title: High precision prediction of functional sites in protein structures.
abstract: We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta.
authors.affiliation: Department of Computer Science, San Francisco State University, San Francisco, California, United States of America.
authors.forename: Ljubomir
authors.initials: L
authors.lastname: Buturovic
authors.affiliation: Center for Computing for Life Sciences, San Francisco State University, San Francisco, California, United States of America.
authors.forename: Mike
authors.initials: M
authors.lastname: Wong
authors.affiliation: Department of Bioengineering, Stanford University, Stanford, California, United States of America.
authors.forename: Grace W
authors.initials: GW
authors.lastname: Tang
authors.affiliation: Department of Bioengineering, Stanford University, Stanford, California, United States of America.
authors.forename: Russ B
authors.initials: RB
authors.lastname: Altman
authors.affiliation: Department of Computer Science, San Francisco State University, San Francisco, California, United States of America; Center for Computing for Life Sciences, San Francisco State University, San Francisco, California, United States of America.
authors.forename: Dragutin
authors.initials: D
authors.lastname: Petkovic
mesh_terms: D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins