automatic synthesizer, using a program such as that reported in Rivier et al. (1978). After the desired amino acid sequence has been completed, the intermediate peptide can be removed from the resin support by treatment with a reagent, such as liquid hydrogen fluoride or TFA (if using Fmoc chemistry), which not only cleaves the peptide from the resin but also cleaves all remaining side chain protecting groups and also the a-amino protecting group at the N-terminus if it was not previously removed to obtain the peptide in the form of the free acid. If Met is present in the sequence, the Boc protecting group is preferably first removed using trifluoroacetic acid (TFA)/ethanedithiol prior to cleaving the peptide from the resin with HF to eliminate potential S- alkylation. When using hydrogen fluoride or TFA for cleaving, one or more scavengers such as anisole, cresol, dimethyl sulfide and methylethyl sulfide are included in the reaction vessel. Cyclization of the linear peptide is preferably affected, as opposed to cyclizing the peptide while a part of the peptido-resin, to create bonds between Cys residues. To effect such a disulfide cyclizing linkage, fully protected peptide can be cleaved from a hydroxymethylated resin or a chloromethylated resin support by ammonolysis, as is well known in the art, to yield the fully protected amide intermediate, which is thereafter suitably cyclized and deprotected. Alternatively, deprotection. as well as cleavage of the peptide from the above resins or a benzhydrylamine (BHA) resin or a methylbenzhydrylamine (MBHA), can take place at 0°C with hydrofluoric acid (HF) or TFA, followed by oxidation as described above. The conopeptide derivatives of the present invention may possess biological activity different from Mil or may demonstrate the same or varying degrees of the same biological activity as Mil which is known to block native α3β2-containing nAChRs and with lower potencies, α3β4 containing nAChRs (U.S. Patent 5,780,433 incoφorated herein by reference), as well as other activities described herein. III. Three-Dimensional Structure of Mil A. Overview Another aspect of the present invention is directed to the discovery of the 3 -dimensional structure of Mil and the relationship of its structure to its specificity for the α3β2 subtype of the neuronal nicotinic acetylcholine receptor (nAChR). The discovery of the 3-dimensional structure enables the design of α-4/7 conotoxin peptide analogs and peptide mimetics which will demonstrate the same specificity to neuronal nAChR. Such analogs and peptide mimetics are useful as cardiovascular agents and for treating or detecting small-cell lung carcinoma (SCLC) . Mil has the following amino acid sequence (SEQ ID NO:l): Gly-Cys-Cys-Ser-Asn-Pro-Val-Cys-His-Leu-Glu-His-Ser-Asn-Leu-Cys. The C-terminus may contain a carboxyl or amide group, preferably an amide group. The amino acid at position 6 may be proline or 4-trans-hydroxyproline, preferably proline. The identification of Mil is described in U.S. Patent 5,514,774 and U.S. Patent 5,780,433, incoφorated herein by reference. The use of Mil for: (a) treating a patient having small-cell lung carcinoma (SCLC); (b) inhibiting SCLC proliferation; (c) detecting the presence of SCLC tumors, and (d) detecting the location of SCLC tumors is described in application U.S. Patent 5,595,972, incoφorated herein by reference. The use of Mil to treat CNS disorders is described in U.S. Patent 5,780.433, incoφorated herein by reference. The use of Mil as a cardiovascular agent is described in U.S. Serial No. 60/031,141, filed 18 November 1996, incoφorated herein by reference. B. Determination of the peptide three-dimensional structures using NMR. Different techniques give different and complementary information about protein structure. The primary structure is obtained by biochemical methods, either by direct determination of the amino acid sequence from the protein, or from the nucleotide sequence of the corresponding gene or cDNA. NMR methods may be employed to obtain the secondary and tertiary structure, which requires detailed information about the arrangement of atoms within a protein. NMR methods use the magnetic properties of atomic nuclei. Certain atomic nuclei, such as 'H, l3 C, N, and 31 P have a magnetic moment or spin. The chemical environment of such nuclei can be probed by nuclear magnetic resonance, NMR, and this technique can be exploited to give information on the distances between atoms in a molecule. These distances can then be used to derive a three-dimensional model of the molecule. Most structure determinations of protein molecules by NMR have used the spin of 'H. since hydrogen atoms are abundant in proteins. When protein molecules are placed in a strong magnetic field, the spin of their hydrogen atoms aligns along the field. This equilibrium alignment can be changed to an excited state by applying radio frequency (RF) pulses to the sample. When the nuclei of the protein molecule revert to their equilibrium state, they emit RF radiation that can be measured. The exact frequency of the emitted radiation from each nucleus depends on the molecular environment of the nucleus and is different for each atom, unless they are chemically equivalent and have the same molecular environment. These different frequencies are obtained relative to a reference signal and are called chemical shifts. The nature, duration and combination of applied RF pulses can be varied enormously and different molecular properties of the sample can be probed by selecting the appropriate combination of pulses. In principle, it is possible to obtain a unique signal (chemical shift) for each hydrogen atom in a protein molecule, except those that are chemically equivalent, for example, the protons on the CH, side chain of an alanine residue. In practice, however, such one-dimensional NMR spectra of protein molecules contain overlapping signals from many hydrogen atoms because the differences in chemical shifts are often smaller than the resolving power of the instrument. This problem has been overcome by designing experimental conditions that yield a two-dimensional NMR spectrum, the results of which are usually plotted in a diagram. The diagonal in such a diagram corresponds to a normal one-dimensional NMR spectrum. The peaks off the diagonal result from interactions between hydrogen atoms that are close to each other in space. By varying the nature of the applied RF pulses, these off-diagonal peaks can reveal different types of interactions. Two-dimensional experiments consist of discreet elements: a preparation period; an evolution period where spins are "labeled" as they process in the xy plane according to their chemical shift; a mixing period, during which correlations are made with other spins; and a detection period, where a free induction decay is recorded. Experiments are distinguished by the nature of the correlation that are probed during the mixing period. A COSY (correlation spectroscopy) experiment gives peaks between hydrogen atoms that are covalently connected through one or two other atoms, for example, the hydrogen atoms attached to the nitrogen and Cα atoms within the same amino acid residue. For amino acids with a single H β proton, a standard double quantum filtered COSY (DQF-COSY) recorded in D 2 O may be used. However, for amino acids with a β-methylene group, modified COSY experiments such as P.E. COSY, is better suited. Nuclear overhauser effect spectroscopy (NOESY), on the other hand, gives peaks between pairs of hydrogen atoms that are close together in space even if they are from amino acid residues that are quite distant in the primary sequence. In total correlation spectroscopy (TOCSY), correlations are observed between all protons which share mutual coupling partners, whether or not they are directly coupled to each other. Two dimensional NMR spectra of proteins are inteφreted by the method of sequential assignment. Obviously, two-dimensional NOE spectra, by specifying which groups are close together in space, contain three-dimensional information about the protein molecule. It is far from trivial, however, to assign the observed peaks in the spectra to hydrogen atoms in specific residues along the polypeptide chain because the order of peaks along the diagonal has no simple relation to the order of amino acids along the polypeptide chain. This problem has in principle been solved in the laboratory of Kurt Wϋthrich in the E.T.H., Zurich, where the method of sequential assignment was invented. Sequential assignment is based on the differences in the number of hydrogen atoms and their covalent connectivity in the different amino acid residues. Each type of amino acid has a specific set of covalently connected hydrogen atoms that will give a specific combination of cross-peaks, a "fingeφrint." in a COSY spectrum. From the COSY spectrum, it is therefore possible to identify the H atoms that belong to each amino acid residue and, in addition, determine the nature of the side chain of that residue. However, the order of these fingeφrints along the diagonal has no relation to the amino acid sequence of the protein. The sequence-specific assignment, however, can be made from NOE spectra that record signals from H atoms that are close together in space. In addition to the interactions between H atoms that are far apart in the sequent, these spectra also record interactions between H atoms from sequentially adjacent residues. These signals in the NOE spectra therefore in principle make it possible to determine which fingeφrint in the COSY spectrum comes from a residue adjacent to the one previously identified. In practice, it is difficult to make unique assignments for longer pieces than di- or tri- peptides, since NOE signals also occur between residues close together in space but far apart in the sequence. Therefore, the peptide segments that have been uniquely identified by NMR are usually matched with corresponding segments in the independently determined amino acid sequence of the protein. NMR spectroscopy identifies H atoms in the protein that are close together in space, and this information is then used to derive, indirectly, a three-dimensional model of the protein. Distance constraints can be used to derive possible structures of a protein molecule. The result of the sequence-specific assignment of NMR signals, preferably done using interactive computer graphics, is a list of distance constraints from specific hydrogen atoms in one residue to hydrogen atoms in a second residue. The list contains a large number of such distances, which are usually divided into three intervals within the region 1.8 A to 5 A, depending on the intensity of the NOE peak. This list immediately identifies the secondary structure elements of the peptide or protein molecules because both α helices and β sheets have very specific sets of interactions of less than 5 Λ between their hydrogen atoms. It is also possible to derive models of the three-dimensional structure of the molecule. In order to obtain a more qualitative picture of conformations of a peptide and to generate three-dimensional structures compatible with NMR data, the principles of simulated annealing (Nilges, M. (1988)) may be employed. Simulated annealing calculations carry out an extensive search for all possible three-dimensional conformations that satisfy given experimental data (e.g., NOE-derived distances and dihedral angles) and root mean square (RMS) deviation (described herein) is used as a measure of degree of convergence among those calculated structures. C. Description of Mil Structure Even though α-CT x Mil is a small peptide made of only 16 amino acid residues, it has a well-defined three-dimensional solution structure. In addition to two disulfide bridges which form a hydrophobic Cys knot, there are three helical regions in the structure which contribute to form a very tight conformation. The presence of such stable secondary structures and disulfide bridges allows the multidimensional NMR method to be effective in obtaining a very high resolution structure of the peptide. The amino-terminal region has almost a full turn of α-helix (Cys 2 - Ser 4 ); this is followed by Asn 5 which has backbone dihedral angles of φ= -89° and ψ= +132° (measured from the minimum energy structure), thereby essentially making a 90° turn. The helix with almost two turns (Pro 6 - Glu") is the major secondary structural component of the peptide. This helix is terminated by His 12 (φ = -136°, ψ= +77°; measured from the minimum energy structure) which orients the remaining C-terminal distorted 3 , 0 helix (Ser -Cys 16 ) toward the N-terminus. These two turns associated with Asn 5 and His 12 are perhaps critical residues for the overall fold of the peptide and the presence of such turns is further supported by Car proton shift data presented in Figure 4 (positive shifts compare to the rest having negative shifts) as well as well as 3 J NH . Cfl . coupling constants in Figure 2 (>8.0 Hz coupling constants compare to the rest having <5.0 Hz). A possible function of Asn 5 is to induce a turn between the N-terminal segment and the main α-helix; this function is consistent with the survey by Richardson and Richardson (Richardson. J.S. (1988)) of 215 α-helices from 45 different globular protein structures. They reported a striking preference of 3.5:1 for Asn at the N-cap position and 2.6:1 for Pro at the N-cap + 1 position (helix initiator) for α-helices. With respect to the second turn around His 12 , the function of His may be to bring Cys 3 and Cys 16 close together to form the second disulfide bridge. The space-filling model of α-CT x Mil shown in Figure 7B is oriented to explore the surface distribution of hydrophobic and hydrophilic side chain groups of the molecule. Hydrophobic residues are colored puφle to distinguish them from polar residues which are yellow, or charged residues which are red (positive) and blue (negative). A flat surface located on top of the molecule in puφle is a distinct structural feature representing the cluster of hydrophobic residues exposed to solvent. This hydrophobic surface is formed largely by Gly 1 (excluding the N-terminal amino group), Cys 2 , Cys 3 , Leu 15 , Cys 16 and the disulfide bond between Cys 3 and Cys 16 . This flat surface may be important for ligand-receptor binding through hydrophobic interactions. There is another very distinct surface