From: Rob Pooley <rjp@dcs.ed.ac.uk>
Newsgroups: comp.simulation
Subject: Fianl programme for Tools and Techniques Conference
Date: 1 Sep 92 15:01:14 GMT
Distribution: world
Organization: Department of Computer Science, University of Edinburgh


                            CALL FOR PARTICIPATION
                                       
            6TH INTERNATIONAL CONFERENCE ON MODELLING TECHNIQUES
                AND TOOLS FOR COMPUTER PERFORMANCE EVALUATION
                                       
                           September 16-18th, 1992
                             Scandic Crown Hotel
                           Edinburgh, Scotland, UK.


The sixth International Conference on Modelling Techniques and Tools
for Computer Performance Evaluation will be held in Edinburgh, UK.
This is the major European forum for the presentation of research and 
applications of performance analysis tools and techniques.

The conference will be held in the Scandic Crown Hotel, a modern luxury
hotel in the middle of Edinburgh's historic Old Town, on the Royal Mile.  


The provisional programme is given below:

WEDNESDAY 16th SEPTEMBER


9:20 - 9:30     Opening Remarks 

9:30 - 10:30    Arnold Allen - invited paper
                Session Chairman: R. Pooley

10:30 - 11:00   Coffee Break 

11:00 - 12:00   PETRI NETS (Chairman: G. Balbo)
                C. Lindemann
                  DSPNexpress: A Software Package for Efficiently Solving
                  Deterministic and Stochastic Petri Nets
                J.A. Rolia and K.C. Sevcik 
                  Fast Performance Estimates for a Class of Generalized
                  Stochastic Petri Nets

12:00 - 12:30   Overview of tools to be demonstrated (Chairman: M. Calzarossa)

12:30 - 2:30    Lunch and Tool Demonstrations

2:30 - 3:30     MEASUREMENTS  (Chairman: D. Thomas)
                J.K. Flanagan, K. Grimsrud et al 
                  BACH: BYU Address Collection Hardware
                N.J. Gunther 
                  On the Application of Barycentric Coordinates to the Prompt
                  and Visually Efficient Display of Multiprocessor Performance
                  Data

3:30 - 4:00     Tea Break 

4:00 - 5:30     WORKLOADS  (Chairman: G. Serazzi)
                B.M. Carlson et al
                  Speedup Properties of Phases in the Execution Profile of
                  Distributed Parallel Programs
                K.J. McDonell
                  Benchmark Frameworks and Tools for Modelling the Workload
                  Profile
                M.K. Acharya et al. 
                  Real-time Hierarchical Traffic Characterization of a Campus
                  Area Network

THURSDAY 17th SEPTEMBER

9:00 - 10:30    ESPRIT III projects  - invited papers
                Chairman: P. Hughes
                Trevor Chambers - ESPRIT project 6942 
                  PEPS: Performance Evaluation of Parallel Systems
                Horst Lindmeier - ESPRIT project 6271 
                  Benchmarking for Embedded Control and Real-time Applications
                Kam-Fai Wong - ESPRIT project 7091 
                  Pythagoras: Performance Quality Assessment of Advanced
                  Database Systems

10:30 - 11:00   Coffee Break 

11:00 - 12:30   METHODS I  (Chairman: R. Puigjaner)
                E.W. Brehm, R.T. Goettge and F. McCaleb
                  START/ES - An Expert System Tool for System Performance
                  and Reliability Analysis
                A. Valderruten et al. 
                  Deriving Queueing Networks Performance Models from Annotated
                  LOTOS Specifications
                J. Hillston 
                  A Tool to Enhance Model Exploitation

12:30 - 2:00    Lunch and Tool Demonstrations

2:00 - 4:00     PARALLEL AND DISTRIBUTED SYSTEMS  (Chairman: R. Candlin)
                F. Hartleb and V. Mertsiotakis
                  Bounds for the Mean Runtime of Parallel Programs
                G. Lyon, R. Snelick and R. Kacker 
                  Time-Perturbation Tuning of MIMD Programs
                A. Birman, D. Ferguson and Y. Kogan
                  Asymptotic Solutions for a Model of Large Multiprocessing
                  Systems with Multiple Workloads
                R. Kroeger, M. Gergeleit and F. Lange 
                  JEWEL: Experiences with a Distributed Measurement System

