Kemp Eliminase Research Articles

Directed Evolution as a Probe of Rate Promoting Vibrations Introduced via Mutational Change.

In this article, we study with transition path sampling and reaction coordinate analysis how directed evolution in the Kemp eliminase family of artificial enzymes makes differential use of rapid rate promoting vibrations as a component of their chemical mechanism. Even though this family was initially created by placing the expected active site in a fixed protein matrix, we find a shift from largely static to more dynamic active sites that make use of donor-acceptor compression as the evolutionary process proceeds. We see that this introduction of dynamics significantly shifts the order of processes in the reaction. We also suggest that the lack of "design for dynamics" may help explain the relatively low proficiency of such designed enzymes.

Computational Optimization of Electric Fields for Improving Catalysis of a Designed Kemp Eliminase

Here we report a computational method to improve efficiency of a de novo designed Kemp eliminase enzyme KE15, by identifying mutations that enhance electric fields and chemical positioning of the substrate that contribute to free energy stabilization of the transition state. Starting from the design that has a kcat/KM of 27 M–1 s–1, the most improved variant introduced four computationally targeted mutations to yield a kcat/KM of 403 M–1 s–1, with almost all of the enzyme improvement realized through a 43-fold improvement in kcat, indicative of a direct impact on the chemical step. This work raises the prospect of computationally designing enzymes that achieve better efficiency with more minimal experimental intervention using electric field optimization as guidance.

Revealing the Origin of the Efficiency of the De Novo Designed Kemp Eliminase HG-3.17 by Comparison with the Former Developed HG-3.

The design of new biocatalysts is a goal in biotechnology to improve the rate, selectivity and environmental impact of industrial chemical processes. In this regard, the use of computational techniques has provided valuable assistance in the design of new enzymes with remarkable catalytic activity. In this paper, hybrid QM/MM molecular dynamics simulations have allowed insights to be gained on the origin of the limited efficiency of a computationally designed enzyme for the Kemp elimination; the HG-3. Comparison of results derived from this enzyme with those of a more evolved protein containing additional point mutations, HG-3.17, rendered important information that should be taken into account in the design of new enzymes. For this Kemp eliminase reaction, higher reactivity has been demonstrated to be related to a better electrostatic preorganisation of an environment that creates a more favourable electrostatic potential for the reaction to proceed. The limitations of HG-3 can be related to a lack of flexibility, a not well-fitted active site, and a lack of protein electrostatic preorganisation, which decrease the reorganisation around the oxyanion hole.

The Importance of the Scaffold for de Novo Enzymes: A Case Study with Kemp Eliminase.

We report electric field values relevant to the reactant and transition states of designed Kemp eliminases KE07 and KE70 and their improved variants from laboratory directed evolution (LDE), using atomistic simulations with the AMOEBA polarizable force field. We find that the catalytic base residue contributes the most to the electric field stabilization of the transition state of the LDE variants of the KE07 and KE70 enzymes, whereas the electric fields of the remainder of the enzyme and solvent disfavor the catalytic reaction in both cases. By contrast, we show that the electrostatic environment plays a large and stabilizing role for the naturally occurring enzyme ketosteroid isomerase (KSI). These results suggest that LDE is ultimately a limited strategy for improving de novo enzymes since it is largely restricted to optimization of chemical positioning in the active site, thus yielding a ∼3 order magnitude improvement over the uncatalyzed reaction, which we suggest may be an absolute upper bound estimate based on LDE applied to comparable de novo Kemp eliminases and other enzymes like KSI. Instead de novo enzymatic reactions could more productively benefit from optimization of the electrostatics of the protein scaffold in early stages of the computational design, utilizing electric field optimization as guidance.

A redox-mediated Kemp eliminase

The acid/base-catalysed Kemp elimination of 5-nitro-benzisoxazole forming 2-cyano-4-nitrophenol has long served as a design platform of enzymes with non-natural reactions, providing new mechanistic insights in protein science. Here we describe an alternative concept based on redox catalysis by P450-BM3, leading to the same Kemp product via a fundamentally different mechanism. QM/MM computations show that it involves coordination of the substrate’s N-atom to haem-Fe(II) with electron transfer and concomitant N–O heterolysis liberating an intermediate having a nitrogen radical moiety Fe(III)–N· and a phenoxyl anion. Product formation occurs by bond rotation and H-transfer. Two rationally chosen point mutations cause a notable increase in activity. The results shed light on the prevailing mechanistic uncertainties in human P450-catalysed metabolism of the immunomodulatory drug leflunomide, which likewise undergoes redox-mediated Kemp elimination by P450-BM3. Other isoxazole-based pharmaceuticals are probably also metabolized by a redox mechanism. Our work provides a basis for designing future artificial enzymes.

