Literature DB >> 20225257

Contact prediction for beta and alpha-beta proteins using integer linear optimization and its impact on the first principles 3D structure prediction method ASTRO-FOLD.

R Rajgaria1, Y Wei, C A Floudas.   

Abstract

An integer linear optimization model is presented to predict residue contacts in beta, alpha + beta, and alpha/beta proteins. The total energy of a protein is expressed as sum of a C(alpha)-C(alpha) distance dependent contact energy contribution and a hydrophobic contribution. The model selects contact that assign lowest energy to the protein structure as satisfying a set of constraints that are included to enforce certain physically observed topological information. A new method based on hydrophobicity is proposed to find the beta-sheet alignments. These beta-sheet alignments are used as constraints for contacts between residues of beta-sheets. This model was tested on three independent protein test sets and CASP8 test proteins consisting of beta, alpha + beta, alpha/beta proteins and it was found to perform very well. The average accuracy of the predictions (separated by at least six residues) was approximately 61%. The average true positive and false positive distances were also calculated for each of the test sets and they are 7.58 A and 15.88 A, respectively. Residue contact prediction can be directly used to facilitate the protein tertiary structure prediction. This proposed residue contact prediction model is incorporated into the first principles protein tertiary structure prediction approach, ASTRO-FOLD. The effectiveness of the contact prediction model was further demonstrated by the improvement in the quality of the protein structure ensemble generated using the predicted residue contacts for a test set of 10 proteins.

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Year:  2010        PMID: 20225257      PMCID: PMC2858251          DOI: 10.1002/prot.22696

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


  57 in total

1.  Protein secondary structure prediction based on position-specific scoring matrices.

Authors:  D T Jones
Journal:  J Mol Biol       Date:  1999-09-17       Impact factor: 5.469

2.  Prediction of contact maps with neural networks and correlated mutations.

Authors:  P Fariselli; O Olmea; A Valencia; R Casadio
Journal:  Protein Eng       Date:  2001-11

3.  Progress in predicting inter-residue contacts of proteins with neural networks and correlated mutations.

Authors:  P Fariselli; O Olmea; A Valencia; R Casadio
Journal:  Proteins       Date:  2001

4.  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

5.  Scoring function for automated assessment of protein structure template quality.

Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  Proteins       Date:  2004-12-01

6.  Prediction of distant residue contacts with the use of evolutionary information.

Authors:  Spyridon Vicatos; Boojala V B Reddy; Yiannis Kaznessis
Journal:  Proteins       Date:  2005-03-01

7.  Reconstruction of 3D structures from protein contact maps.

Authors:  Marco Vassura; Luciano Margara; Pietro Di Lena; Filippo Medri; Piero Fariselli; Rita Casadio
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2008 Jul-Sep       Impact factor: 3.710

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.  Nativelike topology assembly of small proteins using predicted restraints in Monte Carlo folding simulations.

Authors:  A R Ortiz; A Kolinski; J Skolnick
Journal:  Proc Natl Acad Sci U S A       Date:  1998-02-03       Impact factor: 11.205

10.  Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives.

Authors:  Petras J Kundrotas; Emil G Alexov
Journal:  BMC Bioinformatics       Date:  2006-11-16       Impact factor: 3.169

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  9 in total

1.  Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement.

Authors:  Dong Xu; Jian Zhang; Ambrish Roy; Yang Zhang
Journal:  Proteins       Date:  2011-08-23

2.  Protein WISDOM: a workbench for in silico de novo design of biomolecules.

Authors:  James Smadbeck; Meghan B Peterson; George A Khoury; Martin S Taylor; Christodoulos A Floudas
Journal:  J Vis Exp       Date:  2013-07-25       Impact factor: 1.355

3.  BCov: a method for predicting β-sheet topology using sparse inverse covariance estimation and integer programming.

Authors:  Castrense Savojardo; Piero Fariselli; Pier Luigi Martelli; Rita Casadio
Journal:  Bioinformatics       Date:  2013-09-23       Impact factor: 6.937

4.  WeFold: a coopetition for protein structure prediction.

Authors:  George A Khoury; Adam Liwo; Firas Khatib; Hongyi Zhou; Gaurav Chopra; Jaume Bacardit; Leandro O Bortot; Rodrigo A Faccioli; Xin Deng; Yi He; Pawel Krupa; Jilong Li; Magdalena A Mozolewska; Adam K Sieradzan; James Smadbeck; Tomasz Wirecki; Seth Cooper; Jeff Flatten; Kefan Xu; David Baker; Jianlin Cheng; Alexandre C B Delbem; Christodoulos A Floudas; Chen Keasar; Michael Levitt; Zoran Popović; Harold A Scheraga; Jeffrey Skolnick; Silvia N Crivelli
Journal:  Proteins       Date:  2014-07-08

5.  Enhanced Inter-helical Residue Contact Prediction in Transmembrane Proteins.

Authors:  Y Wei; C A Floudas
Journal:  Chem Eng Sci       Date:  2011-10-01       Impact factor: 4.311

6.  Inter-Residue Distance Prediction From Duet Deep Learning Models.

Authors:  Huiling Zhang; Ying Huang; Zhendong Bei; Zhen Ju; Jintao Meng; Min Hao; Jingjing Zhang; Haiping Zhang; Wenhui Xi
Journal:  Front Genet       Date:  2022-05-16       Impact factor: 4.772

7.  ASTRO-FOLD 2.0: an Enhanced Framework for Protein Structure Prediction.

Authors:  A Subramani; Y Wei; C A Floudas
Journal:  AIChE J       Date:  2011-05-31       Impact factor: 3.993

Review 8.  Protein folding and de novo protein design for biotechnological applications.

Authors:  George A Khoury; James Smadbeck; Chris A Kieslich; Christodoulos A Floudas
Journal:  Trends Biotechnol       Date:  2013-11-19       Impact factor: 19.536

9.  BetaSearch: a new method for querying β-residue motifs.

Authors:  Hui Kian Ho; Graeme Gange; Michael J Kuiper; Kotagiri Ramamohanarao
Journal:  BMC Res Notes       Date:  2012-07-30
  9 in total

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