新型蒽醌类拓扑异构酶Ⅱ抑制剂的深度学习设计与合成

Deep Learning Design and Synthesis of Novel Anthraquinone Topoisomerase Ⅱ Inhibitors

收集并整理了102个蒽醌化合物以及对应抗肿瘤活性和毒性,建立QSAR和分子对接模型。以1,4-二羟基蒽醌为基础,设计具有磺酰基和胺烷基结构的新型蒽醌衍生物。利用模型对所设计的衍生物进行筛选,经两步反应合成了11个潜在的拓扑异构酶II抑制剂(B1~B11),其结构经^(1)H NMR,^(13)C NMR和HR-MS(ESI)表征。药理实验结果表明:化合物对DU-145和HELA癌细胞均显现出良好的抗肿瘤活性。其中B6和B11对DU-145有显著抑制作用,IC_(50)分别为16.88μM和5.48μM。

One hundred and two derivatives of anthraquinone and their corresponding anti-tumor activities data were collected and applied to build the docking and Quantitative Structure-Activity Relationship(QSAR)model.Based on the results of molecular docking and QSAR calculation model,eleven potential topoisomerase Ⅱ inhibitors(B1-B11)containing sulfonyl and amidoalkyl frameworks were synthesized by two-step reaction.The structures were characterized by^(1)H NMR,^(13)C NMR and HR-MS(ESI).Among them,B6 and B11 have significant inhibitory effects on prostatic carcinoma cell line DU-145 cells,with IC_(50)of 16.88μM and 5.48μM,respectively.The result showed that it was similar to docking scoring of DNA topoisomerase Ⅱ(PDB code:1ZXM)and pharmacological experiments.