Quantum chemistry as a tool in asymmetric biocatalysis: limonene epoxide hydrolase test case

Eliminating Imaginary Vibrational Frequencies in Quantum-Chemical Cluster Models of Enzymatic Active Sites

In constructing finite models of enzyme active sites for quantum-chemical calculations, atoms at the periphery of the model must be constrained to prevent unphysical rearrangements during geometry relaxation. A simple fixed-atom or "coordinate-lock" approach is commonly employed but leads to undesirable artifacts in the form of small imaginary frequencies. These preclude evaluation of finite-temperature free-energy corrections, limiting thermochemical calculations to enthalpies only. Full-dimensional vibrational frequency calculations are possible by replacing the fixed-atom constraints with harmonic confining potentials. Here, we compare that approach to an alternative strategy in which fixed-atom contributions to the Hessian are simply omitted. While the latter strategy does eliminate imaginary frequencies, it tends to underestimate both the zero-point energy and the vibrational entropy while introducing artificial rigidity. Harmonic confining potentials eliminate imaginary frequencies and provide a flexible means to construct active-site models that can be used in unconstrained geometry relaxations, affording better convergence of reaction energies and barrier heights with respect to the model size, as compared to models with fixed-atom constraints.

Biocatalytic strategy for the construction of sp3-rich polycyclic compounds from directed evolution and computational modelling

Catalysis with engineered enzymes has provided more efficient routes for the production of active pharmaceutical agents. However, the potential of biocatalysis to assist in early-stage drug discovery campaigns remains largely untapped. In this study, we have developed a biocatalytic strategy for the construction of sp3-rich polycyclic compounds via the intramolecular cyclopropanation of benzothiophenes and related heterocycles. Two carbene transferases with complementary regioisomer selectivity were evolved to catalyse the stereoselective cyclization of benzothiophene substrates bearing diazo ester groups at the C2 or C3 position of the heterocycle. The detailed mechanisms of these reactions were elucidated by a combination of crystallographic and computational analyses. Leveraging these insights, the substrate scope of one of the biocatalysts could be expanded to include previously unreactive substrates, highlighting the value of integrating evolutionary and rational strategies to develop enzymes for new-to-nature transformations. The molecular scaffolds accessed here feature a combination of three-dimensional and stereochemical complexity with 'rule-of-three' properties, which should make them highly valuable for fragment-based drug discovery campaigns.

The Quantum Chemical Cluster Approach in Biocatalysis

ConspectusThe quantum chemical cluster approach has been used for modeling enzyme active sites and reaction mechanisms for more than two decades. In this methodology, a relatively small part of the enzyme around the active site is selected as a model, and quantum chemical methods, typically density functional theory, are used to calculate energies and other properties. The surrounding enzyme is modeled using implicit solvation and atom fixing techniques. Over the years, a large number of enzyme mechanisms have been solved using this method. The models have gradually become larger as a result of the faster computers, and new kinds of questions have been addressed. In this Account, we review how the cluster approach can be utilized in the field of biocatalysis. Examples from our recent work are chosen to illustrate various aspects of the methodology. The use of the cluster model to explore substrate binding is discussed first. It is emphasized that a comprehensive search is necessary in order to identify the lowest-energy binding mode(s). It is also argued that the best binding mode might not be the productive one, and the full reactions for a number of enzyme-substrate complexes have therefore to be considered to find the lowest-energy reaction pathway. Next, examples are given of how the cluster approach can help in the elucidation of detailed reaction mechanisms of biocatalytically interesting enzymes, and how this knowledge can be exploited to develop enzymes with new functions or to understand the reasons for lack of activity toward non-natural substrates. The enzymes discussed in this context are phenolic acid decarboxylase and metal-dependent decarboxylases from the amidohydrolase superfamily. Next, the application of the cluster approach in the investigation of enzymatic enantioselectivity is discussed. The reaction of strictosidine synthase is selected as a case study, where the cluster calculations could reproduce and rationalize the selectivities of both the natural and non-natural substrates. Finally, we discuss how the cluster approach can be used to guide the rational design of enzyme variants with improved activity and selectivity. Acyl transferase from Mycobacterium smegmatis serves as an instructive example here, for which the calculations could pinpoint the factors controlling the reaction specificity and enantioselectivity. The cases discussed in this Account highlight thus the value of the cluster approach as a tool in biocatalysis. It complements experiments and other computational techniques in this field and provides insights that can be used to understand existing enzymes and to develop new variants with tailored properties.

