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 × 10(8)-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.

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.

Computational design of catalytic dyads and oxyanion holes for ester hydrolysis.

Nucleophilic catalysis is a general strategy for accelerating ester and amide hydrolysis. In natural active sites, nucleophilic elements such as catalytic dyads and triads are usually paired with oxyanion holes for substrate activation, but it is difficult to parse out the independent contributions of these elements or to understand how they emerged in the course of evolution. Here we explore the minimal requirements for esterase activity by computationally designing artificial catalysts using catalytic dyads and oxyanion holes. We found much higher success rates using designed oxyanion holes formed by backbone NH groups rather than by side chains or bridging water molecules and obtained four active designs in different scaffolds by combining this motif with a Cys-His dyad. Following active site optimization, the most active of the variants exhibited a catalytic efficiency (k(cat)/K(M)) of 400 M(-1) s(-1) for the cleavage of a p-nitrophenyl ester. Kinetic experiments indicate that the active site cysteines are rapidly acylated as programmed by design, but the subsequent slow hydrolysis of the acyl-enzyme intermediate limits overall catalytic efficiency. Moreover, the Cys-His dyads are not properly formed in crystal structures of the designed enzymes. These results highlight the challenges that computational design must overcome to achieve high levels of activity.

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.

Design of a highly specific and noninvasive biosensor suitable for real-time in vivo imaging of mercury (II) uptake.

Mercury is a ubiquitous pollutant that when absorbed is extremely toxic to a wide variety of biochemical processes. Mercury (II) is a strong, "invisible" poison that is rapidly absorbed by tissues of the intestinal tract, kidneys, and liver upon ingestion. In this study, a novel fluorescence-based biosensor is presented that allows for the direct monitoring of the uptake and distribution of the metal under noninvasive in vivo conditions. With the introduction of a cysteine residue at position 205, located in close proximity to the chromophore, the green fluorescent protein (GFP) from Aequorea victoria was converted into a highly specific biosensor for this metal ion. The mutant protein exhibits a dramatic absorbance and fluorescence change upon mercuration at neutral pH. Absorbance and fluorescence properties with respect to the metal concentration exhibit sigmoidal binding behavior with a detection limit in the low nanomolar range. Time-resolved binding studies indicate rapid subsecond binding of the metal to the protein. The crystal structures obtained of mutant eGFP205C indicate a possible access route of the metal into the core of the protein. To our knowledge, this engineered protein is a first example of a biosensor that allows for noninvasive and real-time imaging of mercury uptake in a living cell. A major advantage is that its expression can be genetically controlled in many organisms to enable unprecedented studies of tissue specific mercury uptake.