Literature DB >> 21586517

Hidden conformations in protein structures.

Haim Ashkenazy1, Ron Unger, Yossef Kliger.   

Abstract

MOTIVATION: Prediction of interactions between protein residues (contact map prediction) can facilitate various aspects of 3D structure modeling. However, the accuracy of ab initio contact prediction is still limited. As structural genomics initiatives move ahead, solved structures of homologous proteins can be used as multiple templates to improve contact prediction of the major conformation of an unsolved target protein. Furthermore, multiple templates may provide a wider view of the protein's conformational space. However, successful usage of multiple structural templates is not straightforward, due to their variable relevance to the target protein, and because of data redundancy issues.
RESULTS: We present here an algorithm that addresses these two limitations in the use of multiple structure templates. First, the algorithm unites contact maps extracted from templates sharing high sequence similarity with each other in a fashion that acknowledges the possibility of multiple conformations. Next, it weights the resulting united maps in inverse proportion to their evolutionary distance from the target protein. Testing this algorithm against CASP8 targets resulted in high precision contact maps. Remarkably, based solely on structural data of remote homologues, our algorithm identified residue-residue interactions that account for all the known conformations of calmodulin, a multifaceted protein. Therefore, employing multiple templates, which improves prediction of contact maps, can also be used to reveal novel conformations. As multiple templates will soon be available for most proteins, our scheme suggests an effective procedure for their optimal consideration. AVAILABILITY: A Perl script implementing the WMC algorithm described in this article is freely available for academic use at http://tau.ac.il/~haimash/WMC.

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Year:  2011        PMID: 21586517     DOI: 10.1093/bioinformatics/btr292

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

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  3 in total

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