Towards quantitative computer-aided studies of enzymatic enantioselectivity: the case of Candida antarctica lipase A

Enhancing the Catalytic Performance of Candida antarctica Lipase B by Chemical Modification With Alkylated Betaine Ionic Liquids

Various betaine ionic liquids composed of different chain lengths and different anions were designed and synthesized to modify Candida antarctica lipase B (CALB). The results showed that the catalytic activity of all modified lipases improved under different temperature and pH conditions, while also exhibiting enhanced thermostability and tolerance to organic solvents. With an increase in ionic liquid chain length, the modification effect was greater. Overall, CALB modified by [BetaineC₁₆][H₂PO₄] performed best, with the modified CALB enzyme activity increased 3-fold, thermal stability increased 1.5-fold when stored at 70°C for 30 min, with tolerance increased 2.9-fold in 50% DMSO and 2.3-fold in 30% mercaptoethanol. Fluorescence and circular dichroism (CD) spectroscopic analysis showed that the introduction of an ionic liquid caused changes in the microenvironment surrounding some fluorescent groups and the secondary structure of the CALB enzyme protein. In order to establish the enzyme activity and stability change mechanisms of the modified CALB, the structures of CALB modified with [BetaineC₄][Cl] and [BetaineC₁₆][Cl] were constructed, while the reaction mechanisms were studied by molecular dynamics simulations. Results showed that the root mean square deviation (RMSD) and total energy of modified CALB were less than those of native CALB, indicating that modified CALB has a more stable structure. Root mean square fluctuation (RMSF) calculations showed that the rigidity of modified CALB was enhanced. Solvent accessibility area (SASA) calculations exhibited that both the hydrophilicity and hydrophobicity of the modified enzyme-proteins were improved. The increase in radial distribution function (RDF) of water molecules confirmed that the number of water molecules around the active sites also increased. Therefore, modified CALB has enhanced structural stability and higher hydrolytic activity.

Microsecond timescale MD simulations at the transition state of PmHMGR predict remote allosteric residues

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to reach the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale. Application of this approach to the second hydride transfer transition state of HMG-CoA reductase from Pseudomonas mevalonii (PmHMGR) identified three remote residues, R396, E399 and L407, (15-27 Å away from the active site) that have a remote dynamic effect on enzyme activity. The predictions were subsequently validated experimentally via site-directed mutagenesis. These results show that microsecond timescale MD simulations of transition states are possible and can predict rather than just rationalize remote allosteric residues.

Ground-State Destabilization by Active-Site Hydrophobicity Controls the Selectivity of a Cofactor-Free Decarboxylase

Bacterial arylmalonate decarboxylase (AMDase) and evolved variants have become a valuable tool with which to access both enantiomers of a broad range of chiral arylaliphatic acids with high optical purity. Yet, the molecular principles responsible for the substrate scope, activity, and selectivity of this enzyme are only poorly understood to date, greatly hampering the predictability and design of improved enzyme variants for specific applications. In this work, empirical valence bond and metadynamics simulations were performed on wild-type AMDase and variants thereof to obtain a better understanding of the underlying molecular processes determining reaction outcome. Our results clearly reproduce the experimentally observed substrate scope and support a mechanism driven by ground-state destabilization of the carboxylate group being cleaved by the enzyme. In addition, our results indicate that, in the case of the nonconverted or poorly converted substrates studied in this work, increased solvent exposure of the active site upon binding of these substrates can disturb the vulnerable network of interactions responsible for facilitating the AMDase-catalyzed cleavage of CO2. Finally, our results indicate a switch from preferential cleavage of the pro-(R) to the pro-(S) carboxylate group in the CLG-IPL variant of AMDase for all substrates studied. This appears to be due to the emergence of a new hydrophobic pocket generated by the insertion of the six amino acid substitutions, into which the pro-(S) carboxylate binds. Our results allow insight into the tight interaction network determining AMDase selectivity, which in turn provides guidance for the identification of target residues for future enzyme engineering.

The control of the discrimination between dNTP and rNTP in DNA and RNA polymerase

Understanding the origin of discrimination between rNTP and dNTP by DNA/RNA polymerases is important both for gaining fundamental knowledge on the corresponding systems and for advancing the design of specific drugs. This work explores the nature of this discrimination by systematic calculations of the transition state (TS) binding energy in RB69 DNA polymerase (gp43) and T7 RNA polymerase. The calculations reproduce the observed trend, in particular when they included the water contribution obtained by the water flooding approach. Our detailed study confirms the idea that the discrimination is due to the steric interaction between the 2'OH and Tyr416 in DNA polymerase, while the electrostatic interaction is the source of the discrimination in RNA polymerase. Proteins 2016; 84:1616-1624. © 2016 Wiley Periodicals, Inc.

