UCLA

Enzymes are complex biomolecules capable of performing unique catalysis under physiological conditions at neutral temperature and pH. However, the architecture of enzymatic catalysis is often a combination of the quantum influence of the immediate active site, as well as the electrostatic and configurational influences of amino acids surrounding the active site. As a result of this cooperation between baseline chemical reactivity and electrostatic assistance, it has become important to model enzymes using multiscale methods that take advantage of treating the active site with quantum mechanical methods, while approximately treating the surrounding protein using cheaper, classically driven force-field molecular mechanics methods. Here we describe the use of a multiscale engine which utilizes a combination of density functional theory with discrete molecular dynamics (dubbed QM/DMD) to aid in the characterization of metalloenzymes.