Chen Jiahui, Gao Kaifu, Wang Rui, Nguyen Duc Duy, Wei Guo-Wei
Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA; email:
Department of Mathematics, University of Kentucky, Lexington, Kentucky 40506, USA.
Annu Rev Biophys. 2021 May 6;50:1-30. doi: 10.1146/annurev-biophys-062920-063711. Epub 2020 Oct 16.
In the global health emergency caused by coronavirus disease 2019 (COVID-19), efficient and specific therapies are urgently needed. Compared with traditional small-molecular drugs, antibody therapies are relatively easy to develop; they are as specific as vaccines in targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and they have thus attracted much attention in the past few months. This article reviews seven existing antibodies for neutralizing SARS-CoV-2 with 3D structures deposited in the Protein Data Bank (PDB). Five 3D antibody structures associated with the SARS-CoV spike (S) protein are also evaluated for their potential in neutralizing SARS-CoV-2. The interactions of these antibodies with the S protein receptor-binding domain (RBD) are compared with those between angiotensin-converting enzyme 2 and RBD complexes. Due to the orders of magnitude in the discrepancies of experimental binding affinities, we introduce topological data analysis, a variety of network models, and deep learning to analyze the binding strength and therapeutic potential of the 14 antibody-antigen complexes. The current COVID-19 antibody clinical trials, which are not limited to the S protein target, are also reviewed.
在由2019冠状病毒病（COVID-19）引发的全球卫生紧急状况下，迫切需要高效且特异的治疗方法。与传统小分子药物相比，抗体疗法相对易于研发；在靶向严重急性呼吸综合征冠状病毒2（SARS-CoV-2）方面，它们与疫苗一样具有特异性；因此在过去几个月里备受关注。本文综述了七种已有的可中和SARS-CoV-2的抗体，其三维结构已存于蛋白质数据库（PDB）中。还评估了五个与SARS-CoV刺突（S）蛋白相关的三维抗体结构中和SARS-CoV-2的潜力。将这些抗体与S蛋白受体结合域（RBD）的相互作用，与血管紧张素转换酶2和RBD复合物之间的相互作用进行了比较。由于实验结合亲和力差异达几个数量级，我们引入拓扑数据分析、多种网络模型和深度学习，来分析这14种抗体-抗原复合物的结合强度和治疗潜力。本文还综述了当前不限于S蛋白靶点的COVID-19抗体临床试验。
