Design of an optimal combination therapy with broadly neutralizing antibodies to suppress HIV-1

  1. Colin LaMont
  2. Jakub Otwinowski
  3. Kanika Vanshylla
  4. Henning Gruell
  5. Florian Klein
  6. Armita Nourmohammad  Is a corresponding author
  1. Max Planck Institute for Dynamics and Self-Organization, Germany
  2. University of Cologne, Germany
  3. 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.

The following previously published data sets were used
    1. Zanini et al
    (2015) Project: PRJEB9618
    European Nucleotide Archive, Accession no: PRJEB9618.

Article and author information

Author details

  1. Colin LaMont

    Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
    Competing interests
    No competing interests declared.
  2. Jakub Otwinowski

    Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
    Competing interests
    No competing interests declared.
  3. Kanika Vanshylla

    University of Cologne, Cologne, Germany
    Competing interests
    No competing interests declared.
  4. Henning Gruell

    University of Cologne, Cologne, Germany
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0725-7138
  5. Florian Klein

    University of Cologne, Cologne, Germany
    Competing interests
    No competing interests declared.
  6. Armita Nourmohammad

    Department of Physics, University of Washington, Seattle, United States
    For correspondence
    armita@uw.edu
    Competing interests
    Armita Nourmohammad, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6245-3553

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.

Reviewing Editor

  1. Kayla Sprenger, MIT

Publication history

  1. Received: December 1, 2021
  2. Accepted: July 4, 2022
  3. Accepted Manuscript published: July 19, 2022 (version 1)

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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  1. Colin LaMont
  2. Jakub Otwinowski
  3. Kanika Vanshylla
  4. Henning Gruell
  5. Florian Klein
  6. Armita Nourmohammad
(2022)
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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