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

Qi, H and Olson, CA and Wu, NC and Ke, R and Loverdo, C and Chu, V and Truong, S and Remenyi, R and Chen, Z and Du, Y and Su, S and Al-Mawsawi, LQ and Wu, T and Chen, S and Lin, C and Zhong, W and Lloyd-Smith, JO and Sun, R (2014) A Quantitative High-Resolution Genetic Profile Rapidly Identifies Sequence Determinants of Hepatitis C Viral Fitness and Drug Sensitivity. PLoS Pathogens.

Abstract

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients

Item Type: Article
Additional Information: NIBR author: Zhong, W institute: NIBR contributor address: (Qi, Olson, Remenyi, Du, Al-Mawsawi, Wu, Sun) Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, CA, United States (Wu, Sun) The Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA, United States (Ke, Loverdo, Lloyd-Smith) Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States (Chu, Truong) Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, United States (Chen) Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, United States (Su, Chen, Lin) Institute of Information Science, Academia Sinica, Taipei, Taiwan (Republic of China) (Su) Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan (Republic of China) (Zhong) Department of Infectious Diseases, Novartis Institutes for BioMedical Research, Emeryville, CA, United States (Lloyd-Smith) Fogarty International Center, National Institutes of Health, Bethesda, MD, United States (Sun) School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
Date Deposited: 13 Oct 2015 13:12
Last Modified: 13 Oct 2015 13:12
URI: https://oak.novartis.com/id/eprint/22630

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