ArticleJournal of computational chemistry2022
Predicting antibiotic resistance in complex protein targets using alchemical free energy methods.
Article in Journal of computational chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Rapid, accurate, and reproduciblemSphere · 2025Article
- Colistin resistance in clinical isolates of Salmonella enterica from Izmir, Turkiye: association with pmrA/pmrB mutations and variations in adhesion and invasion capabilities.Molecular biology reports · 2025Article
- Multiple Molecule λ-Dynamics: Probing Drug Resistance with Concurrent Protein and Ligand Perturbations.The journal of physical chemistry letters · 2025Article
- Predicting rifampicin resistance inERJ open research · 2025Article
- Prediction of pyrazinamide resistance inJAC-antimicrobial resistance · 2024Article
- Predicting antibiotic resistance in complex protein targets using alchemical free energy methods.Journal of computational chemistry · 2022Article
- Covalent docking and molecular dynamics simulations reveal the specificity-shifting mutations Ala237Arg and Ala237Lys in TEM beta-lactamase.PLoS computational biology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Drug resistant Mycobacterium tuberculosis, which mostly results from single nucleotide polymorphisms in antibiotic target genes, poses a major threat to tuberculosis treatment outcomes. Relative binding free energy (RBFE) calculations can rapidly predict the effects of mutations, but this approach has not been tested on large, complex proteins. We use RBFE calculations to predict the effects of M. tuberculosis RNA polymerase and DNA gyrase mutations on rifampicin and moxifloxacin susceptibility respectively. These mutations encompass a range of amino acid substitutions with known effects and include large steric perturbations and charged moieties. We find that moderate numbers (n = 3-15) of short RBFE calculations can predict resistance in cases where the mutation results in a large change in the binding free energy. We show that the method lacks discrimination in cases with either a small change in energy or that involve charged amino acids, and we investigate how these calculation errors may be decreased.
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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.