An Ke, Zhu Xiaohong, Yan Junfang, Xu Peiyi, Hu Linfeng, Bai Chen
Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, Guangdong, People's Republic of China.
School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui, 230026, P. R. China.
AIMS Microbiol. 2022 Dec 26;8(4):595-611. doi: 10.3934/microbiol.2022038. eCollection 2022.
The COVID-19 pandemic has caused a worldwide health crisis and economic recession. Effective prevention and treatment methods are urgently required to control the pandemic. However, the emergence of novel SARS-CoV-2 variants challenges the effectiveness of currently available vaccines and therapeutic antibodies. In this study, through the assessment of binding free energies, we analyzed the mutational effects on the binding affinity of the coronavirus spike protein to neutralizing antibodies, patient-derived antibodies, and artificially designed antibody mimics. We designed a scoring method to assess the immune evasion ability of viral variants. We also evaluated the differences between several targeting sites on the spike protein of antibodies. The results presented herein might prove helpful in the development of more effective therapies in the future.
新冠疫情引发了全球健康危机和经济衰退。迫切需要有效的预防和治疗方法来控制疫情。然而，新型严重急性呼吸综合征冠状病毒2（SARS-CoV-2）变体的出现对现有疫苗和治疗性抗体的有效性构成了挑战。在本研究中，通过评估结合自由能，我们分析了突变对冠状病毒刺突蛋白与中和抗体、患者来源抗体及人工设计抗体模拟物结合亲和力的影响。我们设计了一种评分方法来评估病毒变体的免疫逃逸能力。我们还评估了抗体在刺突蛋白上几个靶向位点之间的差异。本文给出的结果可能对未来开发更有效的治疗方法有所帮助。
