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Tempo and mode of inhibitor-mutagen antiviral therapies: A multidisciplinary approach

AutorIranzo, Jaime ; Perales, Celia ; Domingo, Esteban ; Manrubia, Susanna C.
Palabras claveViral adaptation
Viral quasispecies
Antiviral design
population dynamics
Mutation
Fecha de publicación29-jun-2011
EditorNational Academy of Sciences (U.S.)
CitaciónPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 108: 16008- 16013 (2011)
ResumenThe continuous emergence of drug-resistant viruses is a major obstacle for the successful treatment of viral infections, thus representing a persistent spur to the search for new therapeutic strategies. Among them, multidrug treatments are currently at the forefront of pharmaceutical, clinical, and computational investigation. Still, there are many unknowns in the way that different drugs interact among themselves and with the pathogen that they aim to control. Inspired by experimental studies with picornavirus, here, we discuss the performance of sequential vs. combination therapies involving two dissimilar drugs: the mutagen ribavirin and an inhibitor of viral replication, guanidine. Because a systematic analysis of viral response to drug doses demands a precious amount of time and resources, we present and analyze an in silico model describing the dynamics of the viral population under the action of the two drugs. The model predicts the response of the viral population to any dose combination, the optimal therapy to be used in each case, and the way to minimize the probability of appearance of resistant mutants. In agreement with the theoretical predictions, in vitro experiments with foot-and-mouth disease virus confirm that the suitability of simultaneous or sequential administration depends on the drug doses. In addition, intrinsic replicative characteristics of the virus (e.g., replication through RNA only or a DNA intermediate) play a key role to determine the appropriateness of a sequential or combination therapy. Knowledge of several model parameters can be derived by means of few, simple experiments, such that the model and its predictions can be extended to other viral systems.
URIhttp://hdl.handle.net/10261/128288
DOI10.1073/pnas.1110489108
Identificadoresdoi: 10.1073/pnas.1110489108
issn: 0027-8424
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