A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.computational protein design | de novo enzyme design | proton transfer T he high efficiency, chemoselectivity, regio-and stereospecificity, and biodegradability of enzymes make them extremely attractive catalysts. However, the finite repertoire of naturally occurring enzymes limits their applicability to broad problems in biotechnology. A general method for the computational design of enzymes that can efficiently catalyze arbitrary chemical reactions would allow the benefits of enzymatic catalysis to be applied to chemical transformations of interest that are currently inaccessible via natural enzymes. Bolon and Mayo provided important early evidence that such an approach is feasible (1), which motivated significant progress toward this goal in recent years. Using quantum mechanics-based active site design and the Rosetta software suite, Baker, Houk, and coworkers designed enzymes for three chemically unrelated nonnatural reactions in a variety of catalytically inert scaffolds (2-4).In early incarnations of computational protein design, a strategy for methods development was put forth in terms of the so-called "protein design cycle" in which experimental evaluation of an initial design is used to inform adjustments to the design process for subsequent rounds of design (5, 6). Ideally, these steps would be continued iteratively until the protein sequences predicted by the algorithm exhibit the desired char...