The Effect of Binding on the Enantioselectivity of an Epoxide

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The Effect of Binding on the Enantioselectivity of an Epoxide Hydrolase Julian Zaugg, Yosephine Gumulya, Mikael Boden, Alan Edward Mark, and Alpeshkumar K Malde J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.7b00353 • Publication Date (Web): 09 Feb 2018 Downloaded from http://pubs.acs.org on February 17, 2018

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Journal of Chemical Information and Modeling

The Effect of Binding on the Enantioselectivity of an Epoxide Hydrolase Julian Zaugg,† Yosephine Gumulya,† Mikael Bodén,†,‡ Alan E. Mark,∗,†,‡ and Alpeshkumar K. Malde∗,† †School of Chemistry and Molecular Biosciences, University of Queensland, 4072, Brisbane, Australia ‡Institute of Molecular Biosciences, University of Queensland, 4072, Brisbane, Australia E-mail: [email protected]; [email protected]

Abstract Molecular dynamics simulations and free energy calculations have been used to investigate the effect of ligand binding on the enantioselectivity of an epoxide hydrolase (EH) from Aspergillus niger. Despite sharing a common mechanism, a wide range of alternative mechanisms have been proposed to explain the origin of enantiomeric selectivity in EHs. By comparing the interactions of (R)- and (S)-glycidyl phenyl ether (GPE) with both the wild type (WT, E = 3) and a mutant showing enhanced enantioselectivity to GPE (LW202, E = 193) we have examined whether enantioselectivity is due to differences in the binding pose, the affinity for the (R)- or (S)- enantiomers or a kinetic effect. The two enantiomers were easily accommodated within the binding pockets of the WT enzyme and LW202. Free energy calculations suggested that neither enzyme had a preference for a given enantiomer. The two substrates sampled a wide variety of conformations in the simulations with the sterically hindered and unhindered carbon atoms of the GPE epoxide ring both coming in close proximity to

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the nucleophilic aspartic acid residue. This suggests alternative pathways could lead to the formation of a (S)- and (R)-diol product. Together the calculations suggest that the enantioselectivity is due to kinetic rather than thermodynamic effects and that the assumption that one substrate results in one product when interpreting the available experimental data and deriving E-values may be inappropriate in the case of EHs.

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Since the early 1990’s the number of drug products approved for new chemical entity (NCE) 1 status by the U.S. Food and Drug Administration (FDA) containing a single enantiomer as the active ingredient has risen significantly, while numbers of approved racemic products has decreased. 2,3 With the FDA and other regulatory agencies encouraging the socalled ‘chiral switch’ from racemic to enantiopure compounds, 2 the development of improved methods for single enantiomer resolution of drug molecules and their synthetic intermediates is on the rise. The use of enzymes to produce enantiopure products (from a racemic substrate) is highly desirable to industry because they offer the potential to improve economics of chemical synthesis as well as lower environmental impact. For these reasons, methods to predict and design enzymes with improved stereoselectivity (both enantio- and diastereo-) has been an area of intense research. 4–15 Of particular interest are epoxide hydrolases (EHs). 16,17 EHs are capable of producing optically pure epoxides and diols, which are valuable intermediates for synthesising many pharmaceuticals. 17 For example, they have been used in the production of β-adrenergic receptor blocking drugs (S)-propranolol, (S)-alprenolol and (R)-nifénalol. 18–20 Given the industrial applications of EHs, considerable effort has gone into expanding their functional capabilities. 19–30 Most EHs are members of the α/β-hydrolase super-family, characterised by a shared structural fold and catalytic triad (Scheme 1). 17 In the case of EHs the catalytic triad consists of an aspartate nucleophile, a histidine and charge-relaying aspartic acid. 31 Most EHs share a three-step reaction mechanism. 17 In the first step, the nucleophilic aspartate attacks an oxirane carbon of the bound epoxide, forming an alkyl-ester intermediate. Two conserved tyrosine residues are positioned close to the nucleophilic aspartate and assist in the positioning and activation of the substrate by forming hydrogen bonds with the oxirane oxygen. 32–35 The second step involves hydrolysis of the ester intermediate through the attack of an activated water molecule, followed by the subsequent release of the diol product. Although there is a wealth of structural and biochemical data available for EHs, the origin of selectivity remains uncertain. Indeed a range of alternative models have been pro-

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posed to explain the source of enantioselectivity among different EHs based on experimental studies. In the case of the EH from Agrobacterium radiobacter involving racemic styrene oxide, the rate of alkylation in the first step of the reaction has been proposed to control enantioselectivity. 36 In contrast, the enantioselectivity of EH from Aspergillus niger (AnEH) for racemic styrene oxide 37 and of rat microsomal EH for racemic glycidyl-4-nitrobenzoate 38

was attributed to the rate of hydrolysis of the ester intermediate. The enantioselectivity

of metagenome-derived EH Kau2 for racemic trans-stilbene oxide has been proposed to be due to differences in the rate of alkylation as well as the rate of hydrolysis. 39 Finally in an alternative study of AnEH with para-substituted styrene oxide, 40 the origin of enantioselectivity was attributed to both a higher affinity and overall rate of catalysis as inferred from the experimental KM and Vmax values. The difficulty is that such experimental studies are unable to examine the origin of the enantioselectivity at an atomic level and as such the alternative mechanisms proposed are largely speculation. A number of studies have tried to complement the available biochemical data using computational methods in order to either analyse the origin of enantioselectivity at an atomic level or predict the enantioselectivity of novel constructs. For example, Hopmann and Himo 43,44

used density functional theory to investigate the reaction mechanism of both wild type

