ArticleBMC bioinformatics2005
A method for the prediction of GPCRs coupling specificity to G-proteins using refined profile Hidden Markov Models.
Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 54 citations in OpenAlex.
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- Characterization of a new type of neuronal 5-HT G- protein coupled receptor in the cestode nervous system.PloS one · 2021Article
- A novel functional cross-interaction between opioid and pheromone signaling may be involved in stress avoidance in Caenorhabditis elegans.Scientific reports · 2020Article
- Expression Profiling, Downstream Signaling, and Inter-subunit Interactions of GPA2/GPB5 in the Adult MosquitoFrontiers in endocrinology · 2020Article
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- Honey Bee Allatostatins Target Galanin/Somatostatin-Like Receptors and Modulate Learning: A Conserved Function?PloS one · 2016Article
- Identification of novel arthropod vector G protein-coupled receptors.Parasites & vectors · 2013Article
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- Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.PloS one · 2011Article
- The impact of window functions on NMR-based paramagnetic relaxation enhancement measurements in membrane proteins.Biochimica et biophysica acta · 2010Article
- GPCRTree: online hierarchical classification of GPCR function.BMC research notes · 2008Article
- Advances in the Development and Application of Computational Methodologies for Structural Modeling of G-Protein Coupled Receptors.Expert opinion on drug discovery · 2008Article
- The satiety signaling neuropeptide perisulfakinin inhibits the activity of central neurons promoting general activity.Frontiers in cellular neuroscience · 2007Article
- Prediction of GPCR-G protein coupling specificity using features of sequences and biological functions.Genomics, proteomics & bioinformatics · 2006Article
- Predicting the coupling specificity of GPCRs to G-proteins by support vector machines.Genomics, proteomics & bioinformatics · 2005Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundG- Protein coupled receptors (GPCRs) comprise the largest group of eukaryotic cell surface receptors with great pharmacological interest. A broad range of native ligands interact and activate GPCRs, leading to signal transduction within cells. Most of these responses are mediated through the interaction of GPCRs with heterotrimeric GTP-binding proteins (G-proteins). Due to the information explosion in biological sequence databases, the development of software algorithms that could predict properties of GPCRs is important. Experimental data reported in the literature suggest that heterotrimeric G-proteins interact with parts of the activated receptor at the transmembrane helix-intracellular loop interface. Utilizing this information and membrane topology information, we have developed an intensive exploratory approach to generate a refined library of statistical models (Hidden Markov Models) that predict the coupling preference of GPCRs to heterotrimeric G-proteins. The method predicts the coupling preferences of GPCRs to Gs, Gi/o and Gq/11, but not G12/13 subfamilies.
resultsUsing a dataset of 282 GPCR sequences of known coupling preference to G-proteins and adopting a five-fold cross-validation procedure, the method yielded an 89.7% correct classification rate. In a validation set comprised of all receptor sequences that are species homologues to GPCRs with known coupling preferences, excluding the sequences used to train the models, our method yields a correct classification rate of 91.0%. Furthermore, promiscuous coupling properties were correctly predicted for 6 of the 24 GPCRs that are known to interact with more than one subfamily of G-proteins.
conclusionOur method demonstrates high correct classification rate. Unlike previously published methods performing the same task, it does not require any transmembrane topology prediction in a preceding step. A web-server for the prediction of GPCRs coupling specificity to G-proteins available for non-commercial users is located at http://bioinformatics.biol.uoa.gr/PRED-COUPLE.
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