Methods for Efficiently and Accurately Computing Quantum Mechanical Free Energies for Enzyme Catalysis

Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples.

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.

Computational Tools Applied to Enzyme Design − a review

The protein design toolbox has been greatly improved by the addition of enzyme computational simulations. Not only do they warrant a more ambitious and thorough exploration of sequence space, but a much higher number of variants and protein-ligand systems can be analyzed in silico compared to experimental engineering methods. Modern computational tools are being used to redesign and also for de novo generation of enzymes. These approaches are contingent on a deep understanding of the reaction mechanism and the enzyme’s three-dimensional structure coordinates, but the wealth of information produced by these analyses leads to greatly improved or even totally new types of catalysis.

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.

Multiple environment single system quantum mechanical/molecular mechanical (MESS-QM/MM) calculations. 1. Estimation of polarization energies

In combined quantum mechanical/molecular mechanical (QM/MM) free energy calculations, it is often advantageous to have a frozen geometry for the quantum mechanical (QM) region. For such multiple-environment single-system (MESS) cases, two schemes are proposed here for estimating the polarization energy: the first scheme, termed MESS-E, involves a Roothaan step extrapolation of the self-consistent field (SCF) energy; whereas the other scheme, termed MESS-H, employs a Newton–Raphson correction using an approximate inverse electronic Hessian of the QM region (which is constructed only once). Both schemes are extremely efficient, because the expensive Fock updates and SCF iterations in standard QM/MM calculations are completely avoided at each configuration. They produce reasonably accurate QM/MM polarization energies: MESS-E can predict the polarization energy within 0.25 kcal/mol in terms of the mean signed error for two of our test cases, solvated methanol and solvated β-alanine, using the M06-2X or ωB97X-D functionals; MESS-H can reproduce the polarization energy within 0.2 kcal/mol for these two cases and for the oxyluciferin–luciferase complex, if the approximate inverse electronic Hessians are constructed with sufficient accuracy.

Computer aided enzyme design and catalytic concepts

Gaining a deeper understanding of enzyme catalysis is of great practical and fundamental importance. Over the years it has become clear that despite advances made in experimental mutational studies, a quantitative understanding of enzyme catalysis will not be possible without the use of computer modeling approaches. While we believe that electrostatic preorganization is by far the most important catalytic factor, convincing the wider scientific community of this may require the demonstration of effective rational enzyme design. Here we make the point that the main current advances in enzyme design are basically advances in directed evolution and that computer aided enzyme design must involve approaches that can reproduce catalysis in well-defined test cases. Such an approach is provided by the empirical valence bond method.

Protein engineering for development of new hydrolytic biocatalysts

Hydrolytic enzymes play important roles as biocatalysts in chemical synthesis. The chemical versatility and structurally sturdy features of Candida antarctica lipase B has placed this enzyme as a common utensil in the synthetic tool-box. In addition to catalyzing acyl transfer reactions, a number of promiscuous activities have been described recently. Some of these new enzyme activities have been amplified by mutagenesis. Epoxide hydrolases are of interest due to their potential as catalysts in asymmetric synthesis. This current update discusses recent development in the engineering of lipases and epoxide hydrolases aiming to generate new biocatalysts with refined features as compared to the wild-type enzymes. Reported progress in improvements in reaction atom economy from dynamic kinetic resolution or enantioconvergence is also included.

Multiscale Free Energy Simulations: An Efficient Method for Connecting Classical MD Simulations to QM or QM/MM Free Energies Using Non-Boltzmann Bennett Reweighting Schemes

