Review of COVID-19 Antibody Therapies

  • Jiahui Chen
  • , Kaifu Gao
  • , Rui Wang
  • , Duc Duy Nguyen
  • , Guo Wei Wei

Research output: Contribution to journalReview articlepeer-review

27 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1-30
Number of pages30
JournalAnnual Review of Biophysics
Volume50
DOIs
StatePublished - May 6 2021

Bibliographical note

Publisher Copyright:
Copyright © 2021 by Annual Reviews. All rights reserved.

Funding

This work was supported in part by National Institutes of Health grant GM126189; National Science Foundation grants DMS-1721024, DMS-1761320, and IIS1900473; theMichigan Economic Development Corporation; George Mason University award PD45722; Bristol-Myers Squibb; and Pfizer. The authors thank the IBM TJWatson Research Center, the COVID-19 High Performance Computing Consortium,NVIDIA, and the Michigan State University High Performance Computing Center for computational assistance.

FundersFunder number
COVID-19 High Performance Computing Consortium
IBM TJWatson Research Center
National Science Foundation Arctic Social Science ProgramIIS1900473, PD45722, DMS-1721024, DMS-1761320
National Institutes of Health (NIH)
National Institute of General Medical Sciences DP2GM119177 Sophie Dumont National Institute of General Medical SciencesR01GM126189
Bristol-Myers Squibb
Pfizer
Nvidia
Michigan State University

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • COVID-19
    • SARS-CoV-2
    • antibody therapy
    • binding affinity
    • deep learning
    • network analysis
    • persistent homology

    ASJC Scopus subject areas

    • Bioengineering
    • Biophysics
    • Structural Biology
    • Biochemistry
    • Cell Biology

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