Ligand |
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Small molecules targeting the colchicine site of tubulin represent an attractive cancer treatment strategy. In this study, a total of 468 models derived from 1076 diverse inhibitors binding to the tubulin colchicine site were constructed based on fingerprints using three machine learning approaches: 1) naive Bayesian (NB); 2) single tree (ST); and 3) random forest (RF). The overall predictive accuracy of the best models exceeded 85.12% for both the training and test sets. We designed an integrated virtual screening (VS) strategy for identifying new tubulin inhibitors by combining established models, molecular docking, and similarity-based analog searching. Through two rounds of VS, compound 23g was identified as a novel potent anticancer agent exhibiting activity against MDA-MB-231, HeLa, A549, HepG2, CNE2, and HCT116 tumor cell lines with IC50 values of 5.45, 8.61, 7.47, 2.29, 2.91, and 4.10 μM, respectively. Compared with taxol, colchicine, and adriamycin, 23g also displayed potent cytotoxicity against the drug-resistant tumor cell lines, HepG2/ADR, A549/CDDP, and A549/TAX cells, with IC50 values of 4.12, 6.58, and 6.38 μM, respectively. Further mechanistic studies revealed that 23g inhibited microtubule polymerization by binding to the colchicine site of tubulin, arrested the cell cycle at the G2/M phase, induced cell apoptosis, and exhibited potent in vitro anti-metastasis activity. Finally, molecular docking, molecular dynamics, and free energy analyses were employed to explore the detailed binding interaction between 23g and tubulin. Collectively, these findings indicated that 23g should be further investigated as a potential novel potent antitumor agent targeting tubulin.
中文翻译：
靶向微管蛋白秋水仙碱位点的小分子代表了一种有吸引力的癌症治疗策略。在这项研究中，使用三种机器学习方法，基于指纹图谱，共构建了468个源自1076种与微管蛋白秋水仙碱位点结合的不同抑制剂的模型：1）朴素贝叶斯（NB）；2）单树（ST）；3）随机森林（RF）。对于训练和测试集，最佳模型的总体预测准确性均超过85.12％。我们设计了一种集成的虚拟筛选（VS）策略，通过结合已建立的模型，分子对接和基于相似度的类似搜索来识别新的微管蛋白抑制剂。通过两轮VS，化合物23g被鉴定为新型抗癌剂，对MDA-MB-231，HeLa，A549，HepG2，CNE2，和HCT116肿瘤细胞系，其IC50值分别为5.45、8.61、7.47、2.29、2.91和4.10μM。与紫杉醇，秋水仙碱和阿霉素相比，23g也显示出对耐药性肿瘤细胞系HepG2 / ADR，A549 / CDDP和A549 / TAX细胞的有效细胞毒性，IC50值分别为4.12、6.58和6.38μM。 。进一步的机理研究表明，23g通过与微管蛋白的秋水仙碱位点结合来抑制微管聚合，在G2 / M期阻止细胞周期，诱导细胞凋亡，并表现出强大的体外抗转移活性。最后，使用分子对接，分子动力学和自由能分析来探索23g与微管蛋白之间的详细结合相互作用。总的来说， |
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