4:00 - 5:15     Tea Break and Poster Session 
                (Poster Session Organiser: J. Hillston)


FRIDAY 18th SEPTEMBER

9:00 - 10:00    Raj Jain - invited paper
                Chairman: R. Marie 

10:00 - 11:00   METHODS II  (Chairman: G. Haring)
                A.L. Opdahl 
                  Sensitivity Analysis of Combined Software and Hardware
                  Performance Models: Open Queueing Networks
                N.M. Patel 
                  Structuring Analytical Performance Models using Mathematica

11:00 - 11:30   Coffee Break 

11:30 - 12:30   METHODS III  (Chairman: P. Harrison)
                R. Chakka and I. Mitrani 
                  A Numerical Solution Method for Multiprocessor Systems
                  with General Breakdowns and Repairs
                P. Buchholz 
                  Hierarchical Markovian Models - Symmetries and Reduction

12:30 - 2:30    Lunch and Tool Demonstrations

2:30 - 3:30     CASE STUDIES  (Chairman: A. Wight)
                S. Salza and R. Tomasso
                  A Modelling Tool for the Performance Analysis of Relational
                  Database Applications
                M. Malhotra and K.S. Trivedi 
                  Reliability of Redundant Arrays of Inexpensive Disks (RAID)

3:30 - 4:00     Tea Break 

4:00 - 4:15     Closing Remarks 


POSTERS AND TOOL DEMONSTRATIONS

A.E. Krzesinski and N.J. Townsend 
        /DASD: A Tool to Model the Performance of IBM DASD Systems

X. Zhang, N. Nalluri and X. Qin 
        MIN-Graph: A Tool for Monitoring and Visualising MIN-based
        Multiprocessor Performance

B.R. Haverkort, A.P.A. van Moorsel and A. Dijkstra 
        MGMtool: A Performance Modelling Tool Based on Matrix Geometric
        Techniques

A. Hutchison and P.S. Kritzinger 
        XWAN: A Tool to Model Adaptive Routing in a Wide Area Network

A.E. Kostin 
        Microsim: E-Net Tool for Modelling Concurrent and Distributed Data
        Processing Systems
 
H. Heiss and A. Payer 
        PASTE: A Tool for Evaluation of Processor Allocation Strategies

G. Fleischmann and M. Gente 
        Modelling and Evaluation of Parallel Programs using GIANT

G. Fairhurst and A.Z.M. Salleh 
        Modelling the Performance of the G.764 Packetised Voice Protocol

R.L. Klevans and W.J. Stewart 
        XMARCA: An X-Windows Interface for Queueing Network Modelling

G. Chiola, R. Gaeta and M. Ribaudo 
        Designing an Efficient Tool for Stochastic Well-Formed Coloured Petri
        Nets

A.J. Field and R.L. While
        A General Framework for Discrete-Event Simulation Using Functional
        Languages


TUTORIALS

Before the conference, on Tuesday 15th September there will be a programme 
of tutorials on aspects of performance modelling.  There will be two long 
tutorials in the morning and two sets of two short tutorials in the afternoon.
Delegates may register for either a full day or a half day programme.  Please
indicate choice of tutorial(s) on the registration form. 

9:00 - 12:00    A       Nico M. van Dijk, 
                        University of Amsterdam, The Netherlands

                        The Product Form Tool

                B       Kishor S. Trivedi
                        Duke University, USA

                        Techniques and Tools for Reliability Modelling

12:00 - 1:30    LUNCH

1:30 - 3:00     C       Ian F. Akyildiz
                        Georgia Institute of Technology, USA

                        Computational Techniques

                D       Edmundo de Sousa e Silva
                        University of Rio de Janeiro, Brazil

                        Numerical Approaches

3:00 - 3:30     COFFEE

3:30 - 5:00     E       Gabriele Kotsis
                        University of Vienna, Austria

