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基于分子动力学模拟和 MM/PBSA 的强力虚拟药物筛选以寻找 METTL16 的有效抑制剂。

Brute Force Virtual Drug Screening with Molecular Dynamics Simulation and MM/PBSA to Find Potent Inhibitors of METTL16.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2023 May-Jun;20(3):2356-2361. doi: 10.1109/TCBB.2022.3233670. Epub 2023 Jun 5.

DOI:10.1109/TCBB.2022.3233670
PMID:37018281
Abstract

Epitranscriptomic modification is a dynamic modification of RNAs. Epitranscriptomic writer proteins are methyltransferases, such as METTL3 and METTL16. The up regulation of METTL3 have been found to be linked to different cancers and targeting METTL3 is an effective way to reduce tumour progression. Drug development against METTL3 is an active field of research. METTL16, SAM dependent methyltransferase, is another writer protein, that has been found to be upregulated in hepatocellular carcinoma and gastric cancer. In this pioneering study METTL16 has been targeted for virtual drug screening for the very first time using brute force strategy to identify a drug molecule that could be repurposed for the treatment of the disease caused. An unbiased library of the commercially available drug molecules has been used for screening using a multipoint validation process developed for this work, which includes molecular docking, ADMET analysis, protein-ligand interaction analysis, Molecular Dynamics Simulation, binding energy calculation via Molecular Mechanics Poisson-Boltzmann Surface Area method. Upon the in-silico screening of over 650 drugs the authors have found NIL and VXL passed the validation process. The data strongly indicates the potency of these two drugs in the treatment of disease where METTL16 needs to be inhibited.

摘要

表观转录组修饰是 RNA 的动态修饰。表观转录组writer 蛋白是甲基转移酶,如 METTL3 和 METTL16。已经发现 METTL3 的上调与不同的癌症有关,靶向 METTL3 是减少肿瘤进展的有效方法。针对 METTL3 的药物开发是一个活跃的研究领域。METTL16,SAM 依赖性甲基转移酶,是另一种 writer 蛋白,已经在肝癌和胃癌中发现上调。在这项开创性的研究中,首次使用暴力策略针对 METTL16 进行了虚拟药物筛选,以确定可重新用于治疗该疾病的药物分子。使用为此项工作开发的多点验证过程,对商业上可用的药物分子库进行了无偏筛选,该过程包括分子对接、ADMET 分析、蛋白-配体相互作用分析、分子动力学模拟、通过分子力学泊松-玻尔兹曼表面积方法计算结合能。在对超过 650 种药物进行计算机筛选后,作者发现 NIL 和 VXL 通过了验证过程。这些数据强烈表明这两种药物在需要抑制 METTL16 的疾病治疗中的潜力。

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