A computational study of the reaction mechanism and stereospecificity of dihydropyrimidinase

Dihydropyrimidinase (DHPase) is a key enzyme in the pyrimidine pathway, the catabolic route for synthesis of β-amino acids. It catalyses the reversible conversion of 5,6-dihydrouracil (DHU) or 5,6-dihydrothymine (DHT) to the corresponding N-carbamoyl-β-amino acids. This enzyme has the potential to be used as a tool in the production of β-amino acids. Here, the reaction mechanism and origin of stereospecificity of DHPases from Saccharomyces kluyveri and Sinorhizobium meliloti CECT4114 were investigated and compared using a quantum mechanical cluster approach based on density functional theory. Two models of the enzyme active site were designed from the X-ray crystal structure of the native enzyme: a small cluster to characterize the mechanism and the stationary points and a large model to probe the stereospecificity and the role of stereo-gate-loop (SGL) residues. It is shown that a hydroxide ion first performs a nucleophilic attack on the substrate, followed by the abstraction of a proton by Asp358, which occurs concertedly with protonation of the ring nitrogen by the same residue. For the DHT substrate, the enzyme displays a preference for the L-configuration, in good agreement with experimental observation. Comparison of the reaction energetics of the two models reveals the importance of SGL residues in the stereospecificity of catalysis. The role of the conserved Tyr172 residue in transition-state stabilization is confirmed as the Tyr172Phe mutation increases the activation barrier of the reaction by ∼8 kcal mol^-1. A detailed understanding of the catalytic mechanism of the enzyme could offer insight for engineering in order to enhance its activity and substrate scope.

Rational enzyme design for enabling biocatalytic Baldwin cyclization and asymmetric synthesis of chiral heterocycles

Chiral heterocyclic compounds are needed for important medicinal applications. We report an in silico strategy for the biocatalytic synthesis of chiral N- and O-heterocycles via Baldwin cyclization modes of hydroxy- and amino-substituted epoxides and oxetanes using the limonene epoxide hydrolase from Rhodococcus erythropolis. This enzyme normally catalyzes hydrolysis with formation of vicinal diols. Firstly, the required shutdown of the undesired natural water-mediated ring-opening is achieved by rational mutagenesis of the active site. In silico enzyme design is then continued with generation of the improved mutants. These variants prove to be versatile catalysts for preparing chiral N- and O-heterocycles with up to 99% conversion, and enantiomeric ratios up to 99:1. Crystal structural data and computational modeling reveal that Baldwin-type cyclizations, catalyzed by the reprogrammed enzyme, are enabled by reshaping the active-site environment that directs the distal RHN and HO-substituents to be intramolecular nucleophiles.

Unraveling the mechanism of enantio-controlling switches of an alcohol dehydrogenase toward sterically small ketone

Efficient synthesis of chiral compounds under mild conditions is highly desirable in the chemical and pharmaceutical communities, but it often faces difficulties. Although various enzymes have been harnessed as biocatalysts...

Computational Study of Mechanism and Enantioselectivity of Imine Reductase from Amycolatopsis orientalis

Imine reductases (IREDs) are NADPH-dependent enzymes (NADPH=nicotinamide adenine dinucleotide phosphate) that catalyze the reduction of imines to amines. They exhibit high enantioselectivity for a broad range of substrates, making them of interest for biocatalytic applications. In this work, we have employed density functional theory (DFT) calculations to elucidate the reaction mechanism and the origins of enantioselectivity of IRED from Amycolatopsis orientalis. Two substrates are considered, namely 1-methyl-3,4-dihydroisoquinoline and 2-propyl-piperideine. A model of the active site is built on the basis of the available crystal structure. For both substrates, different binding modes are first evaluated, followed by calculation of the hydride transfer transition states from each complex. We have also investigated the effect of mutations of certain important active site residues (Tyr179Ala and Asn241Ala) on the enantioselectivity. The calculated energies are consistent with the experimental observations and the analysis of transition states geometries provides insights into the origins of enantioselectivity of this enzyme.

