Computationally restoring the potency of a clinical antibody against Omicron

Thomas A. Desautels, Kathryn T. Arrildt, Adam T. Zemla, Edmond Y. Lau, Fangqiang Zhu, Dante Ricci, Stephanie Cronin, Seth J. Zost, Elad Binshtein, Suzanne M. Scheaffer, Bernadeta Dadonaite, Brenden K. Petersen, Taylor B. Engdahl, Elaine Chen, Laura S. Handal, Lynn Hall, John W. Goforth, Denis Vashchenko, Sam Nguyen, Dina R. Weilhammer, Jacky Kai-Yin Lo, Bonnee Rubinfeld, Edwin A. Saada, Tracy Weisenberger, Tek-Hyung Lee, Bradley Whitener, James B. Case, Alexander Ladd, Mary S. Silva, Rebecca M. Haluska, Emilia A. Grzesiak, Christopher G. Earnhart, Svetlana Hopkins, Thomas W. Bates, Larissa B. Thackray, Brent W. Segelke, Antonietta Maria Lillo, Shivshankar Sundaram, Jesse D. Bloom, Michael S. Diamond, James E. Crowe, Robert H. Carnahan and Daniel M. Faissol ()
Additional contact information
Thomas A. Desautels: Lawrence Livermore National Laboratory
Kathryn T. Arrildt: Lawrence Livermore National Laboratory
Adam T. Zemla: Lawrence Livermore National Laboratory
Edmond Y. Lau: Lawrence Livermore National Laboratory
Fangqiang Zhu: Lawrence Livermore National Laboratory
Dante Ricci: Lawrence Livermore National Laboratory
Stephanie Cronin: Vanderbilt University Medical Center
Seth J. Zost: Vanderbilt University Medical Center
Elad Binshtein: Vanderbilt University Medical Center
Suzanne M. Scheaffer: Washington University School of Medicine
Bernadeta Dadonaite: Fred Hutchinson Cancer Center
Brenden K. Petersen: Lawrence Livermore National Laboratory
Taylor B. Engdahl: Vanderbilt University Medical Center
Elaine Chen: Vanderbilt University Medical Center
Laura S. Handal: Vanderbilt University Medical Center
Lynn Hall: Vanderbilt University Medical Center
John W. Goforth: Lawrence Livermore National Laboratory
Denis Vashchenko: Lawrence Livermore National Laboratory
Sam Nguyen: Lawrence Livermore National Laboratory
Dina R. Weilhammer: Lawrence Livermore National Laboratory
Jacky Kai-Yin Lo: Lawrence Livermore National Laboratory
Bonnee Rubinfeld: Lawrence Livermore National Laboratory
Edwin A. Saada: Lawrence Livermore National Laboratory
Tracy Weisenberger: Lawrence Livermore National Laboratory
Tek-Hyung Lee: Lawrence Livermore National Laboratory
Bradley Whitener: Washington University School of Medicine
James B. Case: Washington University School of Medicine
Alexander Ladd: Lawrence Livermore National Laboratory
Mary S. Silva: Lawrence Livermore National Laboratory
Rebecca M. Haluska: Lawrence Livermore National Laboratory
Emilia A. Grzesiak: Lawrence Livermore National Laboratory
Christopher G. Earnhart: US Department of Defense
Svetlana Hopkins: Joint Rsearch and Development Inc.
Thomas W. Bates: Lawrence Livermore National Laboratory
Larissa B. Thackray: Washington University School of Medicine
Brent W. Segelke: Lawrence Livermore National Laboratory
Antonietta Maria Lillo: Bioscience Division
Shivshankar Sundaram: Lawrence Livermore National Laboratory
Jesse D. Bloom: Fred Hutchinson Cancer Center
Michael S. Diamond: Washington University School of Medicine
James E. Crowe: Vanderbilt University Medical Center
Robert H. Carnahan: Vanderbilt University Medical Center
Daniel M. Faissol: Lawrence Livermore National Laboratory

Nature, 2024, vol. 629, issue 8013, 878-885

Abstract: Abstract The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs1–3 and revealed how quickly viral escape can curtail effective options4,5. When the SARS-CoV-2 Omicron variant emerged in 2021, many antibody drug products lost potency, including Evusheld and its constituent, cilgavimab4–6. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination4 and is challenging to replace with existing approaches. Rapidly modifying such high-value antibodies to restore efficacy against emerging variants is a compelling mitigation strategy. We sought to redesign and renew the efficacy of COV2-2130 against Omicron BA.1 and BA.1.1 strains while maintaining efficacy against the dominant Delta variant. Here we show that our computationally redesigned antibody, 2130-1-0114-112, achieves this objective, simultaneously increases neutralization potency against Delta and subsequent variants of concern, and provides protection in vivo against the strains tested: WA1/2020, BA.1.1 and BA.5. Deep mutational scanning of tens of thousands of pseudovirus variants reveals that 2130-1-0114-112 improves broad potency without increasing escape liabilities. Our results suggest that computational approaches can optimize an antibody to target multiple escape variants, while simultaneously enriching potency. Our computational approach does not require experimental iterations or pre-existing binding data, thus enabling rapid response strategies to address escape variants or lessen escape vulnerabilities.

Date: 2024
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DOI: 10.1038/s41586-024-07385-1

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