Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche No 7019, Université de Lorraine, B.P. 70239, Vandœuvre-lès-Nancy Cedex 54506, France.
School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
J Chem Theory Comput. 2022 Oct 11;18(10):5890-5900. doi: 10.1021/acs.jctc.2c00604. Epub 2022 Sep 15.
Accurate determination of binding free energy is pivotal for the study of many biological processes and has been applied in a number of theoretical investigations to compare the affinity of severe acute respiratory syndrome coronavirus 2 variants toward the host cell. Diversity of these variants challenges the development of effective general therapies, their transmissibility relying either on an increased affinity toward their dedicated human receptor, the angiotensin-converting enzyme 2 (ACE2), or on escaping the immune response. Now that robust structural data are available, we have determined with utmost accuracy the standard binding free energy of the receptor-binding domain to the most widespread variants, namely, Alpha, Beta, Delta, and Omicron BA.2, as well as the wild type (WT) in complex either with ACE2 or with antibodies, namely, S2E12 and H11-D4, using a rigorous theoretical framework that combines molecular dynamics and potential-of-mean-force calculations. Our results show that an appropriate starting structure is crucial to ensure appropriate reproduction of the binding affinity, allowing the variants to be compared. They also emphasize the necessity to apply the relevant methodology, bereft of any shortcut, to account for all the contributions to the standard binding free energy. Our estimates of the binding affinities support the view that while the Alpha and Beta variants lean on an increased affinity toward the host cell, the Delta and Omicron BA.2 variants choose immune escape. Moreover, the S2E12 antibody, already known to be active against the WT (Starr et al., 2021; Mlcochova et al., 2021), proved to be equally effective against the Delta variant. In stark contrast, H11-D4 retains a low affinity toward the WT compared to that of ACE2 for the latter. Assuming robust structural information, the methodology employed herein successfully addresses the challenging protein-protein binding problem in the context of coronavirus disease 2019 while offering promising perspectives for predictive studies of ever-emerging variants.
准确测定结合自由能对于研究许多生物过程至关重要,并且已经在许多理论研究中应用于比较严重急性呼吸综合征冠状病毒 2 变种与宿主细胞的亲和力。这些变种的多样性挑战了有效通用疗法的发展,它们的传染性要么依赖于对其专用人类受体血管紧张素转换酶 2(ACE2)的亲和力增加,要么依赖于逃避免疫反应。既然有了强大的结构数据,我们就可以非常准确地确定受体结合域与最广泛的变种(即 Alpha、Beta、Delta 和 Omicron BA.2)以及与 ACE2 或与抗体(即 S2E12 和 H11-D4)结合的野生型(WT)的标准结合自由能,使用严格的理论框架,结合分子动力学和平均势力计算。我们的结果表明,适当的起始结构对于确保适当再现结合亲和力至关重要,这使得可以比较变种。它们还强调必须应用相关方法,避免任何捷径,以考虑到对标准结合自由能的所有贡献。我们对结合亲和力的估计支持这样的观点,即虽然 Alpha 和 Beta 变种依赖于对宿主细胞的亲和力增加,但 Delta 和 Omicron BA.2 变种选择免疫逃避。此外,S2E12 抗体已被证明对 WT(Starr 等人,2021;Mlcochova 等人,2021)有效,对 Delta 变种也同样有效。相比之下,H11-D4 与 ACE2 相比,对 WT 的亲和力较低。假设结构信息稳健,本文所采用的方法成功解决了 2019 年冠状病毒病背景下具有挑战性的蛋白质-蛋白质结合问题,为不断出现的变种的预测研究提供了有希望的前景。