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Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes

Natural products have been widely used in the treatment of type 2 diabetes (T2D). However, their mechanisms are often obscured due to multi‐components and multi‐targets. The authors constructed a pathway‐based protein–protein association (PPA) network for target proteins of 13 α‐glucosidase inhibito...

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Autores principales: Wang, Le, Diwu, Wenbo, Tan, Nana, Wang, Huan, Hu, Jingbo, Xu, Bailu, Wang, Xiaoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675860/
https://www.ncbi.nlm.nih.gov/pubmed/33900023
http://dx.doi.org/10.1049/syb2.12019
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author Wang, Le
Diwu, Wenbo
Tan, Nana
Wang, Huan
Hu, Jingbo
Xu, Bailu
Wang, Xiaoling
author_facet Wang, Le
Diwu, Wenbo
Tan, Nana
Wang, Huan
Hu, Jingbo
Xu, Bailu
Wang, Xiaoling
author_sort Wang, Le
collection PubMed
description Natural products have been widely used in the treatment of type 2 diabetes (T2D). However, their mechanisms are often obscured due to multi‐components and multi‐targets. The authors constructed a pathway‐based protein–protein association (PPA) network for target proteins of 13 α‐glucosidase inhibitors (AGIs) identified from Scutellaria baicalensis Georgi (SBG), designed to explore the underlying mechanisms. This network contained 118 nodes and 1167 connections. An uneven degree distribution and small‐world property were observed, characterised by high clustering coefficient and short average path length. The PPA network had an inherent hierarchy as C(k)∼k (−0.71). It also exhibited potential weak disassortative mixing pattern, coupled with a decreased function Knn (k) and negative value of assortativity coefficient. These properties indicated that a few nodes were crucial to the network. PGH2, GNAS, MAPK1, MAPK3, PRKCA, and MAOA were then identified as key targets with the highest degree values and centrality indices. Additionally, a core subnetwork showed that chrysin, 5,8,2′‐trihydroxy‐7‐methoxyflavone, and wogonin were the main active constituents of these AGIs, and that the serotonergic synapse pathway was the critical pathway for SBG against T2D. The application of a pathway‐based protein–protein association network provides a novel strategy to explore the mechanisms of natural products on complex diseases.
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spelling pubmed-86758602022-02-16 Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes Wang, Le Diwu, Wenbo Tan, Nana Wang, Huan Hu, Jingbo Xu, Bailu Wang, Xiaoling IET Syst Biol Original Research Papers Natural products have been widely used in the treatment of type 2 diabetes (T2D). However, their mechanisms are often obscured due to multi‐components and multi‐targets. The authors constructed a pathway‐based protein–protein association (PPA) network for target proteins of 13 α‐glucosidase inhibitors (AGIs) identified from Scutellaria baicalensis Georgi (SBG), designed to explore the underlying mechanisms. This network contained 118 nodes and 1167 connections. An uneven degree distribution and small‐world property were observed, characterised by high clustering coefficient and short average path length. The PPA network had an inherent hierarchy as C(k)∼k (−0.71). It also exhibited potential weak disassortative mixing pattern, coupled with a decreased function Knn (k) and negative value of assortativity coefficient. These properties indicated that a few nodes were crucial to the network. PGH2, GNAS, MAPK1, MAPK3, PRKCA, and MAOA were then identified as key targets with the highest degree values and centrality indices. Additionally, a core subnetwork showed that chrysin, 5,8,2′‐trihydroxy‐7‐methoxyflavone, and wogonin were the main active constituents of these AGIs, and that the serotonergic synapse pathway was the critical pathway for SBG against T2D. The application of a pathway‐based protein–protein association network provides a novel strategy to explore the mechanisms of natural products on complex diseases. John Wiley and Sons Inc. 2021-04-26 /pmc/articles/PMC8675860/ /pubmed/33900023 http://dx.doi.org/10.1049/syb2.12019 Text en © 2021 The Authors. IET Systems Biology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Papers
Wang, Le
Diwu, Wenbo
Tan, Nana
Wang, Huan
Hu, Jingbo
Xu, Bailu
Wang, Xiaoling
Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title_full Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title_fullStr Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title_full_unstemmed Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title_short Pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes
title_sort pathway‐based protein–protein association network to explore mechanism of α‐glucosidase inhibitors from scutellaria baicalensis georgi against type 2 diabetes
topic Original Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675860/
https://www.ncbi.nlm.nih.gov/pubmed/33900023
http://dx.doi.org/10.1049/syb2.12019
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