CASVM: web server for SVM-based prediction of caspase substrates cleavage sites

Bioinformatics. 2007 Dec 1;23(23):3241-3. doi: 10.1093/bioinformatics/btm334. Epub 2007 Jun 28.


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.


Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Artificial Intelligence*
  • Binding Sites
  • Caspases / chemistry*
  • Enzyme Activation
  • Internet*
  • Molecular Sequence Data
  • Pattern Recognition, Automated / methods*
  • Protein Binding
  • Sequence Alignment / methods*
  • Sequence Analysis, Protein / methods*
  • Software*
  • Substrate Specificity


  • Caspases