                        Visualization of Performance Information

                F       Boudewijn R. Haverkort
                        University of Twente, The Netherlands

                        Performability Modelling Tools


Abstracts for each tutorial are given below:

A  THE PRODUCT FORM TOOL - Nico M. van Dijk

Queueing network modelling has become a popular tool in telecommunication,
computer performance evaluation and flexible manufacturing.  The tutorial aims
to highlight an approach that can be used as an engineering tool to evaluate
stochastic service or computer networks.  To this end, it will cover the
following two topics:

                1) Product forms and partial balance
                2) A simple bounding methodology.

Part 1 will discuss the physical notion of station balance as a key-property
to deduce closed product form expressions for queueing networks with blocking.
In concrete situations this notion will enable one to directly deduce whether
or not a system will have a product form solution, and if not, why not.

In part 2 these insights will be used further to also obtain simple
performance bounds for non-product form queueing networks, most notably 
networks with blocking.  The steps involved will be outlined and illustrated
for some typical non-product form examples such as: 

        - an overflow model
        - a system with breakdowns 
        - finite tandem or assembly lines 


B  TECHNIQUES AND TOOLS FOR FOR RELIABILITY MODELLING - Kishor S. Trivedi

Various Markov reward models are described and investigated as a tool to
evaluate reliability and availability models for computer networks, for
example fault-tolerant systems.  Both transient and steady-state measures are
considered.  Techniques covered are: 

        - differential equations 
        - numerical solution procedures 
        - uniformization techniques and truncations
        - simulation procedures and enhancements

Particularly, a hierarchical modelling tool is presented, called SHARPE
(Symbolic Hierarchical Automated Reliability and Performance Evaluation), that
combines the different techniques and models.  This tool provides a
specification language and solution methods for a large number of models such
as: 
        - series-parallel reliability block diagrams 
        - reliability graphs and fault trees
        - cyclic and acyclic Markov chains 
        - Generalized Stochastic Petri Nets 
        - PMS (Processor-Memory-Switch) Models



C  COMPUTATIONAL TECHNIQUES FOR COMPUTER NETWORKS - Ian F. Akyildiz

Much of the success of queueing network modelling for computer networks can be
attributed to: 

        - the existence of Jackson's closed product form expression and many
          extensions thereof, and
        - efficient computational techniques to actually compute these forms or
          related performance measures such as the throughput, sojourn time or
          loss probability.

This tutorial will survey a number of these computational techniques
ranging from the classical convolution algorithm to various exact and
approximative versions of the MVA (mean value analysis) method like LBANC and
LBANCBLO.  In doing so, special attention is given to different blocking
protocols when finite capacities are involved.  Finally some recent results
are presented to transform networks with blocking into networks without
blocking.


D  NUMERICAL APPROACHES TO PERFORMABILITY - Edmundo de Souza e Silva

The performance of computer networks under different loads and circumstances
is a relevant indication of its being well-designed and operable.  Computer
systems reliability and availability deals with the representation of changes
in structure of the system due to faults or breakdowns.  As analytic tools are
often not feasible to capture such aspects while simulation techniques may be
unreliable, numerical possibilities are still searched for.  

An overview is provided of past work on performability evaluation by means of
Markov chains and how relevant performance measures can be computed
efficiently by numerical approaches.  Particularly two important topics are
highlighted: 

        - the uniformization or randomization technique to transform
          continuous-time models into discrete-time models
        - the state space explosion by which actual computation becomes
          prohibitively expensive.  Several techniques to deal with this 
          problem are discussed. 


E  VISUALIZATION OF PERFORMABILITY INFORMATION - Gabriele Kotsis

The art of visualizing the performance of computer systems has gained
increasing interest in the past few years.  The pictorial representation of
performance data will help the system analyst to obtain a better understanding
of what is going on in the system, how it works and why it works (or why not).
Visualized information makes use of the eye-brain system, with its great
pattern recognition capability, in a way that is impossible with purely
numeric data.

