The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing the catalytic efficiency of de novo enzymes by several orders of magnitude without relying on directed evolution and high-throughput screening. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models, with catalytic contacts present as designed and transition-state root-mean-square deviations of ≤0.65 Å. Our work shows how ensemble-based design can generate efficient artificial enzymes by exploiting the true conformational ensemble to design improved active sites.
Enzymes , Crystallography, X-Ray , X-Ray Diffraction , Catalytic Domain , Catalysis , Enzymes/metabolism
The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.
Coumarin is an important pharmaceutical structural motif, abundantly found in numerous commonly used drugs. Compounds containing this core show a broad spectrum of medicinal properties and biological activities. The increasing importance and wide usages of coumarin derivatives have drawn attention to its synthetic methods, among which metal-catalyzed and organocatalytic methods have proved the most effective. Several metal-catalyzed and/or organocatalytic synthetic strategies for coumarin have been investigated and reported in recent decades. This review focuses on more recent reports on catalysis methods for synthesizing coumarin and coumarin-like structures (including light-mediated methods and nano-catalysts), exploring the mechanistic aspects, simplicity, efficiency, repeatability, and other advantages and disadvantages of these methods.
Coumarins , Metals , Catalysis , Coumarins/chemistry
