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           COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
                             College of Science
                      (CDS Department CSI 898-Sec 001)
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CATALYTIC SITE IDENTIFICATION IN PROTEINS:  A COMPUTATIONAL GEOMETRY AND
               MULTI-BODY STATISTICAL POTENTIAL APPRAOCH.

                      D. Andrew Carr, Ph.D.
     Computational Materials Science Center, College of Science, 
                    George Mason University 

Protein function is directly linked to the three-dimensional protein
structure.  The eventual goal of structural genomics to understand the
relationship between protein structure and enzyme function.  Currently
numerous structural genomic projects produce known protein structures that
have unknown function.  The rapid increase in number of publicly available
crystallized protein structures in the Protein Data Bank (PDB) has given rise
to the need for algorithms and tools that illuminate the linkage between
protein structure and function.  Detection of key functionally active amino
acids is necessary for protein classification, evolutionary study and drug
design.  A novel approach to predicting functional sites within the
topological space created through the Delaunay tessellation of a proteins
C_alpha backbone.  Likelihood potentials for tetrahedra produce by the Delaunay
tessellation of the protein backbone provide input to ensemble learning
algorithms that create catalytic site assignment models.  This talk discusses
the effective nature of the assignment models as developed on a large set of
proteins structures.
                          April 30, 4:30 pm
                   Room 301, Research I, Fairfax Campus


Refreshments will be served at 4:15 PM.
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Find the schedule at http://www.cmasc.gmu.edu/seminar/schedule.html
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