Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Sanders, Marijn PA, Fleuren, Wilco WM, Verhoeven, Stefan, van den Beld, Sven, Alkema, Wynand, de Vlieg, Jacob, Klomp, Jan PG
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
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
_version_ 1782210903846944768
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
work_keys_str_mv AT sandersmarijnpa ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT fleurenwilcowm ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT verhoevenstefan ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT vandenbeldsven ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT alkemawynand ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT devliegjacob ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs
AT klompjanpg ssteaentropybasedidentificationofreceptorspecificligandbindingresiduesfromamultiplesequencealignmentofclassagpcrs