The reliability of free energy simulations (FES) is limited by two factors: (a) the need for correct sampling and (b) the accuracy of the computational method employed. Classical methods (e.g., force fields) are typically used for FES and present a myriad of challenges, with parametrization being a principle one. On the other hand, parameter-free quantum mechanical (QM) methods tend to be too computationally expensive for adequate sampling. One widely used approach is a combination of methods, where the free energy difference between the two end states is computed by, e.g., molecular mechanics (MM), and the end states are corrected by more accurate methods, such as QM or hybrid QM/MM techniques. Here we report two new approaches that significantly improve the aforementioned scheme; with a focus on how to compute corrections between, e.g., the MM and the more accurate QM calculations. First, a molecular dynamics trajectory that properly samples relevant conformational degrees of freedom is generated. Next, potential energies of each trajectory frame are generated with a QM or QM/MM Hamiltonian. Free energy differences are then calculated based on the QM or QM/MM energies using either a non-Boltzmann Bennett approach (QM-NBB) or non-Boltzmann free energy perturbation (NB-FEP). Both approaches are applied to calculate relative and absolute solvation free energies in explicit and implicit solvent environments. Solvation free energy differences (relative and absolute) between ethane and methanol in explicit solvent are used as the initial test case for QM-NBB. Next, implicit solvent methods are employed in conjunction with both QM-NBB and NB-FEP to compute absolute solvation free energies for 21 compounds. These compounds range from small molecules such as ethane and methanol to fairly large, flexible solutes, such as triacetyl glycerol. Several technical aspects were investigated. Ultimately some best practices are suggested for improving methods that seek to connect MM to QM (or QM/MM) levels of theory in FES.

Validating computer simulations of enantioselective catalysis; reproducing the large steric and entropic contributions in Candida Antarctica lipase B

The prospect for computer-aided refinement of stereoselective enzymes is further validated by simulating the ester hydrolysis by the wild-type and mutants of CalB, focusing on the challenge of dealing with strong steric effects and entropic contributions. This was done using the empirical valence bond (EVB) method in a quantitative screening of the enantioselectivity, considering both k(cat) and k(cat)/K(M) of the R and S stereoisomers. Although the simulations require very extensive sampling for convergence they give encouraging results and major validation, indicating that our approach offers a powerful tool for computer-aided design of enantioselective enzymes. This is particularly true in cases with large changes in steric effects where alternative approaches may have difficulties in capturing the interplay between steric clashes with the reacting substrate and protein flexibility.

Computational tools for designing and engineering enzymes

Protein engineering strategies aimed at constructing enzymes with novel or improved activities, specificities, and stabilities greatly benefit from in silico methods. Computational methods can be principally grouped into three main categories: bioinformatics; molecular modelling; and de novo design. Particularly de novo protein design is experiencing rapid development, resulting in more robust and reliable predictions. A recent trend in the field is to combine several computational approaches in an interactive manner and to complement them with structural analysis and directed evolution. A detailed investigation of designed catalysts provides valuable information on the structural basis of molecular recognition, biochemical catalysis, and natural protein evolution.

In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB

Our previously presented method for high throughput computational screening of mutant activity (Hediger et al., 2012) is benchmarked against experimentally measured amidase activity for 22 mutants of Candida antarctica lipase B (CalB). Using an appropriate cutoff criterion for the computed barriers, the qualitative activity of 15 out of 22 mutants is correctly predicted. The method identifies four of the six most active mutants with ≥3-fold wild type activity and seven out of the eight least active mutants with ≤0.5-fold wild type activity. The method is further used to screen all sterically possible (386) double-, triple- and quadruple-mutants constructed from the most active single mutants. Based on the benchmark test at least 20 new promising mutants are identified.

Modeling catalytic promiscuity in the alkaline phosphatase superfamily

In recent years, it has become increasingly clear that promiscuity plays a key role in the evolution of new enzyme function. This finding has helped to elucidate fundamental aspects of molecular evolution. While there has been extensive experimental work on enzyme promiscuity, computational modeling of the chemical details of such promiscuity has traditionally fallen behind the advances in experimental studies, not least due to the nearly prohibitive computational cost involved in examining multiple substrates with multiple potential mechanisms and binding modes in atomic detail with a reasonable degree of accuracy. However, recent advances in both computational methodologies and power have allowed us to reach a stage in the field where we can start to overcome this problem, and molecular simulations can now provide accurate and efficient descriptions of complex biological systems with substantially less computational cost. This has led to significant advances in our understanding of enzyme function and evolution in a broader sense. Here, we will discuss currently available computational approaches that can allow us to probe the underlying molecular basis for enzyme specificity and selectivity, discussing the inherent strengths and weaknesses of each approach. As a case study, we will discuss recent computational work on different members of the alkaline phosphatase superfamily (AP) using a range of different approaches, showing the complementary insights they have provided. We have selected this particular superfamily, as it poses a number of significant challenges for theory, ranging from the complexity of the actual reaction mechanisms involved to the reliable modeling of the catalytic metal centers, as well as the very large system sizes. We will demonstrate that, through current advances in methodologies, computational tools can provide significant insight into the molecular basis for catalytic promiscuity, and, therefore, in turn, the mechanisms of protein functional evolution.

