Covalent Docking and Molecular Dynamics Simulations Reveal the Specificity-Shifting Mutations Ala237Arg and Ala237Lys in TEM Beta-Lactamase

Abstract

The rate of modern drug discovery using experimental screening methods still lags behind the rate at which pathogens mutate, underscoring the need for fast and accurate predictive simulations of protein evolution. Multidrug-resistant bacteria evade our defenses by expressing a series of proteins, the most famous of which is the 29-kilodalton enzyme, TEM {beta}-lactamase. Considering these challenges, we applied a covalent docking heuristic to measure the effects of all possible alanine 237 substitutions in TEM due to this codons importance for catalysis and effects on the binding affinities of commercially-available {beta}-lactam compounds. In addition to the usual mutations that reduce substrate binding due to steric hindrance, we identified two distinctive specificity-shifting TEM mutations, Ala237Arg and Ala237Lys, and their respective modes of action. Notably, we discovered and verified through minimum inhibitory concentration assays that, while these mutations and their bulkier side chains lead to steric clashes that curtail ampicillin binding, these same groups foster salt bridges with the negatively-charged side-chain of the cephalosporin cefixime, widely used in the clinic to treat multi-resistant bacterial infections. To measure the stability of these unexpected interactions, we used molecular dynamics simulations and found the binding modes to be stable despite the application of biasing forces. Finally, we found that both TEM mutants also bind strongly to other drugs containing negatively-charged R-groups, such as carumonam and ceftibuten. As with cefixime, this increased binding affinity stems from a salt bridge between the compounds negative moieties and the positively-charged side chain of the arginine or lysine, suggesting a shared mechanism. In addition to reaffirming the power of using simulations as molecular microscopes, our results can guide the rational design of next-generation {beta}-lactam antibiotics and bring the community closer to retaking the lead against the recurrent threat of multidrugresistant pathogens. Author SummaryResistance to antibiotics is a major public health threat. Microorganisms are able to resist commonly used drugs by evolving and expressing enzymes capable of neutralizing antibiotics. Understanding the relationships between structural elements in these enzymes and their drug-clearing functions can lead to crucial insights for the discovery of next-generation antibiotics. In this study, we have used cutting-edge computational modeling methods to predict the effects of all naturally-occurring variations of an important region of the binding site of TEM {beta}-lactamase, one of the major resistance-granting enzymes in bacteria. In an effort to identify patterns that could be useful for drug discovery, our simulations sought to understand how chemical changes in the tested region can affect resistance against a collection of over 90 widely used antibiotics. Crucially, through our simulations, we have identified a pathway for bacterial resistance against {beta}-lactam antibiotics containing a negatively-charged moiety. We have also elucidated the mechanism behind the gain of resistance, which involves strong interactions between the drugs negative moieties and the positively-charged chemical shifts resulting from the mutation. Finally, we validated our predictions against fitness experiments for two commonly used antibiotics, which qualitatively corroborated our most important findings.