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A coarse-grained protein force field for folding and structure prediction

Authors

  • Julien Maupetit,

    1. Equipe de Bioinformatique Génomique et Moléculaire, INSERM E0346, Université Paris 7, Tour 53–54, 2 place Jussieu, 75251 Paris, Cedex 05, France
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  • P. Tuffery,

    1. Equipe de Bioinformatique Génomique et Moléculaire, INSERM E0346, Université Paris 7, Tour 53–54, 2 place Jussieu, 75251 Paris, Cedex 05, France
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  • Philippe Derreumaux

    Corresponding author
    1. Laboratoire de Biochimie Théorique, UPR 9080 CNRS, Institut de Biologie Physico-Chimique et Université Paris 7, 13 rue Pierre et Marie Curie, 75005 Paris, France
    • Laboratoire de Biochimie Théorique, UPR 9080 CNRS, Institut de Biologie Physico-Chimique et Université Paris 7, 13 rue Pierre et Marie Curie, 75005 Paris, France
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Abstract

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.

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