College of Pharmacy and Health Sciences, Ajman University, Ajman 346, UAE.
Department of Pharmacology and Toxicology, Faculty of Pharmacy, Beni-Suef University, Beni Suef 62514, Egypt.
Biomed Res Int. 2020 Oct 31;2020:2768403. doi: 10.1155/2020/2768403. eCollection 2020.
The metabolic syndrome increases the risk of different diseases such as type 2 diabetes. The prevalence of metabolic syndrome has rapidly grown and affected more than 230 million people worldwide. is a traditionally used plant for the treatment of diabetes; however, its mechanism to manage diabetes is still unknown.
This study was designed to systematically assess the mechanism of action of in diabetes.
An extensive literature search was made to establish an ingredient-target database of . Of these, targets related to diabetes were identified and used to develop a protein-protein interaction network (PPIN) by utilizing the STITCH database. The obtained PPIN was assessed through Gene Ontology (GO) enrichment analysis based on ClueGO plugin.
According to the acquired data, there were about 143 chemical constituents present in having 119 protein targets. Of these, 31 targets were established to give the pharmacological effect against diabetes. The UniProt database was used for screening of 31 targets, out of which contained 22 targets. Ultimately, 207 GO terms, grouped into 41 clusters, were found by gene analysis, and most of them were found to be linked with diabetes. According to findings, several proteins including TP53, BCL2, CDKN1A, 1L6, CCND1, CDKN2A, and RB1 have a significant role in the treatment of diabetes by .
The possible activity of in the management of diabetes may be mediated by several molecular mechanisms, including the glutamine metabolic process, IRE1-mediated unfolded protein response, and pentose metabolic process.
代谢综合征会增加罹患 2 型糖尿病等多种疾病的风险。代谢综合征的患病率迅速增长，影响了全球超过 2.3 亿人。 是一种传统上用于治疗糖尿病的植物；然而，其管理糖尿病的机制仍不清楚。
本研究旨在系统评估 治疗糖尿病的作用机制。
进行了广泛的文献检索，建立了 的成分-靶标数据库。从这些数据库中，确定了与糖尿病相关的靶点，并利用 STITCH 数据库开发了蛋白质-蛋白质相互作用网络（PPIN）。通过 ClueGO 插件基于基因本体论（GO）富集分析评估获得的 PPIN。
根据获得的数据， 中约有 143 种化学物质具有 119 个蛋白靶点。其中，有 31 个靶点被确定为具有抗糖尿病的药理作用。UniProt 数据库用于筛选 31 个靶点，其中包含 22 个靶点。最终，通过基因分析发现了 207 个 GO 术语，分为 41 个簇，其中大多数与糖尿病有关。根据研究结果，一些蛋白质，包括 TP53、BCL2、CDKN1A、1L6、CCND1、CDKN2A 和 RB1，在 通过 治疗糖尿病方面发挥着重要作用。
可能通过多种分子机制来管理糖尿病，包括谷氨酰胺代谢过程、IRE1 介导的未折叠蛋白反应和戊糖代谢过程。