(WT) and mutant forms of soluble EH using an active site model containing nine residues, calculating full potential energy curves for the hydrolysis of (1S, 2S)-β-methylstyrene oxide. While they were able to explore alternative reaction mechanisms, their calculations led to a considerable overestimation of the effect of different mutations on enantioselectivity. 44 The group of Kamerlin in contrast investigated the effect of conformational diversity and a range of mutations on the enantioselectivity of Solanum tuberosum (potato) EH1 (StEH1) and related enzymes. 14,15 Using molecular dynamics (MD) in conjunction with an empirical valence bond model to describe the substrate and active site allowed some conformational sampling of the substrate. However, for reasons of computational efficiency the majority of the system was highly restrained. These calculations were able to reproduce the enantioselectivity of

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(a)

Tyr314

O H O

R O-

Asp192

Tyr314

Tyr251

O H

O H

Nucleophilic attack

O H

OStep 2

O H

O H

HO

O Step 3

O Asp192

Asp192

Tyr251

O-

R

O

Tyr314

O H

O

O

Step 1

Tyr251

O H

R

O

Tyr314

Tyr251

Hydrolysis

Product leaves

H

O-

OH

R

Asp192

O H N

N N H

His374

O-

O

Asp348 O

(b) PhO

1

2

O

H 2O PhO

An EH

rac-GPE

1

(R)-GPE

HO 2

+

PhO

His374

N H

O-

Asp348

OH 1

2

(2S)-3-phenoxypropane-1,2-diol

Scheme 1: (a) Proposed reaction mechanism of the epoxide hydrolase from Aspergillus niger (AnEH) 17,31,41,42 with glycidyl phenyl ether (GPE). In the first step, the nucleophilic aspartate (Asp192) attacks the sterically unhindered ring carbon of the bound epoxide substrate (C-2), forming an alkyl-ester intermediate. Two conserved tyrosine residues (Tyr251 and Tyr314) present in the lid domain are positioned close to Asp192 and assist in the positioning and activation of the substrate through the formation of hydrogen bonds. The second step involves hydrolysis of the intermediate through the attack of an activated water molecule. The third step sees the release of the diol product. (b) In a solution containing racemic GPE (rac-GPE), wild type (WT) AnEH shows a slight enantioselective preference for the hydrolysis of (S)-GPE leading to formation of (2S)-3-phenoxy-propane-1,2-diol. StEH1, which they attributed to differences in the binding mode of the substrate between different mutant forms. The aim of this study was to investigate, computationally, the possible role of binding thermodynamics on enantioselectivity, focusing on AnEH as a case study. AnEH has been studied extensively with the aim of improving its enantioselective capabilities. 28,42,45–48 In a directed evolution study in the form of iterative saturation mutagenesis (ISM) 49 in combination with the combinatorial active site saturation test (CAST), 50 a number of AnEH mutants with improved preference for (S)-glycidyl phenyl ether ((S)-GPE) were produced. 46

Guided by the crystal structure of WT AnEH 41 a number of residues, the side-chains

of which lie within the binding pocket, were selected and subjected to saturation mutagenesis. The resulting mutant with the most substantial increase in enantioselectivity, desig5


O


nated ‘LW202’, contained nine mutations - Leu215Phe, Ala217Asn, Arg219Ser, Leu249Tyr, Thr317Trp, Thr318Val, Met329Pro, Leu330Tyr and Cys350Val. The crystal structure for the mutant LW202 was subsequently solved. 42 Interestingly, the root-mean-squared deviation (RMSD) between the backbones of the two structures was ≈ 0.11 nm, indicating that the overall structure of the protein was not altered significantly. Reetz et al. 42 reported LW202 had a enantioselective preference of E = 193 vs E = 3 for the WT, where the E-value is the enantiomeric ratio between the fast and slow reacting enantiomers, based on the assumption of a one substrate to one product reaction. Reetz et al. 42 further proposed that the origin of the enhanced enantioselectivity in LW202 was due to the positioning of the preferred substrate in the binding pocket, basing their conclusion on short (1 ns) MD simulations. 42 However, positioning of the substrate is only one possibility. Here a combination of docking, MD simulations and free energy calculations is used to analyse the origin of the enhanced enantioselectivity of the mutant LW202 towards the substrate GPE compared to WT AnEH. The study draws into question whether the use of a one substrate to one product kinetic scheme to interpret the available kinetic data on LW202 is indeed appropriate. This and other sources of error in the experimental E-values are also discussed.

