Literature DB >> 28472402

COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information.

Chengxin Zhang1, Peter L Freddolino1,2, Yang Zhang1,2.   

Abstract

The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein-protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/.
© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2017        PMID: 28472402      PMCID: PMC5793808          DOI: 10.1093/nar/gkx366

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


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