Modelling and Predicting Enzyme Enantioselectivity

Send Orders for Reprints to [email protected] Current Biotechnology, 2015, 4, 000-000

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Modelling and Predicting Enzyme Enantioselectivity: The Aid of Computational Methods for the Rational Use of Lipase B from Candida antarctica Valerio Ferrario, Cynthia Ebert, Patrizia Nitti, Giuliana Pitacco and Lucia Gardossi* Dipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Piazzale Europa 1, Trieste, 34127, Italy Abstract: Lipase B from Candida antarctica (CaLB) is one of the most largely employed biocatalysts for the synthesis of chiral fine chemicals. The successful application of this enzyme has also been promoted by advanced computational methods able to simulate enantiodiscrimination at molecular and energy level. Quantitative prediction of enantioselectivity remains a challenging task, affordable by means of sophisticated and rigorous QM/MM methods or by hybrid methods that combine molecular Lucia Gardossi mechanics with experimental data and regression analysis. Most of the methods reported in the literature aim to predict CaLB enantiopreference and to understand the structural basis of enantiodiscrimination. Various experimental problems, such as resolution of alcohols, amines and carboxylic acids, solvent effect, entropic contribution of substrates, are expected to receive beneficial indications from novel advanced computational methods. However, the choice of the appropriate strategy is crucial for success in solving specific problems within a realistic time frame and with a convenient computational cost. In order to be competitive with experimental work, the rational and computational approach should be ideally within a high throughput scheme. Therefore, automation of computational procedures, software and scoring steps represents a new emerging and promising perspective to make the planning of biotransformation more effective and rational.

Keywords: lipase B from Candida antarctica, computational biocatalysis, chirality, molecular mechanics, quantum mechanics, QM/MM, Molecular Interaction Fields, 3D-QSAR. 1. BIOCATALYSIS IN CHIRAL SYNTHESIS: THE PROMINENT CONTRIBUTION OF CALB The rapid expansion of biocatalysis in organic synthesis has been boosted primarily by the increasing demand for enantiomerically pure fine chemicals and pharmaceuticals [1]. One of the most widely studied biocatalysts for its application in enantioselective reactions is, without any doubt, the lipase B from Candida antarctica (CaLB) [2]. This serine hydrolase finds practical applications in the production of chiral secondary alcohols and primary amines and various successful examples of dynamic kinetic resolution processes are also available in the literature [3,4]. CaLB is a serine hydrolase, whose active site includes the catalytic triad Ser105-His224-Asp187. Different studies have pointed out how CaLB behavior is not completely similar to other “tipycal” lipases [5], since CaLB does not display interfacial activation and accepts short chain fatty acids. Overall, CaLB undergoes very limited conformational changes when it approaches a water-lipid interface [6]. The crystal structure of CaLB was reported already 20 years ago [7-10] and the reaction mechanism has been fully elucidated with the help of modelling. The reactions catalyzed by CaLB *Address correspondence to this author at the Dipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Piazzale Europa 1, Trieste, 34127, Italy; Tel/Fax: +39 040 5583110/+39 040 52572; E-mail: [email protected] 2211-5501/15 $58.00+.00

follow a ping-pong bi-bi mechanism: the substrate enters the active site of the enzyme and the first tetrahedral intermediate is formed. Then the first product leaves the active site with formation of the acyl-enzyme. The second substrate enters the active site to generate the second tetrahedral intermediate then the final product leaves the active site and the enzyme is ready for another catalytic cycle (Fig. 1). As in the case of serine proteases, a proton is transferred from serine thus favoring the nucleophilic attack of the acyl carbon by the deprotonated alcohol. The enzyme catalyzes the reaction by stabilizing the negatively charged oxyanion by means of electrostatic interactions between Thr40 and Gln106 inside the so-called oxyanion hole. The rate determining step of the reaction can be either the formation of the acyl-enzyme (acylation) or the deacylation step. In transesterifications of secondary alcohols, the deacylation step is often rate limiting, especially when they are bulky [11]. After the acylation of Ser105, the His224 residue receives a proton from the secondary alcohol. The latter acts as nucleophile by attacking the acylated-seryl ester with the eventual formation of the ester (Fig. 1). CaLB is commonly applied to lipase-catalyzed hydrolysis of racemic esters in aqueous media as well as in O-acylation of racemic alcohols in anhydrous organic solvents [12]. Similarly, CaLB can catalyze the N-acylation of racemic primary amines in anhydrous organic solvents using achiral esters as acyl donors [13,14]. Amidase activity

