Current Computer-Aided Drug DesignCurrent Computer-Aided Drug DesignCurrent Computer-Aided Drug Design1573-40991875-6697Bentham Science64409510.2174/1573409919666230525122447ChemistryResearch ArticlePredicting the Mechanism of Tiannanxing-shengjiang Drug Pair in Treating Pain Using Network Pharmacology and Molecular Docking TechnologyWangBoninginfo@benthamscience.netWangYanleiinfo@benthamscience.netMaoPenginfo@benthamscience.netZhangYiinfo@benthamscience.netLiYifaninfo@benthamscience.netLiuXinginfo@benthamscience.netFanBifainfo@benthamscience.net, Graduate School of Beijing University of Chinese MedicineDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua UniversityDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua University,, raduate School of Beijing University of Chinese Medicine0105202420546347307012025Copyright ©; 2024, Bentham Science Publishers2024Bentham Science Publishershttps://rjeid.com/1573-4099/article/view/644095

Objective:This study aimed to analyze the potential targets and mechanism of the Tiannanxing-shengjiang drug pair in pain treatment using network pharmacology and molecular docking technology.

Methods:The active components and target proteins of Tiannanxing-Shengjiang were obtained from the TCMSP database. The pain-related genes were acquired from the DisGeNET database. The common target genes between Tiannanxing-Shengjiang and pain were identified and subjected to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses on the DAVID website. AutoDockTools and molecular dynamics simulation analysis were used to assess the binding of the components with the target proteins.

Results:Ten active components were screened out, such as stigmasterol, β-sitosterol, and dihydrocapsaicin. A total of 63 common targets between the drug and pain were identified. GO analysis showed the targets to be mainly associated with biological processes, such as inflammatory response and forward regulation of the EKR1 and EKR2 cascade. KEGG analysis revealed 53 enriched pathways, including pain-related calcium signaling, cholinergic synaptic signaling, and serotonergic pathway. Five compounds and 7 target proteins showed good binding affinities. These data suggest that Tiannanxing-shengjiang may alleviate pain through specific targets and signaling pathways.

Conclusion:The active ingredients in Tiannanxing-shengjiang might alleviate pain by regulating genes, such as CNR1, ESR1, MAPK3, CYP3A4, JUN, and HDAC1 through the signaling pathways, including intracellular calcium ion conduction, cholinergic prominent signaling, and cancer signaling pathway.

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