This tutorial aims to report on the state of the art in performance
visualization from the analyst's point of view.  The usefulness of
visualization techniques and tools supporting performance analysis will be
investigated.  In particular, the tutorial will contain three modules:

   The State of the Art in Performance Visualization
      This presentation will include: visualization primitives and techniques,
      static versus dynamic displays, display of univariate and multivariate
      data, categorization and comparison of existing visualization tools. 

   Representing Performance Characteristics of Conventional Computer Systems 
      The following topics will be discussed: visualization of hardware and
      software performance information, meaningful metaphors and easy
      recognizable presentation techniques. 

   Visualizing the Performance of Parallel and Distributed Systems
      The particular problems arising in visualizing the behaviour of parallel
      systems (representations for massive amounts of data, representation of
      concurrency, visualization of hardware-software mapping) will be
      demonstrated along with possible solution techniques.  


F  PERFORMABILITY MODELLING TOOLS - Boudewijn R. Haverkort

Over the last few years Markov reward models (MRMs) have been used extensively
for the analysis of the performability of computer and communication systems.
Using MRMs for this purpose brings along two basic problems: model generation
and model solution.  Model solution has been the subject of study in a large
number of papers.  Far less attention has been paid to the model generation
problem. 

In this tutorial the mathematical background of MRMs for performability
modelling is briefly addressed.  The emphasis is then on high-level
specification techniques for performability models and various generation
techniques that can be used to automatically generate MRMs from these
specifications.  Aspects addressed are modelling requirements (coming from the
various application areas), high-level specification techniques (such as
stochastic Petri nets, stochastic activity nets, dynamic queueing networks and
object-oriented techniques), implementability of conceptual models,
implementation aspects of MRM generation techniques and existing software
tools for performability modelling and analysis.


SOCIAL PROGRAMME
                                       
Tuesday, 15th September 7.00pm
                                       
Civic Reception at the Edinburgh City Chambers
                                       

Wednesday, 16th September - Optional Excursions
                                       
Murder and Mystery Tour
Whisky Tasting
                                       
                  
Thursday, 17th September 7.00pm for 7.30pm

Conference Dinner at the Royal College of Physicians        
                                       
                                   --------

PROGRAMME COMMITTEE:
        Ian Akyildiz, Georgia Tech, USA
        Heinz Beilner, University of Dortmund, Germany
        Maria Calzarossa, University of Pavia, Italy
        Rosemary Candlin, University of Edinburgh, UK
        Giovanni Chiola, University of Torino, Italy
        Blaine Gaither, Amdahl Inc, USA
        Gunther Haring, University of Vienna, Austria
        Peter Harrison, Imperial College, London, UK
        Peter Hughes, Bell Northern Research (Europe), UK
        Peter King, Heriot-Watt University, UK
        Anthony Krzesinski, University of Stellenbosch, RSA
        Raymond Marie, IRISA, France
        Ramon Puijganer, University of Balearics, Spain
        Herb Schwetman, MCC Inc, USA
        Guiseppe Serazzi, Politecnico di Milano, Italy
        Connie Smith, L & S Computer Technology, USA
        David Thomas, BT Ltd, UK
        Alex Wight, University of Edinburgh, UK

Organisation:

Local Arrangements: Jane Hillston, (jeh@dcs.ed.ac.uk)
                    Dept. of Computer Science, Univ. of Edinburgh, UK

Sponsorship & Exhibitions: Peter King, (pjbk@dcs.hw.ac.uk)
                           Dept. of Computer Science, Heriot-Watt Univ., UK

Tutorials: Nico van Dijk, (fax: +31 20 525 4217)
           Dept. of Econometrics, Univ. of Amsterdam, Netherlands.    
                                       

                                   --------
Travel Arrangements

Air     Edinburgh International Airport is less than 20 minutes from the city
        center and provides access to a worldwide network of international
        flights. There are 26 return flights each day to London provided by
        British Airways, British Midland and Air UK (Gatwick), in addition to
        regular services to Birmingham and Manchester.  Direct air links to
        New York, Chicago and Boston, together with many main European cities
        are provided from Glasgow Airport, one hour's drive from Edinburgh.