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Fig. (1). Schematic illustration of catalytic mechanism of CalB for transesterification reaction. The reaction is initiated by the nucleophilic attack of the catalytic serine 105 that forms the first tetrahedral intermediate (TI) and subsequently the “Acylated enzyme”. The nucleophilic attack of a secondary alcohol to the acylated enzyme determines the second TI and then the re-generation of the free enzyme with the contemporary release of the esterified alcohol.

of CaLB is very poor [15] and few examples of hydrolysis of amides in aqueous media are reported [16,17]. In the light of the impact of chiral technologies on the fine chemical market, the availability of methods able to predict quantitatively the enantioselectivity would be of great practical relevance to avoid tedious experimental screening procedures. The present review intends to provide a critical overview of the most relevant computational methods developed in the last decade and that were applied to the rational planning of enantioselective biotransformations catalyzed by CaLB. The advantages of selected methodologies are here presented, along with perspectives for further advances towards a more effective integration of experimental and computational approaches in modern biocatalysis. 2. QUANTITATIVE PREDICTION OF CALB ENANTIOSELECTIVITY: METHODOLOGICAL CHALLENGES Recent advances in computational sciences have led to novel sophisticated and refined methods that are able to describe the bio-catalytic machinery of enzymes in detail. The wide number of investigations addressing CaLB structural and catalytic properties have promoted some major advances in this field [10,11,19,21]. Generally speaking, the in silico quantitative prediction of enantioselectivity of any enzyme is still a formidable goal

to achieve. For example, at 318 K, a computational error of just 1.83 kJ/mol would make the E value twice as high (from E = exp[-ΔΔGS-R/RT]). Solutions to experimental problems can be found within different time frames and accuracy levels, which depend on the computational techniques used (Table 1) [18]. There are two major computational approaches for the quantitative or semiquantitative prediction of enzyme enantioselectivity and they have been applied to the study of CaLB enantioselectivity. The first approach aims at calculating differences in energies between the fast- and slow-reacting enantiomers [19,20]. Indeed, the kcat/KM ratio depends on the free energy of activation (∆G‡) of the transition state (TS) of the reaction. Quantum Mechanic methods (QM), which are based on the solution of the Schroedinger equation, are able to model the formation and breaking of bonds in the transition state with the necessary level of accuracy but they are computationally too expensive to be applied to the simulation of such large molecular systems and used as a routine prediction tool. Therefore, enantioselective enzymatic reactions have often been examined by theoretical approaches involving Molecular Mechanics (MM). This approach, however, often produces unacceptable predictive errors owing to the great number of assumptions and approximations necessary to implement the computational procedure [10,21,22,23].

Modelling and Predicting Enzyme Enantioselectivity

Table 1.


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Examples of computational approaches used for modeling the enantioselectivity of CaLB. Each listed approach is briefly described in terms of predictivity (qualitative or quantitative) and the type of output obtained. Finally, the experimental problems treated by each method are reported along with the corresponding references. Computational Method

Output

Substrates Addressed by the Study

Reference

QM/MM

Quantitative estimation of ∆∆GS-R of activation and entropic contribution to enantio-discrimination

Resolution of phenylethanol (ester hydrolysis)

[11]

MD simulations + Molecular Interaction Field descriptors (dMIFs) + PLS analysis correlating experimental data

Quantitative: E values for new couples of enantiomers provided that structural and statistical analysis is performed and mathematical (regression) model applied

Chiral secondary alcohols and chiral 1arylethylamines (esters and amide synthesis in neat reagents)

[19]

MD simulations + Molecular Interaction Field descriptors (dHMIFs) + PLS analysis correlating experimental data

Quantitative: ∆∆H‡S-R and ∆∆S‡S-R ; E values for couples of enantiomers

Resolution of chiral secondary phenyl alcohols in ester synthesis

[55]

Co-crystallization of analogues of TS + MD simulations analysing the frequency for NACs (Near Attack Complex)

