Mini-Workshop on Geometrical Methods for Conformational Modeling

August 2 - 3, 1995
CoRE Building, Rutgers University, Piscataway, NJ

Organizers:

Leonidas J. Guibas, Stanford U., guibas@cs.stanford.edu

Tim Havel, Harvard, havel@ptolemy.med.harvard.edu

Tentative Speakers:

John Canny (Computer Science, UC Berkeley, CA)

Bob Connelly (Mathematics, Cornell U., Ithaca, NY)

Gordon Crippen (College of Pharmacy, U. MI, Ann Arbor, MI)

Herbert Edelsbrunner (Computer Science, U. IL, Urbana, IL)

Rick Fine (BIOSYM Technologies, Parsippany, NJ)

Tim Havel (Biol. Chem. & Mol. Pharm., Harvard U., Boston, MA)

Tom Hayden (Mathematics, U. KY, Lexington, KY)

Jean-Claude Latombe (Computer Science, Stanford, CA)

Mike Levitt (Dept. of Cell Biology, Stanford U., Stanford, CA)

Ruth Nussinov (Computer Science/Chemistry, Tel Aviv, Israel)

Wilma Olson (Chemistry, Rutgers U., NJ)

In modeling physical systems in general, it is well-known that the choice of variables, i.e. how the system is represented geometrically, plays a crucial role in determining how easily the resulting equations can be solved. Given the diversity of molecular structure, it is therefore not surprising that a wide variety of geometric representations have been considered, each of which seeks to capture some important aspect of the complete structure. The term "molecular conformation" refers to those aspects of the structure of a molecule that can change without breaking or making any chemical bonds. These are generally the only interactions among atoms strong enough to resist thermal motions, and hence the "conformation" of a molecule can be identified with a set of spatial atomic structures, having a given bond arrangement, which can interconvert at ambient temperatures. Since this is generally a continuous (uncountable) set, it can only be described by a list of the invariant geometric properties that are common to all its members. The properties that have been used for this purpose include the topological (linking numbers or knot polynomials), differential (curvature, torsion and writhing), affine (linearity, planarity and chirality), and metric (lengths, angles and volumes). The task of understanding these descriptions and the relations among them is a source of many challenging mathematical and computational problems, which this workshop will seek to illustrate by means of concrete examples of chemical and biological significance.

The workshop format will aim to allow ample time for the participants to interact and get to know each other. A more detailed workshop schedule will be mailed shortly.

Additional information is available from:

Leonidas J. Guibas (Stanford University, guibas@cs.stanford.edu)

Timothy F. Havel (Harvard University, havel@ptolemy.med.harvard.edu)

Pat Toci (toci@dimacs.rutgers.edu) at DIMACS

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