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A Systems Biology-Based Approach to Uncovering Molecular Mechanisms Underlying Effects of Traditional Chinese Medicine Qingdai in Chronic Myelogenous Leukemia, Involving Integration of Network Pharmacology and Molecular Docking Technology.

ABSTRACT: BACKGROUND The method of multiple targets overall control is increasingly used to predict the main active ingredient and potential target group of Chinese traditional medicines and to determine the mechanisms involved in their curative effects. Qingdai is the main traditional Chinese medicine used in the treatment of chronic myelogenous leukemia (CML), but the complex active ingredients and antitumor targets in treatment of CML have not been clearly defined in previous studies. MATERIAL AND METHODS We constructed a protein-protein interaction network diagram of CML with 638 nodes (proteins) and 1830 edges, based on the biological function of chronic myelocytic leukemia by use of Cytoscape, and we determined 19 key gene nodes in the CML molecule by network topological properties analysis in a data bank. Then, we used the Surflex-dock plugin in SYBYL7.3 docking and acquired the protein crystal structures of key genes involved in CML from the chemical composition of the traditional Chinese medicine Qingdai with key proteins in CML networks. RESULTS According to the score and the spatial structure, the pharmacodynamically active ingredients of Qingdai are Isdirubin, Isoindigo, N-phenyl-2-naphthylamine, and Isatin, among which Isdirubin is the most important. We further screened the most effective activity key protein structures of CML to find the best pharmacodynamically active ingredients of Qingdai, according to the binding interactions of the inhibitors at the catalytic site performed in best docking combinations. CONCLUSIONS The results suggest that Isdirubin plays a role in resistance to CML by altering the expressions of PIK3CA, MYC, JAK2, and TP53 target proteins. Network pharmacology and molecular docking technology can be used to search for possible reactive molecules in traditional chinese medicines (TCM) and to elucidate their molecular mechanisms.

SUBMITTER: Zhou C

PROVIDER: S-EPMC6049014 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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A Systems Biology-Based Approach to Uncovering Molecular Mechanisms Underlying Effects of Traditional Chinese Medicine Qingdai in Chronic Myelogenous Leukemia, Involving Integration of Network Pharmacology and Molecular Docking Technology.

Zhou Chao C Liu LiJuan L Zhuang Jing J Wei JunYu J Zhang TingTing T Gao ChunDi C Liu Cun C Li HuaYao H Si HongZong H Sun ChangGang C

Medical science monitor : international medical journal of experimental and clinical research 20180623

BACKGROUND The method of multiple targets overall control is increasingly used to predict the main active ingredient and potential target group of Chinese traditional medicines and to determine the mechanisms involved in their curative effects. Qingdai is the main traditional Chinese medicine used in the treatment of chronic myelogenous leukemia (CML), but the complex active ingredients and antitumor targets in treatment of CML have not been clearly defined in previous studies. MATERIAL AND METH ...[more]

PMID: 29934492

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Project description:AimThe incidence of ulcerative colitis (UC) is increasing steadily in developed countries, it is plaguing nearly 1 million people in the United States and European countries, while developing countries have had a rapidly increased incidence over the past decades. Curcuma is widely used in treating malaria, UC, Crohn's disease, and colon cancer, which lead to diarrhea and bloody stool. However, the systemic mechanism of curcuma in treating UC is still unclear. Our work was supposed to expound how does curcuma alleviate UC in a comprehensive and systematic way by network pharmacology, molecular docking, and experiment verification.MethodsTraditional Chinese Medicine System Pharmacology Database (TCMSP), Shanghai Chemistry & Chemical Industry Data Platform (SGST), and papers published in Chinese Network Knowledge Infrastructure (CNKI) and PubMed were used to collect the chemical constituents of curcuma based on ADME (absorption, distribution, metabolism, and excretion). And effective targets were predicted by Swiss Target Prediction to establish the curcuma-related database. The disease targets of UC were screened by GeneCards and DrugBank databases, and Wayne (Venn) analysis was carried out with curcuma targets to determine the intersection targets. AutoDock software and TCMNPAS system were used to dock the core chemical components of curcuma with key UC targets. Protein interaction (PPI) network was constructed based on the STRING database and Cytoscape software. Gene function GO analysis and KEGG pathway enrichment analysis were carried out by using Metascape database. Finally, HE staining was performed to identify the inflammatory infiltration and expression difference in TNF-α and STAT3 before and after the treatment of curcuma which was verified by immunoblotting.ResultsTwelve active components containing 148 target genes were selected from curcuma. Potential therapeutic targets of curcuma in the treatment of UC were acquired from 54 overlapped targets from UC and curcuma. Molecular docking was used to filter the exact 24 core proteins interacting with compounds whose docking energy is lower than -5.5 and stronger than that of 5-aminosalicylic acid (5-ASA). GO and KEGG analyses showed that these targets were highly correlated with EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, MAPK signaling pathway, and inflammatory bowel disease (IBD). Experiments verified curcuma relieved pathological manifestation and decreased the expression of TNF-α and STAT3.ConclusionCurcuma relieved the colon inflammation of ulcerative colitis via inactivating TNF pathway, inflammatory bowel disease pathway, and epithelial cell signaling in Helicobacter pylori infection pathway, probably by binding to STAT3 and TNF-α.

Project description:Because of their strong anti-cancer efficacy with fewer side effects, traditional Chinese medicines (TCM) have attracted considerable attention for their potential application in treating breast cancer (BC). However, knowledge about the underlying systematic mechanisms is scarce. Gynostemma pentaphyllum (Thunb.) Makino (GP), a creeping herb, has been regularly used as a TCM to prevent and treat tumors including BC. Again, mechanisms underlying its anti-BC properties have remained elusive. We used network pharmacology and molecular docking to explore the mechanistic details of GP against BC. The TCM systems pharmacology database and analysis platform and PharmMapper Server database were used to retrieve the chemical constituents and potential targets in GP. In addition, targets related to BC were identified using DrugBank and Therapeutic Target Database. Protein-protein interaction network, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of crucial targets were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins and database for annotation, visualization, and integrated discovery databases, whereas the network visualization analysis was performed using Cytoscape 3.8.2. In addition, the molecular docking technique was used to validate network pharmacology-based predictions. A comparison of the predicted targets of GP with those of BC-related drugs revealed 26 potential key targets related to the treatment of BC, among which ALB, EGFR, ESR1, AR, PGR, and HSP90AA1 were considered the major potential targets. Finally, network pharmacology-based prediction results were preliminarily verified by molecular docking experiments. In addition, chemical constituents and potential target proteins were scored, followed by a comparison with the ligands of the protein. We provide a network of pharmacology-based molecular mechanistic insights on the therapeutic action of GP against BC. We believe that our data will serve as a basis to conduct future studies and promote the clinical applications of GP.

Dataset Information

A Systems Biology-Based Approach to Uncovering Molecular Mechanisms Underlying Effects of Traditional Chinese Medicine Qingdai in Chronic Myelogenous Leukemia, Involving Integration of Network Pharmacology and Molecular Docking Technology.

Publications

A Systems Biology-Based Approach to Uncovering Molecular Mechanisms Underlying Effects of Traditional Chinese Medicine Qingdai in Chronic Myelogenous Leukemia, Involving Integration of Network Pharmacology and Molecular Docking Technology.

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