Qualitative enantiopreference prediction

Resolution of chiral phenylethylamines in amide synthesis reactions

[58]

∆∆G‡S-R and enantiopreference predictions

Resolution of chiral aliphatic secondary alcohols in ester synthesis reactions

[25]

QM/MM simulations for each TI + analysis of frequency NACs (Near Attack Complex)

Qualitative enantiopreference predictions

Acetylation of propranolol

[36]

Docking + energy minimization + multi-step refinement of the procedures

Qualitative enantiopreference predictions (docking scores)

Methyldecanoic acid butyl esters

[37]

MD simulations and potential energy estimation

Qualitative enantiopreference predictions

Esterification of 3-methyl-2-butanol with aliphatic carboxylic acids

[23]

Docking + Molecular Interaction Field descriptors + PLS statistical analysis of experimental data

E values for each couple of enantiomers provided that structural and statistical analysis is performed and mathematical (regression) model is applied

Resolution of chiral carboxylic acids

[49]

(Empirical Valence Bond Method)

MD simulations + Free Energy Perturbation

Quantitative evaluation of

The potential advantages of QM and MM have also been combined in the QM/MM approaches. The method simulates the enzyme active site and the substrate at high theory level (QM), whereas the rest of the system is simulated by MM theory level, in order to take advantage of the accuracy of the QM calculation and reduce the computational cost for the rest of the simulated system [24]. More frequently, studies make use of simplified docking, MD and QM/MM approaches to provide useful insights into structural basis of CaLB enantiodiscrimination rather than producing quantitative predictive models [23]. Another approach that has been used for the analysis of differential energetic contributions between two specific enantiomers in CaLB catalyzed reactions is based on Free Energy Perturbation (FEP) [25]. FEP represents a particular MM approach based on measurements of the progressive transformation of the system from an initial state to a final state, usually by following a non-physical (often coined alchemical) path. Throughout this process, free energy variations are measured. Consequently, FEP calculations provide both internal energy and entropy contributions to the free energy. A second group of methods used to predict CaLB enantioselectivity involves the construction of mathematical models that correlate structural properties of enantiomers with experimentally determined data (e.g. e.e. % or enantiomeric ratio E) [19,26]. These hybrid approaches exploit molecular descriptors to extract relevant structural

information from the enantiomers and then they use regression analysis to construct the predictive models. Therefore, the methods are not intended to calculate energies but rather to generate models that “learn” from “training sets” of structures and experimental data. The predictive ability of these approaches strongly relies on the type and variability of information contained in the training set as well as on the reliability of the data. Table 1 provides specific examples of applications of the computational methods cited above to the study and prediction of CaLB enantioselectivity. 3. BEYOND “KAZLAUSKAS RULE”: UNDERSTANDING STRUCTURAL BASIS OF CALB ENANTIOSELECTIVITY An issue that has played an important role in the discussion of the selectivity of CaLB is the nature of the binding modes of secondary alcohols [8,10,21,25,27-33]. The empirical Kazlauskas rule [34] has been used to assess the most likely binding mode of the fast-reacting enantiomer (Fig. 2). The rule, also confirmed by experiments [35,36], suggests that CaLB has a clear preference for the (R)enantiomer of bulky chiral secondary alcohols, such as 1phenylethanol. The enantiopreference of CaLB is mainly determined by the bulkiness of Trp104 inside the so-called stereospecificity pocket [8]. In general, the most stable binding mode has the large sized substituent pointing towards the active site entrance (Fig. 2) whereas the medium size substituent is located inside the stereospecificity pocket [11].

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Fig. (2). Schematic representation of the Kazlauskas rule. The represented binding model elucidates the structural reasons of CaLB enantioselectivity towards secondary alcohols, where the Trp104 is the main responsible for creating the steric constraints that translate into the CaLB stereospecificity pocket.

