COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information. Issue Volume 45:Issue W1(2017) (2nd May 2017)

• Record Type: Journal Article
• Authors: Zhang, Chengxin; Freddolino, Peter L.; Zhang, Yang
• Is Part Of: Nucleic acids research. Volume 45:Issue W1(2017)
• Page Start: W291
• Page End: W299
• Publication Date: 2017-05-02
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx366
• Languages: English
• ISSNs: 0305-1048

Abstract

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/ .