Computer-aided understanding and engineering of enzymatic selectivity

Enzymes offering chemo-, regio-, and stereoselectivity enable the asymmetric synthesis of high-value chiral molecules. Unfortunately, the drawback that naturally occurring enzymes are often inefficient or have undesired selectivity toward non-native substrates hinders the broadening of biocatalytic applications. To match the demands of specific selectivity in asymmetric synthesis, biochemists have implemented various computer-aided strategies in understanding and engineering enzymatic selectivity, diversifying the available repository of artificial enzymes. Here, given that the entire asymmetric catalytic cycle, involving precise interactions within the active pocket and substrate transport in the enzyme channel, could affect the enzymatic efficiency and selectivity, we presented a comprehensive overview of the computer-aided workflow for enzymatic selectivity. This review includes a mechanistic understanding of enzymatic selectivity based on quantum mechanical calculations, rational design of enzymatic selectivity guided by enzyme-substrate interactions, and enzymatic selectivity regulation via enzyme channel engineering. Finally, we discussed the computational paradigm for designing enzyme selectivity in silico to facilitate the advancement of asymmetric biosynthesis.

Machine Learning Enables Selection of Epistatic Enzyme Mutants for Stability Against Unfolding and Detrimental Aggregation

Machine learning (ML) has pervaded most areas of protein engineering, including stability and stereoselectivity. Using limonene epoxide hydrolase as the model enzyme and innov'SAR as the ML platform, comprising a digital signal process, we achieved high protein robustness that can resist unfolding with concomitant detrimental aggregation. Fourier transform (FT) allows us to take into account the order of the protein sequence and the nonlinear interactions between positions, and thus to grasp epistatic phenomena. The innov'SAR approach is interpolative, extrapolative and makes outside-the-box, predictions not found in other state-of-the-art ML or deep learning approaches. Equally significant is the finding that our approach to ML in the present context, flanked by advanced molecular dynamics simulations, uncovers the connection between epistatic mutational interactions and protein robustness.

The role of the halogen bond in iodothyronine deiodinase: Dependence on chalcogen substitution in naphthyl-based mimetics

The effects on the activity of thyroxine (T4) due to the chalcogen replacement in a series of peri-substituted naphthalenes mimicking the catalytic function of deiodinase enzymes are computationally examined using density functional theory. In particular, T4 inner-ring deiodination pathways assisted by naphthyl-based models bearing two tellurols and a tellurol-thiol pair in peri-position are explored and compared with the analogous energy profiles for the naphthalene mimic having two selenols. The presence of a halogen bond (XB) in the intermediate formed in the first step and involved in the rate-determining step of the reaction is assumed to facilitate the process increasing the rate of the reaction. The rate-determining step calculated energy barrier heights allow rationalizing the experimentally observed superior catalytic activity of tellurium containing mimics. Charge displacement analysis is used to ascertain the presence and the role of the electron density charge transfer occurring in the rate-determining step of the reaction, suggesting the incipient formation or presence of a XB interaction. © 2019 Wiley Periodicals, Inc.