Kemp Elimination Catalyzed by Naturally Occurring Aldoxime Dehydratases.

Recently, the Kemp elimination reaction has been extensively studied in computational enzyme design of new catalysts, as no natural enzyme has evolved to catalyze this reaction. In contrast to in silico enzyme design, we were interested in searching for Kemp eliminase activity in natural enzymes with catalytic promiscuity. Based on similarities of substrate structures and reaction mechanisms, we assumed that the active sites of naturally abundant aldoxime dehydratases have the potential to catalyze the non-natural Kemp elimination reaction. We found several aldoxime dehydratases that are efficient catalysts of this reaction. Although a few natural enzymes have been identified with promiscuous Kemp eliminase activity, to the best of our knowledge, this is a rare example of Kemp elimination catalyzed by naturally occurring enzymes with high catalytic efficiency.

The role of side chain entropy and mutual information for improving the de novo design of Kemp eliminases KE07 and KE70.

Side chain entropy and mutual entropy information between residue pairs have been calculated for two de novo designed Kemp eliminase enzymes, KE07 and KE70, and for their most improved versions at the end of laboratory directed evolution (LDE). We find that entropy, not just enthalpy, helped to destabilize the preference for the reactant state complex of the designed enzyme as well as favoring stabilization of the transition state complex for the best LDE enzymes. Furthermore, residues with the highest side chain couplings as measured by mutual information, when experimentally mutated, were found to diminish or annihilate catalytic activity, some of which were far from the active site. In summary, our findings demonstrate how side chain fluctuations and their coupling can be an important design feature for de novo enzymes, and furthermore could be utilized in the computational steps in lieu of or in addition to the LDE steps in future enzyme design projects.

Physics-based enzyme design: predicting binding affinity and catalytic activity.

Computational enzyme design is an emerging field that has yielded promising success stories, but where numerous challenges remain. Accurate methods to rapidly evaluate possible enzyme design variants could provide significant value when combined with experimental efforts by reducing the number of variants needed to be synthesized and speeding the time to reach the desired endpoint of the design. To that end, extending our computational methods to model the fundamental physical-chemical principles that regulate activity in a protocol that is automated and accessible to a broad population of enzyme design researchers is essential. Here, we apply a physics-based implicit solvent MM-GBSA scoring approach to enzyme design and benchmark the computational predictions against experimentally determined activities. Specifically, we evaluate the ability of MM-GBSA to predict changes in affinity for a steroid binder protein, catalytic turnover for a Kemp eliminase, and catalytic activity for α-Gliadin peptidase variants. Using the enzyme design framework developed here, we accurately rank the most experimentally active enzyme variants, suggesting that this approach could provide enrichment of active variants in real-world enzyme design applications.

Side Chain Entropy in Enzymes and its Role in Catalysis

Directed Evolution is a popular biochemical engineering technique used to improve, and in some cases alter the activity of enzymes. Although many empirical strategies have been developed to carry out directed evolution, it is still an opaque process that could benefit from more rational design. In this work, we try to rationalize directed evolution based on the physical principles of thermodynamics. Our model system is the Kemp Eliminase KE07, which was designed computationally to catalyze the conversion of 5-nitrobenzisoxazole to cyanophenol, but showed poor activity in solution (kcat/KM ∼12 M-1s-1). Seven rounds of directed evolution lead to a 2 order of magnitude improvement in kcat/KM but structural analysis could not explain why many of the mutations were made. Using a sequential Monte Carlo technique we have been able to calculate and identify systematic changes in the side chain entropy through the 7 rounds of directed evolution. Our technique uses a realistic energy function coupled with a rotamer library to estimate the important rotameric states. These results suggest that the functional partitioning of structure (enthalpy) and statistical fluctuations (entropy) that occurs at the side chain level could give us important leads to predict further mutations. This work also provides further evidence to start looking beyond the traditional structure-function paradigm and incorporate entropic contributions for designing/improving enzymes.

