Evidence map›Paper›PMID 37231756›Full record

ArticleCurrent computer-aided drug design2024

Predicting the Mechanism of Tiannanxing-shengjiang Drug Pair in Treating Pain Using Network Pharmacology and Molecular Docking Technology.

Boning Wang, Yanlei Wang, Peng Mao, Yi Zhang, Yifan Li, Xing Liu, Bifa Fan

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Article in Current computer-aided drug design, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

7 authors.

Boning WangGraduate School of Beijing University of Chinese Medicine, Beijing, 100029, China.
Yanlei WangGraduate School of Beijing University of Chinese Medicine, Beijing, 100029, China.
Peng MaoDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua University, Beijing 100016, China.
Yi ZhangDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua University, Beijing 100016, China.
Yifan LiDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua University, Beijing 100016, China.
Xing LiuGraduate School of Beijing University of Chinese Medicine, Beijing, 100029, China.
Bifa FanDepartment of Pain Medicine, The First Affiliated Hospital of Tsinghua University, Beijing 100016, China.

Funding

Joint Project of the Biomedical Transformation Engineering Research Center of Beijing University of Chemical Technology and China-Japan Friendship Hospital Grant No: XK2020-13].National Key Clinical Specialty Construction Project Grant No: 2014- zdzk-002
6 · The paper itself

Abstract

objectiveThis 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.

methodsThe 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.

resultsTen 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.

conclusionThe 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.

Indexed as

Drugs, Chinese HerbalMolecular Docking SimulationNetwork PharmacologyPainAnalgesicsHumansMolecular Dynamics SimulationAnalgesicsDrugs, Chinese Herbalcholinergic synaptic signaling.Molecular docking technologynetwork pharmacologypainShengjiangsignaling pathwayTiannanxing

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