Jana Abhisek, Naga Rahul, Saha Sougata, Banerjee Deb Ranjan
Department of Chemistry, National Institute of technology Durgapur, Durgapur, India.
Department of Biotechnology, National Institute of technology Durgapur, Durgapur, India.
J Biomol Struct Dyn. 2023 Oct-Nov;41(18):8635-8653. doi: 10.1080/07391102.2022.2135600. Epub 2022 Oct 20.
The G9a, Lysine Methyltransferase that methylates the histone 3 lysine 9 (H3K9) of the nucleosome, is an excellent epigenetic target having no clinically passed inhibitor currently owing to adverse in vivo ADMET toxicities. In this work, we have carried out detailed computational investigations to find novel and safer lead against the target using advanced 3 D QSAR pharmacophore screening of databases containing more than 400000 entrees of natural compounds. The screening was conducted at different levels at increasing stringencies by employing pharmacophore mapping, druglikenesses and interaction profiles of the selected to identify potential hit compounds. The potential hits were further screened by advanced flexible docking, ADME and toxicity analysis to eight hit compounds. Based on the comparative analysis of the hits with the reference inhibitor, we identified one lead inhibitor against the G9a, having better binding efficacy and a safer ADMET profile than the reference inhibitor. Finally, the results were further verified using robust molecular dynamics simulation and MM-GBSA binding energy calculation. The natural compounds are generally considered benign due to their long human uses and this is the first attempt of screening of a large natural compound library against G9a to our best knowledge. Therefore, the finding of this study may add value towards the development of epigenetic therapeutics against the G9a.Communicated by Ramaswamy H. Sarma.
G9a是一种赖氨酸甲基转移酶，可使核小体的组蛋白3赖氨酸9（H3K9）发生甲基化，它是一个出色的表观遗传靶点，但由于体内药代动力学、药物代谢及毒性方面的不良反应，目前尚无临床可用的抑制剂。在这项研究中，我们利用先进的三维定量构效关系药效团筛选方法，对包含超过400000种天然化合物条目的数据库进行了详细的计算研究，以寻找针对该靶点的新型且更安全的先导化合物。通过采用药效团映射、类药性以及所选化合物的相互作用图谱，在不同严格程度下进行筛选，以识别潜在的命中化合物。通过先进的柔性对接、药物代谢动力学/药物代谢及毒性分析对潜在命中化合物进行进一步筛选，得到了8种命中化合物。基于对命中化合物与参考抑制剂的比较分析，我们确定了一种针对G9a的先导抑制剂，其结合效力优于参考抑制剂，且具有更安全的药代动力学、药物代谢及毒性特征。最后，通过稳健的分子动力学模拟和MM-GBSA结合能计算对结果进行了进一步验证。由于天然化合物长期以来被人类使用，一般被认为是安全的，据我们所知，这是首次针对G9a筛选大型天然化合物库。因此，本研究的发现可能为开发针对G9a的表观遗传疗法增添价值。由拉马斯瓦米·H·萨尔马通讯。
