Research Unit in Bioinformatics, Department of Microbiology and Biochemistry, Rhodes University, Grahamstown 6140, South Africa.
Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States.
J Chem Inf Model. 2020 Oct 26;60(10):5080-5102. doi: 10.1021/acs.jcim.0c00634. Epub 2020 Sep 16.
A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (M), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of M behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant M dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, , averaged betweenness centrality, and geometry calculations. The results showed that SARS-CoV-2 M essentially behaves in a similar manner to its SAR-CoV homolog. However, we report the following new findings from the variants: (1) Residues GLY15, VAL157, and PRO184 have mutated more than once in SARS CoV-2; (2) the D48E variant has lead to a novel "TSEEMLN"" loop at the binding pocket; (3) inactive apo M does not show signs of dissociation in 100 ns MD; (4) a non-canonical pose for PHE140 widens the substrate binding surface; (5) dual allosteric pockets coinciding with various stabilizing and functional components of the substrate binding pocket were found to display correlated compaction dynamics; (6) high betweenness centrality values for residues 17 and 128 in all M samples suggest their high importance in dimer stability-one such consequence has been observed for the M17I mutation whereby one of the N-fingers was highly unstable. (7) Independent coarse-grained Monte Carlo simulations suggest a relationship between the rigidity/mutability and enzymatic function. Our entire approach combining database preparation, variant retrieval, homology modeling, dynamic residue network (DRN), relevant conformation retrieval from 1-D kernel density estimates from reaction coordinates to other existing approaches of structural analysis, and data visualization within the coronaviral M is also novel and is applicable to other coronaviral proteins.
一种新型冠状病毒(SARS-CoV-2)对世界卫生和经济构成全球性威胁。其二聚体主蛋白酶(M)是病毒前体蛋白蛋白水解切割所必需的,由于其保守性和缺乏人类同源物,是药物开发的良好候选物。提高我们对 M 行为的理解可以加速发现有效的治疗方法来降低死亡率。使用均方根偏差、均方根波动、平均介数中心度和几何计算分析从 GISAID 数据库中过滤的序列获得的 50 个突变 M 二聚体的全原子分子动力学(MD)模拟(100ns)。结果表明,SARS-CoV-2 M 基本表现出与其 SARS-CoV 同源物相似的行为。然而,我们从变体中报告了以下新发现:(1)残基 GLY15、VAL157 和 PRO184 在 SARS CoV-2 中已经发生了不止一次突变;(2)D48E 变体在结合口袋处导致了一个新的“TSEEMLN”环;(3)无活性 apo M 在 100ns MD 中没有显示出解离的迹象;(4)非典型构象的 PHE140 拓宽了底物结合表面;(5)与底物结合口袋的各种稳定和功能成分重合的双变构口袋被发现具有相关的压缩动力学;(6)所有 M 样本中残基 17 和 128 的高介数中心度值表明它们在二聚体稳定性方面的重要性-对于 M17I 突变,其中一个 N-手指非常不稳定,就观察到了这种后果之一;(7)独立的粗粒化蒙特卡罗模拟表明刚性/可变性和酶功能之间存在关系。我们结合数据库准备、变体检索、同源建模、动态残基网络(DRN)、从反应坐标到其他现有结构分析方法的一维核密度估计中检索到的相关构象以及数据可视化的整个方法,在冠状病毒 M 中也是新颖的,并且适用于其他冠状病毒蛋白。