Journal Article

MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8

Zheng Wang, Jesse Eickholt and Jianlin Cheng

in Bioinformatics

Volume 26, issue 7, pages 882-888
Published in print April 2010 | ISSN: 1367-4803
Published online February 2010 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btq058

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Motivation: Protein structure prediction is one of the most important problems in structural bioinformatics. Here we describe MULTICOM, a multi-level combination approach to improve the various steps in protein structure prediction. In contrast to those methods which look for the best templates, alignments and models, our approach tries to combine complementary and alternative templates, alignments and models to achieve on average better accuracy.

Results: The multi-level combination approach was implemented via five automated protein structure prediction servers and one human predictor which participated in the eighth Critical Assessment of Techniques for Protein Structure Prediction (CASP8), 2008. The MULTICOM servers and human predictor were consistently ranked among the top predictors on the CASP8 benchmark. The methods can predict moderate- to high-resolution models for most template-based targets and low-resolution models for some template-free targets. The results show that the multi-level combination of complementary templates, alternative alignments and similar models aided by model quality assessment can systematically improve both template-based and template-free protein modeling.

Availability: The MULTICOM server is freely available at http://casp.rnet.missouri.edu/multicom_3d.html

Contact: chengji@missouri.edu

Journal Article.  5273 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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