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A Quantitative High-Resolution Genetic Profile Rapidly Identifies Sequence Determinants of Hepatitis C Viral Fitness and Drug Sensitivity


The emergence of drug resistance during antiviral treatment limits treatment options and poses challenges to pharmaceutical development. Meanwhile, the search for novel antiviral compounds with chemical genetic screens has led to the identification of antiviral agents with undefined drug mechanisms. Daclatasvir, an effective NS5A inhibitor, is one such example. In traditional methods to identify critical residues governing drug-protein interactions, wild type virus is passaged under drug treatment pressure, enabling the identification of resistant mutations evolved after multiple viral passages. However, this method only characterizes a fraction of the positively selected variants. Here we have simultaneously quantified the relative change in replication fitness as well as the relative sensitivity to Daclatasvir for all possible single amino acid mutations in the NS5A domain IA, thereby identifying the entire panel of positions that interact with the drug. Using mathematical models, we predicted which mutations pose the greatest risk of causing emergence of resistance under different scenarios of treatment compliance. The mutant fitness and drug-sensitivity profiles obtained can also inform the patient-specific use of Daclatasvir and may facilitate the development of second-generation drugs with a higher genetic barrier to resistance.


Vyšlo v časopise: A Quantitative High-Resolution Genetic Profile Rapidly Identifies Sequence Determinants of Hepatitis C Viral Fitness and Drug Sensitivity. PLoS Pathog 10(4): e32767. doi:10.1371/journal.ppat.1004064
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.ppat.1004064

Souhrn

The emergence of drug resistance during antiviral treatment limits treatment options and poses challenges to pharmaceutical development. Meanwhile, the search for novel antiviral compounds with chemical genetic screens has led to the identification of antiviral agents with undefined drug mechanisms. Daclatasvir, an effective NS5A inhibitor, is one such example. In traditional methods to identify critical residues governing drug-protein interactions, wild type virus is passaged under drug treatment pressure, enabling the identification of resistant mutations evolved after multiple viral passages. However, this method only characterizes a fraction of the positively selected variants. Here we have simultaneously quantified the relative change in replication fitness as well as the relative sensitivity to Daclatasvir for all possible single amino acid mutations in the NS5A domain IA, thereby identifying the entire panel of positions that interact with the drug. Using mathematical models, we predicted which mutations pose the greatest risk of causing emergence of resistance under different scenarios of treatment compliance. The mutant fitness and drug-sensitivity profiles obtained can also inform the patient-specific use of Daclatasvir and may facilitate the development of second-generation drugs with a higher genetic barrier to resistance.


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Hygiena a epidemiológia Infekčné lekárstvo Laboratórium

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