Kemp elimination catalysts by computational enzyme design.

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(-1)s(-1) 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.

Prediction of structures of multidomain proteins from structures of the individual domains.

We describe the development of a method for assembling structures of multidomain proteins from structures of isolated domains. The method consists of an initial low-resolution search in which the conformational space of the domain linker is explored using the Rosetta de novo structure prediction method, followed by a high-resolution search in which all atoms are treated explicitly and backbone and side chain degrees of freedom are simultaneously optimized. The method recapitulates, often with very high accuracy, the structures of existing multidomain proteins.

New algorithms and an in silico benchmark for computational enzyme design.

The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.

A novel engineered meganuclease induces homologous recombination in yeast and mammalian cells.

Homologous gene targeting is the ultimate tool for reverse genetics, but its use is often limited by low efficiency. In a number of recent studies, site- specific DNA double-strand breaks (DSBs) have been used to induce efficient gene targeting. Engineering highly specific, dedicated DNA endonucleases is the key to a wider usage of this technology. In this study, we present two novel, chimeric meganucleases, derived from homing endonucleases. The first one is able to induce recombination in yeast and mammalian cells, whereas the second cleaves a novel (chosen) DNA target site. These results are a first step toward the generation of custom endonucleases for the purpose of targeted genome engineering.

de novo computational enzyme design.

Recent advances in systems and synthetic biology as well as metabolic engineering are poised to transform industrial biotechnology by allowing us to design cell factories for the sustainable production of valuable fuels and chemicals. To deliver on their promises, such cell factories, as much as their brick-and-mortar counterparts, will require appropriate catalysts, especially for classes of reactions that are not known to be catalyzed by enzymes in natural organisms. A recently developed methodology, de novo computational enzyme design can be used to create enzymes catalyzing novel reactions. Here we review the different classes of chemical reactions for which active protein catalysts have been designed as well as the results of detailed biochemical and structural characterization studies. We also discuss how combining de novo computational enzyme design with more traditional protein engineering techniques can alleviate the shortcomings of state-of-the-art computational design techniques and create novel enzymes with catalytic proficiencies on par with natural enzymes.

Computational design of novel enzymes without cofactors.

In this review we present a recently developed computational method to design de novo enzymes. Starting from the three-dimensional arrangement of the transition state structure and the catalytic side chains around it (theozyme), RosettaMatch identifies successful placements of the theozyme into protein scaffolds. Subsequently, RosettaEnzDes (for EnzymeDesign) redesigns the active site around the theozyme for binding and stabilization of the transition state and the catalytic residues. The resulting computationally designed enzymes are expressed and experimentally tested for catalytic activity.

Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction.

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.

De novo computational design of retro-aldol enzymes.

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.