Comprehensive Network Analysis Reveals the Targets and Potential Multitarget Drugs of Type 2 Diabetes Mellitus

被引:5
作者
Zhou, Wan [1 ]
Liu, Qiang [2 ]
Wang, Wei [1 ]
Yuan, Xiao-Jing [3 ]
Xiao, Chun-Chun [1 ]
Ye, Shan-Dong [1 ]
机构
[1] Univ Sci & Technol China, Affiliated Hosp 1, Div Life Sci & Med, Lab Diabet,Dept Endocrinol, Hefei 230001, Peoples R China
[2] Univ Sci & Technol China, Affiliated Hosp 1, Hefei Natl Lab Phys Sci Microscale, Inst Aging & Brain Disorders,Div Life Sci & Med, Hefei 230026, Peoples R China
[3] Univ Sci & Technol China, Affiliated Hosp 1, Div Life Sci & Med, Hefei 230026, Peoples R China
基金
中国国家自然科学基金;
关键词
CCR5; MUTATION; DISEASE; SYSTEM;
D O I
10.1155/2022/8255550
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Type 2 diabetes mellitus (T2DM) is a metabolic disease with increasing prevalence and mortality year by year. The purpose of this study was to explore new therapeutic targets and candidate drugs for multitargets by single-cell RNA expression profile analysis, network pharmacology, and molecular docking. Single-cell RNA expression profiling of islet beta cell samples between T2DM patients and nondiabetic controls was conducted to identify important subpopulations and the marker genes. The potential therapeutic targets of T2DM were identified by the overlap analysis of insulin-related genes and diabetes-related genes, the construction of protein-protein interaction network, and the molecular complex detection (MCODE) algorithm. The network distance method was employed to determine the potential drugs of the target. Molecular docking and molecular dynamic simulations were carried out using AutoDock Vina and Gromacs2019, respectively. Eleven cell clusters were identified by single-cell RNA sequencing (scRNA-seq) data, and three of them (C2, C8, and C10) showed significant differences between T2DM samples and normal samples. Eight genes from differential cell clusters were found from differential cell clusters to be associated with insulin activity and T2DM. The MCODE algorithm built six key subnetworks, with five of them correlating with inflammatory pathways and immune cell infiltration. Importantly, CCR5 was a gene within the key subnetworks and was differentially expressed between normal samples and T2DM samples, with the highest area under the ROC curve (AUC) of 82.5% for the diagnosis model. A total of 49 CCR5-related genes were screened, and DB05494 was identified as the most potential drug with the shortest distance to CCR5-related genes. Molecular docking illustrated that DB05494 stably bound with CCR5 (-8.0 kcal/mol) through multiple hydrogen bonds (LYS26, TYR37, TYR89, CYS178, and GLN280) and hydrophobic bonds (TRP86, PHE112, ILE198, TRP248, and TYR251). This study identified CCR5 as a potential therapeutic target and screened DB05494 as a potential drug for T2DM treatment.
引用
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页数:12
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