Chou Kuo-Chen, Shen Hong-Bin
Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai, 200240, China.
Biochem Biophys Res Commun. 2008 Nov 14;376(2):321-5. doi: 10.1016/j.bbrc.2008.08.125. Epub 2008 Sep 5.
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.
蛋白酶对生命周期至关重要，已成为药物开发的主要靶点。根据其作用机制，蛋白酶可分为六种类型：（1）天冬氨酸蛋白酶，（2）半胱氨酸蛋白酶，（3）谷氨酸蛋白酶，（4）金属蛋白酶，（5）丝氨酸蛋白酶，以及（6）苏氨酸蛋白酶。给定一个未鉴定的蛋白质序列，我们能否确定它是蛋白酶还是非蛋白酶？如果是，它属于哪种类型？为了解决这些问题，通过融合功能域和序列进化信息开发了一种名为“ProtIdent”的两层预测器：第一层用于将查询蛋白质鉴定为蛋白酶或非蛋白酶；如果是蛋白酶，该过程将自动进入第二层，在六种类型中进一步鉴定它。通过严格的交叉验证测试，两种情况下的总体成功率均高于92%。公众可通过网页服务器http://www.csbio.sjtu.edu.cn/bioinf/Protease免费访问ProtIdent。