Methods Molecular dynamics simulations MD simulations were performed using the GROMACS 3.3.3 51 simulation package with the GROMOS 54a7 force field 52 for the protein. The topologies of both GPE enantiomers were generated using the ‘Automated Topology Builder’ (ATB, http://atb.uq.edu.au). 53,54 The initial complexes of (R)- and (S)-GPE with WT (3G0I) and LW202 (3G02) were obtained as described below. Each complex was placed in a truncated octahedron periodic box and solvated with simple point charge (SPC) 55 water molecules. Crystallographically modelled water molecules were retained, except those which clashed with (R)- and (S)-GPE molecules 6


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in the binding pocket. One challenge when performing any simulation is the assignment of the protonation states of titratable residues. Indeed, during review of the present study, it was questioned as to whether the results presented were sensitive to the protonation state of individual residues. Using PROPKA, 56,57 the N-terminus as well as all lysine and arginine residues were predicted to be protonated at pH 7, while the C-terminus and all aspartate and glutamate residues were predicted to be deprotonated. The protonation state of the catalytic residue His374 was predicted to be protonated (positively charged). His374 is of particular importance as it lies between Asp192 and Asp348 and it has been previously shown that the protonated form is required for the stability of the complex. 10,12,42,58 PROPKA suggests that most of the remaining histidine residues in both the WT and LW202 proteins should be deprotonated (neutral), for some the appropriate protonation state is unclear. We have therefore generated complexes for both WT and LW202 where all histidine residues, with the exception of the protonated His374, are either positively charged or neutral. In the neutral form, a net charge of −13 and −14 is yielded on the WT and LW202 proteins respectively, while in the positively charged form a net charge of −4 and −5 is yielded respectively. Each complex was energy minimised using a steepest descent method with an initial step size of 0.001 nm for 500 steps. The systems were further equilibrated by performing a 500 ps simulation, during which time the heavy atoms of the protein and ligand were positionally restrained using a harmonic potential with a force constant of 1000 kJ mol−1 nm−2 before commencing the series of unrestrained MD simulations. All MD simulations were performed at constant temperature (298 K) and pressure (1 atm) using a Berendsen thermostat (coupling time of 0.1 ps) and barostat (coupling time of 1.0ps and isothermal compressibility of 4.5e−5 bar−1 ). 59,60

A twin-range cutoff was used. Interactions within a shorter-range cutoff of 0.8 nm

were updated every step (0.002 ps). Interactions within the longer-range cutoff of 1.4 nm were updated every 0.01 ps together with the pairlist. To correct for the truncation of the electrostatic interactions beyond the 1.4 nm long-range cutoff, a reaction-field correction was

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applied using a dielectric permittivity of 78. Initial velocities at a given temperature were taken from a Maxwell-Boltzmann distribution. All bonds were constrained using the LINCS algorithm. 61 Three sets of 50 ns MD simulations were run for each of the eight complexes with different initial velocity distributions, giving a total of 24×50 ns = 1.2 µs of trajectories. All coordinates, velocities, forces and energies were saved every 25000 steps for analysis.

Ligand and protein structure preparation To generate the initial complexes for MD simulations, Autodock Vina 62 was used to perform the docking of (R)- and (S)-GPE (Figure 1) into the binding pockets of WT AnEH and LW202. The coordinates of WT AnEH and LW202 were obtained from the RCSB Protein Data Bank (PDB, www.rcsb.org), 63 chain A of entries 3G0I and 3G02 respectively. 42 Input structure files were prepared in the PDBQT format. 64,65 Residues that formed the part of missing loop regions of 3G0I (320-328) and 3G02 (321-327) were generated using the MODELLER 66 web service provided through the Chimera molecular modelling tool. 67 The structure which gave the lowest Discrete Optimised Protein Energy (DOPE) score was chosen. 68 The positions of all other residue atoms were held fixed during the loop building. The resulting structure was energy minimised using GROMACS (see Molecular dynamics simulations for details). Both (R)- and (S)-GPE were constructed and minimised in Avogadro. 69 Minimisation was performed using a steepest descent algorithm and the Universal force field 70

with an initial step size of 0.2 Å. A minimum of 500 steps were performed. The system

was considered converged when the change in energy was less than 1 × 10−6 kJ mol−1 . To validate the docking procedure before use, the ligand valpromide (VPR) from the PDB structure 3G0I was removed from the structure and re-docked using Autodock Vina with a grid box of size 35 × 20 × 20 Å centred between the nucleophile Asp192 and lid tyrosines Tyr251 and Tyr314. An exhaustiveness value = 200 and a pose number = 20 was used. Up to 200 poses were generated over 10 independent runs while keeping the protein rigid while rotations around single bonds in the VPR ligand were allowed. Comparing the top 8


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Tyr251

Tyr314

Oδ2 Oδ1

Asp192

Figure 1: Substrates (R)- and (S)-GPE docked into 3G0I, shown as pink and blue sticks respectively. For the two poses shown, distances between the oxygen and the sterically unhindered carbon (C-2) atoms of the epoxide ring to the side chain oxygen atoms of Tyr251 and Tyr314, and those of Asp192 (Oδ1 and Oδ2), respectively, are ≤ 0.4 nm. Catalytic residues are represented as ball and sticks. (lowest scoring) 50 poses of VPR to the crystal structure, a mean RMSD of 0.24 ± 0.03 nm was obtained for all atoms. While considering only the reaction critical amide oxygen and nitrogen atoms, the mean RMSD was 0.19 ± 0.01 nm. The top two poses by RMSD are presented in Figure 2. Ligands (R)- and (S)-GPE were docked into the WT (3G0I) binding pocket using the parameters and set up used for the docking of VPR. Again, the protein molecule was held rigid while the ligand was flexible in the sense that rotations around single bonds were allowed during the docking runs. For docking, we defined an optimal active binding pose as when the distance between the sterically unhindered carbon (C-2) of the epoxide ring and Asp192 side chain carboxylate oxygen atoms (Oδ1 and Oδ2) and between the oxygen of the epoxide ring to the hydroxyl group of Tyr251 and Tyr314 was ≤ 0.4 nm. Amongst multiple docking solutions for the active binding pose, the one with the best (lowest) score was selected for use in MD simulations. Docking using Autodock Vina failed to generate 9



