title: ProtIdent: a web server for identifying proteases and their types by fusing functional domain and sequential evolution information.
abstract: Proteases are vitally important to life cycles and have become a main target in drug development. According to their action mechanisms, proteases are classified into six types: (1) aspartic, (2) cysteine, (3) glutamic, (4) metallo, (5) serine, and (6) threonine. Given the sequence of an uncharacterized protein, can we identify whether it is a protease or non-protease? If it is, what type does it belong to? To address these problems, a 2-layer predictor, called "ProtIdent", is developed by fusing the functional domain and sequential evolution information: the first layer is for identifying the query protein as protease or non-protease; if it is a protease, the process will automatically go to the second layer to further identify it among the six types. The overall success rates in both cases by rigorous cross-validation tests were higher than 92%. ProtIdent is freely accessible to the public as a web server at http://www.csbio.sjtu.edu.cn/bioinf/Protease.
authors.affiliation: Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai, 200240, China. kcchou@gordonlifescience.org
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
authors.forename: Hong-Bin
authors.initials: HB
authors.lastname: Shen
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003195:Computer Communication Networks; D030562:Databases, Protein; D019143:Evolution, Molecular; D006801:Humans; D010447:Peptide Hydrolases / Q000737:chemistry* / Q000145:classification*; D017434:Protein Structure, Tertiary; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D010447:Peptide Hydrolases