An optimization approach to the problem of protein structure prediction

• 成果类型: Article
• 署名作者: Eskow, E; Bader, B; Byrd, R; Crivelli, S; Head-Gordon, T; Lamberti, V; Schnabel, R
• 署名单位: University of Colorado System; University of Colorado Boulder; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; University of California System; University of California Berkeley; University of California System; University of California Berkeley; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; University of California System; University of California Berkeley
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-003-0493-4
• 发表日期: 2004
• 页码: 497-514
• 关键词: diffusion equation method; global optimization; energy; hydration; minimization; hypersurface; algorithm; sequence; DYNAMICS

摘要

We describe a large-scale, stochastic-perturbation global optimization algorithm used for determining the structure of proteins. The method incorporates secondary structure predictions (which describe the more basic elements of the protein structure) into the starting structures, and thereafter minimizes using a purely physics-based energy model. Results show this method to be particularly successful on protein targets where structural information from similar proteins is unavailable, i.e., the most difficult targets for most protein structure prediction methods. Our best result to date is on a protein target containing over 4000 atoms and similar to12,000 cartesian coordinates.