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A coarse‐grained protein force field for folding and structure prediction
Author(s) -
Maupetit Julien,
Tuffery P.,
Derreumaux Philippe
Publication year - 2007
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.21505
Subject(s) - threading (protein sequence) , protein structure prediction , force field (fiction) , computer science , protein folding , folding (dsp implementation) , monte carlo method , statistical potential , native state , protein structure , biological system , statistical physics , physics , artificial intelligence , mathematics , biology , engineering , statistics , nuclear magnetic resonance , electrical engineering
We have revisited the protein coarse‐grained optimized potential for efficient structure prediction (OPEP). The training and validation sets consist of 13 and 16 protein targets. Because optimization depends on details of how the ensemble of decoys is sampled, trial conformations are generated by molecular dynamics, threading, greedy, and Monte Carlo simulations, or taken from publicly available databases. The OPEP parameters are varied by a genetic algorithm using a scoring function which requires that the native structure has the lowest energy, and the native‐like structures have energy higher than the native structure but lower than the remote conformations. Overall, we find that OPEP correctly identifies 24 native or native‐like states for 29 targets and has very similar capability to the all‐atom discrete optimized protein energy model (DOPE), found recently to outperform five currently used energy models. Proteins 2007. © 2007 Wiley‐Liss, Inc.