Nowadays, the integrated use of novel computational methods pushed biocatalysis beyond empirical rules and towards a more rational and effective approach for designing CaLB biocatalyzed reactions. As discussed above, in most cases MM based computational tools provide qualitative or semiquantitative evaluation of CaLB enantioselectivity towards enantiomers. Nevertheless, molecular modelling techniques can be useful in predicting the stereochemical course of reactions and they provide insight into potential substrate or enzyme modifications that may increase selectivity [37]. Different computational approaches can be applied to the analysis of the structural/energetic contributions that are at the basis of enantiodiscrimination. Energy differences between two enzyme-enantiomer systems can be evaluated by MM approaches based on specific force-field definition, in other words by using high approximation levels. In the case of CaLB, a serine hydrolase, the Tetrahedral Intermediate (TI) is often used as a model of the Transition State (TS) and the enthalpic contribution for the stabilization of the two enantiomeric TI’s is evaluated and compared (Fig. 3). In the case of transesterifications of secondary alcohols, the deacylation step is generally rate limiting, especially in the case of chiral bulky secondary alcohols [11]. The model for TI is generally constructed after docking the substrate inside the active site following the formation of the covalent bond with the enzyme. Minimization algorithms are often applied in order to search for potential energy minimum of the molecular system, which will constitute the starting point for subsequent Molecular Dynamics (MD) simulations. MD simulations are performed to explore the conformational possibilities of a molecular system within a defined time frame. The trajectories of the atoms provide information on the conformational behavior of the model before reaching an equilibrium state. Such information can be exploited in order to select (sampling) most frequent conformers, which are expected to be also the most representative and stable. However, this choice implies that enthalpies are calculated only for such selected conformations and, therefore, the extension and frequency of the sampling procedure will affect the reliability of the final energetic outcome. Overall, this procedure does not take into account entropic

contributions and therefore it does not provide an estimation of ∆∆G‡.

Fig. (3). Example of Tetraedral Intermediate (TI) docked into the active site of CaLB and covalently bound to the catalytic Ser 105. In the case of R-phenylethanol acetate, the corresponding TI (TI 2; See Figure 1) is stabilized by hydrogen bonds with Thr 40 and Glu 106. The stereospecificity pocket is delimited by Trp 104.

A particular refinement of this approach was provided by Raza et al. [23] who examined the enantioselectivity of CaLB with different couples of enantiomers (3-methyl-2butanol, 2-butanol and 3,3-dimethyl-2-butanol). By using a non-minimized structure, the Authors intended to “expand” the conformational possibilities and consequently to gain a more accurate description of conformational freedom of the system, which, indirectly, is related to entropic contributions. This kind of approach succeeded in the prediction of the fast reacting enantiomers for the substrates considered [23]. In the work of Escorcia et al. [38] the moderate enantioselectivity observed in the acetylation of (R,S)propranolol, was analyzed by a non-conventional QM/MM approach. In this case, the QM/MM approach was employed for the study of the complexes between acetylated CaLB and the two enantiomers. QM/MM simulations of 1.5 ns were performed to evaluate interatomic distances which are


crucial to form near attack conformations (NACs) and thus generate the tetrahedral intermediate. More in detail, NACs correspond to conformers in which the atoms involved in bond formation are at van der Waals distance. At the same time, the angle of approach of the atoms must be ±15° with respect to the angle of the bond formed in the transition state (TS). A numerous population of NACs indicates that low free energy changes are required to reach such NACs. Therefore, the population of NACs provides an indirect idea of the reaction rate. The NAC analysis reveals that reactive complexes of R-propranolol present a better ability to be transformed by CaLB than those of S-propranolol. Another methodology, which provided qualitative information about CaLB enantiopreference, is related to the application of substrate-imprinted docking described in the work of Juhl et al. [39]. The method combines covalent docking, geometry optimization, and geometric filter criteria to identify productive substrate poses. The enantioselectivity of CaLB towards 1-phenylethyl butyrate was analyzed and compared with the behavior of CaLB mutant W104A because the latter presents a larger stereospecificity pocket [8], thus inducing a lower enantiodiscrimination. The substrate-imprinted docking procedure consisted in molecular docking of enantiomers and filtering of productive poses according to geometric criteria. Then, the tetrahedral intermediates for the two enantiomers were constructed and optimized through energy minimization. The substrates were finally removed from the 3D models and the resulting geometrically-optimized protein structures were used for a second round of docking and construction of the covalent TI. The resulting docking poses were filtered according to the geometric criteria and classified by applying a scoring function accounting for potential energies of binding. The method was validated experimentally, and resulted particularly accurate for modelling substrate specificity but less accurate for modelling enantioselectivity. Acylation of enantiopure butan-2-ol and pentan-2-ol catalyzed by CaLB was studied by Chaput et al. [25] using Free Energy Perturbation (FEP) as a methodology for free energy calculation. FEP theory is a method based on statistical mechanics that is used in computational chemistry for computing free energy differences from Molecular Dynamics [40] and, more specifically, in this case it was applied to the evaluation the ∆∆G‡ between the MD simulations of each couple of enantiomers. The FEP calculated ∆∆G‡ were experimentally validated. 4. CALB RESOLUTION OF SECONDARY ALCOHOLS: QUANTITATIVE EVALUATION OF ∆∆GS-R‡ OF ACTIVATION During the last 40 years, rigorous Quantum Mechanic (QM) based computational methodologies have been developed and applied for the investigation of the physicalchemical features, thermodynamic parameters and electrostatic contributions of enzyme active site, in order to fully understand the source of the catalytic power of enzymes. As discussed above, QM simulations result to be very expensive in terms of computational so that the enzyme system is usually QM defined just in its catalytic machinery or in a limited portion of the enzyme corresponding to the


