GRIFFIN: a system for predicting GPCR-G-protein coupling selectivity using a support vector machine and a hidden Markov model
- PMID: 15980445
- PMCID: PMC1160255
- DOI: 10.1093/nar/gki495
GRIFFIN: a system for predicting GPCR-G-protein coupling selectivity using a support vector machine and a hidden Markov model
Abstract
We describe a novel system, GRIFFIN (G-protein and Receptor Interaction Feature Finding INstrument), that predicts G-protein coupled receptor (GPCR) and G-protein coupling selectivity based on a support vector machine (SVM) and a hidden Markov model (HMM) with high sensitivity and specificity. Based on our assumption that whole structural segments of ligands, GPCRs and G-proteins are essential to determine GPCR and G-protein coupling, various quantitative features were selected for ligands, GPCRs and G-protein complex structures, and those parameters that are the most effective in selecting G-protein type were used as feature vectors in the SVM. The main part of GRIFFIN includes a hierarchical SVM classifier using the feature vectors, which is useful for Class A GPCRs, the major family. For the opsins and olfactory subfamilies of Class A and other minor families (Classes B, C, frizzled and smoothened), the binding G-protein is predicted with high accuracy using the HMM. Applying this system to known GPCR sequences, each binding G-protein is predicted with high sensitivity and specificity (>85% on average). GRIFFIN (http://griffin.cbrc.jp/) is freely available and allows users to easily execute this reliable prediction of G-proteins.
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References
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- Drews J. Genomic sciences and the medicine of tomorrow. Nat. Biotechnol. 1996;14:1516–1518. - PubMed
-
- Gaulton A., Attwood T.K. Bioinformatics approaches for the classification of G-protein-coupled receptors. Curr. Opin. Pharmacol. 2003;3:114–120. - PubMed
-
- Karchin R., Karplus K., Haussler D. Classifying G-protein coupled receptors with support vector machines. Bioinformatics. 2002;18:147–159. - PubMed
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