Tyr251

Tyr314

Oδ2 Oδ1

Asp192

Figure 2: Valpromide (VPR) from 3G0I crystal structure (green sticks) and the best docked conformations by root-mean-square deviation of i) reaction critical amide oxygen and nitrogen atoms (blue sticks) or ii) by all atoms (pink sticks). The catalytic residues, conserved Tyr251 and Tyr314 and the nucleophilic Asp192, are coloured in green and represented as ball and sticks. suitable active binding poses for the mutant LW202 (3G02) due to steric clashes between the GPE ligands and residues within the binding pocket. The initial complexes of (R)- and (S)-GPE with LW202 were instead obtained by superimposing the backbone atoms of the LW202 structure onto the corresponding backbone of GPE:WT complexes obtained from docking. Superimposition was performed using the ‘align’ function in PyMOL v1.7.2.1, 71 with the resulting complexes energy minimised.

Analysis of MD simulations To compare the protein configurations obtained from the simulations to the available experimental structures, the RMSD of the backbone atoms for residues in stable regions of the protein was calculated. An unstable region was defined as a set of contiguous residues whose backbone root-mean-squared fluctuations (RMSFs) were > 0.25 nm. Residues excluded from the RMSD calculation are provided as supplementary information (Supplementary material 10


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S1) and were located predominantly within loop or solvent exposed regions, and within the lid domain and the N-terminal meander. Note, although simulated as a monomer for reasons of computational efficiency, AnEH is a dimer in solution, with interactions between the lids and the tips of the N-terminal meanders of each monomer forming the dimer interface. 41 To check the stability of the ligand:protein complexes, distances between pairs of heavy atoms, from ligand and amino acids crucial for binding and catalysis respectively, were calculated. This included the following distance pairs: Asp192 Oδ1/Oδ2 and C-2 of the epoxide ring; Asp192 Oδ1/Oδ2 and the sterically hindered carbon atom of the epoxide ring (C-1); side chain oxygen atom of Tyr251 and the oxygen of the epoxide ring; and side chain oxygen atom of Tyr314 and the oxygen of the epoxide ring. To determine the presence of catalytically competent ligand binding orientations, complexes from each simulation trajectory were first superimposed onto the corresponding crystal structure using all protein backbone atoms of the elements of secondary structure and then inspected visually. Ligand orientations were defined as catalytically competent when the distance between Asp192Oδ1 or Oδ2 to either of the carbon atoms (C-1 or C-2) of the epoxide ring was ≤ 0.4 nm 42 and the distance between the oxygen atom of the epoxide ring to the side chain oxygen of at least one of the conserved tyrosines (Tyr251 or Tyr314) was ≤ 0.4 nm. Further discussion of this criteria can be found in Results and Discussion.

Free energy calculations GROMACS 3.3.3 was used to calculate the difference in Gibbs energy ∆G between alternate enantiomers of the GPE ligand, estimated by using the coupling parameter (λ) approach in conjunction with the thermodynamic integration formula, Zλ=1 ∆G = λ=0

11

∂H ∂λ

dλ λ


Eq.(1)


∆Gb

(R)-GPE(sol)

∆G(sol) =0

(R)-GPE(pro)

∆G(pro)

∆G(sol)

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∆G(pro)

=0

(S)-GPE(pro)

(S)-GPE(sol) ∆Gb

Figure 3: Thermodynamic cycle used to determine the difference in binding free enthalpy between (R)- and (S)-GPE in solution and bound to protein. where λ = 0 corresponded to the initial state of the system (e.g. (S)-GPE) and λ = 1 corresponded to the final state of the system (e.g. (R)-GPE). H is the Hamiltonian of the system and the brackets < ... > λ correspond to an average over an equilibrium ensemble at λ. The relative free enthalpy of binding ∆∆Gb was determined from the difference in the change in free enthalpy by performing the same alchemic mutation free in solution (∆Gsol ) and bound to the protein (∆Gpro ), i.e. ∆∆GS→R = ∆GSb − ∆GR b b

Eq.(2)

S→R = ∆GS→R pro − ∆Gsol

∆Gb is the free enthalpy required to transfer the ligand from being free in solution to bound in the protein (as shown in the thermodynamic cycle in Figure 3). -0.335

O

0.191

O CH2

O

CH2 O

0.191

-0.335

(S)-GPE

(R)-GPE

Scheme 2: Alchemic mutation between (R)- and (S)-GPE involving the swapping of the non-bonded parameters (van der Waals and electrostatic) of the O and CH2 (C-2) of the epoxide ring. The alchemic mutation between (R)- and (S)-GPE was performed as shown in Scheme 2. Eq.(1) was integrated by performing separate simulations at a series of λ points, e.g. 12


