结合网络药理学和转录组鉴定马钱子抗结直肠癌的分子靶点OA

Objective To identify the key genes and active components of nux vomica against colorectal cancer by combining transcriptomics and network pharmacology.Methods The colorectal cancer datasets(GSE89076,GSE110223 and GSE11024)were downloaded from the GEO database.The differentially expressed genes were analyzed by R language,the active components of nux vomica were downloaded from TCMSP database,and the binding targets of active components of nux vomica were predicted by SwissTargetPrediction platform.Differentially expressed genes and nux vomica binding targets were intersected to obtain differential drug targets.The differential drug targets were enriched by KEGG pathway,and the key characteristic targets were screened by random forest and support vector machine algorithm.Finally,molecular docking verification was carried out by AutoDock Vina.Results A total of 495 co-differentially expressed genes were screened from GSE89076,GSE110223 and GSE11024 datasets.A total of 13 active ingredients were obtained from the TCMSP database,and 283 drug targets were predicted by the SwissTargetPrediction platform.VN analysis identified 30 differential drug targets.KEGG pathway enrichment showed that the differential drug targets were enriched in the cell cycle pathway;five key characteristic targets(CCNA2,PRKDC,HSD17B2,CDK4 and CCNB1)were screened by machine learning.Molecular docking results showed that Stylopine could stably bind to CCNA2,PRKDC,CDK4 and CCNB1,respectively,and Naringenin could stably bind to HSD17B2.Conclusion The active component Stylopine of nux vomica primarily exerts its anti-colorectal cancer effects by synergistically regulating the genes CDK4,CCNA2,CCNB1,and PRKDC,providing a novel candidate drug for colorectal cancer treatment.