Laboratório de Modelagem Computacional, Instituto de Ciências Exatas, Universidade Federal de Alfenas, Brazil.
Laboratório de Modelagem Computacional, Instituto de Ciências Exatas, Universidade Federal de Alfenas, Brazil.
Comput Biol Chem. 2022 Jun;98:107668. doi: 10.1016/j.compbiolchem.2022.107668. Epub 2022 Mar 23.
The emergence of COVID-19 caused by SARS-CoV-2 and its spread since 2019 represents the major public health problem worldwide nowadays, which has generated a high number of infections and deaths. The spike protein (S protein) is the most studied protein of SARS-CoV-2, and key to host-cell entry through ACE2 receptor. This protein presents a large pattern of glycosylations with important roles in immunity and infection mechanisms. Therefore, understanding key aspects of the molecular mechanisms of these structures, during drug recognition in SARS-CoV-2, may contribute to therapeutic alternatives. In this work, we explored the impact of glycosylations on the drug recognition on two domains of the S protein, the receptor-binding domain (RBD) and the N-terminal domain (NTD) through molecular dynamics simulations and computational biophysics analysis. Our results show that glycosylations in the S protein induce structural stability and changes in rigidity/flexibility related to the number of glycosylations in the structure. These structural changes are important for its biological activity as well as the correct interaction of ligands in the RBD and NTD regions. Additionally, we evidenced a roto-translation phenomenon in the interaction of the ligand with RBD in the absence of glycosylation, which disappears due to the influence of glycosylation and the convergence of metastable states in RBM. Similarly, glycosylations in NTD promote an induced fit phenomenon, which is not observed in the absence of glycosylations; this process is decisive for the activity of the ligand at the cryptic site. Altogether, these results provide an explanation of glycosylation relevance in biophysical properties and drug recognition to S protein of SARS-CoV-2, which must be considered in the rational drug development and virtual screening targeting S protein.
由 SARS-CoV-2 引起的 COVID-19 的出现及其自 2019 年以来的传播是当今全球主要的公共卫生问题,它导致了大量的感染和死亡。刺突蛋白(S 蛋白)是 SARS-CoV-2 研究最多的蛋白,也是通过 ACE2 受体进入宿主细胞的关键。该蛋白具有大量糖基化模式,在免疫和感染机制中具有重要作用。因此,了解这些结构在 SARS-CoV-2 药物识别过程中分子机制的关键方面,可能有助于提供治疗选择。在这项工作中,我们通过分子动力学模拟和计算生物物理分析,探讨了糖基化对 S 蛋白两个结构域(受体结合域(RBD)和 N 端结构域(NTD)上药物识别的影响。我们的结果表明,S 蛋白中的糖基化诱导结构稳定性和与结构中糖基化数量相关的刚性/柔性变化。这些结构变化对于其生物活性以及 RBD 和 NTD 区域中配体的正确相互作用很重要。此外,我们在没有糖基化的情况下,在 RBD 配体相互作用中证明了旋转平移现象,由于糖基化的影响和 RBM 中亚稳态的收敛,这种现象消失了。同样,NTD 中的糖基化促进了诱导契合现象,在没有糖基化的情况下观察不到这种现象;这个过程对于配体在隐匿部位的活性是决定性的。总之,这些结果解释了 SARS-CoV-2 S 蛋白中糖基化在生物物理性质和药物识别中的重要性,在针对 S 蛋白的合理药物开发和虚拟筛选中必须考虑这一点。