A Structural and Mathematical Modeling Analysis of the Likelihood of Antibody-Dependent Enhancement in Influenza
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nihms882723.pdf
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Author(s)
Ramakrishnan, Boopathy
Viswanathan, Karthik
Tharakaraman, Kannan
Dančík, Vlado
Raman, Rahul
Babcock, Gregory J.
Shriver, Zachary
Sasisekharan, Ram
Date Issued
October 2016
Journal
Trends in Microbiology
Publisher
Elsevier BV
Citation
Ramakrishnan, Boopathy, et al. “A Structural and Mathematical Modeling Analysis of the Likelihood of Antibody-Dependent Enhancement in Influenza.” Trends in Microbiology, vol. 24, no. 12, Dec. 2016, pp. 933–43.
Version
Author's final manuscript
Abstract
Broadly neutralizing monoclonal antibodies (bNAbs) for viral infections, such as HIV, respiratory syncytial virus (RSV), and influenza, are increasingly entering clinical development. For influenza, most neutralizing antibodies target influenza virus hemagglutinin. These bNAbs represent an emerging, promising modality for treatment and prophylaxis of influenza due to their multiple mechanisms of antiviral action and generally safe profile. Preclinical work in other viral diseases, such as dengue, has demonstrated the potential for antibody-based therapies to enhance viral uptake, leading to enhanced viremia and worsening of disease. This phenomenon is referred to as antibody-dependent enhancement (ADE). In the context of influenza, ADE has been used to explain several preclinical and clinical phenomena. Using structural and viral kinetics modeling, we assess the role of ADE in the treatment of influenza with a bNAb.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.TIM.2016.09.003
