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Gag-Pol Processing during HIV-1 Virion Maturation: A Systems Biology Approach

Overview of attention for article published in PLoS Computational Biology, June 2013
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Title
Gag-Pol Processing during HIV-1 Virion Maturation: A Systems Biology Approach
Published in
PLoS Computational Biology, June 2013
DOI 10.1371/journal.pcbi.1003103
Pubmed ID
Authors

Balázs Könnyű, S. Kashif Sadiq, Tamás Turányi, Rita Hírmondó, Barbara Müller, Hans-Georg Kräusslich, Peter V. Coveney, Viktor Müller

Abstract

Proteolytic processing of Gag and Gag-Pol polyproteins by the viral protease (PR) is crucial for the production of infectious HIV-1, and inhibitors of the viral PR are an integral part of current antiretroviral therapy. The process has several layers of complexity (multiple cleavage sites and substrates; multiple enzyme forms; PR auto-processing), which calls for a systems level approach to identify key vulnerabilities and optimal treatment strategies. Here we present the first full reaction kinetics model of proteolytic processing by HIV-1 PR, taking into account all canonical cleavage sites within Gag and Gag-Pol, intermediate products and enzyme forms, enzyme dimerization, the initial auto-cleavage of full-length Gag-Pol as well as self-cleavage of PR. The model allows us to identify the rate limiting step of virion maturation and the parameters with the strongest effect on maturation kinetics. Using the modelling framework, we predict interactions and compensatory potential between individual cleavage rates and drugs, characterize the time course of the process, explain the steep dose response curves associated with PR inhibitors and gain new insights into drug action. While the results of the model are subject to limitations arising from the simplifying assumptions used and from the uncertainties in the parameter estimates, the developed framework provides an extendable open-access platform to incorporate new data and hypotheses in the future.

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Geographical breakdown

Country Count As %
Spain 2 2%
Netherlands 1 <1%
United Kingdom 1 <1%
France 1 <1%
Canada 1 <1%
United States 1 <1%
Unknown 103 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 21%
Student > Master 22 20%
Student > Ph. D. Student 20 18%
Student > Bachelor 15 14%
Other 3 3%
Other 6 5%
Unknown 21 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 30%
Agricultural and Biological Sciences 28 25%
Medicine and Dentistry 6 5%
Immunology and Microbiology 4 4%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 12 11%
Unknown 23 21%