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Scoring docking models with evolutionary information
Author(s) -
Tress Michael,
de Juan David,
Graña Osvaldo,
Gómez Manuel J.,
GómezPuertas Paulino,
González Jose M.,
López Gonzalo,
Valencia Alfonso
Publication year - 2005
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.20570
Subject(s) - docking (animal) , computer science , sequence (biology) , computational biology , multiple sequence alignment , machine learning , artificial intelligence , data mining , sequence alignment , biology , peptide sequence , genetics , medicine , nursing , gene
We have developed methods for the extraction of evolutionary information from multiple sequence alignments for use in the study of the evolution of protein interaction networks and in the prediction of protein interaction. For Rounds 3, 4, and 5 of the CAPRI experiment, we used scores derived from the analysis of multiple sequence alignments to submit predictions for 7 of the 12 targets. Our docking models were generated with Hex and GRAMM, but all our predictions were selected using methods based on multiple sequence alignments and on the available experimental evidence. With this approach, we were able to predict acceptable level models for 4 of the targets, and for a fifth target, we located the residues involved in the binding surface. Here we detail our successes and highlight several of the limitations and problems that we faced while dealing with particular docking cases. Proteins 2005;60:275–280. © 2005 Wiley‐Liss, Inc.