Rail    Edinburgh benefits from an extensive network of rail services from
        London and other principal UK cities.  High speed trains operate on
        the London route with a journey time of 4 hours to Waverley Station,
        in the heart of the city, a short walk from the Scandic Crown hotel.
        Inter City Sleeper services are provided on most routes.

Road    Express coach services are available to and from all major UK cities,
        operating on a comprehensive motorway or trunk road system.
                                       
                                   --------

        
The conference fee includes attendance at all sessions of the conference;
refreshments and lunch each day; a local copy of the proceedings; attendance
at the civic reception and the conference dinner; car parking at the hotel.
The student conference fee does not include the conference dinner.

Additional tickets for the conference dinner, price 35 pounds, will be
available on arrival.

Delegates registering before 14th August can take advantage of a preferential
rate.  

Cancellation before 14th August will be eligible for 100% refund of all fees.
Subsequent cancellation, up to 4th September, will be eligible for 75% refund.
After that date no refund will be possible.  Delegate substitution will be
acceptable at any time.



To register please detach and complete the form below and return it to:

        Mrs Edith Field
        UNIVED Technologies Ltd.
        University of Edinburgh,
        16, Buccleuch Place,
        Edinburgh EH8 9LN
        SCOTLAND.
        efield@castle.ed.ac.uk

        fax: +44 31 650 6532

8<---8<---8<---8<---8<--- please detach and print 8<---8<---8<---8<---


Name ____________________________________________

Company/Institute________________________________

Address__________________________________________

_________________________________________________

_________________________________________________

_________________________________________________

Telephone________________________________________

Email____________________________________________

Signed___________________________ Date___________


CONFERENCE REGISTRATION
                        Before 14/8/92        After 14/8/92

Academic Delegate         275 pounds           295 pounds    ______ pounds

Non-academic Delegate     325 pounds           345 pounds    ______ pounds

Student Delegate          150 pounds           170 pounds    ______ pounds

(Students will be required to bring some form of identification of
 certification of student status.)


TUTORIAL REGISTRATION

Which tutorial(s) would you like to attend? (Please tick)

A ___    B ___    C ___    D ___    E ___    F ___

Tutorial fee includes lunch and refreshments during the day, tutorial notes
of the tutorial attended and attendance at the civic reception.

Half day tutorial attendance  50 pounds

Full day tutorial attendance  80 pounds  

                                                           ______ pounds

Do you require vegetarian meals?    Yes/No      ______

Accommodation has been reserved in the Scandic Crown Hotel and in Pollock
Halls, the University's major residence complex in the south of the city,
approximately 20 minutes walk from the Scandic Crown.

Scandic Crown Hotel:

64.75 pounds per person per night (B&B)
             single or double room                         _________ pounds

59.00 pounds per night for accompanying 
             spouse sharing double room                    _________ pounds


Pollock Halls:

21.75 pounds per person per night (B&B)
             (single rooms)                                 _________ pounds

                                       
Arrival Date _____________    Departure Date _____________

 
                                                TOTAL COST  __________ pounds

Cheques, Money Orders and Bank Drafts in Sterling 
payable to UNIVED Technologies Ltd.





------------------------------


Subject: [DEPARTMENTS]


------------------------------


Date:    Sun, 30 Aug 92 22:38:09 GMT
From: mcleod@Sdsc.Edu
Subject: E-S3 Vol.1, No.8, Part Two
X-St-Vmsmail-To: @AB

The following sample issue of our electronic magazine, "E-S3",
covering selected topics about computer modeling and simulation,
is sent to you with the compliments of the publisher of the
technical journal SIMULATION, the Society for Computer
Simulation, and John and Suzette McLeod, the Editors of
Simulation in the Service of Society (S3), a special section of
that journal.  If you do not care to receive future issues please 
type REPLY -- cancel.  Let's not clutter up our E-mail with "Junk 
Mail".
 -----------------------------------------------------------------
 
