Our two-pronged approach (computational design of stabilizing variants targeting NMRdetermined catalytic hotspots) sharply focuses screening to the small regions of the sequence space in which catalysis is efficiently modulated without compromising stability. In this way, we avoid the detrimental catalysis-stability trade-offs that are often observed 8 as a result of the fact that most mutations in a protein are destabilizing. The effectiveness of our approach is highlighted by the fact that we targeted for enhancement a de novo Kemp eliminase which had already been highly optimized by previous engineering efforts. Based on the already high activities of our starting enzyme (kcat ~600 s -1 and kcat/KM ~2•10 5 M -1 s -1 ) one would expect further rate enhancements to be challenging if not even impossible. Particularly, our starting variant already has activities comparable to HG3.17, 32 the best proton abstraction Kemp eliminase to date, kcat = 700 s -1 , kcat/KM = 2.3•10 5 M -1 s -1 , which resulted from 17 rounds of directed evolution on an iterative design background. Yet, despite this high starting activity, we were able to achieve additional optimization and reach de novo biocatalysis levels that are above most reported values for engineered de novo enzymes and modern natural enzymes while also improving stability, as