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active site, while the remaining part of the system is defined with Molecular Mechanic (MM) theory level [18]. Recent studies on CaLB enantioselectivity [11] have demonstrated the potential and robustness of QM/MM approaches. In fact, since such strategies involve extensive sampling, they can evaluate the actual activation free energies, as they are able to explore entropic effects and more realistic relaxations of the active site. The study of Schopf and Warshel [11] addresses the issue that energy minimization strategies are unlikely to allow for proper relaxation of the protein steric forces because approaches that do not involve extensive sampling are unlikely to give stable results. The computational method developed by Schopf and Warshel [11] involve calculation of the activation free energies by means of Empirical Valence Bond (EVB) method. The method was able to calculate ∆∆G‡ for the reactions and computational results were validated, by considering both kcat and kcat/KM of the R and S stereoisomers. The study started from the simulation of an ester hydrolysis catalyzed by wild type and mutants of CaLB. It was focused on the challenge of dealing with strong steric effects and entropic contributions. The method required very extensive sampling for convergence but gave encouraging results and proved its validity particularly in showing large changes in steric effects and for which alternative approaches may have difficulties in capturing the interplay between steric clashes with the reacting substrate and protein flexibility. The EVB method [41] is an empirical Quantum Mechanics/Molecular Mechanics (QM/MM) method [42-45] that can be considered as a mixture of diabatic states describing the reactant(s), intermediate(s), and product(s) in such a way that it retains the correct change in structure and charge distribution along the reaction coordinate. In that manner, this method provides an effective way for evaluating the reaction free energy surface, as it drives the system from the reactant states to the product states in a “free energy perturbation umbrella” sampling procedure [46]. The reason for the remarkable reliability of the EVB is that it is calibrated on the reference solution reaction. Therefore, the calculations for the enzyme active site only reflect the change in the environment, taking advantage of the fact that the reacting system is the same in both the enzyme and solution. Thus, the EVB approach is calibrated only once in a study of a given enzymatic reaction. In their study, Schopf and Warshel [11] used the states and the parameters necessary to generate the surfaces of the reaction in solution by using the available experimental information on the reactions studied for calibration. They were kept unchanged for the generation of the protein EVB surface. The Authors also concluded that further studies should focus on the change in entropy with the change in solvent as this remarkable effect may give interesting clues on the role of organic solvents in catalysis. 5. MOLECULAR DESCRIPTORS AND 3D-QSAR MODELS FOR QUANTITATIVE PREDICTION OF CALB ENANTIOSELECTIVITY Recent advances in computer sciences have led to sophisticated and refined molecular descriptors able to