                  E-S3  Vol. 1, No. 8, Part Two
 
                based on the August 1992 issue of
              "Simulation in the Service of Society"
John McLeod, Technical Editor     Suzette McLeod, Managing Editor
          8484 La Jolla Shores Dr., La Jolla, CA 92037.
                   E-mail: mcleod@sdsc.bitnet
                                *
                   S3 is a special section of
                           SIMULATION
                   the monthly journal of the
                 SOCIETY for COMPUTER SIMULATION
             P.O.Box 17900, San Diego, CA 92177-7900
            Phone: (619) 277-3888 FAX: (619) 277-3930
                                *
[Copyright Notice: E-S3 is the electronically delivered version 
of "Simulation in the Service of Society" which is a special 
section of SIMULATION, a monthly technical journal of the  
Society for Computer Simulation International. It may be 
reproduced only for personal use or for the use of students. In 
any case full credit must be given to the original source of 
publication: SIMULATION 59:2, August, 1992. 
  All rights  reserved, (c) 1992, Simulation Councils, Inc.]
 ----------------------------------------------------------------------
 
A DESIGNER DRUG AGAINST AIDS?
 
Herewith the edited version of a press release from the
University of California/San Francisco on a paper delivered at
the February 1992 annual meeting of the American Association for
the Advancement of Science.
 
                                *
 
A University of California/San Francisco theoretical chemist,
Peter A. Kollman, Ph.D., Professor of Pharmaceutical Chemistry
at the University of California/San Francisco, has invented a
computer model widely adopted by drug companies to speed the
search for potential pharmaceuticals has improved the model and
used it to accurately predict the forces binding an AIDS virus
enzyme, called protease, to a molecule that disrupts the enzyme's
natural function.
 
The molecules under investigation are called protease inhibitors,
and they prevent the AIDS virus enzyme from fashioning the parts
needed to make a new virus from raw material provided by a human
host.
 
Although the inhibitors examined were not useful drugs, the
agreement of the model predictions with reality highlights the
growing power that researchers have to model the interactions of
biologically active molecules, and the promise of computer-
assisted drug design.
 
In computer-assisted drug design, researchers pool their
knowledge of biological structure and pharmaceutical chemistry --
and sometimes quantum physics -- to put together models that
more accurately describe the interactions of biological
molecules.
 
The most advanced computational techniques and computer graphics
capabilities are used to run the models.  The goal is to identify
molecules that will interact with disease vectors or toxins in a
way that limits the damaging impact of the invaders.
 
As knowledge grows, the use of molecular modeling in computer-
assisted drug design is steadily decreasing the amount of time
and money spent on trial-and-error approaches.
 
According to Professor Kollman, "In modeling you want to
represent enough of the known facts so that you can predict the
facts that aren't known yet."  Representing the known facts
requires a lot of power and valuable supercomputer time, but
ultimately can save pharmaceutical companies millions of dollars
spent on drug screening.  To run his model, Dr. Kollman uses work
stations and mini-supercomputers, and for most of the major
projects, a Cray Y/MP at the Supercomputer Center on the campus
of the University of California/San Diego.
 
Protein and DNA are "macromolecules" built up from hundreds or
thousands of smaller molecules.  The quest for the Holy Grail in
molecular modeling is to be able to predict the three-dimensional
structures of macromolecules, using as input only the knowledge
of the order in which their constituent building-block molecules
are linked together.
 
Although not so important in the trial-and-error approach,
knowledge of three-dimensional structure -- of the protein shell
encasing a virus, or of a macromolecule on the cell-surface of a
bacterium, for example -- is the foundation for computer-aided
drug design.
 
Agents of disease are like unwelcome guests that somehow got hold
of the house keys.  The idea behind inhibitor drugs is to stop
the invaders by luring them to the wrong house, where their keys
get stuck in the lock.  To predict a good design to trap an
invader, it helps to know the shape of the key and lock.
 
The determination of the sequence of amino acids in purified
protein, or of nucleotide base pairs in an isolated DNA molecule,
has become almost routine.  But the Holy Grail model must await
quantum leaps in computer power, and in the scientific
understanding of basic rules linking knowledge of amino acids "on
a string" to three-dimensional structure.
 
