CASVM: web server for SVM-based prediction of caspase substrates cleavage sites.
Caspases belong to a unique class of cysteine proteases which function as critical effectors of apoptosis, inflammation and other important cellular processes. Caspases cleave substrates at specific tetrapeptide sites after a highly conserved aspartic acid residue. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. We have recently developed a support vector machines (SVM) method to address this issue. Our algorithm achieved an accuracy ranging from 81.25 to 97.92%, making it one of the best methods currently available. CASVM is the web server implementation of our SVM algorithms, written in Perl and hosted on a Linux platform. The server can be used for predicting non-canonical caspase substrate cleavage sites. We have also included a relational database containing experimentally verified caspase substrates retrievable using accession IDs, keywords or sequence similarity.


BACKGROUND
http://www.casbase.org/casvm/index.html
Wee
Lawrence J K
LJ
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Tan
Tin Wee
TW
Ranganathan
Shoba
S
D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D001665:Binding Sites; D020169:Caspases / Q000737:chemistry*; D004789:Enzyme Activation; D020407:Internet; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D011485:Protein Binding; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013379:Substrate Specificity
D020169:Caspases