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通过高通量虚拟筛选与自由能计算相结合,鉴定出新型硫醚-酰胺或胍基连接子类 SARS-CoV-2 病毒 RNA 依赖性 RNA 聚合酶抑制剂。

Potential Novel Thioether-Amide or Guanidine-Linker Class of SARS-CoV-2 Virus RNA-Dependent RNA Polymerase Inhibitors Identified by High-Throughput Virtual Screening Coupled to Free-Energy Calculations.

机构信息

Laboratory of Physical Chemistry and Chemical Thermodynamics, Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia.

Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000 Koper, Slovenia.

出版信息

Int J Mol Sci. 2021 Oct 15;22(20):11143. doi: 10.3390/ijms222011143.

Abstract

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new pathogen from the family of that caused a global pandemic of COVID-19 disease. In the absence of effective antiviral drugs, research of novel therapeutic targets such as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) becomes essential. This viral protein is without a human counterpart and thus represents a unique prospective drug target. However, in vitro biological evaluation testing on RdRp remains difficult and is not widely available. Therefore, we prepared a database of commercial small-molecule compounds and performed an in silico high-throughput virtual screening on the active site of the SARS-CoV-2 RdRp using ensemble docking. We identified a novel thioether-amide or guanidine-linker class of potential RdRp inhibitors and calculated favorable binding free energies of representative hits by molecular dynamics simulations coupled with Linear Interaction Energy calculations. This innovative procedure maximized the respective phase-space sampling and yielded non-covalent inhibitors representing small optimizable molecules that are synthetically readily accessible, commercially available as well as suitable for further biological evaluation and mode of action studies.

摘要

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)属于冠状病毒科,是一种新型病原体,引发了 COVID-19 疾病的全球大流行。在缺乏有效抗病毒药物的情况下,研究新型治疗靶点,如 SARS-CoV-2 RNA 依赖性 RNA 聚合酶(RdRp)变得至关重要。这种病毒蛋白在人体内没有相应的蛋白,因此是一个独特的潜在药物靶点。然而,RdRp 的体外生物学评价测试仍然具有挑战性,并且并不广泛可用。因此,我们准备了一个商业小分子化合物数据库,并使用基于配体的对接对 SARS-CoV-2 RdRp 的活性位点进行了基于集合的高通量虚拟筛选。我们鉴定了一类新型硫醚-酰胺或胍-连接体类潜在的 RdRp 抑制剂,并通过分子动力学模拟和线性相互作用能计算,计算了代表性命中物的有利结合自由能。这种创新的方法最大限度地增加了各自的相空间采样,并产生了非共价抑制剂,这些抑制剂代表了可优化的小分子,它们易于合成、可获得、适合进一步的生物学评价和作用模式研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/129f/8540652/0580d1e6a440/ijms-22-11143-g001.jpg

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