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A Web Server for GPCR-GPCR Interaction Pair Prediction
The GGIP web server (https://protein.b.dendai.ac.jp/GGIP/) provides a web application for GPCR-GPCR interaction pair prediction by a support vector machine. The server accepts two sequences in the FASTA format. It responds with a prediction that the input GPCR sequence pair either interacts or not....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989088/ https://www.ncbi.nlm.nih.gov/pubmed/35399947 http://dx.doi.org/10.3389/fendo.2022.825195 |
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author | Nemoto, Wataru Yamanishi, Yoshihiro Limviphuvadh, Vachiranee Fujishiro, Shunsuke Shimamura, Sakie Fukushima, Aoi Toh, Hiroyuki |
author_facet | Nemoto, Wataru Yamanishi, Yoshihiro Limviphuvadh, Vachiranee Fujishiro, Shunsuke Shimamura, Sakie Fukushima, Aoi Toh, Hiroyuki |
author_sort | Nemoto, Wataru |
collection | PubMed |
description | The GGIP web server (https://protein.b.dendai.ac.jp/GGIP/) provides a web application for GPCR-GPCR interaction pair prediction by a support vector machine. The server accepts two sequences in the FASTA format. It responds with a prediction that the input GPCR sequence pair either interacts or not. GPCRs predicted to interact with the monomers constituting the pair are also shown when query sequences are human GPCRs. The server is simple to use. A pair of amino acid sequences in the FASTA format is pasted into the text area, a PDB ID for a template structure is selected, and then the ‘Execute’ button is clicked. The server quickly responds with a prediction result. The major advantage of this server is that it employs the GGIP software, which is presently the only method for predicting GPCR-interaction pairs. Our web server is freely available with no login requirement. In this article, we introduce some application examples of GGIP for disease-associated mutation analysis. |
format | Online Article Text |
id | pubmed-8989088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89890882022-04-08 A Web Server for GPCR-GPCR Interaction Pair Prediction Nemoto, Wataru Yamanishi, Yoshihiro Limviphuvadh, Vachiranee Fujishiro, Shunsuke Shimamura, Sakie Fukushima, Aoi Toh, Hiroyuki Front Endocrinol (Lausanne) Endocrinology The GGIP web server (https://protein.b.dendai.ac.jp/GGIP/) provides a web application for GPCR-GPCR interaction pair prediction by a support vector machine. The server accepts two sequences in the FASTA format. It responds with a prediction that the input GPCR sequence pair either interacts or not. GPCRs predicted to interact with the monomers constituting the pair are also shown when query sequences are human GPCRs. The server is simple to use. A pair of amino acid sequences in the FASTA format is pasted into the text area, a PDB ID for a template structure is selected, and then the ‘Execute’ button is clicked. The server quickly responds with a prediction result. The major advantage of this server is that it employs the GGIP software, which is presently the only method for predicting GPCR-interaction pairs. Our web server is freely available with no login requirement. In this article, we introduce some application examples of GGIP for disease-associated mutation analysis. Frontiers Media S.A. 2022-03-24 /pmc/articles/PMC8989088/ /pubmed/35399947 http://dx.doi.org/10.3389/fendo.2022.825195 Text en Copyright © 2022 Nemoto, Yamanishi, Limviphuvadh, Fujishiro, Shimamura, Fukushima and Toh https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Nemoto, Wataru Yamanishi, Yoshihiro Limviphuvadh, Vachiranee Fujishiro, Shunsuke Shimamura, Sakie Fukushima, Aoi Toh, Hiroyuki A Web Server for GPCR-GPCR Interaction Pair Prediction |
title | A Web Server for GPCR-GPCR Interaction Pair Prediction |
title_full | A Web Server for GPCR-GPCR Interaction Pair Prediction |
title_fullStr | A Web Server for GPCR-GPCR Interaction Pair Prediction |
title_full_unstemmed | A Web Server for GPCR-GPCR Interaction Pair Prediction |
title_short | A Web Server for GPCR-GPCR Interaction Pair Prediction |
title_sort | web server for gpcr-gpcr interaction pair prediction |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989088/ https://www.ncbi.nlm.nih.gov/pubmed/35399947 http://dx.doi.org/10.3389/fendo.2022.825195 |
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