>>Center for New Methods for High-Resolution Comparative Modeling
This center is a collaboration among five investigators, three from
structural computational biology and two from mathematics,
statistics, and computer science. The goal of this project is to
improve the accuracy of comparative modeling with the Rosetta program. Some of the resources developed from this project are available from this page.
Conformation-dependent library for backbone geometry in proteins
This library contains information on the variation of backbone bond angles and bond lengths as a function of the backbone dihedral angles phi and psi. For some parameters, there is a systematic variation with phi or psi or both. This study was initiated by P. Andrew Karplus at Oregon State University. We performed kernel regression analysis to produce smoothly varying regression values for bond lengths and bond angles on phi and psi.
You can download the conformation-dependent backbone geometry library in an uncompressed, text format or in a zip archive. The text format is both human- and computer-friendly. The library file has Quick-Start information in its header.
Protein structure determination and predictive modeling have long been guided by the paradigm that the peptide backbone has a single, context-independent ideal geometry. Both quantum-mechanics calculations and empirical analyses have shown this is an incorrect simplification in that backbone covalent geometry actually varies systematically as a function of the phi and psi backbone dihedral angles. Here, we use a nonredundant set of ultrahigh-resolution protein structures to define these conformation-dependent variations. The trends have a rational, structural basis that can be explained by avoidance of atomic clashes or optimization of favorable electrostatic interactions. To facilitate adoption of this paradigm, we have created a conformation-dependent library of covalent bond lengths and bond angles and shown that it has improved accuracy over existing methods without any additional variables to optimize. Protein structures derived from crystallographic refinement and predictive modeling both stand to benefit from incorporation of the paradigm.
Center for New Methods for High-Resolution Comparative Modeling
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
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
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), and
high-accuracy polarizable force fields and solvation models (Ponder). The project will be based on
extensive benchmarking on realistic modeling situations.
virtualized webserver, webdesign: Adrian A. Canutescu and Maxim V. Shapovalov
This page was last modified on
Wednesday, June 1, 2011