湖北民族大学学报（自然科学版）2025，Vol.43Issue(2)：174-181,8.DOI:10.13501/j.cnki.42-1908/n.2025.06.008
代谢组学联合网络药理学揭示大叶黄精核苷酸抗T2DM的机制研究
Metabolomics Combined with Network Pharmacology Reveals the Anti-T2DM Mechanism of Polygonatum kingianum var.grandifolium
摘要
Abstract
In order to gain insight into the potential therapeutic effects of nucleotides and their derivatives from Polygonatum kingianum Var.grandifolium rhizomes on type 2 diabetes mellitus(T2DM),broadly targeted metabolomics,network pharmacology and molecular docking were used for analysis.The intersecting targets of key active components in traditional Chinese medicine for the treatment of T2DM were obtained through widely targeted metabolomics and relevant databases.Subsequently,enrichment analysis was performed on the intersecting targets.A ″component-target-pathway″ network model was constructed,and molecular docking was conducted.The results showed that the key active ingredient of nucleotides and their derivatives in Polygonatum kingianum Var.grandifolium rhizomes for the treatment of T2DM may be Adenosine,Cyclic 3',5'-Adenylic acid and Uridine 5'-diphosphate;The core targets may be AKT1,RAC1,HSPA8 and P2RY1;Signaling pathways may include the Rap1 signaling pathway,nucleotide metabolism,lysine degradation,and purine metabolism.The molecular docking results showed that the nucleotides and their derivatives in Polygonatum kingianum Var.grandifolium rhizomes had good binding activity to the target.This study demonstrated that nucleotides and their derivatives in Polygonatum kingianum Var.grandifolium rhizomes had multi-components,multi-targets and multi-pathways for treating T2DM.It provided a certain theoretical basis for T2DM drug development.关键词
代谢组学/网络药理学/大叶黄精/核苷酸及其衍生物/T2DM/分子对接Key words
metabolomics/network pharmacology/Polygonatum kingianum Var.grandifolium/nucleotides and their derivatives/type 2 diabetes mellitus/molecular docking分类
农业科学引用本文复制引用
兰德淼,姚锦坤,黄杰,韦志煜,石广地,肖强..代谢组学联合网络药理学揭示大叶黄精核苷酸抗T2DM的机制研究[J].湖北民族大学学报（自然科学版）,2025,43(2):174-181,8.基金项目
国家自然科学基金项目(31260057) （31260057）
湖北省自然科学基金项目(2023AFD077). （2023AFD077）