that consists entirely of hydrophilic residues with both polar and charged groups. On the left side of the model, the cluster of red, blue and yellow represents a region of the turn at His 12 (Glu' '-Asn' 4 ). This highly charged surface, almost perpendicular to the hydrophobic surface, could be responsible for its initial recognition by nAChR based on long-range electrostatic attractions. This potential receptor-binding interface is composed of sequential residues Glu", His 12 , Ser 13 and Asn 14 . In view of the above analysis and the Examples which follow, the conceptually important structural features unique to nAChR targeting α-4/7 conotoxins can be summarized as follows: (1 ) There are two disulfide bridges between the first and third cysteine and the second and fourth cysteine. Several isoforms generated with different disulfide pairings have been tested for their activity towards the nAChRs and shown not to retain the native activity. (2) There is a central α-helix consisting of six residues starting precisely at the position +3 where i is the second cysteine residue and ending at +3 where / is the third cysteine residue. It is believed that this α-helix is essential for the overall backbone conformation and, in particular, its length (six amino acids in Mil) and helical pitch are identified as critical features for targeting nAChRs. NMR data from an α-4/7 conotoxin Mil mutant suggests that the mutation causes the central helix to further extend beyond the j+3 position towards the C-terminal end and thereby causing its helical pitch to change. This structural change is associated with the loss of activity by three orders of magnitude. (3) Two turns at both the N and C terminal ends (N- and C-caps) of the central helix are also unique structural features found in this class of conotoxins. They are intimately linked with the central helix to dictate the three dimensional folding motif and their positions are i+2 for the N-cap where is the second cysteine residue and ; " +4 for the C-cap where y is the third cysteine. Based on the primary sequence comparison among the sequenced α-4/7 conotoxins, there appears to be some preference for both N- and C-cap positions. These are asparagine, which is a good hydrogen bonding partner, and histidine and tyrosine, which are sterically bulky aromatic residues. For example, there are 3.5: 1 preference for Asn at the N-cap position from 215 α-helices subjected for studies by Richardson J.S. et al. (1988). It has been found that mutations at these positions in conotoxins results in the loss of their functions by three orders of magnitude. (4) Proline residue at position /+3 where . is the second cysteine residue is conserved among all α-4/7 conotoxins. Its structural role is mostly likely to prevent continuation of the central helix in the amino terminal direction due to its sterically hindering ring structure. (5) Analysis of the kinetics of binding of Mil indicate that this peptide has two distinct binding surfaces which interact with the α and β subunit of the nAChR. NMR analysis is consistent with this and indicates that one Mil face is hydrophobic in nature consisting of residues i-2, i-l, i (where i is the second cysteine residue), j+1 (where y is the third cysteine) and the fourth cysteine, and the disulfide bond between the second and fourth cysteine residues. The other face is hydrophilic in nature and consists of residues y ' +3,y+4,y+5 andy+6 where j is the third cysteine. Mutational analysis indicates that the hydrophilic face is particularly important for peptide on-rate (peptide docking) and the hydrophobic face is particularly important for peptide off-rate (peptide locking). The use of two physically distinct peptide surfaces to interact with adjacent α and β receptor subunits represents a specific strategy for designing ligands selective for receptors with different combinations of α and β subunits. IV. Interaction of Mil with nAChRs Mil achieves its remarkable subtype specificity through double-faced interacting with the receptor. Mil's rank order of potency suggests that Mil interacts with both α and non-α subunits of nAChRs. Block by Mil is consistent with competitive inhibition as evidenced by voltage- independence of Mil's activity and the ability of competitive antagonist dihydro-β-erythroidine to interfere with Mil's ability to block the receptor. The shape of the time course recovery curve following block of α3β2 and α3β4 receptors by high concentrations of Mil indicates that each of these receptors has two binding sites for Mil, and occupancy of either site by toxin blocks receptor function. There appears to be a general pattern of two ligand binding sites for α/non-α subunit combinations of neuronal nAChRs. This is in contrast to α7 homomeric receptors which may have up to five Ach binding sites. Rates of recovery following block by Mil are markedly longer for α3- containing receptors than for receptors with no α3 subunits. However, the IC 50 for Mil's block of α3β2 receptors is approximately 4 orders of magnitude lower than that of α3β4 receptors. Remarkably, Mil's off-rate is essentially the same for both receptor subtypes and the IC 50 difference is almost entirely accounted for by a difference in Mil's on-rate. Taken together, the data suggest that Mil's on-rate is largely controlled by its interaction with the β subunit whereas interaction with the α subunit is primarily responsible for Mil's off-rate. The kinetics of a synthetic chimera of Mil support this conclusion (Example 10). Mil's selective actions can be accounted for by a "dock and lock" model (Example 12). The 3-dimensional solution structure of Mil taken together with the data discussed in detail herein leads to a two-step dock-and-lock mechanism to explain the remarkable subtype specificity of MIL The NMR structure suggests that Mil is a roughly wedge-shaped peptide with a hydrophilic edge and a hydrophobic edge. The four amino-acids of α-conotoxin Mil (HLEH) which were substituted to FATN are all located on the hydrophilic edge of the peptide. The results with the FATN analog, and the kinetic results obtained with wild-type toxin acting on the α3β2 nicotinic receptor are thus suggestive that the docking face of the toxin is located on the hydrophilic side of the wedge, and that this hydrophilic face interacts with a fast on-time with the β2 subunit. The other side of the wedge which is characterized by hydrophobic residues exposed to solvent, would be an attractive locus for the locking face of α-conotoxin Mil, which is postulated to interact with high affinity on a site on the α3 subunit of nAChR targets of this peptide. A cartoon representation of α-conotoxin Mil interacting with the α3β2 and α3β4 receptors, and of the FATN-α-conotoxin Mil analog is shown in Figure 14. The differential on and off rates for Mil can be used to develop an assay to screen compounds for nAChR antagonistic activity and receptor subtype specificity. The on and off rates for the binding of Mil and a compound to be screened to the α3β2 and α3β4 subunits are determined and compared. If the on rate for the compound is greater than or equal to the on rate for Mil with respect to the α3β2 subtype, the on rate for the compound is less than or equal to the on rate for Mil with respect to the α3β4 subtype and the off rates for the compound are greater than or equal to the off rates for Mil , then the compound is a nAChR antagonist and specific for the α3β2 subtype. If the on rate for the compound is less than or equal to the on rate for Mil with respect to the α3β2 subtype, the on rate for the compound is greater than or equal to the on rate for Mil with respect to the α3β4 subtype and the off rates for the compound are greater than or equal to the off rates for Mil, then the compound is a nAChR antagonist and specific for the α3β4 subtype. In addition, compounds can be developed which modulate the activity of neuronal nAChRs having α3β2 or α3β4 subtype specificity based on the three dimensional structure of Mil as disclosed herein, the structure/biological activity of Mil disclosed herein and molecular modeling analysis. Thus, in accordance with the present invention, compounds are developed which modulate the activity of neuronal nAChRs and which have subtype specificity for either the α3β2 or α3β4 subtype. V. Rational Drug Design The goal of rational drug design is to produce structural analogs of biologically active polypeptides or compounds with which they interact (agonists, antagonists, inhibitors, binding partners, etc.). By creating such analogs, it is possible to fashion drugs which are more active or stable than the natural molecules, which have different susceptibility to alteration or which may affect the function of various other molecules. In one approach, one would generate a three- dimensional structure for MIL such as described herein, or by computer modeling, or by a combination of both approaches. An alternative approach, "alanine scan, " involves the random replacement of residues throughout molecule with alanine, and the resulting affect on function determined. It also is possible to isolate an Mil specific antibody, selected by a functional assay, and then solve its crystal structure. In principle, this approach yields a pharmacore upon which subsequent drug design can be based. It is possible to bypass protein crystallograph altogether by generating anti-idiotypic antibodies to a functional, pharmacologically active antibody. As a mirror image of a mirror image, the binding site of anti-idiotype would be expected to be an analog of the original antigen. The anti-idiotype could then be used to identify and isolate peptides from banks of chemically- or biologically-produced peptides. Selected peptides would then serve as the pharmacore. Anti-idiotypes may be generated using the methods described herein for producing antibodies, using an antibody as the antigen. Thus, one may design drugs which have improved Mil activity or which act as stimulators, inhibitors, agonists, antagonists or Mil or molecules affected by Mil function. In addition, knowledge of the polypeptide sequences permits computer employed predictions of structure- function relationships. A substance identified as a modulator of polypeptide function may be peptide or non-peptide in nature. Non-peptide "small molecules " are often preferred for many in vivo pharmaceutical uses. Accordingly, a mimetic or mimic of the substance (particularly if a peptide) may be designed for pharmaceutical use. The designing of mimetics to a known pharmaceutically active compound is a known approach to the development of pharmaceuticals based on a "lead" compound. This might be desirable where the active compound is difficult or expensive to synthesize or where it is unsuitable for a particular method of administration, e.g., pure peptides are unsuitable active agents for oral compositions as they tend to be quickly degraded by proteases in the alimentary canal. Mimetic design, synthesis and testing is generally used to avoid randomly screening large numbers of molecules for a target property. There are several steps commonly taken in the design of a mimetic from a compound having a given target property. First, the particular parts of the compound that are critical and/or important in determining the target property are determined. In the case of a peptide. this can be done by systematically varying the amino acid residues in the peptide. e.g., by substituting each residue in turn. Alanine scans of peptide are commonly used to refine such peptide motifs. These parts or residues constituting the active region of the compound are known as its "pharmacophore". Once the pharmacophore has been found, its structure is modeled according to its physical properties, e.g., stereochemistry, bonding, size and/or charge, using data from a range of sources, e.g., spectroscopic techniques, x-ray diffraction data and NMR. Computational analysis, similarity mapping (which models the charge and/or volume of a pharmacophore, rather than the bonding between atoms) and other techniques can be used in this modeling process. In a variant of this approach, the three-dimensional structure of the ligand and its binding partner are modeled. This can be especially useful where the ligand and/or binding partner change conformation on binding, allowing the model to take account of this in the design of the mimetic. A template molecule is then selected onto which chemical groups which mimic the pharmacophore can be grafted. The template molecule and the chemical groups grafted onto it can conveniently be selected so that the mimetic is easy to synthesize, is likely to be pharmacologically acceptable, and does not degrade in vivo, while retaining the biological activity of the lead compound. Alternatively, where the mimetic is peptide-based, further stability can be achieved by cyclizing the peptide, increasing its rigidity. The mimetic or mimetics found by this approach can then be screened to see whether they have the target property, or to what extent they exhibit it. Further optimization or modification can then be carried out to arrive at one or more final mimetics for in vivo or clinical testing. VI. Designing Biologically Active Molecules Based on Structure of Mil A. Overview In general, biologically active molecules exert their effect by binding to a receptor. The ability of a given molecule to bind to a receptor is determined by the presence of certain important functional groups and the three-dimensional (3D) presentation of these features by the molecule. A goal of molecular modeling in the context of designing bioactive molecules is to understand the determinants of receptor binding and to sue this knowledge in the design or discovery of novel molecules with the desired activity. The availability of structure-activity data or the structure of a receptor enables the proposal of a pharmacophoric pattern which, in the best case, would include the functionality required for activity and the relative orientation of the functional groups. (Gund, 1979). Recent advances in techniques for generating 3D molecular structures for typical drug-sized organic molecules and for searching databases of 3D structures combined with a 3D pharmacophore hypothesis give the medicinal chemist new tools that can assist in discovering novel active molecules. A 3D pharmacophore can be used as a query to