Literature DB >> 18774775

ProtIdent: a web server for identifying proteases and their types by fusing functional domain and sequential evolution information.

Kuo-Chen Chou1, Hong-Bin Shen.   

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.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18774775     DOI: 10.1016/j.bbrc.2008.08.125

Source DB:  PubMed          Journal:  Biochem Biophys Res Commun        ISSN: 0006-291X            Impact factor:   3.575


  32 in total

1.  Prediction of metalloproteinase family based on the concept of Chou's pseudo amino acid composition using a machine learning approach.

Authors:  Majid Mohammad Beigi; Mohaddeseh Behjati; Hassan Mohabatkar
Journal:  J Struct Funct Genomics       Date:  2011-12-03

2.  Quat-2L: a web-server for predicting protein quaternary structural attributes.

Authors:  Xuan Xiao; Pu Wang; Kuo-Chen Chou
Journal:  Mol Divers       Date:  2010-02-11       Impact factor: 2.943

3.  Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information.

Authors:  Jagat S Chauhan; Nitish K Mishra; Gajendra P S Raghava
Journal:  BMC Bioinformatics       Date:  2010-06-03       Impact factor: 3.169

4.  PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.

Authors:  Jiangning Song; Fuyi Li; André Leier; Tatiana T Marquez-Lago; Tatsuya Akutsu; Gholamreza Haffari; Kuo-Chen Chou; Geoffrey I Webb; Robert N Pike; John Hancock
Journal:  Bioinformatics       Date:  2018-02-15       Impact factor: 6.937

5.  Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks.

Authors:  Lázaro Guillermo Pérez-Montoto; María Auxiliadora Dea-Ayuela; Francisco J Prado-Prado; Francisco Bolas-Fernández; Florencio M Ubeira; Humberto González-Díaz
Journal:  Polymer (Guildf)       Date:  2009-06-03       Impact factor: 4.430

6.  Predicting drug-target interaction networks based on functional groups and biological features.

Authors:  Zhisong He; Jian Zhang; Xiao-He Shi; Le-Le Hu; Xiangyin Kong; Yu-Dong Cai; Kuo-Chen Chou
Journal:  PLoS One       Date:  2010-03-11       Impact factor: 3.240

7.  Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization.

Authors:  Kuo-Chen Chou; Hong-Bin Shen
Journal:  PLoS One       Date:  2010-06-28       Impact factor: 3.240

8.  Comparative docking study of anibamine as the first natural product CCR5 antagonist in CCR5 homology models.

Authors:  Guo Li; Kendra M Haney; Glen E Kellogg; Yan Zhang
Journal:  J Chem Inf Model       Date:  2009-01       Impact factor: 4.956

9.  Protein domain boundary predictions: a structural biology perspective.

Authors:  Svetlana Kirillova; Suresh Kumar; Oliviero Carugo
Journal:  Open Biochem J       Date:  2009-01-21

10.  Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model.

Authors:  Wei-Zhong Lin; Jian-An Fang; Xuan Xiao; Kuo-Chen Chou
Journal:  PLoS One       Date:  2012-11-26       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.