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• W2104812418 abstract "We have developed a new COFACTOR webserver for automated structure-based protein function annotation. Starting from a structural model, given by either experimental determination or computational modeling, COFACTOR first identifies template proteins of similar folds and functional sites by threading the target structure through three representative template libraries that have known protein-ligand binding interactions, Enzyme Commission number or Gene Ontology terms. The biological function insights in these three aspects are then deduced from the functional templates, the confidence of which is evaluated by a scoring function that combines both global and local structural similarities. The algorithm has been extensively benchmarked by large-scale benchmarking tests and demonstrated significant advantages compared to traditional sequence-based methods. In the recent community-wide CASP9 experiment, COFACTOR was ranked as the best method for protein-ligand binding site predictions. The COFACTOR sever and the template libraries are freely available at http://zhanglab.ccmb.med.umich.edu/COFACTOR." @default.
• W2104812418 created "2016-06-24" @default.
• W2104812418 creator A5022802322 @default.
• W2104812418 creator A5039823039 @default.
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• W2104812418 date "2012-05-08" @default.
• W2104812418 modified "2023-10-17" @default.
• W2104812418 title "COFACTOR: an accurate comparative algorithm for structure-based protein function annotation" @default.
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• W2104812418 doi "https://doi.org/10.1093/nar/gks372" @default.
• W2104812418 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3394312" @default.
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