search a database of molecules for those that are predicted to possess the desired activity if the pharmacophore hypothesis is correct. If a receptor structure or receptor site model is available, another type of 3D searching can be used. For this, molecules are selected based on their steric and chemical match to the receptor structure, without the need to propose which interactions might be most important. The methods are complementary and both have assisted in the discovery of active molecules. The significance of the HLEH fragment of Mil has been investigated and its biological activity and receptor binding has been correlated to its structural, chemical and physical attributes (features). These features are used to help understand the range of biological activity observed in a series of compounds, as well as to help guide the design of new compounds with potentially different affinities for nicotinic nAChRs, e.g., compounds with higher affinity for the α3β2 subtype or compounds with higher affinity for the α3β4 subtype. A wide range of experimental and theoretical data is routinely used to develop patterns of such features. This process is generally referred to as pharmacophore mapping and involves three main aspects: finding the features required for biological activity; determining the molecular conformation required (i.e., the "bioactive" conformation); and developing a supeφosition or alignment rule for the series of compounds. The primary information used in pharmacophore mapping is derived naturally from the compounds synthesized in a series and their measured biological activity. From this, structure-activity relations emerge and rudimentary pharmacophore hypotheses can begin to be formulated. If the structure of the macromolecular target or target-ligand complex is known, either as determined experimentally or as computationally modeled, this information is obviously very useful to the pharmacophore-mapping process. A variety of molecular-modeling and computational chemistry techniques can then be applied, in conjunction with the experimental data, to develop pharmacophore models. These techniques range from simple, qualitative molecular graphics comparisons of several members in a series to sophisticated, quantitative methodologies for generating pharmacophore maps and measuring their ability to reproduce experimental results. Pharmacophore mapping is largely a qualitative exercise. Allied with pharmacophore mapping is the field of three-dimensional quantitative structure-activity relations (3D-QSAR). 3D- QSAR techniques attempt to derive and investigate quantitative models of biological activity; namely, models that fit the potency of the studied compounds and that can be used to predict the potency of compounds outside the study set. In fact, the application of many 3D-QSAR methods requires a proposed pharmacophore model. Pharmacophore mapping has its roots in traditional medicinal chemistry and the structure- activity relations derived from the synthesis and biological testing of series of compounds. From the relative measured potencies of individual members of a series, a picture of the types of functionality, and perhaps their spatial relations that are important for activity, begins to emerge. More detailed molecular-modeling studies can then be used to formulate a more rigorous model but even in their absence proposed pharmacophore hypotheses can begin to take shape. Many ligand-design studies employ molecular modeling as well as chemical synthesis to help elucidate pharmacophoric patterns. Structure-activity data and the conformational analysis results are used to propose a bioactive conformation and supeφosition rule for the series. This may be done by using molecular graphics. Another common approach in pharmacophore mapping is the use of structurally rigid molecules to probe requirements for receptor binding. One of the advantages of using less conformationally flexible molecules is that they can more exactly define the bioactive conformation, provided that the rigid molecules selected show good affinity. Use of rigidification to better define pharmacophore space has been used successfully in generating active nonpeptidic compounds from peptide leads. Ku, et al. (1995) and co-workers' recent work with nonpeptide compounds based on cyclic RGD peptide analogues is a good example of this. Receptor site mapping encompasses a variety of computational procedures that identify energetically favorable binding sites on macromolecules. The most straightforward procedures involve "painting" a solvent-accessible surface (or an otherwise generated cast) of the macromolecular target according to empirically determined physical properties, such as electrostatic or lipophilic potential, degree of curvature, and hydrogen-bonding character. Such methods for thus characterizing the surface of a macromolecule are incoφorated in programs such as Grasp (Columbia University), DelPhi (Biosym Technologies), MOLCAD (Tripos. Inc.), and Hint (Virginia Commonwealth University). Subsequent molecule design involves identification or design of ligands that possess features complimentary to the identified surface characteristics. More advanced algorithms involve the actual calculation of interaction enthalpies between the target and potential ligands or fragments. In practice, the coordinates of the protein or protein fragment of interest (which may be rotated or otherwise transformed) are stripped of any undesired ligand (or portion thereof) and/or of any undesired solvent molecules. The coordinates are then processed to attach molecular mechanics parameters to the atomic positions to provide a processed target for mapping. The target may be partitioned into discrete binding sites. The target or partitioned sites thereof are flooded with given functional group fragments that are subsequently allowed to relax into desired locations, as in the program MCSS (Molecular Simulations, Inc.), or are encased within a regular lattice of site points on which single fragment probes are positioned sequentially; examples of programs that exploit the site-lattice algorithm include Grin Grid (Molecular Discovery, Ltd.), Ludi (Biosym Technologies), Leapfrog (Tripos, Inc.), and Legend (University of Tokyo). In both techniques, the enthalpic contribution to binding affinity is estimated with a molecular mechanics force-field, and appropriate positions of selected functional groups are determined systematically. In the site-lattice approach, a box is defined enclosing a desired portion of the target within a defined lattice. The lattice resolution, i.e., the distance between lattice points, may be defined by the practitioner or may be set by the computer program. Likewise, the other parameters of points within the lattice, such as hydrophobicity or other characteristics, may be similarly defined. Probes (i.e., computer models) of one or more selected moieties, functional groups, molecules or molecular fragments are positioned at lattice points and the interaction energy of the probe-target pair is determined for each such lattice point. The data for each selected moiety, functional group, etc. is collected and may be recovered as a data set, visualized on a computer monitor or printed out in various text or graphic formats. As an alternative to positioning a moiety at each of a set of lattice points, one may, as previously mentioned, flood the target (defined by the coordinates as described above) with multiple copies of a selected fragment, moiety, molecule, etc. by superimposing the multiple copies into the vicinity of the protein target. The model is then subjected to group minimization (i.e., molecular mechanics minimization) calculations to identify points or areas of favorable interaction. Data may be handled as in the lattice approach. Receptor site maps provide the seeds for ligand evolution via Database searches, which are described above, and for Grow/link methods for de Novo design of new chemical entities. Programs for ligand growth first access extensible fragment dictionaries in order to place appropriate functional groups at site points. A genetic algorithm or a subgraph isomoφhism protocol is then invoked to connect the fragments with small aliphatic chains or rings. Stochastic enhancements may be introduced by modification of internal degrees of freedom as well as translation and rotation of the candidate model within the binding cavity. The resulting sets of molecules are scored and filtered by functions that consider the steric constraints of the binding site, the complimentarity of electrostatic and hydrophobic interactions, and a solvation estimate. Programs of this type that could be applied include Ludi (Biosym Technologies), Leapfrog (Tripos, Inc.), Legend (University of Tokyo), Grow (Upjohn), Builder/Delegate (University of California, San Francisco), and Sprout (University of Leeds). Clique detection methods provide an alternative strategy to site mapping and ligand growth. DOCK (University of California, San Francisco) and similar programs fill a given binding site with the smallest set of atom-sized spheres possible; a database search then attempts to orient ligands such that the atoms superimpose onto the centers (or "nuclei") of the site-filling spheres. The shape complimentarity of augmented by scoring functions that include the steric requirements of the cavity and a potential energy function. Optimization of ligands (from any source) may be enhanced using the three dimensional structural of MIL Use of receptor site maps or hydropathic profiles of Mil may be used to identify preferred positions for functional group components of ligands, and can be used to filter or constrain conformational searches of ligand structures which would otherwise typically be controlled by minimal steric considerations of the ligand structures themselves. The availability of an explicit binding site also permits one to determine the mode of ligand binding to the target protein via methods that utilize force-fields directly in simulated annealing, distance geometry, Metropolis Monte Carlo, or stochastic searches for binding modes. Examples of programs that can be applied to rationalize ligand binding include Autodock (Scripps Clinic), DGEOM (QCPE #590), Sculpt (Interactive Simulations, Inc.), or any of the molecular dynamics programs described above. Once a tractable set of possible binding orientations is obtained, one can readily identify the appropriate mode of binding through modifications in test ligands designed to alter in a predictable fashion the binding affinity of each model under consideration. For instance, a ligand may be modified to contain a functional group at a position which is inconsistent with one binding model, yet consistent with another model. Binding data can then be used to weed out "disproven" models. Once iterative weeding of unlikely binding modes generates an appropriate model, possibilities for improvement of the lead become readily apparent from the local protein environment. An alternative protocol for ligand optimization involves 3D database searching in conjunction with knowledge of the binding site. Modeling can reveal multiple candidates for the bioactive conformation of a given ligand. A probe for the correct conformation can include a 3D search to identify several constrained mimics of each possible conformer. Structure-activity relationships of the unconstrained ligand would suggest which functional groups should be retained in the constrained mimics. Finally, the steric and electrostatic requirements of the binding site could constitute a filter for prioritizing the resultant possibilities. The structure of Mil permits accurate model-building of homologous peptides and their subsequent use in drug design. The Mil structure may be readily used in the development of a reliable model by either knowledge-based template building methods, or by iterations of directed point mutations followed by local molecular mechanics minimizations. Examples of programs that can be applied in the development of a model of Syk-NC include Composer (Birbeck College), Modeler (MSI), and Homology (Biosym Technologies). The resultant model can then be subjected to any of the CADD techniques described above. B. Utilization of the structure of the α-conotoxin Mil in computer-aided drug design. The availability of the three-dimensional structure of the α-conotoxin Mil makes structure- based drug discovery approaches possible. Structure-based approaches include de Novo molecular design, computer-aided optimization of lead molecules, and computer-based selection of candidate drug structures based on structural criteria. New pepidomimetic modules may be developed directly from the structure of the peptide ligand by design or database searches for conformationally- restricted peptide replacements. Alternatively, structure-based lead discovery may be accomplished using the target protein structure, e.g. receptor, stripped of its ligand. Multiple uncomplexed states of Mil can be generated by several methods to provide additional target conformations. The experimental coordinates and the resulting uncomplexed models can be subjected to techniques such as receptor site mapping to identify sites of favorable interaction energies between the structure of the target protein and potential ligands or chemical moieties ("fragments" or "seeds"). Such evaluation may be followed by procedures such as fragment seed linking and growth. Fragment seed linking refers to methods for designing structures that contain "linked" "seeds," i.e. chemical structures comprising two or more of the mapped moieties appropriately spaced to reach the respective sites of favorable interactions. Growth refers to the design of structures which extend, based on receptor site mapping or to fill available space, a given molecule or moiety. Based on the receptor site mapping data, one may also select potential ligands from databases of chemical structures. Potential ligands, or suboptimal ligands, of whatever source, can be refined by using the receptor site maps to filter multiple ligand conformations and orientations according to energetic preferences. The structure of Mil permits one to generate a high- quality model of Mil by either knowledge-based homology template methods or iterative site- mutations followed by minimizations. The generated structure of Mil may then be treated as an additional protein target by the methods outlined above. These methods and their application to Mil are described in the sections that follow. The amino acid sequence of α-conotoxin Mil has been determined (Cartier, et al.. 1996) and the determinants for specificity (specific amino acid residues) for Mil on α3β2 neuronal nicotinic receptors have been identified (Harvey, et al., 1997, incoφorated herein by reference). Knowledge of the determinants and the binding orientation of a peptide can suggest avenues for conformational restriction and peptide bond replacement. A less biased approach involves computer algorithms for searching databases of three-dimensional structures to identify replacements for one or more portions of the peptide ligand, preferably non-peptidic replacement moieties. By this method, one can generate compounds for which the bioactive conformation is heavily populated, i.e., compounds which are based on particularly biologically relevant conformations of the peptide ligand. Algorithms for this puφose are implemented in programs such as Cast-3D (Chemical Abstracts Service), 3DB Unity (Tripos, Inc.) and MACCS/ISIS-3D (Molecular Design Limited). These geometric searches can be augmented by steric searching, in which the size and shape requirements of the binding site are used to weed out hits that have prohibitive dimensions. Programs that may be used to synchronize the geometric and steric requirements in a search applied to Mil include CAVEAT (University of California, Berkeley). By way of illustration, a non-exclusive list of computer programs for performing rigid three- dimensional searches include the following: 3Dsearch (Seridan, r.p. et al., J. Chen. Inf. Comput. Sci. 29:255. 