Center for Systems Biology, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, Jiangsu, People's Republic of China.
Adv Protein Chem Struct Biol. 2020;121:49-84. doi: 10.1016/bs.apcsb.2019.12.005. Epub 2020 Jan 10.
DNA methyltransferases (DNMTs) not only play key roles in epigenetic gene regulation, but also serve as emerging targets for several diseases, especially for cancers. Due to the multi-domains of DNMT structures, targeting allosteric sites of protein-protein interactions (PPIs) is becoming an attractive strategy in epigenetic drug discovery. This chapter aims to review the major contemporary approaches utilized for the drug discovery based on PPIs in different dimensions, from the enumeration of allosteric mechanism to the identification of allosteric pockets. These include the construction of protein structure networks (PSNs) based on molecular dynamics (MD) simulations, performing elastic network models (ENMs) and perturbation response scanning (PRS) calculation, the sequence-based conservation and coupling analysis, and the allosteric pockets identification. Furthermore, we complement this methodology by highlighting the role of computational approaches in promising practical applications for the computer-aided drug design, with special focus on two DNMTs, namely, DNMT1 and DNMT3A.
DNA 甲基转移酶（DNMTs）不仅在表观遗传学基因调控中发挥着关键作用，而且还是多种疾病的新兴靶点，尤其是癌症。由于 DNMT 结构的多结构域性，靶向蛋白质-蛋白质相互作用（PPIs）的变构位点已成为表观遗传药物发现中的一种有吸引力的策略。本章旨在综述基于不同维度的 PPIs 的药物发现的主要现代方法，从变构机制的列举到变构口袋的鉴定。这些方法包括基于分子动力学（MD）模拟的蛋白质结构网络（PSN）的构建、弹性网络模型（ENM）和扰动响应扫描（PRS）计算、基于序列的保守性和耦合分析以及变构口袋的鉴定。此外，我们通过强调计算方法在计算机辅助药物设计中有前途的实际应用中的作用来补充该方法，特别关注两种 DNMT，即 DNMT1 和 DNMT3A。