Computational Design of Enantiocomplementary Epoxide Hydrolases for Asymmetric Synthesis of Aliphatic and Aromatic Diols

The use of enzymes in preparative biocatalysis often requires tailoring enzyme selectivity by protein engineering. Herein we explore the use of computational library design and molecular dynamics simulations to create variants of limonene epoxide hydrolase that produce enantiomeric diols from meso‐epoxides. Three substrates of different sizes were targeted: cis‐2,3‐butene oxide, cyclopentene oxide, and cis‐stilbene oxide. Most of the 28 designs tested were active and showed the predicted enantioselectivity. Excellent enantioselectivities were obtained for the bulky substrate cis‐stilbene oxide, and enantiocomplementary mutants produced (S,S)‐ and (R,R)‐stilbene diol with >97 % enantiomeric excess. An (R,R)‐selective mutant was used to prepare (R,R)‐stilbene diol with high enantiopurity (98 % conversion into diol, >99 % ee). Some variants displayed higher catalytic rates (k_cat) than the original enzyme, but in most cases K_M values increased as well. The results demonstrate the feasibility of computational design and screening to engineer enantioselective epoxide hydrolase variants with very limited laboratory screening.

Computational Understanding of the Selectivities in Metalloenzymes

Metalloenzymes catalyze many different types of biological reactions with high efficiency and remarkable selectivity. The quantum chemical cluster approach and the combined quantum mechanics/molecular mechanics methods have proven very successful in the elucidation of the reaction mechanism and rationalization of selectivities in enzymes. In this review, recent progress in the computational understanding of various selectivities including chemoselectivity, regioselectivity, and stereoselectivity, in metalloenzymes, is discussed.

Quantum chemical study of mechanism and stereoselectivity of secondary alcohol dehydrogenase

Secondary alcohol dehydrogenase from Thermoanaerobacter brockii (TbSADH) is a Zn- and NADP-dependent enzyme that catalyses the reversible transformation of secondary alcohols into ketones. It is of potential biocatalytic interest as it can be used in the synthesis of chiral alcohols by asymmetric reduction of ketones. In this paper, density functional theory calculations are employed to elucidate the origins of the enantioselectivity of TbSADH using a large model of the active site and considering two different substrates, 2-butanol and 3-hexanol. For these two substrates the enzyme has experimentally been shown to have the opposite enantioselectivity. The energy profiles for the reactions are calculated and the stationary points along the reaction path are characterised. The calculations first confirm that the general mechanism proposed for other alcohol dehydrogenases is energetically viable. In this mechanism, a proton is first transferred from the substrate to a histidine residue at the surface, followed by a hydride transfer to the NADP cofactor. The calculated overall energy barrier is consistent with the measured rate constant. Very importantly, the calculations are able to reproduce and rationalise the enantioselectivity of the enzyme for both substrates. The detailed characterisation of the energies and geometries of the involved transition states will be valuable in the rational engineering of TbSADH to expand its utility in biocatalysis.

Recent Trends in Quantum Chemical Modeling of Enzymatic Reactions

The quantum chemical cluster approach is a powerful method for investigating enzymatic reactions. Over the past two decades, a large number of highly diverse systems have been studied and a great wealth of mechanistic insight has been developed using this technique. This Perspective reviews the current status of the methodology. The latest technical developments are highlighted, and challenges are discussed. Some recent applications are presented to illustrate the capabilities and progress of this approach, and likely future directions are outlined.

CADEE: Computer-Aided Directed Evolution of Enzymes

The tremendous interest in enzymes as biocatalysts has led to extensive work in enzyme engineering, as well as associated methodology development. Here, a new framework for computer-aided directed evolution of enzymes (CADEE) is presented which allows a drastic reduction in the time necessary to prepare and analyze in silico semi-automated directed evolution of enzymes. A pedagogical example of the application of CADEE to a real biological system is also presented in order to illustrate the CADEE workflow.

Computational tools for the evaluation of laboratory-engineered biocatalysts

Biocatalysis is based on the application of natural catalysts for new purposes, for which enzymes were not designed. Although the first examples of biocatalysis were reported more than a century ago, biocatalysis was revolutionized after the discovery of an in vitro version of Darwinian evolution called Directed Evolution (DE). Despite the recent advances in the field, major challenges remain to be addressed. Currently, the best experimental approach consists of creating multiple mutations simultaneously while limiting the choices using statistical methods. Still, tens of thousands of variants need to be tested experimentally, and little information is available on how these mutations lead to enhanced enzyme proficiency. This review aims to provide a brief description of the available computational techniques to unveil the molecular basis of improved catalysis achieved by DE. An overview of the strengths and weaknesses of current computational strategies is explored with some recent representative examples. The understanding of how this powerful technique is able to obtain highly active variants is important for the future development of more robust computational methods to predict amino-acid changes needed for activity.