1989) Aladdin (Van Drie, J.H. et al., J. Comput. Aided Mol. Design 3:225. 1989) UNITY (Tripos, Inc.) MACCS-3D (MDL) CATALYST (Biosyn/MSI, Inc.) All of these searching protocols may be used in conjunction with existing coφorate databases, the Cambridge Structural Database, or available chemical databases from chemical suppliers. As practitioners in this art will appreciate, various computational analyses may be used to determine the degree of similarity between the three-dimensional structure of a given peptide and Mil (or a portion or complex thereof) or another α-conotoxin peptide or portion or complex thereof such as are described herein. Such analyses may be carried out with commercially available software applications, such as CAVEAT (Molecular Simulations, Inc., Waltham. MA) as described by Lauri and Bartlott (1994). CAVEAT is a program that uses a database search to assist in the design of novel molecules. It is a special-puφose program that was written to aid in the design of small molecules that could mimic a protein loop important in a protein-protein interaction. The basic assumption of the programs is that protein-protein recognition is based on specific positioning of amino acid side chains and that the backbone is not critical and could be replaced. The CAVEAT program attempts to find ring systems that can present the side chains in the desired orientation. A CAVEAT database consists of the distance and angle relations of vectors, defined by the exocyclic bonds of ring systems, and an index back to the 3D structure of the ring. A typical query might define the Cα-Cβ vector relations that would be required to present the necessary side chain analogues. Such a vector search could be conducted by most generic database-searching programs discussed in this chapter; however, CAVEAT is optimized for this task. Although the initial CAVEAT applications were for protein mimicry, the program could be useful in any situation for which one needed a novel scaffold to present a set of functional groups in a defined orientation. The latest CAVEAT suite of programs includes the ability to cluster the hits, based on size or substructure similarity, and to rank hits by size, number of atoms at ring fusions, and whether the designed molecule would have eclipsing interactions. Two novel databases are available for use with CAVEAT: Triad, a computer-generated collection of all tricyclic hydrocarbons, and Iliad, a collection of acyclic molecules. Software is also available to create CAVEAT databases from the Cambridge Structural Database. In addition to the retention of potential pharmacophoric elements that are present in the peptide explicitly, the incoφoration into a ligand structure of hydrogen-bond donating or accepting groups that can displace ordered water molecules usually provides a significant entropic gain that leads to a favorable free energy of binding. Such ordered waters are identifiable from the structure, and other ordered waters may be located during computer simulations of a fully solvated structure. Structural coordinates of the peptides of this invention may be stored in a machine-readable form on a machine-readable storage medium, e.g. a computer hard drive, diskette, DAT tape, etc., for display as a three-dimensional shape or for other uses involving computer-assisted manipulation of, or computation based on, the structural coordinates or the three-dimensional structures they define. In order to use the structural coordinates generated for Mil as set forth in Figure 8, it is often necessary to display them as. or convert them to, a three-dimensional shape, or to otherwise manipulate them. This is typically accomplished by the use of commercially available software such as a program which is capable of generating three-dimensional graphical representations of molecules or portions thereof from a set of structural coordinates. By way of illustration, a nonexclusive list of computer programs for viewing or otherwise manipulating protein or peptide structures include the following: Midas (University of California, San Francisco) MidasPlus (University of California, San Francisco) MOIL (University of Illinois) Yummie (Yale University) Sybyl (Tripos, Inc.) Insight/Discovery (Biosym Technologies) MacroModel (Columbia University) Quanta (Molecular Simulations, Inc.) Cerius (Molecular Simulations. Inc.) Alchemy (Tripos, Inc.) LabVision (Tripos, Inc.) Rasmol (Glaxo Research and Development) Ribbon (University of Alabama) NAOMI (Oxford University) Explorer Eyechem (Silicon Graphics, Inc.) Univision (Cray Research) Molscript (Uppsala University) Chem-3D (Cambridge Scientific) Chain (Baylor College of Medicine) O (Uppsala University) GRASP (Columbia University) X-Plor (Molecular Simulations, Inc.; Yale University) Spartan (Wavefunction, Inc.) Catalyst (Molecular Simulations, Inc.) Molcadd (Tripos, Inc. VMD (University of Illinois/Beckman Institute) Sculpt (Interactive Simulations, Inc.) Procheck (Brookhaven National Laboratory) DGEOM (QCPE) RE_VIEW (Brunei University) Modeller (Birbeck College, University of London) Xmol (Minnesota Supercomputing Center) Protein Expert (Cambridge Scientific) HyperChem (Hypercube) MD Display (University of Washington) PKD (National Center for Biotechnology Information, NIH) For example, data defining the three-dimensional structure of an α-conotoxin peptide, or portions or structurally similar homologs or analogs of Mil, may be stored in a machine-readable storage medium and may be displayed as a graphical three-dimensional representation of the peptide structure, typically using a computer capable of reading the data from said storage medium and programmed with instructions for creating the representation from such data. This invention thus encompasses a machine, such as a computer, having a memory which contains data representing the structural coordinates of a composition of this invention, e.g. the coordinates set forth in Example 8, together with additional optional data and instructions for manipulating such data. Such data may be used for a variety of puφoses, such as the elucidation of other related structures and drug discovery (WO 97/08300). In comparative protein modeling, a first set of such machine readable data may be combined with a second set of machine-readable data using a machine programmed with instructions for using the first data set and the second data set to determine at least a portion of the coordinates corresponding to the second set of machine-readable data. For instance, the first set of data may comprise a Fourier transform of at least a portion of the coordinates for Mil set forth in Figure 8, while the second data set may comprise coordinates for a potential analog of MIL In this manner, one may use molecular replacement to exploit a set of coordinates such as set forth in Figure 8 to determine the effect on the structure of such a replacement. Therefore, another object of the invention is to provide a method for determining the three- dimensional structure of a peptide analog or peptide mimetic of Mil using comparative protein modeling techniques and structural coordinates for a composition of this invention. Comparative protein modeling involves constructing a model of an unknown structure using structural coordinates of one or more related peptides. Comparative protein modeling may be conducted by fitting common or homologous portions of the protein or peptide whose three-dimensional structure is to be solved to the three-dimensional structure of known homologous structural elements. Comparative protein modeling can include rebuilding part or all of a three-dimensional structure with replacement of amino acids (or other components) by those of the related structure to be solved. For example, using the structural coordinates of Mil, one may determine the three dimensional structure of a peptide analog of Mil using comparative protein modeling. Those coordinates may be stored, displayed, manipulated and otherwise used in like fashion as the Mil coordinates of Example 8. This invention further provides for the use of the structural coordinates of a peptide of this invention, or portions thereof, to identify reactive amino acids, such as cysteine residues, within the three-dimensional structure, preferably within or adjacent to a receptor binding site; to generate and visualize a molecular surface, such as a water-accessible surface or a surface comprising the spacefilling van der Waals surface of all atoms; to calculate and visualize the size and shape of surface features of the peptide; to locate potential H-bond donors and acceptors within the three-dimensional structure, preferably within or adjacent to a receptor binding site and to calculate regions of hydrophobicity and hydrophilicity within the three-dimensional structure, preferably within or adjacent to a receptor binding site. One may use the foregoing approaches for characterizing the peptide and its interactions with a receptor to design or select compounds of complementary characteristics (e.g., size, shape, charge, hydrophobicity/hydrophilicity, receptor specificity, etc.) to surface features of the peptide, a set of which may be preselected. Using the structural coordinates, one may also predict or calculate the orientation, binding constant or relative affinity of the peptide to a given receptor subtype in the bound state, and use that information to design or select compounds of improved or altered affinity. In such cases, the structural coordinates of the α-conotoxin peptide, or portion thereof, are entered in machine readable form into a machine programmed with instructions for carrying out the desired operation and containing any necessary additional data, e.g. data defining structural and/or functional characteristics of a potential analog, defining molecular characteristics of the various amino acids, etc. Compounds of the structures selected or designed by any of the foregoing means may be tested for their ability to bind to an nAChR, inhibit the binding of an nAChR to a natural or non- natural ligand therefor, and/or inhibit a biological function mediated by an nAChR. This invention also provides peptidomimetic and mimetic methods for designing a compound capable of binding to an nAChR. One such method involves graphically displaying a three-dimensional representation based on coordinates defining the three-dimensional structure of Mil or a portion thereof bound to an nAChR. Interactions between portions of an Mil and the receptor are characterized in order to identify candidate moieties for replacement. One or more portions of Mil which interact with the receptor may be replaced with substitute moieties selected from a knowledge base of one or more candidate substitute moieties, and/or moieties may be added to Mil to permit additional interactions with the receptor. The computational approaches and structural insights disclosed herein, also permit the design or identification of molecules with reduced capacity, or substantial inability, to bind to an nAChR subtype. For example, one may apply the same modeling and computational methods to the data described herein, but with the opposite goal, i.e., to design or identify compounds which lack substantial binding affinity to one or more nAChR subtypes. Such information can be useful in research efforts aimed at identifying antagonists of a single subtype of nAChR. Compounds first identified by any such methods are also encompassed by this invention. For storage, transfer and use with such programs of structural coordinates for a crystalline substance of this invention, a machine-readable storage medium is provided comprising a data storage material encoded with machine readable data which, when using a machine programmed with instructions for using said data, e.g. a computer loaded with one or more programs of the sort identified above, is capable of displaying a graphical three-dimensional representation of any of the molecules or molecular complexes described herein. Machine-readable storage media comprising a data storage material include conventional computer hard drives, floppy disks, DAT tape, CD- ROM, and other magnetic, magneto-optical, optical, floptical and other media which may be adapted for use with a computer. Even more preferred is a machine-readable data storage medium that is capable of displaying a graphical three-dimensional representation of a molecule or molecular complex that is defined by the structural coordinates of Mil or portion thereof, and in particular, structural coordinates of Mil set forth in Fig. 8 ± a root mean square deviation from the backbone atoms of the amino acids of such protein of not more than 1.5 A. An