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PRECOG: PREdicting COupling probabilities of G-protein coupled receptors

G-protein coupled receptors (GPCRs) control multiple physiological states by transducing a multitude of extracellular stimuli into the cell via coupling to intra-cellular heterotrimeric G-proteins. Deciphering which G-proteins couple to each of the hundreds of GPCRs present in a typical eukaryotic o...

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Autores principales: Singh, Gurdeep, Inoue, Asuka, Gutkind, J Silvio, Russell, Robert B, Raimondi, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602504/
https://www.ncbi.nlm.nih.gov/pubmed/31143927
http://dx.doi.org/10.1093/nar/gkz392
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author Singh, Gurdeep
Inoue, Asuka
Gutkind, J Silvio
Russell, Robert B
Raimondi, Francesco
author_facet Singh, Gurdeep
Inoue, Asuka
Gutkind, J Silvio
Russell, Robert B
Raimondi, Francesco
author_sort Singh, Gurdeep
collection PubMed
description G-protein coupled receptors (GPCRs) control multiple physiological states by transducing a multitude of extracellular stimuli into the cell via coupling to intra-cellular heterotrimeric G-proteins. Deciphering which G-proteins couple to each of the hundreds of GPCRs present in a typical eukaryotic organism is therefore critical to understand signalling. Here, we present PRECOG (precog.russelllab.org): a web-server for predicting GPCR coupling, which allows users to: (i) predict coupling probabilities for GPCRs to individual G-proteins instead of subfamilies; (ii) visually inspect the protein sequence and structural features that are responsible for a particular coupling; (iii) suggest mutations to rationally design artificial GPCRs with new coupling properties based on predetermined coupling features.
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spelling pubmed-66025042019-07-05 PRECOG: PREdicting COupling probabilities of G-protein coupled receptors Singh, Gurdeep Inoue, Asuka Gutkind, J Silvio Russell, Robert B Raimondi, Francesco Nucleic Acids Res Web Server Issue G-protein coupled receptors (GPCRs) control multiple physiological states by transducing a multitude of extracellular stimuli into the cell via coupling to intra-cellular heterotrimeric G-proteins. Deciphering which G-proteins couple to each of the hundreds of GPCRs present in a typical eukaryotic organism is therefore critical to understand signalling. Here, we present PRECOG (precog.russelllab.org): a web-server for predicting GPCR coupling, which allows users to: (i) predict coupling probabilities for GPCRs to individual G-proteins instead of subfamilies; (ii) visually inspect the protein sequence and structural features that are responsible for a particular coupling; (iii) suggest mutations to rationally design artificial GPCRs with new coupling properties based on predetermined coupling features. Oxford University Press 2019-07-02 2019-05-30 /pmc/articles/PMC6602504/ /pubmed/31143927 http://dx.doi.org/10.1093/nar/gkz392 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Singh, Gurdeep
Inoue, Asuka
Gutkind, J Silvio
Russell, Robert B
Raimondi, Francesco
PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title_full PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title_fullStr PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title_full_unstemmed PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title_short PRECOG: PREdicting COupling probabilities of G-protein coupled receptors
title_sort precog: predicting coupling probabilities of g-protein coupled receptors
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602504/
https://www.ncbi.nlm.nih.gov/pubmed/31143927
http://dx.doi.org/10.1093/nar/gkz392
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