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(0.00, 0.025, 0.05, . . . 0.95, 0.975, 1.00) in both the bound and unbound states. The systems were first equilibrated for 500 ps at each λ followed by production runs of 2 ns or until the value of h∂H/∂λi had converged. To prevent numerical instabilities as atoms were created or destroyed, the soft-core potential as described by Beutler et al. 72 was used with αijLJ = αijC = 0.5 nm2 . The area beneath the curve given by Eq.(1) was estimated using a trapezoidal approximation. For statistical error analysis, λ points were either added or extended based on an analysis of convergence by trapezoidal numerical integration (Martin Stroet, personal communication). In addition, the convergence of the calculations was checked by calculating the relative free enthalpy for mutations in the forward, (S) to (R), as well as backward, (R) to (S), directions. Equal and opposite free enthalpy values would be expected to be obtained if the calculations had converged. A set of eight calculations were performed for the following alchemic mutations: (S) to (R) and (R) to (S) in WT (3G0I) and LW202 (3G02) with histidine residues (with the exception of His374) in either their positively charged or neutral forms. Additional calculations were performed by mutating (S)- to (R)-GPE while restraining the GPE ligand molecule in an active binding pose in the mutant LW202. This was achieved through the application of a weak 10 kJ mol−1 nm−2 harmonic distance restraint with a lower and upper bound limit of 0.3 nm and 0.4 nm respectively, applied between the side chain oxygen atoms of Asp192 (Oδ1 and Oδ2) and C-2.

Results and Discussion Molecular dynamics simulations To better understand how the two GPE enantiomers may interact with WT AnEH and the mutant LW202, a series of MD simulations were performed. These involved eight complexes: (S)-GPE:WT, (R)-GPE:WT, (S)-GPE:LW202 and (R)-GPE:LW202, with histidine residues either positively charged or neutral (see above). The MD simulations were run in triplicate for 50 ns for each of the eight complexes. To ensure the protein remained stable during 13



the simulations, the RMSD of protein backbone atoms for stable regions of the protein was calculated. The RMSD plots are provided as supplementary information (Figures S1 and S2). The RMSD indicated that protein structures stabilised after 5 ns. As described in the methods the RMSD values were calculated excluding residues in the N-terminal meander, the lid domains as well as several solvent exposed loops. In regard to this, it is important to note that in solution AnEH is believed to be dimeric, whereas in this work it was simulated as a monomer. The N-terminal meander and the lid domains form part of the proposed dimer interface and therefore are expected to be mobile when simulated as a monomer. To check the stability of ligand:protein complexes, distances between pairs of heavy atoms from ligand and protein catalytic residues (Asp192, Tyr251 and Tyr314) were calculated. Plots of distances between the ligand and catalytic residues are provided as supplementary information (Figures S3-6). Generally, both (R)- and (S)-GPE remain within the binding pocket. In runs involving (R)-GPE:LW202 (Run 1), with histidine residues in either their positively charged or neutral form, the ligand left the binding pocket and entered the surrounding water. In all other simulations the ligand was highly mobile, sampling multiple orientations as well as different locations within the binding pocket. A major question regarding the position of the ligand within the binding pocket is whether the states sampled are catalytically competent. This requires assumptions to be made regarding the catalytic mechanism and the preferred relationship between the key chemical groups. Others have attempted to express this in terms of a ‘near attack conformer’ or NAC. 73–75 What is clear from the current work is that the ligand can move within the binding pocket. Certainly some of the orientations sampled during simulations could be catalytically competent assuming similar criteria to those used by others, i.e. C-1 or C-2 were within 0.4 nm of either Asp192Oδ1 or Oδ2 and the oxygen of the epoxide ring was within 0.4 nm of either of the side chain oxygen atoms of Tyr251 or Tyr314. Ligand orientations that fit such criteria, which were sampled during MD simulations, are shown in Figure 4. For comparison, Wijma et al. 7 considered catalysis would occur if the oxygen atom of the proposed nucleophilic wa-

14


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ter came within 3.22 Å of one of the carbon atoms of the epoxide ring of cyclopentene oxide in mutants of limonene EH. However, what is also clear from the current work is that even three sets of 50 ns simulations is far from sufficient to obtain reliable statistics as to the true probability of a particular arrangement between the ligand and the active site residues being sampled. The difficulty is that the previous studies that have used such NACs to predict enantiomeric or regiomeric selectivity 6,7,12 have been based on the use of what are, in comparison, very short simulations ranging from 10 ps 6 to a maximum of 4 ns. 12 Furthermore, they effectively biased the results by initiating the simulations from close to the proposed transition state. Indeed, Wijma et al. 6 found that their predictive ability decreased with increased sampling time. Another potential consideration in enantiomer selectivity is that depending upon whether Asp192 attacks C-2 or C-1, an enantiopure GPE ((S) or (R)) can produce both (S)- as well as (R)-diol products as depicted in Scheme 3. The attack on C-2 would lead to the retention of chirality, whereas the attack on C-1 would lead to the inversion of chirality of the product. 7

Thus the enhanced enantioselectivity of the mutant LW202 towards the GPE substrate HO

