Enzymes are “Nature's catalysts”, reducing the timescales of the chemical reactions that drive biology from millions of years to fractions of seconds. As a result of their tremendous catalytic proficiencies, they are also in great demand as extracellular catalysts for a whole host of processes, from the synthesis of fine chemicals and pharmaceuticals to the production of novel biofuels. However, these tremendous proficiencies are as yet unmatched in any artificial system, in part due to the vastness of the sequence space that needs navigating, and the almost surgical precision by which enzyme catalysis is regulated. Our aim in this project was to combine state-of-the-art and novel computational approaches in order to construct an evolutionary-based strategy for in silico enzyme design. Our focus was on two showcase systems, functional evolution among enzymes that catalyze phosphoryl transfer and enzyme-catalyzed chiral chemistry, both as a training set to understand how enzyme functions evolve naturally, as well as model systems for subsequent computational work. Through detailed modeling of the fundamental chemistry of the systems of interest, as well as the corresponding enzymatic reactions (catalyzed by both wild-type and mutant enzymes), we have been able to obtain substantial insight into the driving forces for selectivity, promiscuity, and evolution among these enzymes. In particular, we have been able to highlight the roles of structural dynamics, entropy, cooperative electrostatics, and active site hydrophobicity in driving the evolution of enzyme function. From the perspective of fundamental mechanistic chemistry, by modeling phosphoryl and related group transfer in aqueous solution, we have provided a unifying framework for the mechanisms of phosphate and sulfate monoester hydrolysis in aqueous solution, resolving long-standing experimental controversies, as well as discussing the key challenges involved in reliably interpreting both experimental and computational data. From a methodological perspective, we have provided a set of non-bonded force-field independent parameters for a range of alkali earth and transition metals, which are particularly useful for modeling on-metal chemistry using classical approaches, we have made substantial upgrades to the Q simulation package resulting in a new open-source Q6 release, we have developed a new web server (
http://www.micellemaker.net) to generating and preparing micelles as input for molecular simulations, and we have developed a new simulation toolkit, CADEE, to automatize the in silico directed evolution of enzymes. Finally, in collaboration with colleagues from Spain and the US, we have used resurrected Precambrian beta lactamases with novel non-natural catalytic functions as a showcase for the power of ancestral protein resurrection and harnessing enzyme dynamics in artificial enzyme design. Taken together, the insights and methodologies this project has provided, all of which are freely available to the scientific community as Open Access publications and Open Source software, have advanced methodologies for computational enzymology, our understanding of fundamental biochemistry, and the toolkit for artificial enzyme design.