Literature DB >> 10736233

Structure-based evaluation of sequence comparison and fold recognition alignment accuracy.

F S Domingues1, P Lackner, A Andreeva, M J Sippl.   

Abstract

The biological role, biochemical function, and structure of uncharacterized protein sequences is often inferred from their similarity to known proteins. A constant goal is to increase the reliability, sensitivity, and accuracy of alignment techniques to enable the detection of increasingly distant relationships. Development, tuning, and testing of these methods benefit from appropriate benchmarks for the assessment of alignment accuracy.Here, we describe a benchmark protocol to estimate sequence-to-sequence and sequence-to-structure alignment accuracy. The protocol consists of structurally related pairs of proteins and procedures to evaluate alignment accuracy over the whole set. The set of protein pairs covers all the currently known fold types. The benchmark is challenging in the sense that it consists of proteins lacking clear sequence similarity. Correct target alignments are derived from the three-dimensional structures of these pairs by rigid body superposition. An evaluation engine computes the accuracy of alignments obtained from a particular algorithm in terms of alignment shifts with respect to the structure derived alignments. Using this benchmark we estimate that the best results can be obtained from a combination of amino acid residue substitution matrices and knowledge-based potentials. Copyright 2000 Academic Press.

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Year:  2000        PMID: 10736233     DOI: 10.1006/jmbi.2000.3615

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  29 in total

1.  Evaluation of PSI-BLAST alignment accuracy in comparison to structural alignments.

Authors:  I Friedberg; T Kaplan; H Margalit
Journal:  Protein Sci       Date:  2000-11       Impact factor: 6.725

2.  Motif-based fold assignment.

Authors:  L Salwinski; D Eisenberg
Journal:  Protein Sci       Date:  2001-12       Impact factor: 6.725

3.  Pcons: a neural-network-based consensus predictor that improves fold recognition.

Authors:  J Lundström; L Rychlewski; J Bujnicki; A Elofsson
Journal:  Protein Sci       Date:  2001-11       Impact factor: 6.725

4.  Tools for comparative protein structure modeling and analysis.

Authors:  Narayanan Eswar; Bino John; Nebojsa Mirkovic; Andras Fiser; Valentin A Ilyin; Ursula Pieper; Ashley C Stuart; Marc A Marti-Renom; M S Madhusudhan; Bozidar Yerkovich; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

5.  Fold recognition by combining sequence profiles derived from evolution and from depth-dependent structural alignment of fragments.

Authors:  Hongyi Zhou; Yaoqi Zhou
Journal:  Proteins       Date:  2005-02-01

6.  Comprehensive evaluation of protein structure alignment methods: scoring by geometric measures.

Authors:  Rachel Kolodny; Patrice Koehl; Michael Levitt
Journal:  J Mol Biol       Date:  2005-01-16       Impact factor: 5.469

7.  Ab initio protein structure prediction using chunk-TASSER.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2007-05-11       Impact factor: 4.033

8.  Protein model quality assessment prediction by combining fragment comparisons and a consensus C(alpha) contact potential.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Proteins       Date:  2008-05-15

9.  Catalytic domain architecture of metzincin metalloproteases.

Authors:  F Xavier Gomis-Rüth
Journal:  J Biol Chem       Date:  2009-02-05       Impact factor: 5.157

10.  Protein structure prediction by pro-Sp3-TASSER.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2009-03-18       Impact factor: 4.033

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