Discovery Informatics Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Academy of Scientific and Innovative Research, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Mol Divers. 2020 Feb;24(1):45-60. doi: 10.1007/s11030-019-09924-9. Epub 2019 Feb 23.
The traditional method of drug discovery process has been surpassed by a rational approach where computer-aided drug designing plays a vital role in the identification of leads from large compound databases. Further, natural products have an important role in drug discovery as these have been the source of most active ingredients of medicines. Herein, in silico structure- and ligand-based approaches have been applied to screen in-house IIIM natural product repository for Akt1 (serine/threonine protein kinases) which is a well-known therapeutic target for cancer due to its overexpression and preventing the cells from undergoing apoptosis. Combined ligand-based and structure-based strategies were applied on to the existing library comprising of about 700 pure natural products, and the compounds identified from screening were biologically evaluated for Akt1 inhibition using Akt1 kinase activity assay. Fourteen promising compounds showed significant inhibition at 500 nM through in vitro screening, and from them, eight were new for Akt1 inhibition. Through the MD studies of Akt1 with the most active compound IN00145, it was inferred that Lys179, Glu191, Glu228, Ala230, Glu234 and Asp292 are the important amino acid residues which provide stability to the Akt1-IN00145 complex. Lead optimization studies were also performed around the actives to design better and selective inhibitors for Akt1. The results emphasized the successful application of virtual screening to identify new Akt1 inhibitor scaffolds that can be developed into a drug candidate in drug discovery programme.
传统的药物发现过程方法已经被一种合理的方法所超越,其中计算机辅助药物设计在从大型化合物数据库中识别先导化合物方面发挥着至关重要的作用。此外,天然产物在药物发现中也具有重要作用,因为它们是大多数药物有效成分的来源。在此,本文应用了基于结构和基于配体的计算方法,对 IIIM 天然产物库进行了筛选,以寻找 Akt1(丝氨酸/苏氨酸蛋白激酶)的抑制剂,Akt1 由于过度表达而成为癌症的一个众所周知的治疗靶点,因为它可以阻止细胞凋亡。将基于配体和基于结构的联合策略应用于现有的包含约 700 种纯天然产物的库中,从筛选中鉴定出的化合物通过 Akt1 激酶活性测定法进行了 Akt1 抑制的生物评估。通过体外筛选,有 14 种有前途的化合物在 500nM 时表现出显著的抑制作用,其中 8 种是 Akt1 抑制的新化合物。通过对 Akt1 与最活跃化合物 IN00145 的 MD 研究,推断 Lys179、Glu191、Glu228、Ala230、Glu234 和 Asp292 是为 Akt1-IN00145 复合物提供稳定性的重要氨基酸残基。还对活性化合物进行了先导优化研究,以设计更好和更具选择性的 Akt1 抑制剂。这些结果强调了虚拟筛选在识别新的 Akt1 抑制剂骨架方面的成功应用,这些骨架可以在药物发现计划中开发成候选药物。