illustrative embodiment of this aspect of the invention is a conventional 3.5" diskette, DAT tape or hard drive encoded with a data set, preferably in PDB format, comprising the coordinates of Fig. 8. In another embodiment, the machine-readable data storage medium comprises a data storage material encoded with a first set of machine readable data which comprises the Fourier transform of the structural coordinates set forth in Appendix I. Appendix II or Appendix III (or again, a derivative thereof), and which, when using a machine programmed with instructions for using said data, can be combined with a second set of machine readable data comprising the X-ray diffraction pattern of a molecule or molecular complex to determine at least a portion of the structural coordinates corresponding to the second set of machine readable data. Examples of systems useful for this aspect of the present invention are shown in WO/97/08300. VII. Definitions The present invention employs the following definitions. "Biological Activity" is used herein to broadly denote function. "Derivative" refers to an amino acid sequence wherein one or more residue of the natural sequence is substituted. "Features" of a compound include any combination of structural, physical or chemical attributes of the compound which are required to elicit a certain biological activity. A peptide "fragment," "portion" or "segment" is a stretch of amino acid residues of at least about two contiguous amino acids, typically at least about three contiguous amino acids and, most preferably, at least about four or more contiguous amino acids. "Neuronal nAChR" refers to a natural nicotinic acetylcholine receptor found in the CNS. "Peptide Analog(s)" refers to molecules which have more, fewer, different or modified residues from an α-conotoxin amino acid sequence. The modifications may be by addition, substitution or deletion of one or more amino acid residues. The modification may include the addition or substitution of analogs of the amino acids themselves, such as peptidomimetics or amino acids with altered moieties such as altered side groups. The analogs may possess functions different from natural α-conotoxin molecule, or may exhibit the same functions, or varying degrees of the same functions. For example, the analogs may be designed to have a higher or lower biological activity, have a longer shelf-life or increased stability or be easier to formulate. From time to time herein, the present analogs are referred to as proteins or peptides for convenience, but contemplated herein are other types of molecules, such as peptidomimetics or chemically modified peptides. A peptide analog may be referred to herein as a peptide for convenience. "Peptide mimetic or mimetic" is intended to refer to a substance which has the essential biological activity of an α-conotoxin peptide. A peptide mimetic or mimetic may be a peptide- containing molecule that mimics elements of peptide secondary structure (Johnson et al., 1993). The underlying rationale behind the use of peptide mimetics or mimetics is that the peptide backbone exists chiefly to orient amino acid side chains in such a way as to facilitate molecular interactions, such as those of ligand and receptor. A peptide mimetic is designed to permit molecular interactions similar to the natural molecule. A mimetic may not be a peptide at all, but it will retain the essential biological activity of a natural conotoxin peptide. "Related Composition" refers to compositions comprising a conotoxin peptide analog or peptide mimetic as an active ingredient. "Simulated annealing" refers to a strategy for superimposing flexible molecules to investigate potential alignments. "Substantially pure" refers to a peptide which is present in the substantial absence of other biological molecules of the same type; it is preferably present in an amount of at least about 85% purity and most preferably at least about 95% purity. "Substantially similar activity" refers to the activity of a modified peptide, with reference to a natural α-conotoxin peptide. The modified peptide will have substantially similar activity. The modified peptide may have an altered amino acid sequence and/or may contain modified amino acids. In addition to the similarity of activity, the modified polypeptide may have other useful properties, such as a longer half-life. Alternatively, the similarity of activity of the modified peptide may be higher than the activity of the natural α-conopeptide. The modified peptide is synthesized using conventional techniques or is encoded by a modified nucleic acid and produced using conventional techniques. The modified nucleic acid is prepared by conventional techniques. A nucleic acid with an activity substantially similar to the natural α-conotoxin gene function may be used to produce the modified peptide described above. "Subtype of nAChR" refers to different molecular forms of nicotinic acetylcholine receptors. VIII. Preparation of peptide analogs and mimetics. Peptide analogs and peptide mimetics of the present invention specific for the α3β2 or α3β4 subtypes of the nAChR. are prepared on the basis of procedures described herein, using conventional techniques, such as drug modeling, drug design and combinatorial chemistry. Suitable techniques include, but are not limited to those described in U.S. Patent 5,571,698, U.S. Patent 5,514,774, WO 95/21 193 (Ecker, et al. (1995); Persidis (1997); Johnson et al. (1993); Sun et al. (1993)) and the references cited therein which are all incoφorated herein by reference. The development of peptide analogs and peptide mimetics are prepared using commercially available drug design software, including those set forth in Persidis et al. (1997). These peptide analogs and peptide mimetics have the substantially similar activities as an α-conotoxin described herein and in the published literature. IX. Preparation of pharmaceutical compositions containing peptide analogs and mimetics Pharmaceutical compositions containing a compound of the present invention as the active ingredient can be prepared according to conventional pharmaceutical compounding techniques, such as those in Remington 's Pharmaceutical Sciences (1990). Typically, an antagonistic amount of the active ingredient will be admixed with a pharmaceutically acceptable carrier. The carrier may take a wide variety of forms depending on the form of preparation desired for administration, e.g., intravenous, oral or parenteral. For oral administration, the compounds can be formulated into solid or liquid preparations such as capsules, pills, tablets, lozenges, melts, powders, suspensions or emulsions. In preparing the compositions in oral dosage form, any of the usual pharmaceutical media may be employed, such as, for example, water, glycols. oils, alcohols, flavoring agents, preservatives, coloring agents, suspending agents, and the like in the case of oral liquid preparations (such as, for example, suspensions, elixirs and solutions); or carriers such as starches, sugars, diluents, granulating agents, lubricants, binders, disintegrating agents and the like in the case of oral solid preparations (such as, for example, powders, capsules and tablets). Because of their ease in administration, tablets and capsules represent the most advantageous oral dosage unit form, in which case solid pharmaceutical carriers are obviously employed. If desired, tablets may be sugar-coated or enteric-coated by standard techniques. For parenteral administration, the compound may be dissolved in a pharmaceutical carrier and administered as either a solution or a suspension. Illustrative of suitable carriers are water, saline, dextrose solutions, fructose solutions, ethanol, or oils of animal, vegetative or synthetic origin. The carrier may also contain other ingredients, for example, preservatives, suspending agents, solubilizing agents, buffers and the like. When the compounds are being administered intrathecally, they may also be dissolved in cerebrospinal fluid. The active ingredients, which are peptides, can also be administered in a cell based delivery system in which a DNA sequence encoding an active agent is introduced into cells designed for implantation in the body of the patient, especially in the spinal cord region. Suitable delivery systems are described in U.S. Patent No. 5,550,050 and published PCT Application Nos. WO 92/19195, WO 94/25503, WO 95/01203, WO 95/05452, WO 96/02286, WO 96/02646, WO 96/40871 , WO 96/40959 and WO 97/12635. Suitable DNA sequences can be prepared synthetically for each active ingredient on the basis of the developed sequences and the known genetic code. The active ingredients of the present invention are administered in an amount sufficient to generate the desired effect. The dosage range at which these agents exhibit this effect can vary widely, depending upon the severity of the patient's defect, the patient, the route of administration and the presence of other underlying disease states within the patient. Typically, the active ingredients exhibit their therapeutic effect at a dosage range from about 0.05 mg/kg to about 250 mg/kg, and preferably from about 0.1 mg/kg to about 100 mg/kg of the active ingredient. A suitable dose can be administered in multiple sub-doses per day. Typically, a dose or sub-dose may contain from about 0.1 mg to about 500 mg of the active ingredient per unit dosage form. A more preferred dosage will contain from about 0.5 mg to about 100 mg of active ingredient per unit dosage form. Dosages are generally initiated at lower levels and increased until desired effects are achieved. EXAMPLES The present invention is further detailed in the following Examples, which are offered by way of illustration and are not intended to limit the invention in any manner. Standard techniques well known in the art of the techniques specifically described below are utilized. EXAMPLE 1 Synthesis of α-Conotoxin Mil and Mil Derivatives MIL originally isolated from Conus magus, was chemically synthesized using standard Fmoc chemistry on an ABI model 431 peptide synthesizer and properly folded to its biologically active conformation using two-step oxidation protocols (Monje et al., 1993). Once purified, the peptide's identity with the native Mil was confirmed as described by Cartier et al., 1996. Mil derivatives were chemically synthesized and folded in the similar manner. Initial derivatives were prepared with alanine substitutions for each non-cysteine amino acid residue, (i.e., an alanine walk) in order to determine the effect of substitutions at each residue. Additional derivatives or analogs are prepared in the similar manner by substituting any amino acid for the amino acid residues of Mil except the cysteine and His, 2 amino acid residues. EXAMPLE 2 Biological Activity of α-Conotoxins Mil and Mil Derivatives. Peptide Analogs and Peptide Mimetics Each of the Mil derivatives, peptide analogs and peptide mimetics were tested for activity on neuronal nAChRs in Xenopus laevis oocytes containing the α3 and β2 subunits of nAChRs as described by Cartier et al. (1996). Briefly, oocytes (1-2 days after harvesting) were injected with cRNA encoding the α3 and β2 subunits of rat nAChRs and incubated at 25° C for 1-4 days prior to use. Electrophysiological currents were measured using conventional techniques, such as described in Cartier et al. (1996). Measurements were made for oocytes perfused with acetylcholine as controls and for oocytes incubated with either Mil or the analogs prepared in Example 1. Figure 1 shows the effect of alanine substitutions in the conopeptide Mil on the ability of the analogs to block acetylcholine-gated currents in voltage-clamped Xenopus oocytes expressing cloned rat α3 and β2 subunits. Most substitutions decreased Mil's potency 4-fold or less. The notable exceptions are: Glu, ,: 8-fold decrease; Hist,: 25-fold decrease; His, 2 : >10 4 -fold decrease. In addition, it was seen that Asn 5 (which can be substituted with His) and Pro 6 along with His, 2 (which can be substituted with Asn) were essential for high affinity binding to the α3β2 nAChR. Similar effects are seen when other amino acids are substituted for the various residues of MIL The more conservative the substitution of amino acid residues in the analogs, the more similar the activity which is seen for the synthesized analogs. Sequences of several α-conotoxins and their biological activity is shown in Shon et al. (1997). EXAMPLE 3 NMR Spectroscopy N R Spectroscopy. A sample containing 8 mg. of the peptide was dissolved in 500 μL of 5mM sodium phosphate buffer made of 90% H 2 0 and 10% D 2 O (Cambridge Isotope Laboratory). The final pH of the peptide solution was 3.3, and the peptide concentration was 9.4 mM. For experiments requiring "100%" replacement of labile amide hydrogens with deuterons, the sample was lyophilized and dissolved in D 2 O (99.96% isotope enriched). After being allowed to sit overnight at room temperature, the sample was again lyophilized and dissolved in D 2 O (99.996% isotope enriched). All NMR data were obtained with a Varian 600 MHZ Unity Plus spectrometer equipped with a pulsed-field-gradient (z) unit. A set of 2-D 'H NMR experiments were carried out at 275 K: these were NOESY (Jeener, J. (1979); Kumar, A. (1980); Macura, S. (1981)) with mixing times of 75, 150, 250 and 350 ms, TOCSY (Braunschweiler, L. (1983); Davis, D.G. (1985)) with a mixing time of 64 ms, DQF-COSY (Piantini, U. (1982); Ranee, M. (1983)) and PE-COSY (Muller, L. (1987)). All spectra were recorded in a phase sensitive mode (States, D.J. (1982)) with a spectral width of 6600 Hz and 4K data points except for PE-COSY (8K data points). Eight to 32 scans were signal averaged for each free induction decay (FID) with a relaxation delay of 2 s; each 2-D experiment was completed with 400-512 FIDs. In NOESY experiments, the solvent signal was suppressed by gradient echo combined with the WATERGATE sequence (Piotto, M. (1992)). A "flip-back" pulse was inserted right after the mixing time to restore the residual magnetization along the z-axis. In TOCSY, a spin lock field of 7.7 kHz necessary for the coherence transfer among scalar-coupled 'H spins was generated with the DIPSI-2 sequence (Rucker. S. (1989)), and water suppression was obtained using the WATERGATE sequence along with minimum presaturation set at the residual water signal during the relaxation delay. In PE-COSY, water suppression was not needed since the sample was prepared in 100% D 2 O. A mixing pulse of 30° was used for PE-COSY, and each FID was recorded with 32 scans to compensation for the sensitivity loss due to the small mixing pulse. 