Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme Gutiérrez Rus, Luis Ignacio Risso, Valeria Alejandra Sánchez Ruiz, José Manuel Enzyme design De novo enzymes Kemp elimination Ancestral enzymes Beta-lactamases Focused library screening Focused directed evolution The routine generation of enzymes with completely new active sites is a major unsolved problem in protein engineering. Advances in this field have thus far been modest, perhaps due, at least in part, to the widespread use of modern natural proteins as scaffolds for de novo engineering. Most modern proteins are highly evolved and specialized and, consequently, difficult to repurpose for completely new functionalities. Conceivably, resurrected ancestral proteins with the biophysical properties that promote evolvability, such as high stability and conformational diversity, could provide better scaffolds for de novo enzyme generation. Kemp elimination, a non-natural reaction that provides a simple model of proton abstraction from carbon, has been extensively used as a benchmark in de novo enzyme engineering. Here, we present an engineered ancestral beta-lactamase with a new active site that is capable of efficiently catalyzing Kemp elimination. The engineering of our Kemp eliminase involved minimalist design based on a single function-generating mutation, inclusion of an extra polypeptide segment at a position close to the de novo active site, and sharply focused, low-throughput library screening. Nevertheless, its catalytic parameters (k(cat)/K-M similar to 2.10(5) M-1 s(-1), k(cat)similar to 635 s(-1)) compare favorably with the average modern natural enzyme and match the best proton-abstraction de novo Kemp eliminases that are reported in the literature. The general implications of our results for de novo enzyme engineering are discussed. 2022-09-27T06:29:37Z 2022-09-27T06:29:37Z 2022-08-11 info:eu-repo/semantics/article Gutierrez-Rus, L.I... [et al.]. Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme. Int. J. Mol. Sci. 2022, 23, 8934. [https://doi.org/10.3390/ijms23168934] https://hdl.handle.net/10481/76988 10.3390/ijms23168934 eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional MDPI