Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume 43, Issue 26, Pages 1771-1782Publisher
WILEY
DOI: 10.1002/jcc.26979
Keywords
alchemical free energy methods; antibiotic resistance; molecular dynamics; relative binding free energy calculations; tuberculosis
Categories
Funding
- CompBioMed
- National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance
- National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC)
- Oxford Medical Research Council Doctoral Training Partnership
- Nuffield Department of Clinical Medicine
- UK High-End Computing Consortium for Biomolecular Simulation [EP/R029407/1]
- Wellcome Trust [203141/Z/16/Z]
- EU H2020 Centre of Excellence Project
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Drug resistant Mycobacterium tuberculosis poses a major threat to tuberculosis treatment outcomes. This study used relative binding free energy (RBFE) calculations to predict the effects of mutations in M. tuberculosis RNA polymerase and DNA gyrase on the susceptibility to rifampicin and moxifloxacin, respectively. The study found that RBFE calculations can predict resistance in cases where the mutation results in a large change in binding free energy, but lacks discrimination in cases with small energy changes or involving charged amino acids.
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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