Computational Biology/Drug Discovery Laboratory, Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomosho, Nigeria.
Department of Biochemistry and Nutrition, Nigerian Institute of Medical Research (NIMR), Yaba, Lagos, Nigeria.
J Mol Model. 2022 May 10;28(6):142. doi: 10.1007/s00894-022-05131-w.
In the vast majority of malignancies, the p53 tumor suppressor pathway is compromised. In some cancer cells, high levels of MDM2 polyubiquitinate p53 and mark it for destruction, thereby leading to a corresponding downregulation of the protein. MDM2 interacts with p53 via its hydrophobic pocket, and chemical entities that block the dimerization of the protein-protein complex can restore p53 activity. Thus far, only a few chemical compounds have been reported as potent arsenals against p53-MDM2. The Protein Data Bank has crystallogaphic structures of MDM2 in complex with certain compounds. Herein, we have exploited one of the complexes in the identification of new p53-MDM2 antagonists using a hierarchical virtual screening technique. The initial stage was to compile a targeted library of structurally appropriate compounds related to a known effective inhibitor, Nutlin 2, from the PubChem database. The identified 57 compounds were subjected to virtual screening using molecular docking to discover inhibitors with high binding affinity for MDM2. Consequently, five compounds with higher binding affinity than the standard emerged as the most promising therapeutic candidates. When compared to Nutlin 2, four of the drug candidates (CID_140017825, CID_69844501, CID_22721108, and CID_22720965) demonstrated satisfactory pharmacokinetic and pharmacodynamic profiles. Finally, MD simulation of the dynamic behavior of lead-protein complexes reveals the stability of the complexes after a 100,000 ps simulation period. In particular, when compared to the other three leads, overall computational modeling found CID_140017825 to be the best pharmacological candidate. Following thorough experimental trials, it may emerge as a promising chemical entity for cancer therapy.
在绝大多数恶性肿瘤中,p53 肿瘤抑制途径都受到了损害。在一些癌细胞中,MDM2 会使大量 p53 多泛素化,并将其标记为破坏目标,从而导致蛋白质相应地下调。MDM2 通过其疏水性口袋与 p53 相互作用,而阻止蛋白质-蛋白质复合物二聚化的化学实体可以恢复 p53 的活性。到目前为止,只有少数几种化学物质被报道为针对 p53-MDM2 的有效武器。蛋白质数据库中已有 MDM2 与某些化合物形成复合物的晶体结构。在此,我们利用其中一个复合物,通过分层虚拟筛选技术来鉴定新的 p53-MDM2 拮抗剂。初始阶段是从 PubChem 数据库中编译一个与已知有效抑制剂 Nutlin 2 结构相关的靶向化合物库。鉴定出的 57 种化合物随后通过分子对接进行虚拟筛选,以发现对 MDM2 具有高结合亲和力的抑制剂。结果,有 5 种化合物的结合亲和力高于标准抑制剂,成为最有希望的治疗候选物。与 Nutlin 2 相比,4 种候选药物(CID_140017825、CID_69844501、CID_22721108 和 CID_22720965)表现出令人满意的药代动力学和药效学特征。最后,对配体-蛋白质复合物的动态行为进行 MD 模拟,发现在模拟 100000 ps 后复合物仍然稳定。特别是与其他三种先导化合物相比,总体计算模型发现 CID_140017825 是最佳的药理学候选物。经过彻底的实验验证,它可能成为癌症治疗的一种有前途的化学实体。