Journal
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
Volume 376, Issue 2, Pages 321-325Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2008.08.125
Keywords
Protease type; Evolution; Functional domain; Fusion approach; OET-KNN; ProtIdent; Web-server
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Funding
- National Natural Science Foundation of China [60704047]
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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. (C) 2008 Elsevier Inc. All rights reserved.
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