Conformational diversity and enantioconvergence in potato epoxide hydrolase 1

Potato epoxide hydrolase 1 (StEH1) is a biocatalytically important enzyme that exhibits rich enantio- and regioselectivity in the hydrolysis of chiral epoxide substrates. In particular, StEH1 has been demonstrated to enantioconvergently hydrolyze racemic mixes of styrene oxide (SO) to yield (R)-1-phenylethanediol. This work combines computational, crystallographic and biochemical analyses to understand both the origins of the enantioconvergent behavior of the wild-type enzyme, as well as shifts in activities and substrate binding preferences in an engineered StEH1 variant, R-C1B1, which contains four active site substitutions (W106L, L109Y, V141K and I155V). Our calculations are able to reproduce both the enantio- and regioselectivities of StEH1, and demonstrate a clear link between different substrate binding modes and the corresponding selectivity, with the preferred binding modes being shifted between the wild-type enzyme and the R-C1B1 variant. Additionally, we demonstrate that the observed changes in selectivity and the corresponding enantioconvergent behavior are due to a combination of steric and electrostatic effects that modulate both the accessibility of the different carbon atoms to the nucleophilic side chain of D105, as well as the interactions between the substrate and protein amino acid side chains and active site water molecules. Being able to computationally predict such subtle effects for different substrate enantiomers, as well as to understand their origin and how they are affected by mutations, is an important advance towards the computational design of improved biocatalysts for enantioselective synthesis.

Learning lessons from directed evolution of stereoselective enzymes

With the advent of directed evolution of stereoselective enzymes almost 20 years ago and the rapid development of this exciting area of research, the traditional limitations of biocatalysts in organic chemistry have been eliminated.

Expanding the Catalytic Triad in Epoxide Hydrolases and Related Enzymes

Potato epoxide hydrolase 1 exhibits rich enantio- and regioselectivity in the hydrolysis of a broad range of substrates. The enzyme can be engineered to increase the yield of optically pure products as a result of changes in both enantio- and regioselectivity. It is thus highly attractive in biocatalysis, particularly for the generation of enantiopure fine chemicals and pharmaceuticals. The present work aims to establish the principles underlying the activity and selectivity of the enzyme through a combined computational, structural, and kinetic study using the substrate trans-stilbene oxide as a model system. Extensive empirical valence bond simulations have been performed on the wild-type enzyme together with several experimentally characterized mutants. We are able to computationally reproduce the differences between the activities of different stereoisomers of the substrate and the effects of mutations of several active-site residues. In addition, our results indicate the involvement of a previously neglected residue, H104, which is electrostatically linked to the general base H300. We find that this residue, which is highly conserved in epoxide hydrolases and related hydrolytic enzymes, needs to be in its protonated form in order to provide charge balance in an otherwise negatively charged active site. Our data show that unless the active-site charge balance is correctly treated in simulations, it is not possible to generate a physically meaningful model for the enzyme that can accurately reproduce activity and selectivity trends. We also expand our understanding of other catalytic residues, demonstrating in particular the role of a noncanonical residue, E35, as a "backup base" in the absence of H300. Our results provide a detailed view of the main factors driving catalysis and regioselectivity in this enzyme and identify targets for subsequent enzyme design efforts.

Enantioselective enzymes by computational design and in silico screening

Computational enzyme design holds great promise for providing new biocatalysts for synthetic chemistry. A strategy to design small mutant libraries of complementary enantioselective epoxide hydrolase variants for the production of highly enantioenriched (S,S)-diols and (R,R)-diols is developed. Key features of this strategy (CASCO, catalytic selectivity by computational design) are the design of mutations that favor binding of the substrate in a predefined orientation, the introduction of steric hindrance to prevent unwanted substrate binding modes, and ranking of designs by high-throughput molecular dynamics simulations. Using this strategy we obtained highly stereoselective mutants of limonene epoxide hydrolase after experimental screening of only 37 variants. The results indicate that computational methods can replace a substantial amount of laboratory work when developing enantioselective enzymes.