OH 1

2

tio en

et R

n io

rs ve

O 1

**

In

*

n

PhO ** *

(2R)-3-phenoxypropane-1,2-diol

PhO ** 2*

PhO ** *

n tio R

n

io

et

rs

**

(S)-GPE

en

ve

(R)-GPE

O 1

2 In

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


HO

*

OH 1

2

PhO ** * (2S)-3-phenoxypropane-1,2-diol

Scheme 3: Overview of possible stereochemically different diol products from hydrolysis of racemic GPE. Nucleophilic attack at C-2 will result in a retention (∗) of configuration, while attack at C-1 will result in an inverted (∗∗) configuration. could be also due to enantioconvergence originating from the complementary regioselectivity. For example, if (S)-GPE is preferentially attacked at the sterically unhindered C-2 atom 15



leading to the retention of chirality and formation of the (S)-diol, whereas (R)-GPE is preferentially attacked at the sterically hindered C-1 atom leading to the inversion of chirality and formation of the (S)-diol. Enantioconvergence has been proposed by Monterde et al. 76 to account for the enantioselectivity observed in the biohydrolysis of racemic styrene oxide derivatives by StEH. Indeed, a recent study successfully trapped and crystallised ester intermediates covalently linked to the EH from Pseudomonas aeruginosa, 77 demonstrating that the enzyme could potentially attack a distinct carbon atom on the epoxide moiety of each enantiomeric pair of the substrate. Equations to determine regioselectivity in potentially enantioconvergent reactions involving the biohydrolysis of epoxides have been proposed (see below for details). 78,79 The possibility of enantioconvergence also has broader implications. For example a fundamental assumption of the model used by Reetz and others to analyse the kinetic data is that a single substrate leads to a single product. This would invariably change the meaning of the reported kcat values. 42

Free energy calculations As noted above the complementary regioselectivity could contribute to the enhanced enantioselectivity of the mutant LW202. Since both (R) and (S) enantiomers remain in the binding pocket, we have tested whether the enhanced enantioselectivity of LW202 could originate from the preferential binding of (S)- over (R)-GPE as suggested previously. 42 Determining the binding free enthalpy of a reacting substrate (such as GPE binding to AnEH) experimentally is challenging. Thus in this work we have used the Thermodynamic Integration 80 method employing a closed thermodynamic cycle as shown in Figure 3 to estimate the binding free enthalpy computationally. The free enthalpy of binding, as might be measured experimentally, is represented by the horizontal legs. The vertical legs represent the alchemic mutation (chirality inversion), in solution as well as in the binding pocket of the protein. The free enthalpy change involving a chiral inversion of a molecule in water would by definition be 0 kJ mol−1 and the overall change in the free enthalpy of a closed cycle would also be 16


Page 16 of 31

Page 17 of 31

LW202

WT 1

2 Tyr251

Tyr251

1

(S)-GPE

2

Tyr314

Tyr314

Tyr251

Tyr314

Tyr251

3.4

Tyr314

3.6

3.7 4.2 3.1

4.3

3.9 Oδ2

Oδ2

3.3 Oδ1

3.6

3.2

3.8

4.2

Oδ1

Oδ2

Asp192

2 Tyr251

Asp192

Asp192

1

Tyr251 Tyr314

Tyr314

Oδ2

Oδ1

Oδ1

Asp192

1

(R)-GPE

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


2 Tyr251 Tyr314

Tyr251

Tyr314

3.8 2.9

3.3

2.7

2.6

Oδ2

3.3

Oδ1

3.6

3.6 3.3

3.2

3.6

Oδ2

3.4 Oδ2

Oδ2 Oδ1

Oδ1

Oδ1

Asp192

Asp192

Asp192

Figure 4: Catalytically competent ligand orientations sampled during molecular dynamics simulations. Both (R)- and (S)-GPE, when in complex with either the WT AnEH or the mutant LW202, adopted orientations where either the hindered (1, C-1) or unhindered (2, C-2) carbon of the epoxide ring was within 0.4 nm of the nucleophilic Asp192 and where the oxygen atom of the epoxide ring was positioned within 0.4 nm of the side chain oxygen of at least one of the conserved tyrosines (Tyr251 or Tyr314). Catalytic residues are shown as ball and sticks and coloured in green. Relevant distances are indicated by dashed lines and reported in ångströms (Å). 0 kJ mol−1 . Hence, one needs only to estimate the change in the free enthalpy for the chiral inversion of a molecule within the binding pocket of the protein to estimate the difference in binding free enthalpy between enantiomers. The relative binding energies between (R)- and (S)-GPE in WT and LW202 are shown in Table 1. The representative free enthalpy profiles (∂H/∂λ vs λ curves) for the (S) to (R) mutation in the protein are provided as supplementary information (Figure S7). The convergence of the free energy calculations was checked by performing alchemic mutations for the forward, (S) to (R), as well as backward, (R) to (S), directions. The relative free enthalpy of binding for (R)- and (S)-GPE in both the WT and LW202 was negligible and generally within the error of the calculation (± 2.0 kJ mol−1 ). This suggests that the protein can not distinguish between the (R) and (S) enantiomers of GPE on binding. An additional 17



