Abstract

Abstract Motivation: Homology or comparative modeling is currently the most accurate method to predict the three-dimensional structure of proteins. It generally consists in four steps: (1) databanks searching to identify the structural homolog, (2) target–template alignment, (3) model building and optimization, and (4) model evaluation. The target–template alignment step is generally accepted as the most critical step in homology modeling. Results: We present here ESyPred3D, a new automated homology modeling program. The method gets benefit of the increased alignment performances of a new alignment strategy. Alignments are obtained by combining, weighting and screening the results of several multiple alignment programs. The final three-dimensional structure is build using the modeling package MODELLER. ESyPred3D was tested on 13 targets in the CASP4 experiment (Critical Assessment of Techniques for Proteins Structural Prediction). Our alignment strategy obtains better results compared to PSI-BLAST alignments and ESyPred3D alignments are among the most accurate compared to those of participants having used the same template. Availability: ESyPred3D is available through its web site at http://www.fundp.ac.be/urbm/bioinfo/esypred/ Contact: christophe.lambert@fundp.ac.behttp://www.fundp.ac.be/~lambertc * To whom correspondence should be addressed.

Keywords

MODELLERComputer scienceWeightingHomology modelingSequence alignmentMultiple sequence alignmentCASPStructural alignmentData miningProtein structure predictionSequence homologyHomology (biology)Artificial intelligenceProtein structureBase sequenceBiologyPeptide sequence

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Publication Info

Year
2002
Type
article
Volume
18
Issue
9
Pages
1250-1256
Citations
610
Access
Closed

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Christophe Lambert, Nadia G. Léonard, Xavier De Bolle et al. (2002). ESyPred3D: Prediction of proteins 3D structures. Bioinformatics , 18 (9) , 1250-1256. https://doi.org/10.1093/bioinformatics/18.9.1250

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DOI
10.1093/bioinformatics/18.9.1250