To design protein inhibitors, modelers ideally would like to know
the three-dimensional structure in some detail.  This is not
easy, but for pure protein crystals these structures can be
determined with a technique called x-ray crystallography, while
for smaller proteins in solution, nuclear resonance spectroscopy
can be used. 
 
Once this structure is known it can be modeled, and the model
visualized on a screen.  Graphics do not provide quantitative
information, Kollman says, "But enable the chemist to use
intuition to tap into new ideas about how molecules fit
together."
 
Kollman's colleague Irwin D. Kuntz, Ph.D., Professor of
Pharmaceutical Chemistry at UC/San Francisco, has developed a
space-filling model in which proteins are represented as a series
of spheres of various sizes.  The shape of the space around the
protein is also modeled as a collection of spheres, and computer
programs determine which potential protein-binding molecules best
fit this "ball space."  The model scans standard chemical data
bases for potential inhibitors.
 
Kuntz and his colleagues used the model, called DOCK, to identify
an AIDS protease inhibitor which, though too toxic for therapy,
helped demonstrate the power of his approach and provided a lead
in the pursuit of a more effective inhibitor.
 
The search for drugs that act as protein inhibitors has often
focused on molecules called peptides, typically modified versions
of well-known molecules to which the proteins already bind. 
However, peptides are often ineffective as drugs because they are
chewed up by the body's enzymes, and do not easily enter the
brain.  Programs such as DOCK enable researchers to search for
inhibitors in less well-charted waters.
 
Kollman's model, called AMBER, is aimed at gaining a more
refined understanding of the forces governing molecular
interactions when one already knows what kinds of inhibitors fit
the space, and needs to know which of them would be most
energetically favored to bind tightly.
 
Kollman is applying AMBER to the potential AIDS protein
inhibitors identified with Kuntz's DOCK model, focusing on a
limited number of molecules that are most important in predicting
how tightly AIDS protease will bond to the inhibitors.
 
He calls the approach molecular dynamics.  The atoms within
molecules flex and vibrate like balls connected by springs in
response to forces within the molecules.  Kollman models these
forces, as well as the forces of electrical attractions between
molecules, and the force necessary to maintain the molecules in
the liquid phase (called van der Waals interactions), to simulate
the structure and motion of the protein and its inhibitors.
 
The laws of thermodynamics favor low-energy states.  AMBER
explores many different shapes that macromolecules theoretically
might assume in interacting with other complex molecules, and
tries to identify ones which are energetically favored.
 
The most detailed versions of molecular models used by
theoretical chemists -- those which yield the most accurate
predictions of the strength of interactions formed between
molecules -- also incorporate the principles of quantum mechanics
to describe sub-atomic forces.  This approach requires even more
computer time than molecular dynamics, Kollman says.
 
"We could apply quantum mechanical methods to study the formation
and breaking of bonds in systems with only tens of atoms, but not
with hundreds or thousands."  Since there is not an infinite
supply of computer power available, Kollman explained, "We can't
know the forces and energies as precisely as you would like, and
we cannot try out all the conformational possibilities as
effectively as you would like."
 
This poses what Kollman calls the "local minimum problem" meaning
that of the many shapes an inhibitor might assume in binding to a
protein, there are usually multiple conformations that would have
favorable, low binding energies.  The trick is to devise a model
that will find the best.
 
"Imagine an egg carton where the troughs are of different depths. 
With the wrong search strategy you might end up in the wrong
trough, a local energy minimum.  We use our dynamic model to go
over the dividers from trough to trough in order to find the
deepest."
 
Computer technology is now probably the biggest limit to
usefulness of molecular models, according to Kollman.  More
powerful computers are needed, he said, especially parallel-
processing machines capable of running many components of
molecular modeling programs simultaneously.  But better
mathematical and computational representations of molecular
interactions, called algorithms, will still be indispensable, he
says.
 
"Parallel processing means that faster algorithms will solve
their part of the program before slower ones.  If 90% of the
slowdown is solved, you still have only speeded up the process by
a factor of 10," he says, not enough to describe larger molecules
accurately.
 
