Decoding Partner Specificity of Opioid Receptor Family

Detalhes bibliográficos
Autor(a) principal: Barreto, Carlos A. V.
Data de Publicação: 2021
Outros Autores: Baptista, Salete, Preto, Antonio J., Silvério, Daniel, Melo, Rita, Moreira, Irina S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/104528
https://doi.org/10.3389/fmolb.2021.715215
Resumo: This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (μ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.
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spelling Decoding Partner Specificity of Opioid Receptor Familydatabasefunctional signatureGPCRsopioid receptorG-proteinarrestinThis paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (μ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.Frontiers Media S.A.2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/104528http://hdl.handle.net/10316/104528https://doi.org/10.3389/fmolb.2021.715215eng2296-889XBarreto, Carlos A. V.Baptista, SaletePreto, Antonio J.Silvério, DanielMelo, RitaMoreira, Irina S.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-01-16T21:44:57Zoai:estudogeral.uc.pt:10316/104528Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:21:13.518380Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Decoding Partner Specificity of Opioid Receptor Family
title Decoding Partner Specificity of Opioid Receptor Family
spellingShingle Decoding Partner Specificity of Opioid Receptor Family
Barreto, Carlos A. V.
database
functional signature
GPCRs
opioid receptor
G-protein
arrestin
title_short Decoding Partner Specificity of Opioid Receptor Family
title_full Decoding Partner Specificity of Opioid Receptor Family
title_fullStr Decoding Partner Specificity of Opioid Receptor Family
title_full_unstemmed Decoding Partner Specificity of Opioid Receptor Family
title_sort Decoding Partner Specificity of Opioid Receptor Family
author Barreto, Carlos A. V.
author_facet Barreto, Carlos A. V.
Baptista, Salete
Preto, Antonio J.
Silvério, Daniel
Melo, Rita
Moreira, Irina S.
author_role author
author2 Baptista, Salete
Preto, Antonio J.
Silvério, Daniel
Melo, Rita
Moreira, Irina S.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Barreto, Carlos A. V.
Baptista, Salete
Preto, Antonio J.
Silvério, Daniel
Melo, Rita
Moreira, Irina S.
dc.subject.por.fl_str_mv database
functional signature
GPCRs
opioid receptor
G-protein
arrestin
topic database
functional signature
GPCRs
opioid receptor
G-protein
arrestin
description This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (μ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/104528
http://hdl.handle.net/10316/104528
https://doi.org/10.3389/fmolb.2021.715215
url http://hdl.handle.net/10316/104528
https://doi.org/10.3389/fmolb.2021.715215
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2296-889X
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Frontiers Media S.A.
publisher.none.fl_str_mv Frontiers Media S.A.
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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repository.mail.fl_str_mv
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