antimicrobial resistance computing molecular dynamics tuberculosis

New publication: Predicting antibiotic resistance in complex protein targets using alchemical free energy methods

In this paper, Alice Brankin calculates how different mutations in the DNA gyrase affect the binding of an antibiotic, moxifloxacin, and thereby potentially whether those mutations confer resistance or not.

She calculates the relative binding free energy using thermodynamic integration, a method that is derived from classical statistical mechanics. To accompany these results, Philip Fowler, carried out a similar investigation but for rifampicin binding to the RNA polymerase. Both are proteins from M. tuberculosis and hence this study is relevant to tuberculosis antibiotic resistance.

In past work, we showed that these methods not only could be used to predict resistance for much smaller proteins (DHFR in S. aureus) but also that very short lambda windows could be used, thereby reducing the time to solution.

In this work we show that applying the same technique to proteins an order of magnitude larger is, at present, much more challenging with the result that the magnitude of the error in the free energy is often too large to permit a qualitative prediction of resistance or susceptibility. If the mutation confers a high degree of resistance (and therefore a large change in the binding free energy), as is the case for the RNA polymerase but not the DNA gyrase, then successful prediction is possible. This paper therefore probes what is currently feasible and we look forward to returning to these ideas and systems in several year’s time.

In an amazing bit of serendipity, the journal, J Comp Chem, posted the paper online the day before Alice was planning on submitting her thesis, allowing her to include the citation!

By Philip Fowler

Philip W Fowler is a computational biophysicist studying antimicrobial resistance working at the John Radcliffe Hospital in Oxford.

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