This center is a collaboration among six investigators, three from
structural computational biology and three from mathematics,
statistics, and computer science. The goal of this project is to
improve the accuracy of comparative modeling both in the 30-90%
sequence identity range and in the 10-30% range.
This center is funded
under grant P20 GM76222 from the National Institutes of Health under the National
Institute for General Medical Sciences, as part of the Protein Structure Initiative
(PSI2).
The investigators involved in this project are:
- Roland Dunbrack, Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia PA
- David Baker, Department of Biochemistry, University of Washington, Seattle WA
- Jay Ponder, Department of Bioehemistry, Washington University, St. Louis, MO
- Michael I. Jordan, Departments of Statistics and of Electrical Engineering and Computer Sciences, University of California, Berkeley CA
- Paul Tseng, Department of Mathematics, University of Washington, Seattle WA
- Martin Tompa, Department of Computer Science and Engineering, University of Washington, Seattle WA
The project is centered on improving the Rosetta program, developed by the Baker group, for the purpose
of comparative modeling based on homologous templates. This is being accomplished by the development
of better statistical potentials for the backbone and side chains using Bayesian non-parametric methods (Dunbrack and Jordan),
modern methods for local and global optimization of functions (Tseng), backtracking search algorithms (Tompa), and
high-accuracy polarizable force fields and solvation models (Ponder). The project will be based on
extensive benchmarking on realistic modeling situations.
As statistical potentials, benchmarks, and other data become available, they will be distributed
via this page.
