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Estimating the stoichiometry of human immunodeficiency virus entry
Carsten Magnus1, Peter Rusert, Sebastian Bonhoeffer
1Integrative Biology, ETH Zurich, Zurich, Switzerland.
Journal of Virology
|November 21, 2008
Summary
Determining the exact number of interactions needed for human immunodeficiency virus (HIV) entry is complex. Mathematical models suggest approximately eight interactions, but reliable estimation of HIV entry stoichiometry remains challenging.
Area of Science:
- Virology
- Biophysics
- Computational Biology
Background:
- Human immunodeficiency virus (HIV) entry into target cells involves envelope glycoprotein trimers interacting with CD4 and chemokine coreceptors.
- The precise number of these interactions, or the stoichiometry of entry, required for infection is not well understood.
- Previous studies used pseudotyped virions with mixed trimers to investigate entry requirements.
Purpose of the Study:
- To develop and apply mathematical models to infer the stoichiometry of HIV entry.
- To estimate the number of trimer-receptor interactions necessary for viral infection.
- To identify limitations in current knowledge and experimental approaches for determining entry stoichiometry.
Main Methods:
- Development of mathematical models to analyze in vitro infectivity assay data.
- Fitting a simple model to previously published experimental data.
- Consideration of extended models to account for data deviations.
Main Results:
- The simplest model estimated approximately eight trimer-receptor interactions for HIV entry, exceeding prior estimates.
- Extended models produced a wide range of stoichiometry estimates, from 2 to 19 interactions.
- Systematic deviations in data suggest limitations of the simplest model.
Conclusions:
- Reliable estimation of HIV entry stoichiometry is currently not feasible with existing data and models.
- Further definition of key parameters is necessary to accurately determine the stoichiometry of HIV entry.
- The study highlights the complexity of viral entry mechanisms and the need for refined modeling approaches.

