Research Computing Center, Lomonosov Moscow State University, 119992 Moscow, Russia.
School of Pharmacy, China Pharmaceutical University, Nanjing 211198, China.
Molecules. 2022 Apr 23;27(9):2721. doi: 10.3390/molecules27092721.
The COVID-19 pandemic is still affecting many people worldwide and causing a heavy burden to global health. To eliminate the disease, SARS-CoV-2, the virus responsible for the pandemic, can be targeted in several ways. One of them is to inhibit the 2'--methyltransferase (nsp16) enzyme that is crucial for effective translation of viral RNA and virus replication. For methylation of substrates, nsp16 utilizes -adenosyl methionine (SAM). Binding of a small molecule in the protein site where SAM binds can disrupt the synthesis of viral proteins and, as a result, the replication of the virus. Here, we performed high-throughput docking into the SAM-binding site of nsp16 for almost 40 thousand structures, prepared for compounds from three libraries: Enamine Coronavirus Library, Enamine Nucleoside Mimetics Library, and Chemdiv Nucleoside Analogue Library. For the top scoring ligands, semi-empirical quantum-chemical calculations were performed, to better estimate protein-ligand binding enthalpy. Relying upon the calculated binding energies and predicted docking poses, we selected 21 compounds for experimental testing.
新冠疫情仍在全球范围内影响着许多人,给全球健康带来沉重负担。为了消灭导致这一疫情的 SARS-CoV-2 病毒,可以通过几种方法对其进行靶向处理。其中一种方法是抑制 2'--甲基转移酶(nsp16)酶,该酶对病毒 RNA 的有效翻译和病毒复制至关重要。nsp16 利用 -腺苷甲硫氨酸(SAM)对底物进行甲基化。小分子与 SAM 结合的蛋白质位点结合,可以破坏病毒蛋白的合成,从而阻止病毒的复制。在这里,我们对近 4 万个结构进行了高通量对接,这些结构是为来自三个库的化合物准备的:Enamine 冠状病毒库、Enamine 核苷类似物库和 Chemdiv 核苷类似物库。对于得分最高的配体,我们进行了半经验量子化学计算,以更好地估计蛋白质-配体结合焓。根据计算的结合能和预测的对接构象,我们选择了 21 种化合物进行实验测试。