2-D NMR data were transferred to an SGI workstation (Indigo 2 ) and were processed using Felix 95.0 (MSI, San Diego) except for PE-COSY, which was processed using VNMR 5.10 (Varian). FIDs were apodized with a window function (90° and 135° shifted sine bell) in both dimensions prior to Fourier transformation. Each Fourier transformed FID was baseline corrected by applying a third-order polynomial, and each dimension was referenced to a chemical shift value of 4.76 ppm at the residual water signal. Even though complete resonance assignments were easily obtained except for the Cβ protons of Ser 13 (not observed), the 1-D spectrum of the peptide in the amide proton region had a few resonance overlaps. Starting with the unique reside Val 7 , identified on the basis of its spin type, sequential d aN NOE connectivity was traced through the carboxyl terminal residue Cys 16 . Along the trace, resonance assignment for each residue was confirmed on the basis of its spin type obtained from the TOCSY experiment. The remaining N-terminal residues were also assigned on the basis of sequential d aN NOE connectivity starting from Asn 5 , whose spin system was identified from NOE cross peaks between its amide proton and β protons as well as its side chain γNH2 protons. In addition, sequential NOEs arising from neighboring amide protons. -/ NN , confirmed the above resonance assignments. Figure 2 depicts two traces of sequential NOE d a connectivities which extend from Cys 2 to Asn 5 and from Val 7 to Cys 16 . EXAMPLE 4 Generation of Dihedral and Distance Restraints NOE cross peak volumes were measured from NOESY data with four different mixing times using FELIX 95.0. NOE buildup curves were then fitted with a second-order polynomial and exact distances were generated for all assigned NOE cross peaks. A distance of 1.8 A was used as an appropriate reference for nonoverlapping geminal Cβ proton cross peaks, as well as for lower distance bounds. Several volumes of nonoverlapping geminal Cβ proton cross peaks were averaged and used for calibrating measured NOE volumes. A pseudoatom correction of 1 A (Wuthrich, K. (1983)) was added to the upper limits of those NOE cross peaks involving spectroscopically degenerate methyl and methylene protons. As for dihedral restraints, J J HN . Ha coupling constants were measured from a 1 -D 'H spectrum recorded with 32K data points and converted to φ dihedral angles centered at -120° (±30°) for 3 JHN . Ha >8.0 Hz and -60° (±30°) for J HN . Ha <5.0 Hz (Pardi, A., et al. (1984)). ^J aβ coupling constants were also measured form PE-COSY recorded from the sample whose amide protons were completely exchanged out with deuterons in " 100%" D 2 0. The measured 3 J α/5 coupling constants derived from those residues with an AMX spin system and with nonoverlapping geminal β protons were used for defining χ, dihedral angles in combination with the sequential -/ HN.Hα and d aβ NOE cross peak intensities (Hyberts, S. (1987); Wagner, G. (1987)). Initially, 99 interresidue NOE cross peaks with a high level of confidence in their assignments were selected and corrected for those NOE cross peaks containing at least one pseudoatom. Fifteen chirality restraints and 11 φand 5 χ, dihedral angles were also included in the restraint file for generating an initial set of 10 structures using the DGII (Havel, T. (1991)) module of the Insightll program (MSI, San Diego). All structures generated by the DGII calculations had similar overall backbone folding patterns, and thus the lowest energy structure with the minimum number of NOE violations was chosen and subjected to an iterative relaxation matrix approach (IRMA). This procedure improves the accuracy and precision of inteφroton NOE-derived distance restraints by evaluating the full relaxation network of spins in a molecule (Boelens, R. (1988). At this stage, the total of 158 NOE-derived inteφroton distances (including intraresidue NOEs with pseudoatom correction) along with 16 dihedral angle and 15 chirality restraints were subjected to IRMA and restrained molecular dynamics (RMD) followed by energy minimization steps. Any distances derived from NOEs containing at least one pseudoatom were not treated by IRMA, and therefore those were not refined by the process. Each cycle of IRMA took experimental NOE intensities measured as a function of mixing time and merged them with the calculated theoretical NOE intensity values for the model structure. A new set of distance restraints was then deduced from this mixed NOE intensity matrix. A rotational correlation time of 1.5 ns, estimated from NOE buildup curves of nonoverlapping geminal β protons, and diagonal leakage rate of 1.0 s were used in each IRMA cycle. After each cycle of IRMA, the structure was subjected to RMD and energy minimization steps using a Lennard- Jones potential with a 12.0 A cutoff. Five cycles of 1,000 steps of RMD of 1.0 fs for a duration of 5 ps was calculated at 700 K followed by cooling over 5 ps at 500 k and another 5 ps at 300 K. The structure was minimized using 100 steps of steepest descents followed by 1500 steps of conjugated gradient minimization. Four IRMA/RMD cycles were carried out and the convergence was achieved with the final R-factors (a measure of the difference in the theoretical and experimental NOE intensities) reaching 0.407 for R, and 0.007 for R 6 (reflects 1/r 6 relationship between NOE intensity and distance, r) (Gonzales, C. (1991)). This IRMA/RMD protocol is well documented in the manual provided by the Insightll software for refining distances converted from experimentally measured NOE cross peaks. It was obvious from both 3 J NH . Ca . coupling constants recorded from a high-resolution 1-D spectrum and short- and medium-range NOE cross peaks from NOESY experiments that a large portion of the peptide was helical. Nine of 16 residues were determined to have 3 J NH .c « coupling constants of less than 5.0 Hz and among those nine resides we have identified short- and medium- range NOE cross peaks, d m , d m(l l+2) , d a , and -/ αN(U+2) , very typical of an a-helix (Wuthrich, K. et al. (1986)). Figure 2 displays those NOE cross peaks according to their intensities along with 3 J NH . Cα coupling constants used to generate dihedral angle restraints. In addition to the observed NOE cross peaks, Cα proton chemical shifts relative to random-coil values (Wuthrich, K. et al. (1986)) are a good assessments for identifying local helical components in peptides and proteins (Wishart, D.S. et al. (1991); Rothemund, S. et al. (1996)). The plot shown in Figure 4 strongly suggests that the peptide contains a large portion of helical conformation throughout the sequence except for residues Asn 5 and His 12 . The backbone conformation of these residues could deviate from a helical conformation on the basis of their positive shifts in the plot. EXAMPLE 5 Molecular Modeling. Distance Geometry and Simulated Annealing Computer models of α-CT x Mil were constructed and manipulated using the Insightll and Discover programs (MSI, San Diego) on a Silicon Graphics workstation. Simulated annealing (SA) computations were conducted on a Cray C-90 supercomputer at the San Diego Supercomputer Center. The consistent valence force field of Hagler and co-workers (Dauber-Osguthoφe, P. (1988)) was employed for both the DGII and simulated annealing calculations. An extended molecule with two disulfide bridges was constructed as the triply charged cation with full positive charges on the N-terminal nitrogen and the imidazole side chains of His 9 and His 12 . A triangle inequality bound smoothing and four-dimensional embedding procedure followed by prospective metrication and majorization with a constant weighting scheme was used for DGII calculations with default settings except for an initial energy of 750 kcal/mol and 20,000 steps of built-in simulated annealing with a step size of 0.3 ps. In order to develop a more qualitative picture of the conformation(s) of α-CT x Mil and to generate three-dimensional structures compatible with the NMR data, a protocol based generally on the principles of simulated annealing as developed by Clore and Gronenborn and co-workers (Nilges, M. (1988)) was employed. The calculations incoφorated two notable departures from previous work. First, the inteφroton distances were introduced in a biphasic manner during high- temperature molecular dynamics (MD); initially they involved only backbone protons, but then subsequently they involved side chain protons. Second, transition from a quartic to a Lennard- Jones nonbonded potential was achieved in a final dynamics phase concomitant with final maturation of the nonbond energy factor. A total of 50 rounds of SA were conducted in order to sample as large a conformational space as practical given computer processor and disk limitations. A final minimization with a convergence criterion of the large derivative not exceeding 0.01 kcal mol "1 A "1 was conducted. A total of 50 structures resulted from the SA calculations were described using 154 distance (85 intraresidue, 42 sequential, 22 medium range and 5 long range), 14 dihedral and 15 chirality restraints. An RMS deviation-based family clustering scheme was used which resulted in the grouping of these structures into 30 families spanning the energy range 396-5360 kcal/mol with the two families of lowest energy encompassing 18 of the 50 structures. Structural statistics of these five families, with minimum energy structure (MES) energies within 22 kcal/mol of the overall MES are given in Table 1. The next lowest energy family (family 3) was at 79 kcal/mol relative to the overall MES. By interactive graphical inspection, we have observed that many of the higher energy family representatives (families 3-30) contained unusually high internal energy terms or pathological features (e.g., broken bonds, knots involving backbone and cystine bridges). An interesting structural pathology is observed in structure 8 of family 1 (PDB accession code lm2c) wherein L -α- Cys 8 is inverted to D -α-Cys 8 . This structure is included because it fits the criterion used for classifying family 1 but in no way influenced the final model and underscores the important of maintaining proper chirality constraints during SA. In Figure 5, the structures of family 1 were superimposed to demonstrate how well they converge in the structural calculations with a given set of experimentally determined and refined restraints. As shown in Table 1, the pairwide backbone and heavy atom RMS deviations among those 14 structures in family 1 calculated over residues Cys -Cys 16 (Gly 1 is excluded due to its mobility) are 0.76 ± 0.31 and 1.35 ± 0.34 Λ, respectively. In the SA procedure, no particular restrains was employed to force backbone amide bonds to the transconfiguration. All amides bonds in all residues of all structures in this family are trans, and all 14 structures in family 1 have almost the same backbone dihedral angles with the exception of Gly 1 , as seen from high values of the backbone angular order parameters (Hyberts, S. et al (1992); Pallaghy, P. et al (1993)). in Figure 6A,B. However, this consistency of the backbone dihedral angles is not maintained at the level of the χ, side chain dihedral. High angular order parameters as seen in Figure 6C for residues 2, 5, 9 and 10 indicate that all structures of family 1 have equivalent side chain rotameric states. All other residues have multiple side chain rotameric states which generally fall into the gauche ' , gauche +, or trans classification. The structures of family 1 are well built as judged by the range and magnitude of the energetic contributions detailed in Table 1. Clearly, important energetic contributions to the maintenance of these structures are found in the nonbonded terms, both van der Waals and Coulombic. These modeling studies were conducted in vacua, and any modulation of the effective dielectric constant by either empirical solvation methods or explicitly solvent inclusion should serve only to decrease the net effect of electrostatics for this simple constrained peptide. TABLE Structural Statistics for the Two Lowest Energy Families of Mil Resulting from Simulated Annealing family 1 2 no. of structures 14 4 energy components α -^total 453±30 476±48 • ^bond 28±2 28±1 Wangle 161±12 165±14 E -'-'torsion 50±6 63±14 -' F-'out ot plane 4±1 4±1 -" Fvan der Waals 75±8 84±17 -^Coulomb 135±9 132±9 - F c 'torce 75±20 77±21 -" Ftotal+torce 527±47 553±68 pairwide RMS b backbone (2-16) 0.76±0.31 0.99±0.25 heavy atoms (2-16) 1.35±0.34 1.61±0.25 NMR violations >0.2A b av no. of violations per structure 16.64±3.13 16.50±3.64 av violation 0.30±0.11 0.31±0.11 dihedral violations >10° l/14 c (Cys 2 χ,) l/4 d (Cys 2 χ,) 2/4 d (His 9 χ,) minimum energy structure -^total 396 418 -^ Ftotal+torce 440 463 no. of violations >0.2 A 13 21 av violation >0.2 A b 0.25±0.04 0.32±0.12 max violation b 0.35 0.66 a All energies in kcal/mol. b All distance in A. c Number of structures in family 1. d Number of structures of a family 2. EXAMPLE 6 Three Dimensional Solution Structure Even though α-CT x Mil is a small peptide made of only 16 amino acid residues, it has a well-defined three-dimensional solution structure. In addition to two disulfide bridges which form a hydrophobic Cys knot, there are three helical regions in the structure which contribute to form a very tight conformation. The presence of such stable secondary structures and disulfide bridges allows the multidimensional NMR method to be effective in obtaining a very high resolution structure of the peptide. The amino-terminal region has almost a full turn of α-helix (Cys 2 - Ser 4 ); this is followed by Asn 5 which has backbone dihedral angles of φ= -89° and ψ= +132° (measured from the minimum energy structure), thereby essentially making a 90° turn. The helix with almost two turns (Pro 6 - Glu") is the major secondary structural component of the peptide. This helix is termination by His 12 (φ= -136°, ψ= +77°; measured from the minimum energy structure) which orients the remaining C-terminal distorted 3, 0 helix (Ser' -Cys 16 ) toward the N-terminus. These two turns associated with Asn 5 and His 12 are perhaps critical