Beta-lactam antibiotics are a mainstay of antibacterial therapy for gram-negative organisms, but increasing drug resistance has in recent years limited the clinical utility of many drugs. In the US, the primary determinant of Enterobacteriaceal drug resistance is the substrate spectrum of beta-lactamase enzymes that degrade the drugs. Of particular concern are CTX-M enzymes, which are either biochemically or genetically associated with resistance to all oral antibiotics, and KPC enzymes, which are associated with resistance to most or all FDA-approved antibiotics. The primary determinant of resistance in these enzymes is catalytic capability rather than ligand binding--the enzymes bind a wide variety of substrates with similar affinity but show substantial differences in catalytic rates. We have studied allosteric effects of mutations to these enzymes via a combined computational/experimental approach to understand changes that affect substrate spectrum and/or catalytic rates. Several computationally predicted allosteric mutations increase experimentally-measured kcat values but do not appreciably change crystallographic structures. We conclude that these mutations alter the conformational ensemble of a key covalent intermediate in hydrolysis and use machine-learning approaches to identify the binding-pocket conformational changes by which the allosteric mutations transmit their effect. These findings show how molecular simulation can predict allosteric mutations that subtly alter conformational equilibria to alter catalytic rates, increasing resistance against clinically important antibiotics.

Understanding allosteric modulation of beta lactamase function and bacterial drug resistance

254th National Meeting (2017)

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