calculation was performed in which the orientation of GPE was restrained within the binding pocket, where the sterically unhindered C-2 of the epoxide ring was within 0.4 nm of Asp192Oδ1 and Oδ2. The relative free enthalpy of binding between (R)- and (S)-GPE was again negligible. The lid domain lies close to the dimer interface. Simulation of the system as a monomer may lead to larger fluctuations in the lid domain. To determine if the positions of the side-chains of Tyr215 and Tyr314 influenced the calculated binding free enthalpy, calculations were also performed in which the distance between the oxygen atom of the epoxide ring and the hydroxyl group of Tyr215 and Tyr314 was restrained in a similar manner to that between C-2 of GPE and the Asp192. The effect on relative free enthalpy was negligible (data not shown). The fact that the free enthalpy values derived from both restrained and unrestrained simulations are similar indicates that not only are the results not very sensitive to the orientation and position of the ligand in the binding pocket, i.e. the ligand can readily sample alternative states, but that the free energy calculations are well converged. These results suggest that the origin of enhanced enantioselectivity of the mutant LW202 towards GPE is not due to the preferential binding of (S)-GPE. Table 1: Free enthalpy differences and relative binding free enthalpies of (R)- and (S)-GPE in complex with the WT AnEH and the mutant LW202 (kJ mol−1 ). With the exception of the protonated His374, all remaining histidine residues were either positively charged or neutral. Positive His Enzyme ∆GS→R ∆GR→S pro pro −2.5 −1.6 WT 1.7 −2.7 LW202 a −0.4 LW202 a

Neutral His ∆GS→R ∆GR→S pro pro 1.1 0.56 2.1 −3.95 −2.5

restrained simulation

Table 2: KM constants and derived free enthalpy values (∆G) for the WT AnEH and the mutant LW202. Enzyme WT LW202

KM,S (mM) 8.65 × 10−2a 1.25a

∆GS (kJ mol−1 ) −23.6 −16.9 a Originally

KM,R (mM) 6.80 × 10−1a 5.13 × 101a

∆GR (kJ mol−1 ) ∆∆GS→R (kJ mol−1 ) −18.4 5.2 −7.5 9.4

reported by Reetz et al. 42

18


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Under the assumption that a one substrate to one product kinetic scheme (as shown in Eq.(3) 81 ) accurately represents the biochemical reaction of WT AnEH and the mutant LW202, KM is the concentration of substrate [S] at half of the maximum rate (Vmax ) and is frequently assumed to reflect the binding affinity. K

k

k3 S 2 − * − * E+S − →E+P ) − −E·S − ) − − EI −

Eq.(3)

k−2

KS (k−2 + k3 ) (k−2 + k2 + k3 ) k2 k3 = k2 + k−2 + k3

KM =

Eq.(4)

kcat

Eq.(5)

The reaction scheme given in Eq.(3) assumes an initial binding event KS followed by formation of an alkyl-intermediate (EI). The value of KM will therefore be a composite of both thermodynamic (KS ) and kinetic (k2 , k−2 , k3 and kcat ) components (Eq.(4) and Eq.(5) 81

). The KM values from Reetz et al. 42 yield the binding free enthalpies shown in Table 2 as

derived using Eq.(6). ∆G = −RT ln(KM )

Eq.(6)

The difference between the binding of (S)- and (R)-GPE based on the KM values is 5.2 kJ mol−1 in the WT and 9.4 kJ mol−1 in the mutant LW202. The free energy calculations suggest however that there is no preference for (S)- over (R)-GPE (∆G ≈ 0 kJ mol−1 ) in either WT or LW202. This lack of a preference indicates the value of KS for (S)- and (R)GPE is not significantly different in either WT and LW202. The observed enantioselectivity therefore has no thermodynamic contribution and is more likely to be of a kinetic origin.

The E -value There are multiple ways to estimate the E-value depending on the nature of the biochemical reaction. 82 Under the assumption of a reaction with a single substrate and single product

19



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formation the E-value can be calculated as

E=

A A /KM kcat B B /KM kcat

Eq.(7)

for enantiomers A and B, where kcat is the overall rate of catalysis for a given enantiomer, while KM is the substrate concentration at half of Vmax . However as discussed above, in the case of EH enyzmes the assumption of a single substrate to a single product may not hold. Alternatively the E-value can be calculated using the less model-dependent equations proposed by Chen et al. 83 , based on the relationship between the extent of conversion (c) and the enantiomeric excess of the substrate (e.e.s ) or the enantiomeric excess of the product (e.e.p ). The extent of conversion is an absolute quantity, while the enantiomeric excess is a relative quantity. E=

E=

ln[1 − c(1 + e.e.p )] ln[1 − c(1 − e.e.p )]

Eq.(8)

ln[(1 − c)(1 − e.e.s )] ln[(1 − c)(1 + e.e.s )]

Eq.(9)

The equations using c (Eq.(8) and Eq.(9)) may not be appropriate for reactions involving very low or very high levels of conversion, where accurate measurement is impeded by errors derived from sample manipulation. In such cases, the equation introduced by Rakels et al. 84 would be appropriate as only values for the optical purities of substrate and product need to be measured. E=

p (1−e.e.s ) ln e.e. (e.e.p +e.e.s ) p (1+e.e.s ) ln e.e. (e.e.p +e.e.s )

20


Eq.(10)

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Table 3: Enantioselectivity E-values for WT AnEH and its mutant LW202, calculated using different equations 42,45,46 . Enzyme WT LW202 a b c