residues for the overall fold of the peptide and the presence of such turns is further supported by Ca proton shift data presented in Figure 4 (positive shifts compare to the rest having negative shifts) as well as well as 3 J NH . CΛ coupling constants in Figure 2 (>8.0 Hz coupling constants compare to the rest having <5.0 Hz). A possible function of Asn 5 is to induce a turn between the N-terminal segment and the main α-helix; this function is consistent with the survey by Richardson and Richardson (Richardson, J.S. et al (1988)) of 215 α-helices from 45 different globular protein structures. They reported a striking preference of 3,5: 1 for Asn at the N-cap position and 2.6: 1 for Pro at the N-cap + 1 position (helix initiator) for α-helices. With respect to the second turn around His' 2 , the function of His may be to bring Cys 3 and Cys 16 close together to form the second disulfide bridge. The space-filling model of α-CT x Mil shown in Figure 7B is oriented to explore the surface distribution of hydrophobic and hydrophilic side chain groups of the molecule. Hydrophobic residues are colored puφle to distinguish them from polar residues which are yellow, or charged residues which are red (positive) and blue (negative). A flat surface located on top of the molecule in puφle is a distinct structural feature representing the cluster of hydrophobic residues exposed to solvent. This hydrophobic surface is formed largely by Gly' (excluding the N-terminal amino group), Cys 2 , Cys 3 , Leu 15 , Cys 16 and the disulfide bond between Cys 3 and Cys 16 . This flat surface may be important for ligand-receptor binding through hydrophobic interactions. There is another very distinct surface that consists entirely of hydrophilic residues with both polar and charged groups. On the left side of the model, the cluster of red, blue and yellow represents a region of the turn at His 12 (Glu 1 '-Asn' 4 ). This highly charged surface, almost peφendicular to the hydrophobic surface, could be responsible for its initial recognition by nAChR based on long-range electrostatic attractions. This potential receptor-binding interface is composed of sequential residues Glu", His 12 , Ser 13 and Asn 14 . EXAMPLE 7 Electrophysiology cDNA clones encoding nAChR subunits were provided by S. Heinemann and D. Johnson (Salk Institute, San Diego, CA). cRNA was transcribed using RiboMAX™ large scale RNA production systems (Promega, Madison, WI). Diguanosine triphosphate (Sigma, St. Louis, MO) was used for synthesis of capped cRNA transcripts according to the protocol of the manufacturer. Plasmid constructs of mouse and rat nAChR subunits were as conventionally described: l, βl, γ, δ; α2; α3; α4;α7; α9; β2; β4. cRNA was injected with a Drummond 10 μl microdispenser (Drummond Scientific, Broomall, PA) using conventional techniques. It was fitted with micropipettes pulled rom glass capillaries provided for the microdispenser. The pipette tips were broken to an OD of 22-25 μm and back-filled with paraffin before mounting on the microdispenser. cRNA were drawn into the micropipette and 50 nl, containing 5 ng cRNA subunit, was injected into each oocyte. In the case of muscle subunits, 0.5-5 ng of each subunit was injected. Oocytes were harvested from Xenopus frogs, cut into clumps of 20-50 oocytes, and placed in a 50 ml polypropylene tube (Sarstedt) containing 580 U/ml type 1 collagenase (Worthington Biochemical, Freehold, NJ) in OR-2 (82.5 mM Nacl, 2.0 MM KC1, 1.0 mM MgCL and 5mM HEPES, pH -7.3). The tube was incubated for 1-2 hr on a rotary shaker rotating at 50 rpm. Halfway through the incubation, the solution was exchanged with fresh collagenase solution. The oocytes were then washed with six to eight -50 ml volumes of OR-2, transferred to a 60 mm x 15 mm petri dish containing ND-96 (96.0 mM Nacl, 2.0 mM KC1, 1.8 mM CaC , 1.0 mM MgCl 2 , 5mM HEPES, pH = 7.1-7.5)/Pen/Strep/Gen (100 U/ml penicillin G (Sigma), 100 μg/ml streptomycin (Sigma), and 100 μg/ml gentamycin (Gibco BRL, Grand Island. NY). The oocytes were visually examined and only healthy appearing oocytes were transferred to a second dish containing ND96 and antibiotics. Oocytes were injected 1-2 days after harvesting and recordings were made 1-7 days after injection. An injected oocyte was placed in a -30 μl recording chamber consisting of a cylindrical well (~4 mm dia x 2 mm deep) fabricated from Sylgard, and gravity-perfused with either ND96 or ND96 containing 1 μM atropine (ND96A) at a rate of -1 ml/min. All toxin solutions also containing 0.1 mg/ml bovine serum albumin (BSA) to reduce nonspecific adsoφtion of peptide. The perfusion medium could be switched to one containing peptide or acetylcholine (ACh) by use of a distributor valve (Smart Valve, Cavro Scientific Instruments, Sunnyvale, CA) and a series of three-way solenoid valves (model 161T031, Neptune Research, Northboro, MA). ACh-gated currents were obtained with a two-electrode voltage-clamp amplifier (model OC-725B, Warner Instrument Coφ., Hamden, CT) set for "fast" clamp and with clamp gain at maximum (x 2000). Glass microelectrodes, pulled from fiber-filled borosilicate capillaries (1 mm OD x 0.75 mm ID, WPI Inc., Sarasota, FL) and filled with 3 M KC1, served as voltage and current electrodes. Resistances were 0.5 - 5 MΩ for voltage, and 0.5 - 2 MΩ for current, electrodes. The membrane potential was clamped at -70 mV, and the current signal, recorded through virtual ground, was low-pass filtered (5 Hz cut-off) and digitized at a sampling frequency of 20 Hz. The solenoid perfusion valves were controlled with solid state relays (model ODC5 in a PB16HC digital I/O backplane, Opto 22, Temecula, CA). A/D conversion and digital control of solenoid valves were performed with a Lab-LC or Lab-NB board (National Instruments, Austin, TX) in a Macintosh (Quadra 630 or Ilex) computer. The computer communicated with the distributor valve via its serial port. Data acquisition and activities of the distributor and solenoid valves were automatically controlled by a home-made virtual instrument constructed with the graphical programming language LabVIEW (National Instruments, Austin. TX). To apply a pulse of ACh to the oocyte, the perfusion fluid was switched to one containing ACh for 1 sec. This was automatically done in intervals of 1 -5 min. The shortest time interval was chosen such that reproducible control responses were obtained with no observable rundown. This time interval was dependent upon the nAChR subtypes being tested. The concentration of ACh was 1 μM for oocytes expressing αl βγδ, 1 mM for α7, and 300 μM for all others. The ACh was diluted in ND96A for all except α7, in which case the diluent was ND96. For control responses, the ACh pulse was preceded by perfusion with ND96 (for α7) or ND96A (all others). No atropine was used with oocytes expressing α7, since it has been demonstrated to be an antagonist of these receptors. (Gerzanich, 1994) For responses in toxin (test responses), the perfusion solution was switched to one containing toxin while maintaining the interval pulses of ACh. Toxin was continuously perfused until equilibrium was reached. All ACh pulses contained no toxin, for it was assumed that little, if any, bound toxin would have washed away in the brief time (<2 sec) it takes for the responses to peak. The peak amplitudes of the ACh-gated current responses were measured by the virtual instrument. All recordings were made at room temperature (-22° C). An injected oocyte was voltage-clamped at a membrane potential of -70 mV and response to ACh was measured every 5 min. After several control responses were determined at -70 mV, the membrane potential was stepped to the test potential for 1 min. beginning 10 sec. before application of ACh. The membrane potential was returned to -70 mV between each test. The test potential was varied, in sequence, from -90 mV to -10 mV in steps of 10 mV followed by a final test at a membrane potential of +10mV. After the test sequence, the perfusion solution was switched to one containing toxin. After equilibrium was achieved, the test sequence was repeated. All data analysis was performed with Prism software (GraphPad Software Inc., San Diego, CA) running on an Apple Power Macintosh 6100/66 equip with a 486 Intel processor and Windows 3.1™. The average of three control responses just preceding a test response was used to normalize the test response to obtain "% response" or "% block." Each data point of a dose response curve represents the average ± standard error of at least three oocytes. Dose response curves were fit to the equation:%Response = 100/(l+(toxin)/IC 50 ) nH where n H is the Hill coefficient. Kinetic traces represent the data from one experiment only. All experiments were repeated on at least three oocytes. Reported kinetic parameters are the average from all experiments performed on that subtype. The data describing the time course of toxin inhibition were fit to an equation describing a simple exponential association of the form: Y = (l-e "kt ). The data describing the time course of recovery from toxin inhibition at low toxin concentrations were fit to an equation describing a simple exponential dissociation of the form: Y = e "kt . The data describing the time course of recovery from toxin inhibition at high toxin concentrations were fit to an equation describing a complex exponential dissociation of the form: Y = (l-(l-e "kt ) 2 ). EXAMPLE 8 Subtype specificity of Mil nAChR subunits expressed in Xenopus oocytes were used to quantitate the potency of Mil at various nAChR combinations. Each subtype was inhibited in a dose-dependent manner by Mil but with widely differing potencies (Fig. 9). α-conotoxin Mil most potently inhibited the α3β2 combination with 200-fold to > 10,000-fold less potency at other subtypes (Table 2). TABLE 2 Inhibition of nAChR Subtypes by Alpha-conotoxin Mil Many small molecules act as non-competitive inhibitors of nAChRs by blocking the open channel. Open channel block of nAChRs is generally dependent upon membrane potential. We examined whether Mil block of the α3β2 nAChR was voltage-dependent. To accomplish this, acetylcholine response of α3β2 nAChRs to acetylcholine was measured over a range of membrane potentials both in the presence and absence of Mil at its approximate IC 5ϋ (500 pM). As shown in Fig. 2, blockade by α-conotoxin Mil shows no voltage dependence over the range tested (-100 mV to +lO mV). To further examine the mechanism of action of Mil, the differing off-rates of dihydro-β- erythroidine (DHβE) and α-conotoxin Mil were utilized. DHβE has been shown to be a competitive antagonist of nAChRs. Blockade of α3β2 nAChRs expressed in oocytes by DHβE is fully reversed after four minutes of washout (Fig. 11 A). In contrast, the α3β2 nAChR recovers relatively slowly from Mil block after toxin washout (Fig. 1 IC). To test whether α-conotoxin Mil was acting at the same site as DHβE, we pre-applied DHβE to α3β2 nAChRs. We then co-applied DHβE and α- conotoxin MIL If α-conotoxin Mil and DHβE act at the same site, pre-application of the DHβE should protect the receptors from block by α-conotoxin MIL In this case, the recovery from block would follow the faster time course of block by DHβE alone. If preapplication of DhβE does not prevent the binding of α-conotoxin Mil to the receptor, then the recovery from blockade by the co- applied DhβE and Mil would be expected to follow the slower time course of block by α-conotoxin Mil alone. As shown in Fig. 1 IB, the time course of recovery following washout of DHβE and α- conotoxin Mil is similar to that of washout of DHβE alone, indicating that DHβE prevents the binding of MIL At low concentrations (e.g., near the IC 50 ) of α-conotoxin Mil, recovery from block following toxin washout has a time course that is well fit by a single exponential decay function consistent with simple bi-molecular dissociation (Fig. 12). However, as the concentration of α- conotoxin Mil approaches saturation, an initial lag in recovery after toxin washout occurs. This lag is maximal at fully saturated concentrations of α-conotoxin Mil (data not shown). The time course of recovery from blockade with saturating concentrations Mil is inconsistent with the simple bi- molecular dissociation (See dash lines in Fig. 13). Instead the time course is well fit by a model in which each receptor is assumed to have two binding sites which can either be occupied by ACh or α-conotoxin MIL Also in this model, occupation of either binding site by α-conotoxin Mil is sufficient to block against induced opening of the receptor. Thus, at saturating concentrations, both binding sites are occupied by MIL Upon toxin washout each binding site becomes unoccupied following a time course of simple bi-molecular dissociation. Since both binding sites must be unoccupied by toxin for a receptor activation by agonist to occur, an initial lag in functional recovery following saturating toxin block is observed. The values of K off calculated using this model under saturating toxin concentration matched those calculated under non-saturated condition validating the model. (Table 3). TABLE 3 Equilibrium and Kinetic Constants of the Functional Block of nAChR by Variants of Class a A-Conotoxins EXAMPLE 9 Kinetics of Interaction with Receptor Subtypes The affinity of a ligand is determined by its microscopic rates of association (k on ) and dissociation (k oK ). As judged by measurements on voltage-clamped Xenopus oocytes expressing nAChRs, when Mil blocks currents of α3β2 receptors, its on rate is relatively rapid (k on - 4 x 10 8 min " ' M " '); its off rate is slow (k ofT = 0.13 min " '). This results in a high affinity interaction between α-conotoxin Mil and α3β2 nAChRs. (K d = 3.3 x 10 " '° M). A substantially lower affinity is observed if either the α3 or β2 subunit is replaced with a different subunit. That is when the α3 subunit is switched to α4, the resulting α4β2 receptor is blocked by Mil with a K d that is 800-fold higher. If the β2 subunit is switched (to yield α3β4) an 8.000-fold decrease in Mil potency is seen. Furthermore, when the k on and k otf values of Mil for these two types of receptors (a3b4 and α3β2) are measured, a most striking result is obtained. Despite a decrease of nearly 4-orders of magnitude in potency, when α-conotoxin blocks the α3β4 versus α3β2 receptor, k 0({ is changed little if any. Thus, the difference in potency is essentially accounted for