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ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs
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 bioinform...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162937/ https://www.ncbi.nlm.nih.gov/pubmed/21831265 http://dx.doi.org/10.1186/1471-2105-12-332 |
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author | Sanders, Marijn PA Fleuren, Wilco WM Verhoeven, Stefan van den Beld, Sven Alkema, Wynand de Vlieg, Jacob Klomp, Jan PG |
author_facet | Sanders, Marijn PA Fleuren, Wilco WM Verhoeven, Stefan van den Beld, Sven Alkema, Wynand de Vlieg, Jacob Klomp, Jan PG |
author_sort | Sanders, Marijn PA |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-3162937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31629372011-08-28 ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs Sanders, Marijn PA Fleuren, Wilco WM Verhoeven, Stefan van den Beld, Sven Alkema, Wynand de Vlieg, Jacob Klomp, Jan PG BMC Bioinformatics Research Article 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/. BioMed Central 2011-08-10 /pmc/articles/PMC3162937/ /pubmed/21831265 http://dx.doi.org/10.1186/1471-2105-12-332 Text en Copyright ©2011 Sanders et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sanders, Marijn PA Fleuren, Wilco WM Verhoeven, Stefan van den Beld, Sven Alkema, Wynand de Vlieg, Jacob Klomp, Jan PG ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title | ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title_full | ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title_fullStr | ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title_full_unstemmed | ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title_short | ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs |
title_sort | ss-tea: entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class a gpcrs |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162937/ https://www.ncbi.nlm.nih.gov/pubmed/21831265 http://dx.doi.org/10.1186/1471-2105-12-332 |
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