Network pharmacology and molecular docking study-based approach to explore mechanism of benzimidazole-based anthelmintics for the treatment of lung cancer

Emerging studies have reported the potential anticancer activity of benzimidazole-based anthelmintics (BBA) against lung cancer (LC). However, mechanism underlying the anticancer activity of BBA is unclear. Therefore, in the current study, network pharmacology and molecular docking-based approach were used to explore the potential molecular mechanism for the treatment of LC. The potential targets for BBA were obtained from multiple databases including SwissTargetPrediction, Drug Bank, Therapeutic Target Database, and Comparative Toxicogenomics Database while LC targets were collected from DisGeNet gene discovery platform, Integrated Genomic Database of NSCLC, Catalogue of Somatic Mutations in Cancer and Online Mendelian Inheritance in Man database. Protein-protein interaction (PPI) diagram of common targets was constructed using STRING online platform. Topological analysis was performed using Cytoscape and gene enrichment analysis was conducted using FunRich software. Highest degree targets were then confirmed using molecular docking and molecular dynamics simulations. The BBA were prioritized according to their S scores, with ricobendazole ranking highest followed by flubendazole, fenbendazole, mebendazole, triclabendazole, albendazole, oxibendazole, parbendazole, thiabendazole and oxfendazole. The potential targets of BBA identified using topological analysis and molecular docking were found to be CCND1 (cyclin D1), EGFR (Epidermal Growth Factor Receptor), ERBB2 (Erb-B2 Receptor Tyrosine Kinase 2/CD340), PTGS2 (Prostaglandin-endoperoxide synthase 2), and SRC (Proto-oncogene tyrosine-protein kinase). Furthermore, molecular dynamics confirmed that CCND1 and EGFR are the potential targets of ricobendazole for the treatment of LC. BBA can be further explored as a therapeutic strategy for the treatment of lung cancer under in vitro and in vivo studies.
Communicated by Ramaswamy H. Sarma

已有新兴研究报道，苯并咪唑类驱虫药（benzimidazole-based anthelmintics, BBA）具备对抗肺癌（lung cancer, LC）的潜在抗癌活性。然而，此类药物发挥抗癌活性的分子机制尚未明确。因此，本研究采用网络药理学与分子对接联合分析方法，探究苯并咪唑类驱虫药治疗肺癌的潜在分子机制。本研究从多个数据库获取苯并咪唑类驱虫药的潜在靶点，包括SwissTargetPrediction、Drug Bank、治疗靶点数据库（Therapeutic Target Database）、比较毒理基因组学数据库（Comparative Toxicogenomics Database）；肺癌相关靶点则采集自DisGeNet基因发现平台、非小细胞肺癌整合基因组数据库（Integrated Genomic Database of NSCLC）、癌症体细胞突变目录（Catalogue of Somatic Mutations in Cancer）以及在线人类孟德尔遗传数据库（Online Mendelian Inheritance in Man）。采用STRING在线平台构建共同靶点的蛋白质相互作用（protein-protein interaction, PPI）网络图；使用Cytoscape进行拓扑分析，通过FunRich软件开展基因富集分析。随后借助分子对接与分子动力学模拟，对度中心性最高的靶点进行验证。本研究基于S评分对苯并咪唑类驱虫药进行优先级排序，其中雷西硝唑（ricobendazole）排名最高，依次为氟苯达唑（flubendazole）、芬苯达唑（fenbendazole）、甲苯达唑（mebendazole）、三氯苯达唑（triclabendazole）、阿苯达唑（albendazole）、奥苯达唑（oxibendazole）、帕苯达唑（parbendazole）、噻苯达唑（thiabendazole）以及奥芬达唑（oxfendazole）。通过拓扑分析与分子对接鉴定出的苯并咪唑类驱虫药潜在靶点包括CCND1（细胞周期蛋白D1，cyclin D1）、EGFR（表皮生长因子受体，Epidermal Growth Factor Receptor）、ERBB2（Erb-B2受体酪氨酸激酶2/CD340，Erb-B2 Receptor Tyrosine Kinase 2/CD340）、PTGS2（前列腺素内过氧化物合酶2，Prostaglandin-endoperoxide synthase 2）以及SRC（原癌基因酪氨酸蛋白激酶，Proto-oncogene tyrosine-protein kinase）。此外，分子动力学模拟证实，CCND1与EGFR是雷西硝唑治疗肺癌的潜在靶点。后续可通过体外与体内实验，进一步探究苯并咪唑类驱虫药作为肺癌治疗策略的应用潜力。由Ramaswamy H. Sarma转交