Institute of Pharmaceutical Science, King's College London, London, UK.
Institute of Chemistry, Technische Universität Berlin, Berlin, Germany.
Sci Rep. 2023 Sep 29;13(1):16387. doi: 10.1038/s41598-023-42015-2.
New variants of SARS-CoV-2 that can escape immune response continue to emerge. Consequently, there is an urgent demand to design small molecule therapeutics inhibiting viral entry to host cells to reduce infectivity rate. Despite numerous in silico and in situ studies, the structural requirement of designing viral-entry inhibitors effective against multiple variants of SARS-CoV-2 has yet to be described. Here we systematically screened the binding of various natural products (NPs) to six different SARS-CoV-2 receptor-binding domain (RBD) structures. We demonstrate that Multi-structural Molecular Docking (MOD) combined with molecular dynamics calculations allowed us to predict a vulnerable site of RBD and the structural requirement of ligands binding to this vulnerable site. We expect that our findings lay the foundation for in silico screening and identification of lead molecules to guide drug discovery into designing new broad-spectrum lead molecules to counter the threat of future variants of SARS-CoV-2.
不断出现能够逃避免疫反应的 SARS-CoV-2 新变体。因此，迫切需要设计抑制病毒进入宿主细胞的小分子治疗药物，以降低感染率。尽管进行了大量的计算和原位研究，但针对 SARS-CoV-2 多种变体设计有效病毒进入抑制剂的结构要求尚未得到描述。在这里，我们系统地筛选了各种天然产物（NPs）与六种不同 SARS-CoV-2 受体结合域（RBD）结构的结合。我们证明，多结构分子对接（MOD）结合分子动力学计算使我们能够预测 RBD 的脆弱部位和配体与该脆弱部位结合的结构要求。我们预计，我们的研究结果将为计算机筛选和鉴定先导分子奠定基础，以指导药物发现，设计新的广谱先导分子，以应对未来 SARS-CoV-2 变体的威胁。
