ArticleMolecular biology and evolution2017
Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.
Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Review
- Predicting side chain conformations in folded proteins by AlphaFold: Perspective and challenges.Biophysical journal · 2025Article
- Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins.bioRxiv : the preprint server for biology · 2025Article
- Article
- Machine learning in biological physics: From biomolecular prediction to design.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
- pycofitness-Evaluating the fitness landscape of RNA and protein sequences.Bioinformatics (Oxford, England) · 2024Article
- Direct-acting antiviral resistance of Hepatitis C virus is promoted by epistasis.Nature communications · 2023Article
- Mechanisms of HIV-1 integrase resistance to dolutegravir and potent inhibition of drug-resistant variants.Science advances · 2023Article
- HCV E1 influences the fitness landscape of E2 and may enhance escape from E2-specific antibodies.Virus evolution · 2023Article
- Contingency and Entrenchment of Drug-Resistance Mutations in HIV Viral Proteins.The journal of physical chemistry. B · 2022Article
- Evolution avoids a pathological stabilizing interaction in the immune protein S100A9.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation.Biophysical journal · 2022Article
- Covariation of viral recombination with single nucleotide variants during virus evolution revealed by CoVaMa.Nucleic acids research · 2022Article
- Evolution of Amino Acid Propensities under Stability-Mediated Epistasis.Molecular biology and evolution · 2022Article
- Evolutionary modeling reveals enhanced mutational flexibility of HCV subtype 1b compared with 1a.iScience · 2022Article
- Article
- Mi3-GPU: MCMC-based Inverse Ising Inference on GPUs for protein covariation analysis.Computer physics communications · 2021Article
- Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins.PLoS genetics · 2021Article
- Deep Mutational Scanning of Viral Glycoproteins and Their Host Receptors.Frontiers in molecular biosciences · 2021Review
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Authors and funding
4 authors.
Funding
Abstract
Understanding the complex mutation patterns that give rise to drug resistant viral strains provides a foundation for developing more effective treatment strategies for HIV/AIDS. Multiple sequence alignments of drug-experienced HIV-1 protease sequences contain networks of many pair correlations which can be used to build a (Potts) Hamiltonian model of these mutation patterns. Using this Hamiltonian model, we translate HIV-1 protease sequence covariation data into quantitative predictions for the probability of observing specific mutation patterns which are in agreement with the observed sequence statistics. We find that the statistical energies of the Potts model are correlated with the fitness of individual proteins containing therapy-associated mutations as estimated by in vitro measurements of protein stability and viral infectivity. We show that the penalty for acquiring primary resistance mutations depends on the epistatic interactions with the sequence background. Primary mutations which lead to drug resistance can become highly advantageous (or entrenched) by the complex mutation patterns which arise in response to drug therapy despite being destabilizing in the wildtype background. Anticipating epistatic effects is important for the design of future protease inhibitor therapies.
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