FuncLib does not per se predict mutations that enhance catalysis, but rather suggests variants with multiple mutations that generate stabilizing interacting networks at the active site, thus focusing the search to safe regions of the sequence space. Furthermore, FuncLib can be used to target regions that are expected to be relevant for catalysis, thus avoiding the inefficiency associated with probing catalytically neutral mutations. Here, we apply the FuncLib approach to the enhancement of the activity of a de novo enzyme activity previously generated by minimalist rational design. Specifically, we recently demonstrated that a simple hydrophobic-to-ionizable residue substitution (Figure ) is sufficient to generate a de novo active site capable of highly proficient Kemp eliminase activity for the cleavage of 5-nitrobenzisoxazole in Precambrian β-lactamases obtained by ancestral inference, with the best of our designs (kcat/KM~5•10 3 M -1 s -1 and kcat ~ 10 s -1 at alkaline pH) showing catalytic proficiencies only two orders of magnitude lower than the best designed Kemp eliminase obtained through iterative design followed by 17 rounds of directed evolution. There are a number of reasons Kemp elimination is particularly attractive as a model system for de novo enzyme design studies. (1) It provides a simple activated model for proton abstraction by carbon, (2) as a non-natural reaction it means that no natural enzyme has evolved to catalyze this reaction reducing the risk of contamination from natural enzymes, and (3) for historical reasons, Kemp elimination has often been used as a benchmark for enzyme (and other catalyst) design studies, providing extensive examples of designed constructs against which to compare our engineered β-lactamases. Certainly, Kemp elimination is a facile reaction that requires a simple catalytic machinery (essentially, a catalytic base to abstract the proton).