ArticleeLife2019
Epistasis and entrenchment of drug resistance in HIV-1 subtype B.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
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Who cites it
34 citing papers in PubMed.
- Epistasis plays a limited role in driving entrenchment during neutral protein evolution.Genome biology · 2026Article
- Epistasis among clustered lineage-specific amino acid substitutions in the Drosophila Trio protein.PLoS genetics · 2026Article
- Review
- Characterisation of RT Connection and RNase H Polymorphisms in HIV-1 Subtype C in Botswana.Viruses · 2026Article
- Functional bottlenecks can emerge from non-epistatic underlying traits.PLoS computational biology · 2026Article
- EZ-DMS - A Simple and Accessible Protocol and Software Package for Deep Mutational Scanning of Virus Proteins.bioRxiv : the preprint server for biology · 2026Article
- Predicting side chain conformations in folded proteins by AlphaFold: Perspective and challenges.Biophysical journal · 2025Article
- Epistasis among clustered lineage-specific adaptive amino acid substitutions in the Drosophila Trio protein.bioRxiv : the preprint server for biology · 2025Article
- Article
- Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins.bioRxiv : the preprint server for biology · 2025Article
- The importance of epistasis in the evolution of viral pathogens.Virus evolution · 2025Review
- Efficient epistasis inference via higher-order covariance matrix factorization.bioRxiv : the preprint server for biology · 2024Article
- Emergent time scales of epistasis in protein evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Kinetic coevolutionary models predict the temporal emergence of HIV-1 resistance mutations under drug selection pressure.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Revolutionizing HIV-1 Viral Load Monitoring in India: The Potential of Dried Blood Spot Analysis for Expanding Access and Improving Care.Healthcare (Basel, Switzerland) · 2024Review
- In vivo functional phenotypes from a computational epistatic model of evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Changing selection on amino acid substitutions in Gag protein between major HIV-1 subtypes.Virus evolution · 2024Article
- Broad synergistic antiviral efficacy between a novel elite controller-derived dipeptide and antiretrovirals against drug-resistant HIV-1.Frontiers in cellular and infection microbiology · 2024Article
- Direct-acting antiviral resistance of Hepatitis C virus is promoted by epistasis.Nature communications · 2023Article
- Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The development of drug resistance in HIV is the result of primary mutations whose effects on viral fitness depend on the entire genetic background, a phenomenon called 'epistasis'. Based on protein sequences derived from drug-experienced patients in the Stanford HIV database, we use a co-evolutionary (Potts) Hamiltonian model to provide direct confirmation of epistasis involving many simultaneous mutations. Building on earlier work, we show that primary mutations leading to drug resistance can become highly favored (or entrenched) by the complex mutation patterns arising in response to drug therapy despite being disfavored in the wild-type background, and provide the first confirmation of entrenchment for all three drug-target proteins: protease, reverse transcriptase, and integrase; a comparative analysis reveals that NNRTI-induced mutations behave differently from the others. We further show that the likelihood of resistance mutations can vary widely in patient populations, and from the population average compared to specific molecular clones.
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Registered trials
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.