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Computational Methods for the Prediction of GPCRs Coupling Selectivity

Computational Methods for the Prediction of GPCRs Coupling Selectivity
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Author(s): Nikolaos G. Sgourakis (Rensselaer Polytechnic Institute, USA), Pantelis G. Bagos (University of Central Greece, and University of Athens, Greece)and Stavros J. Hamodrakas (University of Athens, Greece)
Copyright: 2009
Pages: 15
Source title: Handbook of Research on Systems Biology Applications in Medicine
Source Author(s)/Editor(s): Andriani Daskalaki (Max Planck Institute for Molecular Genetics, Germany)
DOI: 10.4018/978-1-60566-076-9.ch009

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Abstract

GPCRs comprise a wide and diverse class of eukaryotic transmembrane proteins with well-established pharmacological significance. As a consequence of recent genome projects, there is a wealth of information at the sequence level that lacks any functional annotation. These receptors, often quoted as orphan GPCRs, could potentially lead to novel drug targets. However, typical experiments that aim at elucidating their function are hampered by the lack of knowledge on their selective coupling partners at the interior of the cell, the G-proteins. Up-to-date, computational efforts to predict properties of GPCRs have been focused mainly on the ligand-binding specificity, while the aspect of coupling has been less studied. Here, we present the main motivations, drawbacks, and results from the application of bioinformatics techniques to predict the coupling specificity of GPCRs to G-proteins, and discuss the application of the most successful methods in both experimental works that focus on a single receptor and large-scale genome annotation studies.

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