Bioinformatics Research Center, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, 81746-73461 Isfahan, Iran.
Department of Excellence of Biotechnology, Chemistry and Pharmacy, 2018-2022, University of Siena, Via Aldo Moro 2, 53100, Siena, Italy.
Comput Biol Chem. 2019 Dec;83:107105. doi: 10.1016/j.compbiolchem.2019.107105. Epub 2019 Aug 16.
The p53 protein, also called guardian of the genome, plays a critical role in the cell cycle regulation and apoptosis. This protein is frequently inactivated in several types of human cancer by abnormally high levels of its negative regulator, mouse double minute 2 (MDM2). As a result, restoration of p53 function by inhibiting p53-MDM2 protein-protein interaction has been pursued as a compelling strategy for cancer therapy. To date, a limited number of small-molecules have been reported as effective p53-MDM2 inhibitors. X-ray structures of MDM2 in complex with some ligands are available in Protein Data Bank and herein, these data have been exploited to efficiently identify new p53-MDM2 interaction antagonists through a hierarchical virtual screening strategy. For this purpose, the first step was aimed at compiling a focused library of 686,630 structurally suitable compounds, from PubChem database, similar to two known effective inhibitors, Nutlin-3a and DP222669. These compounds were subjected to the subsequent structure-based approaches (quantum polarized ligand docking and molecular dynamics simulation) to select potential compounds with highest binding affinity for MDM2 protein. Additionally, ligand binding energy, ADMET properties and PAINS analysis were also considered as filtering criteria for selecting the most promising drug-like molecules. On the basis of these analyses, three top-ranked hit molecules, CID_118439641, CID_60452010 and CID_3106907, were found to have acceptable pharmacokinetics properties along with superior in silico inhibitory ability towards the p53-MDM2 interaction compared to known inhibitors. Molecular docking and molecular dynamics results well confirmed the interactions of the final selected compounds with critical residues within p53 binding site on the MDM2 hydrophobic clefts with satisfactory thermodynamics stability. Consequently, the new final scaffolds identified by the presented computational approach could offer a set of guidelines for designing promising anti-cancer agents targeting p53-MDM2 interaction.
p53 蛋白，也被称为基因组守护者，在细胞周期调控和细胞凋亡中发挥着关键作用。在几种类型的人类癌症中，p53 的负调节因子——鼠双微体 2（MDM2）的异常高水平导致该蛋白经常失活。因此，通过抑制 p53-MDM2 蛋白-蛋白相互作用来恢复 p53 功能已被作为癌症治疗的一种极具吸引力的策略。迄今为止，已有少数小分子被报道为有效的 p53-MDM2 抑制剂。MDM2 与一些配体形成复合物的 X 射线结构可在蛋白质数据库中获得，在此，通过分层虚拟筛选策略，利用这些数据有效地鉴定了新的 p53-MDM2 相互作用拮抗剂。为此，第一步旨在从 PubChem 数据库中编译一个包含 686630 种结构合适的化合物的聚焦库，这些化合物类似于两种已知有效的抑制剂 Nutlin-3a 和 DP222669。这些化合物随后进行基于结构的方法（量子极化配体对接和分子动力学模拟），以选择对 MDM2 蛋白具有最高结合亲和力的潜在化合物。此外，配体结合能、ADMET 性质和 PAINS 分析也被认为是选择最有前途的类药分子的筛选标准。基于这些分析，发现三个排名最高的命中分子 CID_118439641、CID_60452010 和 CID_3106907，具有可接受的药代动力学性质，并且与已知抑制剂相比，对 p53-MDM2 相互作用具有卓越的计算抑制能力。分子对接和分子动力学结果很好地证实了最终选择的化合物与 MDM2 疏水裂缝中 p53 结合位点的关键残基的相互作用，具有令人满意的热力学稳定性。因此，本研究提出的计算方法所确定的新最终骨架可以为设计针对 p53-MDM2 相互作用的有前途的抗癌药物提供一组指导原则。
