ss-TEA : entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs

M.P.A. Sanders, W.W.M. Fleuren, S. Verhoeven, S. Beld, van den, W. Alkema, J. Vlieg, de, J.P.G. Klomp

    Research output: Contribution to journalArticleAcademicpeer-review

    17 Citations (Scopus)
    284 Downloads (Pure)

    Abstract

    BACKGROUND: G-protein coupled receptors (GPCRs) are involved in many different physiological processes and their function can be modulated by small molecules which bind in the transmembrane (TM) domain. Because of their structural and sequence conservation, the TM domains are often used in bioinformatics approaches to first create a multiple sequence alignment (MSA) and subsequently identify ligand binding positions. So far methods have been developed to predict the common ligand binding residue positions for class A GPCRs. RESULTS: Here we present 1) ss-TEA, a method to identify specific ligand binding residue positions for any receptor, predicated on high quality sequence information. 2) The largest MSA of class A non olfactory GPCRs in the public domain consisting of 13324 sequences covering most of the species homologues of the human set of GPCRs. A set of ligand binding residue positions extracted from literature of 10 different receptors shows that our method has the best ligand binding residue prediction for 9 of these 10 receptors compared to another state-of-the-art method. CONCLUSIONS: The combination of the large multi species alignment and the newly introduced residue selection method ss-TEA can be used to rapidly identify subfamily specific ligand binding residues. This approach can aid the design of site directed mutagenesis experiments, explain receptor function and improve modelling. The method is also available online via GPCRDB at http://www.gpcr.org/7tm/.
    Original languageEnglish
    Pages (from-to)332-1/12
    JournalBMC Bioinformatics
    Volume12
    DOIs
    Publication statusPublished - 2011

    Fingerprint

    Dive into the research topics of 'ss-TEA : entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs'. Together they form a unique fingerprint.

    Cite this