Data from: Predicting allosteric mutants that increase activity of a major antibiotic resistance enzyme
Latallo, Malgorzata J. et al. (2017), Data from: Predicting allosteric mutants that increase activity of a major antibiotic resistance enzyme, Dryad, Dataset, https://doi.org/10.5061/dryad.ck3dh
The CTX-M family of beta lactamases mediate broad-spectrum antibiotic resistance and present in the majority of drug-resistant gram-negative bacteria infections worldwide. Allosteric mutations that increase catalytic rates of these drug resistance enzymes have been identified in clinical isolates but are challenging to predict prospectively. We have used molecular dynamics simulations to predict allosteric mutants increasing CTX-M9 drug resistance, experimentally testing top mutants using multiple antibiotics. Purified enzymes show an increase in catalytic rate and efficiency, while mutant crystal structures show no detectable changes from wild-type CTX-M9. We hypothesize that increased drug resistance results from changes in the conformational ensemble of an acyl intermediate in hydrolysis. Machine-learning analyses on top-scoring mutants identify changes to the binding-pocket conformational ensemble by which these allosteric mutations transmit their effect. These findings show how molecular simulation can predict how allosteric mutations alter active-site conformational equilibria to increase catalytic rates and thus resistance against common clinically used antibiotics.