Alexandre Zanghellini

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 105 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 kcat/Km (kcat/Km of 2,600 M-1s-1 and kcat/kuncat of >106). 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.

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.

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

Biocatalytic Boost Enzymes tend to direct reactions toward specific products much more selectively than synthetic catalysts. Unfortunately, this selectivity has evolved for cellular purposes and may not promote the sorts of reactions chemists are seeking to enhance (see the Perspective by Lutz). Siegel et al. (p. 309) now describe the design of enzymes that catalyze the bimolecular Diels-Alder reaction, a carbon-carbon bond formation reaction that is central to organic synthesis but unknown in natural metabolism. The enzymes display high stereoselectivity and substrate specificity, and an x-ray structure of the most active enzyme confirms that the structure matches the design. Savile et al. (p. 305, published online 17 June) applied a directed evolution approach to modify an existing transaminase enzyme so that it recognized a complex ketone in place of its smaller native substrate, and could tolerate the high temperature and organic cosolvent necessary to dissolve this ketone. This biocatalytic reaction improved the production efficiency of a drug that treats diabetes. Synthetic enzymes catalyze a carbon-carbon bond-forming reaction with high stereoselectivity and substrate specificity. 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.

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.

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.

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.