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

Zheng Wang, Jesse Eickholt, Jianlin Cheng

Research output: Contribution to journalArticle

63 Scopus citations

Abstract

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 templatebased 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.

Original languageEnglish (US)
Article numberbtq058
Pages (from-to)882-888
Number of pages7
JournalBioinformatics
Volume26
Issue number7
DOIs
StatePublished - Feb 11 2010
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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