Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods

The G Protein-Coupled Receptor (GPCR) family consists of more than 800 different members. In this article, we attempt to use the physicochemical properties of Composition, Transition, Distribution (CTD) to represent GPCRs. The dimensionality reduction method of MRMD2.0 filters the physicochemical pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Gu, Xingyue, Chen, Zhihua, Wang, Donghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329982/
https://www.ncbi.nlm.nih.gov/pubmed/32671038
http://dx.doi.org/10.3389/fbioe.2020.00635
_version_ 1783553011813974016
author Gu, Xingyue
Chen, Zhihua
Wang, Donghua
author_facet Gu, Xingyue
Chen, Zhihua
Wang, Donghua
author_sort Gu, Xingyue
collection PubMed
description The G Protein-Coupled Receptor (GPCR) family consists of more than 800 different members. In this article, we attempt to use the physicochemical properties of Composition, Transition, Distribution (CTD) to represent GPCRs. The dimensionality reduction method of MRMD2.0 filters the physicochemical properties of GPCR redundancy. Matplotlib plots the coordinates to distinguish GPCRs from other protein sequences. The chart data show a clear distinction effect, and there is a well-defined boundary between the two. The experimental results show that our method can predict GPCRs.
format Online
Article
Text
id pubmed-7329982
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-73299822020-07-14 Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods Gu, Xingyue Chen, Zhihua Wang, Donghua Front Bioeng Biotechnol Bioengineering and Biotechnology The G Protein-Coupled Receptor (GPCR) family consists of more than 800 different members. In this article, we attempt to use the physicochemical properties of Composition, Transition, Distribution (CTD) to represent GPCRs. The dimensionality reduction method of MRMD2.0 filters the physicochemical properties of GPCR redundancy. Matplotlib plots the coordinates to distinguish GPCRs from other protein sequences. The chart data show a clear distinction effect, and there is a well-defined boundary between the two. The experimental results show that our method can predict GPCRs. Frontiers Media S.A. 2020-06-25 /pmc/articles/PMC7329982/ /pubmed/32671038 http://dx.doi.org/10.3389/fbioe.2020.00635 Text en Copyright © 2020 Gu, Chen and Wang. http://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 Bioengineering and Biotechnology
Gu, Xingyue
Chen, Zhihua
Wang, Donghua
Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title_full Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title_fullStr Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title_full_unstemmed Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title_short Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods
title_sort prediction of g protein-coupled receptors with ctdc extraction and mrmd2.0 dimension-reduction methods
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329982/
https://www.ncbi.nlm.nih.gov/pubmed/32671038
http://dx.doi.org/10.3389/fbioe.2020.00635
work_keys_str_mv AT guxingyue predictionofgproteincoupledreceptorswithctdcextractionandmrmd20dimensionreductionmethods
AT chenzhihua predictionofgproteincoupledreceptorswithctdcextractionandmrmd20dimensionreductionmethods
AT wangdonghua predictionofgproteincoupledreceptorswithctdcextractionandmrmd20dimensionreductionmethods

Ejemplares similares