Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa.
Curr Pharm Biotechnol. 2021;22(11):1520-1537. doi: 10.2174/1389201021666201027154833.
We seek to provide an understanding of the binding mechanism of Remdesivir, as well as structural and conformational implications on SARS-CoV-2 virus RNA-dependent RNA polymerase upon its binding and identify its crucial pharmacophoric moieties.
The coronavirus disease of 2019 (COVID-19) pandemic had infected over a million people, with 65,000 deaths as of the first quarter of 2020. The current limitation of effective treatment options with no approved vaccine or targeted therapeutics for the treatment of COVID-19 has posed serious global health threats. This has necessitated several drug and vaccine development efforts across the globe. To date, the farthest in the drug development pipeline is Remdesivir.
We performed the molecular dynamics simulation, quantified the energy contributions of binding site residues using per-residue energy decomposition calculations, and subsequently generated a pharmacophore model for the identification of potential SARS-CoV-2 virus RNA-dependent RNA polymerase inhibitors.
Integrative molecular dynamics simulations and thermodynamic calculations coupled with advanced post-molecular dynamics analysis techniques were employed.
Our analysis showed that the modulatory activity of Remdesivir is characterized by an extensive array of high-affinity and consistent molecular interactions with specific active site residues that anchor Remdemsivir within the binding pocket for efficient binding. These residues are ASP452, THR456, ARG555, THR556, VAL557, ARG624, THR680, SER681, and SER682. Results also showed that Remdesivir binding induces minimal individual amino acid perturbations, subtly interferes with deviations of C-α atoms, and restricts the systematic transition of SARS-CoV-2 RNA-dependent RNA polymerase from the "buried" hydrophobic region to the "surface-exposed" hydrophilic region. We also mapped a pharmacophore model based on the observed high-affinity interactions with SARSCoV- 2 virus RNA-dependent RNA polymerase, which showcased the crucial functional moieties of Remdesivir and was subsequently employed for virtual screening.
The structural insights and the provided optimized pharmacophoric model would augment the design of improved analogs of Remdesivir that could expand treatment options for COVID-19.
我们旨在了解瑞德西韦的结合机制，以及结合后对 SARS-CoV-2 病毒 RNA 依赖性 RNA 聚合酶的结构和构象影响，并确定其关键药效团部分。
截至 2020 年第一季度，2019 年冠状病毒病（COVID-19）大流行已感染超过 100 万人，死亡 65000 人。目前，COVID-19 治疗方法有限，既没有有效的治疗方法，也没有批准的疫苗或靶向治疗药物，这对全球健康构成了严重威胁。这使得全球范围内都在进行多项药物和疫苗开发工作。迄今为止，药物开发管道中最先进的是瑞德西韦。
我们进行了分子动力学模拟，使用逐残基能量分解计算量化了结合部位残基的能量贡献，随后生成了一个药效团模型，用于鉴定潜在的 SARS-CoV-2 病毒 RNA 依赖性 RNA 聚合酶抑制剂。
采用整合分子动力学模拟和热力学计算，并结合先进的分子动力学后分析技术。
我们的分析表明，瑞德西韦的调节活性具有广泛的高亲和力和一致的分子相互作用，与特定的活性部位残基结合，将瑞德西韦锚定在结合口袋内，以实现有效的结合。这些残基是 ASP452、THR456、ARG555、THR556、VAL557、ARG624、THR680、SER681 和 SER682。结果还表明，瑞德西韦结合诱导最小的单个氨基酸扰动，微妙地干扰 C-α 原子的偏差，并限制 SARS-CoV-2 RNA 依赖性 RNA 聚合酶从“埋藏”的疏水区到“表面暴露”的亲水区的系统跃迁。我们还基于与 SARS-CoV-2 病毒 RNA 依赖性 RNA 聚合酶的观察到的高亲和力相互作用，绘制了一个药效团模型，展示了瑞德西韦的关键功能部分，并随后用于虚拟筛选。
这些结构见解和提供的优化药效团模型将增强瑞德西韦类似物的设计，从而为 COVID-19 的治疗提供更多选择。
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