Identifying Determinants of Antibiotic Resistance in Beta-lactamases

Antibiotic resistant infections greatly increase infectious disease mortality by rendering common drug therapies ineffective. Beta-lactamases mediate resistance to beta-lactam antibiotics, the most commonly prescribed class of antibiotics. Elucidating the mechanisms responsible for drug resistance in beta-lactamases aids in developing future antibiotics. Residues allosteric to the binding site are functionally important in conferring drug resistance and, therefore, predicting change in activity from mutations requires the study of all residues instead of just those in the binding-pocket.

To identify functionally important residues beyond the drug-binding site, we developed a pairwise measure of residue association in a beta-lactamase, CTX-M9, using molecular dynamics simulations. This method ranked residues across the beta-lactamase based on the association of their movement with drug binding-pocket movement. Experimental testing of mutations revealed that high ranking allosteric residues were functionally important to CTX-M9.

Large-scale molecular dynamics simulations provide a computationally intensive but powerful approach to predict mutations that specifically enhance activity. Using these, we identified mutations that increase CTX-M9’s resistance by simulating point mutations and ranking the mutation based on a measure of drug hydrolysis favorability in the binding site. A subset of the top-ranking mutations demonstrated increased drug resistance and kinetic activity. Subsequent machine learning analysis revealed that these allosteric mutations resulted in specific changes to side chains in the binding-pocket.

Simulations also enable detailed physical chemistry and statistical learning-based approaches to probe the conformational changes controlling beta-lactamase catalysis and drug resistance. Through these simulations, we characterized a conformational transition responsible for controlling catalytic activity in another beta-lactamase, KPC-2, and identified residues that were responsible for this transition. Mutations to these residues alter this simulated transition in a manner that highly correlates with experimentally measured kcat kinetic values, thus providing another tool to prospectively study the effect of allosteric mutations on drug resistance.