Literature DB >> 10380223

A combined approach for ab initio construction of low resolution protein tertiary structures from sequence.

R Samudrala1, Y Xia, M Levitt, E S Huang.   

Abstract

An approach to construct low resolution models of protein structure from sequence information using a combination of different methodologies is described. All possible compact self-avoiding C alpha conformations (approximately 10 million) of a small protein chain were exhaustively enumerated on a tetrahedral lattice. The best scoring 10,000 conformations were selected using a lattice-based scoring function. All-atom structures were then generated by fitting an off-lattice four-state phi/psi model to the lattice conformations, using idealised helix and sheet values based on predicted secondary structure. The all-atom conformations were minimised using ENCAD and scored using a second hybrid scoring function. The best scoring 50, 100, and 500 conformations were input to a consensus-based distance geometry routine that used constraints from each the conformation sets and produced a single structure for each set (total of three). Secondary structures were again fitted to the three structures, and the resulting structures were minimised and scored. The lowest scoring conformation was taken to be the "correct" answer. The results of application of this method to twelve proteins are presented.

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Year:  1999        PMID: 10380223     DOI: 10.1142/9789814447300_0050

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  20 in total

1.  An accurate, residue-level, pair potential of mean force for folding and binding based on the distance-scaled, ideal-gas reference state.

Authors:  Chi Zhang; Song Liu; Hongyi Zhou; Yaoqi Zhou
Journal:  Protein Sci       Date:  2004-02       Impact factor: 6.725

2.  Contact order and ab initio protein structure prediction.

Authors:  Richard Bonneau; Ingo Ruczinski; Jerry Tsai; David Baker
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

3.  The dependence of all-atom statistical potentials on structural training database.

Authors:  Chi Zhang; Song Liu; Hongyi Zhou; Yaoqi Zhou
Journal:  Biophys J       Date:  2004-06       Impact factor: 4.033

4.  Database-derived potentials dependent on protein size for in silico folding and design.

Authors:  Yves Dehouck; Dimitri Gilis; Marianne Rooman
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

5.  GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2011-10-19       Impact factor: 4.033

6.  OPUS-Ca: a knowledge-based potential function requiring only Calpha positions.

Authors:  Yinghao Wu; Mingyang Lu; Mingzhi Chen; Jialin Li; Jianpeng Ma
Journal:  Protein Sci       Date:  2007-07       Impact factor: 6.725

7.  OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing.

Authors:  Mingyang Lu; Athanasios D Dousis; Jianpeng Ma
Journal:  J Mol Biol       Date:  2007-11-19       Impact factor: 5.469

8.  Selecting high quality protein structures from diverse conformational ensembles.

Authors:  Ashwin Subramani; Peter A DiMaggio; Christodoulos A Floudas
Journal:  Biophys J       Date:  2009-09-16       Impact factor: 4.033

9.  OPUS-SSF: A side-chain-inclusive scoring function for ranking protein structural models.

Authors:  Gang Xu; Tianqi Ma; Qinghua Wang; Jianpeng Ma
Journal:  Protein Sci       Date:  2019-04-11       Impact factor: 6.725

10.  Explicit orientation dependence in empirical potentials and its significance to side-chain modeling.

Authors:  Jianpeng Ma
Journal:  Acc Chem Res       Date:  2009-08-18       Impact factor: 22.384

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