Enzymes play a significant role as selective, efficient catalysts for biotechnology, biomedicine, biofuels, and industrial pharmacology. Contemporary investigation of non-natural biocatalytic transformations often relies on robust screens of mutant space through protein engineering (e.g., directed evolution (DE)). Although exceptionally effective, engineering campaigns rarely lead to a deeper understanding of the biocatalytic mechanism that affords the desired product, and detailed computational analyses are often required to uncover the interactions between a biocatalyst and reactant that facilitate reactivity and selectivity. Further, translation of the optimized enzyme to new reactants can be challenging. Specifically, expansion of reaction scope often requires additional rounds of engineering or DE optimization, and mechanistic models may need to be (re)developed to explain the observed selectivity of each enzyme/substrate pair. These tasks limit the accessibility of biocatalysis to labs that lack the infrastructure for high throughput experimentation and/or computational resources.