Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models

Authors

  • Pawel Gniewek,

    1. Faculty of Chemistry, University of Warsaw, Warsaw, Poland
    2. Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa
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  • Sumudu P. Leelananda,

    1. Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa
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  • Andrzej Kolinski,

    1. Faculty of Chemistry, University of Warsaw, Warsaw, Poland
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  • Robert L. Jernigan,

    1. Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa
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  • Andrzej Kloczkowski

    Corresponding author
    1. Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa
    2. Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, Ohio
    3. Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio
    • Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, Ohio
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Errata

This article is corrected by:

  1. Errata: Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models Volume 82, Issue 7, 1549, Article first published online: 26 May 2014

Abstract

Multibody potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Our goal was to combine long range multibody potentials and short range potentials to improve recognition of native structure among misfolded decoys. We optimized the weights for four-body nonsequential, four-body sequential, and short range potentials to obtain optimal model ranking results for threading and have compared these data against results obtained with other potentials (26 different coarse-grained potentials from the Potentials ‘R’Us web server have been used). Our optimized multibody potentials outperform all other contact potentials in the recognition of the native structure among decoys, both for models from homology template-based modeling and from template-free modeling in CASP8 decoy sets. We have compared the results obtained for this optimized coarse-grained potentials, where each residue is represented by a single point, with results obtained by using the DFIRE potential, which takes into account atomic level information of proteins. We found that for all proteins larger than 80 amino acids our optimized coarse-grained potentials yield results comparable to those obtained with the atomic DFIRE potential. Proteins 2011; © 2011 Wiley-Liss, Inc.

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