ArticlePLoS pathogens2014
A quantitative high-resolution genetic profile rapidly identifies sequence determinants of hepatitis C viral fitness and drug sensitivity.
Article in PLoS pathogens, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
42 citing papers in PubMed.
- Scanning the horizon: deep mutational scanning approaches in virology.Journal of virology · 2026Review
- EZ-DMS - A Simple and Accessible Protocol and Software Package for Deep Mutational Scanning of Virus Proteins.bioRxiv : the preprint server for biology · 2026Article
- Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy.Nature communications · 2025Article
- MMRT: MultiMut Recursive Tree for predicting functional effects of high-order protein variants from low-order variants.Computational and structural biotechnology journal · 2025Article
- Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning.Nature communications · 2024Article
- ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction.bioRxiv : the preprint server for biology · 2023Article
- Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning.bioRxiv : the preprint server for biology · 2023Article
- Genotype-phenotype landscapes for immune-pathogen coevolution.Trends in immunology · 2023Review
- Mutational fitness landscape and drug resistance.Current opinion in structural biology · 2023Review
- Accurate prediction of functional effect of single amino acid variants with deep learning.Computational and structural biotechnology journal · 2023Article
- A Two-Level, Intramutant Spectrum Haplotype Profile of Hepatitis C Virus Revealed by Self-Organized Maps.Microbiology spectrum · 2021Article
- Applications of Deep Mutational Scanning in Virology.Viruses · 2021Review
- Quantifying the Evolutionary Constraints and Potential of Hepatitis C Virus NS5A Protein.mSystems · 2021Article
- Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease.PLoS genetics · 2020Article
- MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect.Genome biology · 2019Article
- Inferring protein 3D structure from deep mutation scans.Nature genetics · 2019Article
- Mutational pathway maps and founder effects define the within-host spectrum of hepatitis C virus mutants resistant to drugs.PLoS pathogens · 2019Article
- Deep generative models of genetic variation capture the effects of mutations.Nature methods · 2018Article
- Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era.Immunological reviews · 2018Review
- Multiplexed assays of variant effects contribute to a growing genotype-phenotype atlas.Human genetics · 2018Review
Corrections and comments
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Authors and funding
18 authors.
Funding
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.