Literature DB >> 11276086

Lattice protein folding with two and four-body statistical potentials.

H H Gan1, A Tropsha, T Schlick.   

Abstract

The cooperative folding of proteins implies a description by multibody potentials. Such multibody potentials can be generalized from common two-body statistical potentials through a relation to probability distributions of residue clusters via the Boltzmann condition. In this exploratory study, we compare a four-body statistical potential, defined by the Delaunay tessellation of protein structures, to the Miyazawa-Jernigan (MJ) potential for protein structure prediction, using a lattice chain growth algorithm. We use the four-body potential as a discriminatory function for conformational ensembles generated with the MJ potential and examine performance on a set of 22 proteins of 30-76 residues in length. We find that the four-body potential yields comparable results to the two-body MJ potential, namely, an average coordinate root-mean-square deviation (cRMSD) value of 8 A for the lowest energy configurations of all-alpha proteins, and somewhat poorer cRMSD values for other protein classes. For both two and four-body potentials, superpositions of some predicted and native structures show a rough overall agreement. Formulating the four-body potential using larger data sets and direct, but costly, generation of conformational ensembles with multibody potentials may offer further improvements. Proteins 2001;43:161-174. Copyright 2001 Wiley-Liss, Inc.

Mesh:

Year:  2001        PMID: 11276086     DOI: 10.1002/1097-0134(20010501)43:2<161::aid-prot1028>3.0.co;2-f

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  6 in total

1.  Free energies of protein decoys provide insight into determinants of protein stability.

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4.  From isotropic to anisotropic side chain representations: comparison of three models for residue contact estimation.

Authors:  Weitao Sun; Jing He
Journal:  PLoS One       Date:  2011-04-28       Impact factor: 3.240

5.  Structure and age jointly influence rates of protein evolution.

Authors:  Macarena Toll-Riera; David Bostick; M Mar Albà; Joshua B Plotkin
Journal:  PLoS Comput Biol       Date:  2012-05-31       Impact factor: 4.475

6.  Residue contact-count potentials are as effective as residue-residue contact-type potentials for ranking protein decoys.

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Journal:  BMC Struct Biol       Date:  2008-12-08
  6 in total

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