The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10 5 and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a .200-fold increase in k cat /K m (k cat /K m of 2,600 M 21 s 21 and k cat /k uncat of .10 6 ). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.Naturally occurring enzymes are extraordinarily efficient catalysts 1 . They bind their substrates in a well-defined active site with precisely aligned catalytic residues to form highly active and selective catalysts for a wide range of chemical reactions under mild conditions. Nevertheless, many important synthetic reactions lack a naturally occurring enzymatic counterpart. Hence, the design of stable enzymes with new catalytic activities is of great practical interest, with potential applications in biotechnology, biomedicine and industrial processes. Furthermore, the computational design of new enzymes provides a stringent test of our understanding of how naturally occurring enzymes work. In the past several years, there has been exciting progress in designing new biocatalysts 2,3 .Here we describe the use of our recently developed computational enzyme design methodology 4 to create new enzyme catalysts for a reaction for which no naturally occurring enzyme exists: the Kemp elimination 5,6 . The reaction, shown in Fig. 1a, has been extensively studied as an activated model system for understanding the catalysis of proton abstraction from carbon-a process that is normally restricted by high activation-energy barriers 7,8 . Computational design methodThe first step in our protocol for designing new enzymes is to choose a catalytic mechanism and then to use quantum mechanical transition state calculations to create an idealized active site with protein functional groups positioned so as to maximize transition state stabilization (Fig. 1b). The key step for the Kemp elimination is deprotonation of a carbon by a general base. We chose two different catalytic bases for this purpose: first, the carboxyl group of an aspartate or glutamate side chain, and, second, the imidazole of a histidine positioned and polarized by the carboxyl group of an aspartate or glutamate (we refer to this combination as a His-Asp dyad). The two choices have complementary strengths and weaknesses. The advantage of the carboxylate...

The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.

The activation strain or distortion/interaction model is a tool to analyze activation barriers that determine reaction rates. For bimolecular reactions, the activation energies are the sum of the energies to distort the reactants into geometries they have in transition states plus the interaction energies between the two distorted molecules. The energy required to distort the molecules is called the activation strain or distortion energy. This energy is the principal contributor to the activation barrier. The transition state occurs when this activation strain is overcome by the stabilizing interaction energy. Following the changes in these energies along the reaction coordinate gives insights into the factors controlling reactivity. This model has been applied to reactions of all types in both organic and inorganic chemistry, including substitutions and eliminations, cycloadditions, and several types of organometallic reactions.

Surface trap–mediated nonradiative charge recombination is a major limit to achieving high-efficiency metal-halide perovskite photovoltaics. The ionic character of perovskite lattice has enabled molecular defect passivation approaches through interaction between functional groups and defects. However, a lack of in-depth understanding of how the molecular configuration influences the passivation effectiveness is a challenge to rational molecule design. Here, the chemical environment of a functional group that is activated for defect passivation was systematically investigated with theophylline, caffeine, and theobromine. When N-H and C=O were in an optimal configuration in the molecule, hydrogen-bond formation between N-H and I (iodine) assisted the primary C=O binding with the antisite Pb (lead) defect to maximize surface-defect binding. A stabilized power conversion efficiency of 22.6% of photovoltaic device was demonstrated with theophylline treatment.

The conductor-like polarizable continuum model (CPCM) using several cavity models is applied to compute aqueous solvation free energies for a number of organic molecules (30 neutral molecules, 21 anions, and 19 cations). The calculated solvation free energies are compared to the available experimental data from the viewpoint of cavity models, computational methods, calculation time, and aqueous pKa values. The HF/6-31+G(d)//HF/6-31+G(d) and the HF/6-31+G(d)//B3LYP/6-31+G(d) with the UAKS cavities, in which radii are optimized with PBE0/6-31G(d), provide aqueous solvation effects in best agreement with available experimental data. The mean absolute deviations from experiment are 2.6 kcal/mol. The MP2/6-31++G(d,p)//HF/6-31+G(d) with the CPCM-UAKS(HF/6-31+G(d)) calculation is also performed for the base-catalyzed hydrolysis of methyl acetate in water.

The Diels-Alder reaction is a cornerstone in organic synthesis, forming two carbon-carbon bonds and up to four new stereogenic centers in one step. No naturally occurring enzymes have been shown to catalyze bimolecular Diels-Alder reactions. We describe the de novo computational design and experimental characterization of enzymes catalyzing a bimolecular Diels-Alder reaction with high stereoselectivity and substrate specificity. X-ray crystallography confirms that the structure matches the design for the most active of the enzymes, and binding site substitutions reprogram the substrate specificity. Designed stereoselective catalysts for carbon-carbon bond forming reactions should be broadly useful in synthetic chemistry.

A series of oligoacenes from benzene to decacene were studied computationally with DFT and CASSCF methods. In contrast to the common view that acenes are closed-shell systems or may have a triplet ground state, these results offer the first theoretical predictions for the singlet ground state and diradical character for oligoacenes. The nature of the ground states of these molecules arises from the disjoint nature of the NBMOs that are singly occupied in the diradical.

The affinities of hosts—ranging from small synthetic cavitands to large proteins—for organic molecules are well documented. The average association constants for the binding of organic molecules by cyclodextrins, synthetic hosts, and albumins in water, as well as of catalytic antibodies or enzymes for substrates are 103.5±2.5 M−1. Binding affinities are elevated to 108±2 M−1 for the complexation of transition states and biological antigens by antibodies or inhibitors by enzymes, and to 1016±4 M−1 for transition states with enzymes. The origins of the distributions of association constants observed for the broad range of host–guest systems are explored in this Review, and typical approaches to compute and analyze host–guest binding in solution are discussed. In many classes of complexes a rough correlation is found between the binding affinity and the surface area that is buried upon complexation. Enzymes transcend this effect and achieve transition‐state binding much greater than is expected from the surface areas.