Exploration of Pharmacological Mechanisms of Dapagliflozin against Type 2 Diabetes Mellitus through PI3K-Akt Signaling Pathway based on Network Pharmacology Analysis and Deep Learning Technology

Author:

Wu Jie1,Chen Yufan2,Shi Shuai3,Liu Junru4,Zhang Fen1,Li Xingxing1,Liu Xizhi1,Hu Guoliang5,Dong Yang1

Affiliation:

1. Department of Cardiology, Jinhua People's Hospital, Jinhua, Zhejiang, China

2. Department of Blood Donation Service, Central Blood Station of Jinhua, Jinhua, Zhejiang, China

3. Department of IVF, Jinhua People's Hospital, Jinhua, Zhejiang, China

4. Department of Endocrinology, Jinhua People's Hospital, Jinhua, Zhejiang, China

5. Department of Ultrasound in Medicine, Jinhua People's Hospital, Jinhua, Zhejiang, China

Abstract

Background:: Dapagliflozin is commonly used to treat type 2 diabetes mellitus (T2DM). However, research into the specific anti-T2DM mechanisms of dapagliflozin remains scarce. Objective:: This study aimed to explore the underlying mechanisms of dapagliflozin against T2DM. Methods:: Dapagliflozin-associated targets were acquired from CTD, SwissTargetPrediction, and SuperPred. T2DM-associated targets were obtained from GeneCards and DigSee. VennDiagram was used to obtain the overlapping targets of dapagliflozin and T2DM. GO and KEGG analyses were performed using clusterProfiler. A PPI network was built by STRING database and Cytoscape, and the top 30 targets were screened using the degree, maximal clique centrality (MCC), and edge percolated component (EPC) algorithms of CytoHubba. The top 30 targets screened by the three algorithms were intersected with the core pathway-related targets to obtain the key targets. DeepPurpose was used to evaluate the binding affinity of dapagliflozin with the key targets. Results:: In total, 155 overlapping targets of dapagliflozin and T2DM were obtained. GO and KEGG analyses revealed that the targets were primarily enriched in response to peptide, membrane microdomain, protein serine/threonine/tyrosine kinase activity, PI3K-Akt signaling pathway, MAPK signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. AKT1, PIK3CA, NOS3, EGFR, MAPK1, MAPK3, HSP90AA1, MTOR, RELA, NFKB1, IKBKB, ITGB1, and TP53 were the key targets, mainly related to oxidative stress, endothelial function, and autophagy. Through the DeepPurpose algorithm, AKT1, HSP90AA1, RELA, ITGB1, and TP53 were identified as the top 5 anti-targets of dapagliflozin. Conclusion:: Dapagliflozin might treat T2DM mainly by targeting AKT1, HSP90AA1, RELA, ITGB1, and TP53 through PI3K-Akt signaling.

Publisher

Bentham Science Publishers Ltd.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3