by a corresponding decrease in toxin k on . Conversely, when the α subunit is changed (i.e., to yield α2β2 or α4β2 a marked increase in off for Mil is found, the quantitation of which is presently beyond our assay capabilities). These results suggest that the k on of the toxin is largely controlled by determinants on the β2 subunit whereas the α3 subunit may have the major determinants that control k off . EXAMPLE 10 Affinity of Chimera for α3/β2 Subtype To further examine the kinetic interactions of toxin with receptor, a chimera of α-conotoxin Mil was constructed. A series of peptides from the venom Conus aulicus was isolated that, unlike α-conotoxin Mil, prefer the α3/β4 interface over that of the α3/β2. One of these peptides is α- conotoxin AuIA. The presence of either histidine or asparagine at position 12 is highly conserved in all conopeptides. A conserved sequence of each of the aulicus peptides was used in the design of the Mil chimera indicated in Table 4 in which a string of four amino acids (9-12) of Mil are replaced by FATN. In general, substitution of these four amino acids results in a change in selectivity and affinity for the nicotinic receptors. Compared to Mil, the affinity of the chimera for the α3/β2 interface was more than 1, 000-fold lower (K d has changed from 330 pM for the wild-type to 500 nM for the chimera) but k of{ was changed by a factor of less than two. Thus, the four amino acid substitution does not affect toxin residues which determine off-rate (which must be elsewhere on the peptide), but clearly effects residues which determine on-rate. Other chimeras were synthesized in which amino acid fragment 9-12 was substituted from one peptide into another. EXAMPLE 11 Cyclic Peptides Based on Mil Motif In order to test the significance of the HLEH fragment of Mil (amino acid residues 9-12 of SEQ ID NO:l), several cyclic peptides based on this structure were constructed utilizing standard FMOC chemistry. These include: cyclic cys-HLEH-cys (SEQ ID NO:4), cyclic A-HLEH-A (SEQ ID NO:5) connected through an amide bond, and cyclic HLEH (amino acid residues 9-12 of SEQ ID NO: 1) connected through an amide bond. These small peptides are screened for biological activity by the procedures of Example 8. TABLE 4 Sequences of Mil, Aul and a Chimera of the Two Peptide Sequence (ID NO:) Mil GCCSNPVCHLEHSNLC* (1) Chimera (Mil HLEH[(9-12] FATN GCCSNPVCFATNSNLC* (3) Aul GCCSYPPCFATNSGYC* (6) The FATN sequence (amino acid residues 9-12 of SEQ ID NO: 6) shown in bold is a conserved feature of at least three different α3β4-preferring α-conotoxins from C. aulicus venom. EXAMPLE 12 Dock and Lock Model Comparison of the data for interactions between Mil and nAChRs (Examples 9 and 10) emerges as a two-step "dock and lock" mechanism to explain the remarkable subtype specificity of MIL The data suggest that two putative "faces" of the Mil interacts with its respective binding sites on the receptor, and that the dual interaction may provide a general mechanism for the observed high receptor subtype specificity and affinity. Thus, it is proposed that α-conotoxin Mil has two interaction surfaces, which are referred to as the "docking face" and the "locking face." The docking face interacts relatively rapidly with a site on the β2 subunit. which is referred to as the "docking site." The second phase of toxin interaction involves a different surface of the toxin, the "locking face." This locking face binds to a site on the α3 subunit which is referred to as the "locking site." In the absence of docking interactions, the k on for the "locking face- locking site" interaction may be quite slow. However, if the peptide is already docked (through the β2 docking site), the locking phase then proceeds much more rapidly (Figs 14A and 7B). The data discussed above demonstrate that a switch in receptor subunits can cause a decrease in Mil's affinity of several orders of magnitude, without affecting its k otf (implying that the locking site remains intact and that the change in affinity is primarily due to changes in docking interactions). The results with the FATN-αMII analog (Example 11 ; SEQ ID NO:3) and the kinetic results obtained with wild-type toxin acting on the α3β4 nicotinic receptor are thus suggestive that the docking face of the toxin is located on the hydrophilic side of the wedge and that this hydrophilic face interacts with a fast on-time with the β2 subunit. The other side of the wedge which is characterized by hydrophobic residues exposed to solvent, would be an attractive locus for the locking face of α-conotoxin Mil, which is postulated to interact with high affinity on a site on the α3 subunit of neuronal nicotinic receptor targets of this peptide. A cartoon representation of α- cono toxin Mil interacting with the α3β2 and α3β4 receptors and of the FATN-α-conotoxin Mil analog (SEQ ID NO:3) is shown in Fig. 14. The presence of two distinct interaction faces, which lead to distinguishable docking-and- locking interactions as described herein may be a general design feature of many Conus peptides and may represent a novel paradigm for achieving subtype selective interaction with multisubunit receptors. The term "Janus-ligands" is suggested to refer to binding molecules that have two distinct interaction faces (from Janus, the two-faced Roman god of beginnings). α-Conotoxin Mil would be a protype Janus ligand. EXAMPLE 13 Synthesis of Organic Molecules as Ligands The HLEH fragment of Mil appears essential in determining activity and selectivity of the Mil conopeptide. Computational examinations of the HLEH fragment are undertaken in order to develop an organic scaffold for use in developing small molecules. The spacial arrangement of the HLEH fragment is studied computationally using a vector analysis. 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Claims: WHAT IS CLAIMED IS: 1. A substantially pure peptide having the general formula: Xaa-Cys-Cys-Xaa-Xaa,-Xaa 2 -Xaa-Cys-Xaa 3 -Xaa-Xaa 4 -Xaa 5 -Xaa-Xaa-Xaa-Cys, wherein Xaa, Xaa,, Xaa 2 , Xaa 3 and Xaa 4 each is an amino acid selected from the group consisting of natural, modified or non-natural amino acids and Xaa 5 is His or Asn. 2. The peptide of claim 1 wherein the C-terminus is amidated. 3. The peptide of claim 1 wherein Xaa, is Asn or His. 4. The peptide of claim 1 wherein Xaa 2 is Pro or hydroxy-Pro. 5. The peptide of claim 1 wherein Xaa 3 is His. 6. The peptide of claim 1 wherein Xaa 4 is Glu. 7. The peptide of claim 1 wherein Xaa, is Asn or His and Xaa 2 is Pro or hydroxy-Pro. 8. The peptide of claim 7 wherein Xaa, is Asn. 9. The peptide of claim 7 wherein Xaa 4 is Glu and Xaa 5 is His. 10. The peptide of claim 7 wherein Xaa 3 is and Xaa 4 is Glu. 1 1. The peptide of claim 1 wherein the biological activity of the peptide is substantially the same as the biological activity of α-conotoxin MIL 12. The peptide of claim 7 wherein the biological activity of the peptide is substantially the same as the biological activity of α-conotoxin MIL 13. The peptide of claim 10 wherein the biological activity of the peptide is substantially the same as the biological activity of α-conotoxin MIL 14. A peptide analog, peptide mimetic or mimetic of α-conotoxin Mil specific for one or more subtypes of neuronal nicotinic acetylcholine receptor (neuronal nAChR). 15. The peptide analog, peptide mimetic or mimetic of claim 14 wherein the specificity is for the α3β2 subtype of neuronal nAChR. 16. The peptide analog, peptide mimetic or mimetic of claim 14 wherein the specificity is for the α3β4 subtype of neuronal nAChR. 17. The peptide analog, peptide mimetic or mimetic of claim 14 wherein the specificity is for the α2β2 subtype of neuronal nAChR. 18. A method for screening compounds for neuronal nicotinic acetylcholine (nAChR) receptor antagonistic activity and receptor subtype which comprises determining the on and off rates for the binding of α-conotoxin Mil and a compound to be screened to different subunits of nAChR and comparing said on and off rates. 19. The method of claim 18 wherein the subunits of nAChR are the α3β2 and α3β4 subunits. 20. A derivative, peptide analog, peptide mimetic or mimetic of α-conotoxin Mil which selectively modulates biological activity at nAChRs. 21. A method for determining the three-dimensional structure of an alpha-conotoxin, analog which comprises: (a) obtaining NMR spectroscopy data for the peptide; (b) providing three-dimensional structural coordinates for a composition of Mil; and (c) determining the three-dimensional structure of the alpha-conotoxin by analyzing the data with reference to the previous structural coordinates using molecular replacement. 22. A method of claim 21 which further comprises testing a compound so identified for its ability to: (a) bind to a neuronal nicitinic acetylcholine receptor (nAChR); (b) inhibit the binding of a ligand to a neuronal nAChR; and/or (c) inhibit a biological function mediated by a natural ligand of an nAChR. 23. A method for selecting a compound capable of binding to a neuronal nicotinic acetylcholine receptor (NAChR) which comprises: (a) providing coordinates defining the three dimensional structure of Mil or a portion thereof; (b) characterizing points associated with that three dimensional structure with respect to the favorability of interactions with one or more selected functional groups; (c) providing database of one or more dandidate compounds; and (d) identifying from the database those compounds having structures which best fit the points of favorable interaction with the three dimensional structure. 24. A method of claim 23 which further comprises testing a compound so identified for its ability to: (a) bind to neuronal nAChR, (b) inhibit the binding of Mil to a natural or non-natural ligand therefor, and/or (c) inhibit a biological function mediated by MIL 25. A machine readable data storage medium, comprising a data storage material encoded with machine readable data which, when using a machine programmed with instructions for using said data, is capable of displaying a graphical three-dimensional representation of a molecule comprising a Mil peptide or a portion thereof. 26. A machine-readable data storage medium, comprising a data storage material encoded with machine readable data which, when using a machine programmed with instructions for using said data, is capable of displaying a graphical three-dimensional representation of an α-conotoxin or portion thereof based on the coordinates of Fig. 8, or based on coordinates having a root mean square deviation therefrom with respect to conserved protein backbone atoms of not more than 1.5 A. 27. A machine-readable data storage medium comprising a data storage material encoded with a first set of machine-readable data which, when combined with a second set of machine- readable data, using a machine programmed with instructions for using said first set of data and said second set of data, can determine at least a portion of the coordinates corresponding to the second set of machine-readable data, wherein said first set of data comprises a Fourier transform of at least a portion of the coordinates according to Fig. 8; and said second set of data comprises coordinates of a molecule or molecular complex. 28. A method for displaying a three dimensional representation of a composition of Mil which comprises: a) providing a machine capable of reading data stored on a machine-readable storage medium of claim 25, programmed with instructions for using said data to display a graphical three-dimensional representation of a protein or protein ligand complex or portion thereof defined by said data, and loaded with a machine-readable storage medium of claim 25; and b) permitting the machine to read said data and display the three-dimensional representation. 29. A method for designing a compound capable of binding to a neuronal nicotinic acetylcholine receptor (nAChR) which comprises: (a) graphically displaying a three-dimensional representation based on coordinates defining the three-dimensional structure of Mil or a portion thereof; (b) characterizing the interactions between portions of a ligand that is known to bind to the protein to identify candidate moieties for replacement; (c) providing a knowledge base of one or more candidate substitute moieties; and (d) identifying from the knowledge base one or more substitute moieties which may be used to replace one or more selected portions of the ligand and retain at least a portion of the ligand's binding affinity for the protein. 30. The method of claim 29 which further comprises testing the compound for its modulating activity of said neuronal nAChR. 31. A method for designing a compound capable of binding to a neuronal nicotinic acetylcholine receptor (nAChR) which comprises: (a) providing coordinates defining the three-dimensional structure of Mil or a portion thereof; (b) characterizing points associated with that three-dimensional structure to identify preferred points with respect to the favorability of interactions of one or more selected functional groups with the protein; (c) characterizing one or more portions of a ligand that is known to bind to the protein that are proximal to the characterized points; (d) providing a knowledge base of one or more molecular fragments or molecules; (e) identifying from the knowledge base one or more fragments or molecules that permit connection of preferred points identified in (b) to portions of the ligand; and (f) modifying the structure of the ligand by the covalent attachment thereto of one or more such fragments or molecules so identified in an orientation and location selected to permit the modified ligand to bind to the protein. 32. The method of claim 31 which further comprises testing the compound for its modulating activity of said neuronal nAChR.

Inventors: CARTIER G EDWARD, KOERBER STEVEN C, MCINTOSH J MICHAEL, OLIVERA BALDOMERO M, RIVIER JEAN E, SHEN GREGORY S, SHON KI-JOON, YOSHIKAMI DOJU, CARTIER, G., EDWARD, KOERBER, STEVEN, C., MCINTOSH, J., MICHAEL, OLIVERA, BALDOMERO, M., RIVIER, JEAN, E., SHEN, GREGORY, S., SHON, KI-JOON, YOSHIKAMI, DOJU
Applicants: COGNETIX INC, SALK INST, UNIV CASE WESTERN RESERVE, UNIV UTAH RES FOUND, CASE WESTERN RESERVE UNIVERSITY, COGNETIX, INC., SALK INSTITUTE, UNIVERSITY OF UTAH RESEARCH FOUNDATION
Application year: 1998
Main classification: C07K7
IPC codes: A61K38, C07K7, C07K14, C12N15, G01N33, G01R33, G06F17, G06F19