Subject: UCLA short course on "Computational Chemistry for Materials and Drug Design"

From: "Goodin, Bill" <[email-masked]>
Date: Thu, 06 Apr 95 12:19:00 PDT

On August 14-17, 1995, UCLA Extension will present the short course,
"Computational Chemistry for Materials and Drug Design", on the UCLA
campus in Los Angeles.

The instructors are Richard Judson, PhD, Senior Member of the
Technical Staff, Sandia National Laboratories; Tony Hopfinger, PhD,
Professor, Department of Medicinal Chemistry and Pharmacognosy,
University of Illinois at Chicago; and Michael Colvin, PhD, Senior Member
of the Technical Staff, Sandia National Laboratories.

This course provides a broad introduction to computational molecular
modeling.  A variety of methods are discussed which range from statistical
methods based on experimental data to high-level ab initio quantum
chemical calculations.  The course stresses how different methods can be 
appropriately applied in a variety of situations.  These methods include
molecular dynamics, quantum chemistry, and statistical methods such as
QSAR (Quantitative Structure Activity Relationships).  Lectures also 
introduce homology-based protein modeling and general-purpose optimization
methods used across a range of computational chemistry methods.

The course combines descriptions of methods with applications to specific
areas, including predictions of physical properties of molecules 
(solubilities,
conformations, pKa, diffusion coefficients, etc.), predictions of binding
properties of drugs (binding geometries and energetics), and statistical
prediction of various properties from experimental data.  Methods are
illustrated with case studies, and the course also addresses the use of
available commercial modeling software both in lectures and hands-on
sessions.

Specific topics include: Molecular Modeling, Computer Lab Session,
Quantum Chemistry, Case Study, Continuum Solvent Models, Case
Study, Polarizable Treatment of Metals, Computer Lab Session,
Quantitative Structure Activity Relationship (QSAR), Molecular Diversity
and Computer -Assisted Molecular Design, Case Study, Computer Lab
Session, Applications of Computational Methods to Polymeric Materials
Design, Commonly Used Optimization Methods in Chemical Calculations,
Protein Homology Modeling, and Commercially Available Modeling
Software.

For additional information and a complete course description, please
contact Marcus Hennessy at:

(310) 825-1047
(310) 206-2815  fax
[email-masked]