Kollman's team also is focusing on creating a simpler but still
accurate algorithm to describe the interactions between molecules
and the water milieu in which they are dissolved.

"We want to save computer time by finding ways to represent water
without including calculations for every water molecule,"
Kollman explained.
 
UC/SF researchers led by Robert Langridge, Ph.D., director of the
UC/SF Computer Graphics Laboratory, have pioneered the computer
imaging of biological molecules, and many UC/SF senior scientists
with expertise in computer-assisted design and structural
chemistry are now working together in a major effort to identify
potential AIDS drugs.
 
[The December 1990 issue of S3 carried an article entitled
"Empiricism vs. Understanding" which described the efforts of
Agouron Pharmaceuticals Inc. to develop a drug for a specific
purpose -- to design a key to fit a lock of unknown design. JM]
 
                       *        *        *
 
More on Noise
 
In the January 1992 issue of SIMULATION a technical note by
Granino Korn was published under the heading "Noise."  Comments
on the note by Robert Kinnison, and Granino's reply, appeared in
S3 for February 1992.  Here we publish further remarks, by Turkan
Gardenier.
 
Dear John:
 
My comments on the article by Granino Korn can be summarized as
follows.
 
(1)  The idea of "noise" has been and is of interest to
statisticians.  In fact, Box-Jenkins time-series analysis has an
essential component, that of modeling "white noise."
 
(2)  The author distinguishes between pseudorandom noise,
congruential noise, and shift-register-type noise in the first
paragraph.  This is stated in the first paragraph; the
distinction is not made clear to the reader, however.  The
statement "pseudorandom noise is not random: you can predict
future samples if you know sufficiently many (very many) samples"
is reminiscent of Box-Jenkins p, d, q components.  The
distinction between "statistically independent" and
"uncorrelated" is, again, reminiscent of the "first order
autoregression" in Box-Jenkins time-series.
 
(3)  I think the idea of getting the reader involved in thinking
about underlying components other than correlations of the "first
order," such as a first order transition matrix in a Markovian
approach, or a first order autoregression, is good.  The hardware
orientation for designing a noise generator with a knowledge of
"lurking components" is also good.  Yet, I think the author needs
to look into some of the literature in statistical time-series
analysis (e.g., Box-Jenkins) which defines and breaks down "noise"
components into short- and long-term determinants.
 
Turkan K. Gardenier, Ph.D.
U.S. Equal Employment Opportunity Commission
 
 
Enclosed with Dr. Gardenier's letter were abstracts of papers
presented at the session which she co-organized with William Eddy
(Department of Statistics, Carnegie-Mellon University) for the
1992 Annual Meeting of the American Association for the
Advancement of Science.  Herewith the session description as it
appeared in the AAAS program.
 
Statistical Modeling and Analysis Using Personal Computers
 
Microprocessors are gaining increased usage in scientific
settings ranging from medicine to military applications.  A
parallel effort in software development has brought enhanced
applications of artificial intelligence, user-friendly, menu-
driven systems; and the flexibility to branch into various modes
of analysis.  The advances mean the user must be educated
regarding data analysis and mathematical modeling.  For example,
scientific experimenters need to know if a linear regression
analysis is appropriate for the data at hand, need to graphically
display interrelationships among the input variables, and need
tools to track data over time.  This symposium will present
recent developments that address these issues. 
 
And the abstract of Dr. Gardenier's own paper:
 
"Discrete time-series methods for monitoring data"
 
This talk will present a method for tracing the status of
successive observations over time using the Cumulative
Transitional State Score developed by the author.  Implementing
this procedure involves partitioning data into three discrete
categories (+1, 0, and -1) corresponding to "above normal,"
"normal," and "below normal" subdivisions.  This trinomial
partitioning is based upon an examination of prior data and
expert/clinical judgment.  A similar decision process is also
used in evaluating transitions over successive time-period
evaluations.  A scoring scheme based upon both structures is then
implemented in order to cumulate and graphically display
transitions in status between two specified time periods.
 
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