Robust Prediction of Resistance to Trimethoprim in Staphylococcus aureus.

Abstract:

:The rise of antibiotic resistance threatens modern medicine; to combat it new diagnostic methods are required. Sequencing the whole genome of a pathogen offers the potential to accurately determine which antibiotics will be effective to treat a patient. A key limitation of this approach is that it cannot classify rare or previously unseen mutations. Here we demonstrate that alchemical free energy methods, a well-established class of methods from computational chemistry, can successfully predict whether mutations in Staphylococcus aureus dihydrofolate reductase confer resistance to trimethoprim. We also show that the method is quantitatively accurate by calculating how much the most common resistance-conferring mutation, F99Y, reduces the binding free energy of trimethoprim and comparing predicted and experimentally measured minimum inhibitory concentrations for seven different mutations. Finally, by considering up to 32 free energy calculations for each mutation, we estimate its specificity and sensitivity.

journal_name

Cell Chem Biol

journal_title

Cell chemical biology

authors

Fowler PW,Cole K,Gordon NC,Kearns AM,Llewelyn MJ,Peto TEA,Crook DW,Walker AS

doi

10.1016/j.chembiol.2017.12.009

subject

Has Abstract

pub_date

2018-03-15 00:00:00

pages

339-349.e4

issue

3

eissn

2451-9456

issn

2451-9448

pii

S2451-9456(17)30437-3

journal_volume

25

pub_type

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