Eq.(7) 3 42a 193 42a

Eq.(8) Eq.(10) 4.6 45b 4.6 45bc 113 46c 139 46c

pH 7.2, 30◦ C pH 8, 30◦ C calculated from e.e.p , e.e.s and c values

The use of Eqs.(7, 8 and 10) implies that the regioselectivity of the epoxide ring opening is identical for both enantiomers of a given substrate. 85 The enantiomeric excess of the product depends upon both the regioselectivity of the epoxide ring opening as well as enantioselectivity. 78 Different regioselectivity in the attack on each enantiomer could lead to highly erroneous E-values. To determine the regioselectivity for reactions involving oxirane ring opening by EHs, Moussou et al. 78 has proposed the following equation

e.e.p = αS − αR + (1 − αS − αR ) · e.e.s · (1 − c) · c−1

Eq.(11)

where αS and αR are regioselectivity coefficients corresponding to the fraction of (S) and (R) substrates attacked at the C-1 atom respectively. By measuring e.e.p , e.e.s and c at multiple time-points during a reaction, and plotting e.e.p against e.e.s · (1 − c) · c−1 , one can derive αS and αR through (non-)linear regression. The above equation has been applied and extended upon in a number of experimental studies to interpret potential enantioconvergent reactions. 76,79,86–91

The E-values of WT AnEH and mutant LW202 using different equations and based on different experimental data are shown in Table 3. The variation in the E-values of the WT using the different methods is small, whereas that for the mutant LW202 is significant. It should be noted that small variations in the values of e.e.p and e.e.s can lead to significant variation in the possible E-values at high levels of enantioselectivity. For example, changing the value of e.e.p and e.e.s by ± 1 % would result E-values of ± 50. The discrepancies in E-values derived using different equations for LW202 indicates the possibility of different re21



gioselectivity for each enantiomer of GPE, leading to complex underlying kinetics. Although the E-values for LW202 differ significantly across the methods, it is clear that LW202 exhibits a significant enantiomeric preference for the hydrolysis of (S)-GPE (Table 3) over WT.

Conclusions Here a combination of computational methods, including docking, MD simulations and free energy calculations, have been used to better understand the effects of ligand binding on the enantioselectivity of EHs. As a case study, the reaction between racemic GPE and WT AnEH and its mutant LW202 has been analysed. The MD simulations suggest that both enantiomers of GPE can bind to the enzyme, adopting multiple orientations in the binding pocket including potentially catalytic ones, i.e. where both the sterically hindered carbon (C-1) and sterically unhindered carbon (C-2) atoms within the ring of GPE could be attacked by either of the side chain oxygens (Oδ1 or Oδ2) of the nucleophilic Asp192. Attack at both of the epoxide ring carbons could lead to complex kinetics involving multiple alternative pathways and mean that the use of a one substrate to one product kinetic scheme to analyse the available kinetic data would be inappropriate. The possibility of complex kinetics is further supported by the free energy calculations, which show there is no preference for the binding of either enantiomer of GPE towards both WT and LW202, even when the ligand is restrained in a possible catalytic state. These calculations contrast with the reported KM values that suggest a significant difference in binding free enthalpies for each enantiomer. Collectively, the results from this study indicate that the enantioselectivity of LW202 towards GPE does not arise from thermodynamics of binding but is more likely to originate from a kinetic effect. A result that should be examined and validated in other EH systems using a similar combination of MD and free energy calculations.

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Acknowledgement The authors thank Professor Gary Schenk (School of Chemistry and Molecular Biosciences, University of Queensland) for reviewing the manuscript, and Martin Stroet (School of Chemistry and Molecular Biosciences, University of Queensland) for providing scripts for free enthalpy error analysis. Work undertaken in this study was with the assistance of resources and services from the Queensland Cyber Infrastructure Foundation (QCIF; http://www.qcif.edu.au) and the National Computational Infrastructure (NCI; http://nci.org.au; project m72 and n63), which is supported by the Australian Government.

Funding information Funding to support this study was provided by the Australian Research Council Discovery Project scheme (DP160100865) and by the Australian Government Research Training Program (RTP).

Notes The authors declare no competing financial interest.

Supporting Information Available • Supporting information: List of residues excluded from RMSD calculations, RMSD plots of protein backbone atoms, GPE:protein distance plots, free enthalpy profiles for WT and LW202.

Abbreviations AnEH, Aspergillus niger epoxide hydrolase; ATB, Automated Topology Builder; CAST, com-

23



binatorial active site saturation test; DOPE, Discrete Optimised Protein Energy; EH, epoxide hydrolase; FDA, Food and Drug Administration; GROMACS, GROningen MAchine for Chemical Simulation; GROMOS, GROningen MOlecular Simulation; GPE, glycidyl phenyl ether; ISM, iterative saturation mutagenesis; MD, molecular dynamics; NCE, new chemical entity; PDB, Protein Data Bank; RMSD, root-mean-square deviation; SPC, simple-point charge; StEH, Solanum tuberosum epoxide hydrolase; VPR, valpromide; WT, wild type

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Graphical TOC Entry Vmax

KM

Enantioselectivity *

The Effect of Binding on the Enantioselectivity of an Epoxide Hydrolase Julian Zaugg, Yosephine Gumulya, Mikael Bodén, Alan E. Mark and Alpeshkumar K. Malde

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The Effect of Binding on the Enantioselectivity of an Epoxide

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