Protein Engineering from “Scratch” Is Maturing

Precisely tuning the active site by protein engineering has led to the development of a highly efficient Kemp eliminase (see structure with substrate in the binding pocket). The starting protein scaffold with only low activity originated from computational design, as no natural enzyme with this activity was known. This is a breakthrough in protein design, as novel catalytic activities are now in reach that match those of natural enzymes.

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.

Reprogramming EF-hands for design of catalytically amplified lanthanide sensors

We recently reported that a computationally designed catalyst nicknamed AlleyCat facilitates C-H proton abstraction in Kemp elimination at neutral pH in a selective and calcium-dependent fashion by a factor of approximately 100,000 (Korendovych et al. in Proc. Natl. Acad. Sci. USA 108:6823, 2011). Kemp elimination produced a colored product that can be easily read out, thus making AlleyCat a catalytically amplified metal sensor for calcium. Here we report that metal-binding EF-hand motifs in AlleyCat could be redesigned to incorporate trivalent metal ions without significant loss of catalytic activity. Mutation of a single neutral residue at position9 of each of the EF-hands to glutamate results in almost a two orders of magnitude improvement of selectivity for trivalent metal ions over calcium. Development of this new lanthanide-dependent switchable Kemp eliminase, named CuSeCat EE, provides the foundation for further selectivity improvement and broadening the scope of the repertoire of metals for sensing. A concerted effort in the design of switchable enzymes has many environmental, sensing, and metal ion tracking applications.

Optimization of reorganization energy drives evolution of the designed Kemp eliminase KE07

Understanding enzymatic evolution is essential to engineer enzymes with improved activities or to generate enzymes with tailor-made activities. The computationally designed Kemp eliminase KE07 carries out an unnatural reaction by converting of 5-nitrobenzisoxazole to cyanophenol, but its catalytic efficiency is significantly lower than those of natural enzymes. Three series of designed Kemp eliminases (KE07, KE70, KE59) were shown to be evolvable with considerable improvement in catalytic efficiency. Here we use the KE07 enzyme as a model system to reveal those forces, which govern enzymatic evolution and elucidate the key factors for improving activity. We applied the Empirical Valence Bond (EVB) method to construct the free energy pathway of the reaction in the original KE07 design and the evolved R7 1/3H variant. We analyzed catalytic effect of residues and demonstrated that not all mutations in evolution are favorable for activity. In contrast to the small decrease in the activation barrier, in vitro evolution significantly reduced the reorganization energy. We developed an algorithm to evaluate group contributions to the reorganization energy and used this approach to screen for KE07 variants with potential for improvement. We aimed to identify those mutations that facilitate enzymatic evolution, but might not directly increase catalytic efficiency. Computational results in accord with experimental data show that all mutations, which appear during in vitro evolution were either neutral or favorable for the reorganization energy. These results underscore that distant mutations can also play role in optimizing efficiency via their contribution to the reorganization energy. Exploiting this principle could be a promising strategy for computer-aided enzyme design. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Engineering a model protein cavity to catalyze the Kemp elimination

Synthetic cavitands and protein cavities have been widely studied as models for ligand recognition. Here we investigate the Met102→His substitution in the artificial L99A cavity in T4 lysozyme as a Kemp eliminase. The resulting enzyme had k(cat)/K(M)=0.43M(-1)s(-1) and a (k(cat)/K(M))/k(uncat)=10(7) at pH5.0. The crystal structure of this enzyme was determined at 1.30Å, as were the structures of four complexes of substrate and product analogs. The absence of ordered waters or hydrogen bonding interactions, and the presence of a common catalytic base (His102) in an otherwise hydrophobic, buried cavity, facilitated detailed analysis of the reaction mechanism and its optimization. Subsequent substitutions increased eliminase activity by an additional four-fold. As activity-enhancing substitutions were engineered into the cavity, protein stability decreased, consistent with the stability-function trade-off hypothesis. This and related model cavities may provide templates for studying protein design principles in radically simplified environments.

Comparison of designed and randomly generated catalysts for simple chemical reactions.

