Donald Hilvert

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.

Protein design by directed evolution.

While nature evolved polypeptides over billions of years, protein design by evolutionary mimicry is progressing at a far more rapid pace. The mutation, selection, and amplification steps of the evolutionary cycle may be imitated in the laboratory using existing proteins, or molecules created de novo from random sequence space, as starting templates. However, the astronomically large number of possible polypeptide sequences remains an obstacle to identifying and isolating functionally interesting variants. Intelligently designed libraries and improved search techniques are consequently important for future advances. In this regard, combining experimental and computational methods holds particular promise for the creation of tailored protein receptors and catalysts for tasks unimagined by nature.

Iterative approach to computational enzyme design.

A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.

Directed Evolution of a Protein Container

An engineered protein container protects its bacterial host by efficient and selective encapsulation of a toxic protease. Confinement of enzymes in protein nanocompartments represents a potentially powerful strategy for controlling catalytic activity in cells. By using a simple electrostatically based tagging system for protein encapsulation, we successfully sequestered HIV protease, a toxic enzyme when produced cytoplasmically, within an engineered lumazine synthase capsid. The growth advantage resulting from protecting the Escherichia coli host from the protease enabled directed evolution of improved capsids. After four rounds of mutagenesis and selection, we obtained a variant with a 5- to 10-fold higher loading capacity than the starting capsid, which permitted efficient growth even at high intracellular concentrations of HIV protease. The superior properties of the evolved capsid can be ascribed to multiple mutations that increase the net negative charge on its luminal surface and thereby enhance engineered Coulombic interactions between host and guest. Such structures could be used for diverse biotechnological applications in living cells.

Investigating and Engineering Enzymes by Genetic Selection

Natural enzymes have arisen over millions of years by the gradual process of Darwinian evolution. The fundamental steps of evolution-mutation, selection, and amplification-can also be exploited in the laboratory to create and characterize protein catalysts on a human timescale. In vivo genetic selection strategies enable the exhaustive analysis of protein libraries with 10(10) different members, and even larger ensembles can be studied with in vitro methods. Evolutionary approaches can consequently yield statistically meaningful insight into the complex and often subtle interactions that influence protein folding, structure, and catalytic mechanism. Such methods are also being used increasingly as an adjunct to design, thus providing access to novel proteins with tailored catalytic activities and selectivities.

Precision is essential for efficient catalysis in an evolved Kemp eliminase

Linus Pauling established the conceptual framework for understanding and mimicking enzymes more than six decades ago. The notion that enzymes selectively stabilize the rate-limiting transition state of the catalysed reaction relative to the bound ground state reduces the problem of design to one of molecular recognition. Nevertheless, past attempts to capitalize on this idea, for example by using transition state analogues to elicit antibodies with catalytic activities, have generally failed to deliver true enzymatic rates. The advent of computational design approaches, combined with directed evolution, has provided an opportunity to revisit this problem. Starting from a computationally designed catalyst for the Kemp elimination—a well-studied model system for proton transfer from carbon—we show that an artificial enzyme can be evolved that accelerates an elementary chemical reaction 6 × 108-fold, approaching the exceptional efficiency of highly optimized natural enzymes such as triosephosphate isomerase. A 1.09 Å resolution crystal structure of the evolved enzyme indicates that familiar catalytic strategies such as shape complementarity and precisely placed catalytic groups can be successfully harnessed to afford such high rate accelerations, making us optimistic about the prospects of designing more sophisticated catalysts.

Evolution of a designed retro-aldolase leads to complete active site remodeling

Evolutionary advances are often fueled by unanticipated innovation. Directed evolution of a computationally designed enzyme suggests that dramatic molecular changes can also drive the optimization of primitive protein active sites. The specific activity of an artificial retro-aldolase was boosted >4,400 fold by random mutagenesis and screening, affording catalytic efficiencies approaching those of natural enzymes. However, structural and mechanistic studies reveal that the engineered catalytic apparatus, consisting of a reactive lysine and an ordered water molecule, was unexpectedly abandoned in favor of a new lysine residue in a substrate binding pocket created during the optimization process. Structures of the initial in silico design, a mechanistically promiscuous intermediate, and one of the most evolved variants highlight the importance of loop mobility and supporting functional groups in the emergence of the new catalytic center. Such internal competition between alternative reactive sites may have characterized the early evolution of many natural enzymes.

De novo enzymes by computational design

Computational enzyme design has emerged as a promising tool for generating made-to-order biocatalysts. In addition to improving the reliability of the design cycle, current efforts in this area are focusing on expanding the set of catalyzed reactions and investigating the structure and mechanism of individual designs. Although the activities of de novo enzymes are typically low, they can be significantly increased by directed evolution. Analysis of their evolutionary trajectories provides valuable feedback for the design algorithms and can enhance our understanding of natural protein evolution.

Biocatalysts by evolution

Proteins evolve by iterative cycles of mutation, selection and amplification. Analogous evolutionary strategies are being profitably exploited in the laboratory to generate and optimize biocatalysts for diverse biotechnological applications. In this review, we summarize recent efforts to improve this process by creating more effective protein libraries and more efficient screening/selection schemes. Targeted mutagenesis using simplified amino acid alphabets, statistical analyses of sequence-function-stability relationships, and neutral mutational drift have emerged as powerful tools for generating useful molecular diversity, while new techniques for controlling selection stringency and microfluidic methods for screening large populations of molecules promise to facilitate exploration of sequence space. Enzyme engineers interested in creating novel biocatalysts for abiological reactions are sure to profit from these advances.