Literature DB >> 10328270

Averaging interaction energies over homologs improves protein fold recognition in gapless threading.

B A Reva1, J Skolnick, A V Finkelstein.   

Abstract

Protein structure prediction is limited by the inaccuracy of the simplified energy functions necessary for efficient sorting over many conformations. It was recently suggested (Finkelstein, Phys Rev Lett 1998;80:4823-4825) that these errors can be reduced by energy averaging over a set of homologous sequences. This conclusion is confirmed in this study by testing protein structure recognition in gapless threading. The accuracy of recognition was estimated by the Z-score values obtained in gapless threading tests. For threading, we used 20 target proteins, each having from 20 to 70 homologs taken from the HSSP sequence base. The energy of the native structures was compared with the energy from 34 to 75 thousand of alternative structures generated by threading. The energy calculations were done with our recently developed Calpha atom-based phenomenological potentials. We show that averaging of protein energies over homologs reduces the Z-score from approximately -6.1 (average Z-score for individual chains) to approximately -8.1. This means that a correct fold can be found among 3 x 10(9) random folds in the first case and among 3 x 10(15) in the second. Such increase in selectivity is important for recognition of protein folds.

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Year:  1999        PMID: 10328270

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


  6 in total

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Authors:  T Pons; L Hernández; F R Batista; G Chinea
Journal:  Protein Sci       Date:  2000-11       Impact factor: 6.725

2.  Structural analysis of conserved base pairs in protein-DNA complexes.

Authors:  Leonid A Mirny; Mikhail S Gelfand
Journal:  Nucleic Acids Res       Date:  2002-04-01       Impact factor: 16.971

3.  Statistical significance of protein structure prediction by threading.

Authors:  L A Mirny; A V Finkelstein; E I Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-29       Impact factor: 11.205

4.  Associative memory Hamiltonians for structure prediction without homology: alpha/beta proteins.

Authors:  Corey Hardin; Michael P Eastwood; Michael C Prentiss; Zadia Luthey-Schulten; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2003-01-28       Impact factor: 11.205

5.  A new molecular signature method for prediction of driver cancer pathways from transcriptional data.

Authors:  Dmitry Rykunov; Noam D Beckmann; Hui Li; Andrew Uzilov; Eric E Schadt; Boris Reva
Journal:  Nucleic Acids Res       Date:  2016-04-20       Impact factor: 16.971

6.  Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction.

Authors:  Ching-Wai Tan; David T Jones
Journal:  BMC Bioinformatics       Date:  2008-02-11       Impact factor: 3.169

  6 in total

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