There has been recent success in designing enzymes for simple chemical reactions using a two-step protocol. In the first step, a geometric matching algorithm is used to identify naturally occurring protein scaffolds at which predefined idealized active sites can be realized. In the second step, the residues surrounding the transition state model are optimized to increase transition state binding affinity and to bolster the primary catalytic side chains. To improve the design methodology, we investigated how the set of solutions identified by the design calculations relate to the overall set of solutions for two different chemical reactions. Using a TIM barrel scaffold in which catalytically active Kemp eliminase and retroaldolase designs were obtained previously, we carried out activity screens of random libraries made to be compositionally similar to active designs. A small number of active catalysts were found in screens of 10³ variants for each of the two reactions, which differ from the computational designs in that they reuse charged residues already present in the native scaffold. The results suggest that computational design considerably increases the frequency of catalyst generation for active sites involving newly introduced catalytic residues, highlighting the importance of interaction cooperativity in enzyme active sites.

Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59

Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of ≤ 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59's evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of ≤ 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.

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.

Challenges and Advances in Validating Enzyme Design Proposals: The Case of Kemp Eliminase Catalysis

One of the fundamental challenges in biotechnology and biochemistry is the ability to design effective enzymes. Despite recent progress, most of the advances on this front have been made by placing the reacting fragments in the proper places, rather than by optimizing the preorganization of the environment, which is the key factor in enzyme catalysis. Thus, rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work considers the catalytic effects in different Kemp eliminases as a benchmark for a computer-aided enzyme design. It is shown that the empirical valence bond provides a powerful screening tool, with significant advantages over current alternative strategies. The insights provided by the empirical valence bond calculations are discussed with an emphasis on the ability to analyze the difference between the linear free energy relationships obtained in solution and those found in the enzymes. We also point out the trade-off between the reliability and speed of the calculations and try to determine what it takes to realize reliable computer-aided screening.

Optimization of the In-Silico-Designed Kemp Eliminase KE70 by Computational Design and Directed Evolution

Although de novo computational enzyme design has been shown to be feasible, the field is still in its infancy: the kinetic parameters of designed enzymes are still orders of magnitude lower than those of naturally occurring ones. Nonetheless, designed enzymes can be improved by directed evolution, as recently exemplified for the designed Kemp eliminase KE07. Random mutagenesis and screening resulted in variants with > 200-fold higher catalytic efficiency and provided insights about features missing in the designed enzyme. Here we describe the optimization of KE70, another designed Kemp eliminase. Amino acid substitutions predicted to improve catalysis in design calculations involving extensive backbone sampling were individually tested. Those proven beneficial were combinatorially incorporated into the originally designed KE70 along with random mutations, and the resulting libraries were screened for improved eliminase activity. Nine rounds of mutation and selection resulted in > 400-fold improvement in the catalytic efficiency of the original KE70 design, reflected in both higher k cat values and lower K m values, with the best variants exhibiting k cat/ K m values of > 5 × 10 4 s − 1 M − 1 . The optimized KE70 variants were characterized structurally and biochemically, providing insights into the origins of the improvements in catalysis. Three primary contributions were identified: first, the reshaping of the active-site cavity to achieve tighter substrate binding; second, the fine-tuning of electrostatics around the catalytic His-Asp dyad; and, third, the stabilization of the active-site dyad in a conformation optimal for catalysis.

Exploring challenges in rational enzyme design by simulating the catalysis in artificial kemp eliminase

One of the fundamental challenges in biotechnology and in biochemistry is the ability to design effective enzymes. Doing so would be a convincing manifestation of a full understanding of the origin of enzyme catalysis. Despite an impressive progress, most of the advances on this front have been made by placing the reacting fragments in the proper places, rather than by optimizing the environment preorganization, which is the key factor in enzyme catalysis. Rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work takes previously designed kemp eliminases as a benchmark for a computer aided enzyme design, using the empirical valence bond as the main screening tool. The observed absolute catalytic effect and the effect of directed evolution are reproduced and analyzed (assuming that the substrate is in the designed site). It is found that, in the case of kemp eliminases, the transition state charge distribution makes it hard to exploit the active site polarity, even with the ability to quantify the effect of different mutations. Unexpectedly, it is found that the directed evolution mutants lead to the reduction of solvation of the reactant state by water molecules rather that to the more common mode of transition state stabilization used by naturally evolved enzymes. Finally it is pointed out that our difficulties in improving Kemp eliminase are not due to overlooking exotic effect, but to the challenge in designing a preorganized environment that would exploit the small change it charge distribution during the formation of the transition state.