PalmPred: An SVM Based Palmitoylation Prediction Method Using Sequence Profile Information

摘要: Protein palmitoylation is the covalent attachment of 16-carbon fatty acid palmitate to a cysteine residue. It most common acylation protein and occurs only in eukaryotes. Palmitoylation plays an important role regulation subcellular localization, stability, translocation lipid rafts many other functions. Hence, accurate prediction site(s) can help understanding molecular mechanism also designing various related experiments. Here we present novel silico predictor called ‘PalmPred’ identify sites from sequence information using support vector machine model. The best performance PalmPred was obtained by incorporating conservation features peptide window size 11 leave-one-out approach. helped achieving accuracy 91.98%, sensitivity 79.23%, specificity 94.30%, Matthews Correlation Coefficient 0.71. outperformed existing site methods – IFS-Palm WAP-Palm on independent dataset. Based these measures it be anticipated that will helpful identifying candidate sites. All source datasets, standalone web-server are available at http://14.139.227.92/mkumar/palmpred/.