Exploring the role of framework mutations in enabling breadth of a cross-reactive antibody (CR3022) against the SARS-CoV-2 RBD and its variants of concern

Abstract

Cross-reactive and broadly neutralizing antibodies against surface proteins of diverse strains of rapidly evolving viral pathogens like SARS-CoV-2 can prevent infection and therefore are crucial for the development of effective universal vaccines. While antibodies typically incorporate mutations in their complementarity determining regions during affinity maturation, mutations in the framework regions have been reported as players in determining properties of broadly neutralizing antibodies against HIV and the Influenza virus. We propose an increase in the cross-reactive potential of CR3022 against the emerging SARS- CoV-2 variants of concern through enhanced conformational flexibility. In this study, we use molecular dynamics simulations, in silico mutagenesis, structural modeling, and docking to explore the role of light chain FWR mutations in CR3022, a SARS-CoV anti-spike (S)-protein antibody cross-reactive to the S-protein receptor binding domain of SARS-CoV-2. Our study shows that single substitutions in the light chain framework region of CR3022 with conserved epitopes across SARS-CoV strains allow targeting of diverse antibody epitope footprints that align with the epitopes of recently-categorized neutralizing antibody classes while enabling binding to more than one strain of SARS-CoV-2. Our study has implications for rapid and evolution-based engineering of broadly neutralizing antibodies and reaffirms the role of framework mutations in effective change of antibody orientation and conformation via improved flexibility.

Communicated by Ramaswamy H. Sarma

Keywords:

• Framework mutations
• CR3022
• SARS-CoV-2 variants
• antigen-antibody interaction
• cross-reactive antibody
• broadly neutralizing antibody
• antibody affinity maturation

Acknowledgments

All authors thank Dell EMC HPC & AI Innovation Lab, Bangalore, for providing access to high-performance computing facilities and GROMACS modules. MA was supported by a Junior Research Fellowship awarded by the Department of Science and Technology (DST) - Science and Engineering Research Board (SERB) [ECR/2016/001752]. Furthermore, AP acknowledges the Supercomputing Facility for Bioinformatics and Computational Biology (SCFBio) at the Indian Institute of Technology, Delhi, for providing access to the AMBER modules, which were used for preliminary analysis. All authors are grateful for the contributions of Arjun Singh, Shraddha Jain, and Uvija Rani in data organization and presentation.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical approval and consent to participate

Not applicable

Consent for publication

Not applicable

Author contributions

SS, MA, AP and YK conceptualized the study. SS and MA designed the study, SS and MA performed mutagenesis, modeling, and docking. SP, SS, MA, AP, and AK performed molecular dynamics simulations. SS, MA, and AP prepared the tables and figures. SS, MA, and AP wrote the manuscript. SS, MA, and AP compiled the manuscript. SS, MA, AP, and UD analyzed the data. UD, GD, and YK guided, reviewed, and edited the manuscript. All authors read and approved the final manuscript.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Department of Science and Technology (DST) - Science and Engineering Research Board (SERB) [ECR/2016/001752] awarded to YK.