Design of an optimal combination therapy with broadly neutralizing antibodies to suppress HIV-1
- Max Planck Institute for Dynamics and Self-Organization, Germany
- University of Cologne, Germany
- University of Washington, United States
Abstract
Infusion of broadly neutralizing antibodies (bNAbs) has shown promise as an alternative to anti-retroviral therapy against HIV. A key challenge is to suppress viral escape, which is more effectively achieved with a combination of bNAbs. Here, we propose a computational approach to predict the efficacy of a bNAb therapy based on the population genetics of HIV escape, which we parametrize using high-throughput HIV sequence data from bNAb-naive patients. By quantifying the mutational target size and the fitness cost of HIV-1 escape from bNAbs, we predict the distribution of rebound times in three clinical trials. We show that a cocktail of three bNAbs is necessary to effectively suppress viral escape, and predict the optimal composition of such bNAb cocktail. Our results offer a rational therapy design for HIV, and show how genetic data can be used to predict treatment outcomes and design new approaches to pathogenic control.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. Reference to the previously published data used in this manuscript is provided. Modelling code is uploaded on GitHub at https://github.com/StatPhysBio/HIVTreatmentOptimization, and in the Julia package https://github.com/StatPhysBio/EscapeSimulator.
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Project: PRJEB9618European Nucleotide Archive, Accession no: PRJEB9618.
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HIV-1 isolate 2A1_DB7_02 from USA envelope glycoprotein (env) gene, partial cdsGeneBank, accession no: KX016803.
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Antibody 10-1074 suppresses viremia in HIV-1-infected individualsGeneBank, accession no: KY323724-KY324834.
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Safety and antiviral activity of combination HIV-1 broadly neutralizing antibodies in viremic individualsGeneBank, accession no: MH632763 - MH633255.
Article and author information
Author details
Armita Nourmohammad
Funding
Deutsche Forschungsgemeinschaft (1310)
- Armita Nourmohammad
National Science Foundation (2045054)
- Armita Nourmohammad
1Max Planck Institute for Dynamics and Self-organization (open access funding)
- Colin LaMont
- Jakub Otwinowski
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, LaMont et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Design of an optimal combination therapy with broadly neutralizing antibodies to suppress HIV-1
eLife 11:e76004.
https://doi.org/10.7554/eLife.76004
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