Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
Drug Design and Development Research Center, The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran.
J Biomol Struct Dyn. 2022 Jan;40(1):297-311. doi: 10.1080/07391102.2020.1813203. Epub 2020 Sep 4.
Designing dual small molecule inhibitors against enzymes associated with cancer has turned into a new strategy in cancer chemotherapy. Targeting DNA methyltransferase (DNMT) and histone deacetylase (HDAC) enzymes, involved in epigenetic modifications, are considered as promising treatments for a wide range of cancers, due to their association with the initiation, proliferation, and survival of cancer cells. In this study, for the first time, the dual inhibitors of the histone deacetylases 8 (HDAC8) and DNA methyltransferase 1 (DNMT1) has introduced as novel potential candidates for epigenetic-based cancer therapeutics. This research has been facilitated by employing pharmacophore-based virtual screening of ZINC and Maybridge databases, as well as performing molecular docking, molecular dynamics simulations and free binding energy calculation on the top derived compound. Results have demonstrated that the suggested compounds not only adopt highly favorable conformations but also possess strong binding interaction with the HDAC8 enzyme. Additionally, the obtained results from the experimental assay confirmed the predicted behavior of inhibitors from virtual screening. These results can be used for further optimization to yield promising more effective candidates for the treatment of cancer.Communicated by Ramaswamy H. Sarma.
设计针对与癌症相关酶的双小分子抑制剂已经成为癌症化疗的一种新策略。针对 DNA 甲基转移酶 (DNMT) 和组蛋白去乙酰化酶 (HDAC) 等参与表观遗传修饰的酶，由于它们与癌细胞的起始、增殖和存活有关，被认为是广泛癌症的有前途的治疗方法。在这项研究中，首次引入了组蛋白去乙酰化酶 8 (HDAC8) 和 DNA 甲基转移酶 1 (DNMT1) 的双抑制剂，作为基于表观遗传的癌症治疗的新型潜在候选物。这项研究通过基于药效团的虚拟筛选 ZINC 和 Maybridge 数据库，以及对衍生的顶级化合物进行分子对接、分子动力学模拟和自由结合能计算来实现。结果表明，所提出的化合物不仅采用了非常有利的构象，而且与 HDAC8 酶具有很强的结合相互作用。此外，虚拟筛选中抑制剂的预测行为得到了实验测定结果的证实。这些结果可用于进一步优化，以产生更有效的治疗癌症的候选药物。由 Ramaswamy H. Sarma 传达。
