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基于计算机的人复制蛋白 A N 端结构域抑制剂的鉴定

In silico identification of inhibitors targeting N-Terminal domain of human Replication Protein A.

机构信息

Department of Medical Statistics and Bioinformatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, 34752, Turkey.

Department of Medical Statistics and Bioinformatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, 34752, Turkey.

出版信息

J Mol Graph Model. 2019 Jan;86:149-159. doi: 10.1016/j.jmgm.2018.10.011. Epub 2018 Oct 20.

Abstract

Replication Protein A (RPA) mediates DNA Damage Response (DDR) pathways through protein-protein interactions (PPIs). Targeting the PPIs formed between RPA and other DNA Damage Response (DDR) mediators has become an intriguing area of research for cancer drug discovery. A number of studies applied different methods ranging from high throughput screening approaches to fragment-based drug design tools to discover RPA inhibitors. Although these methods are robust, virtual screening approaches may be allocated as an alternative to such experimental methods, especially for screening of large libraries. Here we report the comprehensive screening of the large database, ZINC15 composed of ∼750 M compounds and the comparison of the identified ligands with the previously known inhibitors by means of binding affinity and drug-likeness. Initially, a ligand library sharing similarity with a promising inhibitor of the N-terminal domain of the RPA70 subunit (RPA70N) was generated by screening of the ZINC15 library. 46,999 ligands were collected and screened by LeDock which produced a satisfactory correlation with the experimental values (R = 0.77). 10 of the top-scoring ligands in LeDock were directly progressed to molecular dynamics (MD) simulations, while 10 additional ligands were also selected based on their LeDock scores and the presence of a functional group that could interact with the key amino acids in the RPA70N cleft. MD simulations were used to predict the binding free energy of the ligands by the MM-PBSA method which produced a high level of agreement with the experiments (R = 0.85). Binding free energy predictions pointed out 2 ligands with higher binding affinity than any of the reference inhibitors. Particularly the ligand ZINC000753854163 exhibited superior drug-likeness features than any of the known inhibitors. Overall, this study reports ZINC000753854163 as a possible inhibitor of RPA70N, reflecting its possible use in RPA70N targeted cancer therapy.

摘要

复制蛋白 A(RPA)通过蛋白-蛋白相互作用(PPIs)介导 DNA 损伤反应(DDR)途径。针对 RPA 与其他 DDR 介质之间形成的 PPIs,已经成为癌症药物发现的一个有趣的研究领域。许多研究采用了不同的方法,从高通量筛选方法到基于片段的药物设计工具,以发现 RPA 抑制剂。虽然这些方法很强大,但虚拟筛选方法可能可以作为这些实验方法的替代方法,特别是对于大型文库的筛选。在这里,我们报告了对大型数据库 ZINC15 的全面筛选,该数据库包含约 7500 万个化合物,并通过结合亲和力和药物相似性比较了鉴定的配体与以前已知的抑制剂。最初,通过筛选 ZINC15 库生成了与 RPA70 亚基 N 端结构域有前途的抑制剂(RPA70N)具有相似性的配体文库。收集并筛选了 46999 个配体,通过 LeDock 产生了与实验值的满意相关性(R=0.77)。LeDock 中得分最高的 10 个配体直接进行分子动力学(MD)模拟,而另外 10 个配体也根据它们的 LeDock 得分和存在可以与 RPA70N 裂缝中的关键氨基酸相互作用的功能团进行选择。通过 MM-PBSA 方法对 MD 模拟进行了配体结合自由能的预测,与实验结果高度吻合(R=0.85)。结合自由能预测指出,有 2 个配体的结合亲和力高于任何参考抑制剂。特别是配体 ZINC000753854163 比任何已知的抑制剂都具有更好的药物相似性特征。总的来说,这项研究报告 ZINC000753854163 是 RPA70N 的一种可能抑制剂,反映了其在 RPA70N 靶向癌症治疗中的可能用途。

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