Unravelling novel synergies between organometallic and biological partners: a quantum mechanics/molecular mechanics study of an artificial metalloenzyme

In recent years, the design of artificial metalloenzymes obtained by the insertion of homogeneous catalysts into biological macromolecules has become a major field of research. These hybrids, and the corresponding X-ray structures of several of them, are offering opportunities to better understand the synergy between organometallic and biological subsystems. In this work, we investigate the resting state and activation process of a hybrid inspired by an oxidative haemoenzyme but presenting an unexpected reactivity and structural features. An extensive series of quantum mechanics/molecular mechanics calculations show that the resting state and the activation processes of the novel enzyme differ from naturally occurring haemoenzymes in terms of the electronic state of the metal, participation of the first coordination sphere of the metal and the dynamic process. This study presents novel insights into the sensitivity of the association between organometallic and biological partners and illustrates the molecular challenge that represents the design of efficient enzymes based on this strategy.

Computationally efficient and accurate enantioselectivity modeling by clusters of molecular dynamics simulations

Computational approaches could decrease the need for the laborious high-throughput experimental screening that is often required to improve enzymes by mutagenesis. Here, we report that using multiple short molecular dynamics (MD) simulations makes it possible to accurately model enantioselectivity for large numbers of enzyme-substrate combinations at low computational costs. We chose four different haloalkane dehalogenases as model systems because of the availability of a large set of experimental data on the enantioselective conversion of 45 different substrates. To model the enantioselectivity, we quantified the frequency of occurrence of catalytically productive conformations (near attack conformations) for pairs of enantiomers during MD simulations. We found that the angle of nucleophilic attack that leads to carbon-halogen bond cleavage was a critical variable that limited the occurrence of productive conformations; enantiomers for which this angle reached values close to 180° were preferentially converted. A cluster of 20-40 very short (10 ps) MD simulations allowed adequate conformational sampling and resulted in much better agreement to experimental enantioselectivities than single long MD simulations (22 ns), while the computational costs were 50-100 fold lower. With single long MD simulations, the dynamics of enzyme-substrate complexes remained confined to a conformational subspace that rarely changed significantly, whereas with multiple short MD simulations a larger diversity of conformations of enzyme-substrate complexes was observed.

Theoretical study of the catalytic mechanism of E1 subunit of pyruvate dehydrogenase multienzyme complex from Bacillus stearothermophilus

Pyruvate dehydrogenase multienzyme complex (PDHc) is a member of a family of 2-oxo acid dehydrogenase (OADH) multienzyme complexes involved in several central points of oxidative metabolism, and the E1 subunit is the most important component in the entire PDHc catalytic system, which catalyzes the reversible transfer of an acetyl group from a pyruvate to the lipoyl group of E2 subunit lipoly domain. In this article, the catalytic mechanism of the E1 subunit has been systematically studied using density functional theory (DFT). Four possible pathways with different general acid/base catalysts in decarboxylation and reductive acylation processes were explored. Our calculation results indicate that the 4'-amino pyrimidine of ThDP and residue His128 are the most likely proton donors in the decarboxylation and reductive acylation processes, respectively. During the reaction, each C-C and C-S bond formation or cleavage process, except for the liberation of CO2, is always accompanied by a proton transfer between the substrates and proton donors. The liberation of CO2 is calculated to be the rate-limiting step for the overall reaction, with an energy barrier of 13.57 kcal/mol. The decarboxylation process is endothermic by 5.32 kcal/mol, whereas the reductive acylation process is exothermic with a value of 5.74 kcal/mol. The assignment of protonation states of the surrounding residues can greatly influence the reaction. Residues His128 and His271 play roles in positioning the first substrate pyruvate and second substrate lipoyl group, respectively.