Quantum mechanics/molecular mechanics modeling of regioselectivity of drug metabolism in cytochrome P450 2C9

Cytochrome P450 enzymes (P450s) are important in drug metabolism and have been linked to adverse drug reactions. P450s display broad substrate reactivity, and prediction of metabolites is complex. QM/MM studies of P450 reactivity have provided insight into important details of the reaction mechanisms and have the potential to make predictions of metabolite formation. Here we present a comprehensive study of the oxidation of three widely used pharmaceutical compounds (S-ibuprofen, diclofenac, and S-warfarin) by one of the major drug-metabolizing P450 isoforms, CYP2C9. The reaction barriers to substrate oxidation by the iron-oxo species (Compound I) have been calculated at the B3LYP-D/CHARMM27 level for different possible metabolism sites for each drug, on multiple pathways. In the cases of ibuprofen and warfarin, the process with the lowest activation energy is consistent with the experimentally preferred metabolite. For diclofenac, the pathway leading to the experimentally observed metabolite is not the one with the lowest activation energy. This apparent inconsistency with experiment might be explained by the two very different binding modes involved in oxidation at the two competing positions. The carboxylate of diclofenac interacts strongly with the CYP2C9 Arg108 side chain in the transition state for formation of the observed metabolite—but not in that for the competing pathway. We compare reaction barriers calculated both in the presence and in the absence of the protein and observe a marked improvement in selectivity prediction ability upon inclusion of the protein for all of the substrates studied. The barriers calculated with the protein are generally higher than those calculated in the gas phase. This suggests that active-site residues surrounding the substrate play an important role in controlling selectivity in CYP2C9. The results show that inclusion of sampling (particularly) and dispersion effects is important in making accurate predictions of drug metabolism selectivity of P450s using QM/MM methods.

Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering

The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Obtaining optical purity for product diols in enzyme-catalyzed epoxide hydrolysis: contributions from changes in both enantio- and regioselectivity

Enzyme variants of the plant epoxide hydrolase StEH1 displaying improved stereoselectivities in the catalyzed hydrolysis of (2,3-epoxypropyl)benzene were generated by directed evolution. The evolution was driven by iterative saturation mutagenesis in combination with enzyme activity screenings where product chirality was the decisive selection criterion. Analysis of the underlying causes of the increased diol product ratios revealed two major contributing factors: increased enantioselectivity for the corresponding epoxide enantiomer(s) and, in some cases, a concomitant change in regioselectivity in the catalyzed epoxide ring-opening half-reaction. Thus, variant enzymes that catalyzed the hydrolysis of racemic (2,3-epoxypropyl)benzene into the R-diol product in an enantioconvergent manner were isolated.

Determinants of reactivity and selectivity in soluble epoxide hydrolase from quantum mechanics/molecular mechanics modeling

Soluble epoxide hydrolase (sEH) is an enzyme involved in drug metabolism that catalyzes the hydrolysis of epoxides to form their corresponding diols. sEH has a broad substrate range and shows high regio- and enantioselectivity for nucleophilic ring opening by Asp333. Epoxide hydrolases therefore have potential synthetic applications. We have used combined quantum mechanics/molecular mechanics (QM/MM) umbrella sampling molecular dynamics (MD) simulations (at the AM1/CHARMM22 level) and high-level ab initio (SCS-MP2) QM/MM calculations to analyze the reactions, and determinants of selectivity, for two substrates: trans-stilbene oxide (t-SO) and trans-diphenylpropene oxide (t-DPPO). The calculated free energy barriers from the QM/MM (AM1/CHARMM22) umbrella sampling MD simulations show a lower barrier for phenyl attack in t-DPPO, compared with that for benzylic attack, in agreement with experiment. Activation barriers in agreement with experimental rate constants are obtained only with the highest level of QM theory (SCS-MP2) used. Our results show that the selectivity of the ring-opening reaction is influenced by several factors, including proximity to the nucleophile, electronic stabilization of the transition state, and hydrogen bonding to two active site tyrosine residues. The protonation state of His523 during nucleophilic attack has also been investigated, and our results show that the protonated form is most consistent with experimental findings. The work presented here illustrates how determinants of selectivity can be identified from QM/MM simulations. These insights may also provide useful information for the design of novel catalysts for use in the synthesis of enantiopure compounds.