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describe quantitatively the features of target molecules and macro-molecules [20]. A molecular descriptor is the final result of a logic and mathematical procedure that transforms chemical information encoded within a symbolic representation of a molecule into useful numbers. That makes possible to analyze and compare, without any bias, a series of different objects or molecules of a dataset for the investigation. Different kinds of molecular descriptors are currently available and they are classified according to the type of information enclosed in the descriptor [47]. Descriptors based on Molecular Interaction Fields (MIFs) [48] constitute a particular class of descriptors that have been originally developed for drug-design applications. In that context, the final goal is to increase the energies of interactions between the targets, which are usually a protein receptor and a candidate drug. Molecular Interaction Fields (MIFs) consist in interaction energies computed considering a molecule and a small chemical probe, which can be represented by a chemical functional group. Various probes (Table 1) have been conceived for computing interactions of different nature and several computational methods are available for calculating the molecular interaction fields. In the case of the GRID method [48] energies are calculated in all the nodes of a three-dimensional grid, which spans the structure of the target considered (Fig. 4). The computed interaction energies form the Molecular Interaction Field (MIF), which can be visualized as an isopotential surface. The most relevant probes take into account hydrophobicity (DRY probe), hydratability (WATER probe), H bond donor (O probe representing carbonyl oxygen) and H bond acceptor (N probe, representing an amide nitrogen). Finally, also the global shape of the target molecule can be computed by means of the H probe. It must be underlined that three-dimensional molecular interaction fields contain in general a large amount of data, some of which are redundant or not relevant for a given problem. Therefore, specific algorithms and statistical tools are required to extract relevant descriptors from extensive data matrixes of MIFs. Although MIF-based descriptors were originally conceived for describing molecular recognition and affinity, a recent evolution of the methodology has demonstrated that MIF-based descriptors can also be used for the identification and quantification of interactions that stabilize the relevant Transition State (TS)

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of reactions catalyzed by serine hydrolases [5]. MIF-based descriptors have been applied also to the investigation of CaLB enantioselectivity against a set of amines and alcohols. More specifically, the information contained in the molecular descriptors has been correlated to experimentally determined data (e.g. enantiomeric ratio E) by applying the Partial Least Square (PLS) analysis, where the Y latent variables are correlated to X latent variables [49]. These new latent variables or components were extracted to give the best fit of both Y and X variable matrices [49]. The resulting mathematical models correlated structural feature to chemical properties and are assimilable to the well-known 3D-QSAR models, widely used to predict drug activities. However, in order to predict CaLB enantioselectivity, the method combined molecular descriptors with PLS analysis to construct mathematical models that “learn” from robust “training sets” of structures and experimental data. The methodology is able to predict quantitatively enzyme selectivity because the information related to the free energy of activation is accounted by the model through the set of experimental data. Consequently, the approach overcomes the problem of the calculation of free energies of activation but at the same time the predictive ability strongly relies on the type and variability of information contained in the training set as well as on the reliability of the data. It must be underlined that enantioselectivity is generally expressed quantitatively by the experimentally determined enantiomeric ratio E [50], a single quantitative parameter related to a couple of enantiomers. Therefore, the molecular descriptors must merge information contained in the MIFs of both enantiomers. Such descriptors called “differential Molecular Interaction Fields” (dMIFs) [19] were generated and validated on the basis of a training set constituted by seven racemic amines and twelve racemic alcohols and the corresponding values of enantiomeric ratio (E) measured experimentally in the enzymatic acylations [23,32]. The calculation of dMIFs was performed in a matrix differential procedure where each variable of the MIF of the slowreacting enantiomer was mathematically subtracted from the corresponding variable of the MIF of the fast-reacting enantiomer (i.e. dMIF=MIFR-MIFS). This procedure led to the quantitative evaluation of the differences in interactions between the two enantiomers and the enzyme active site. The construction of the 3D-QSAR model involved the following

Fig. (4). Schematic illustration of the GRID computational method. Interaction energies between a chemical group (PROBE) and each GRID node that spans the structure (or a selected part of that) of a target molecule. The matrix of the interaction energies forms the so-called Molecular Interaction Field (MIF), which is represented as isoenergy surfaces. In this example the target is represented by the acetate ester of R-phenylethanol. The figure illustrates the MIF calculated using a hydrophobic probe.



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Fig. (5). Illustration of the logical operations necessary for the calculation of the differential MIF descriptors (dMIF), generation of the 3DQSAR model by PLS analysis and the quantitative correlation between the E values and the structural properties of enantiomers.

four step protocol: a) definition of the training set and refinement of the structures of both the enzyme and the substrates; b) docking of the substrates, construction of the TI’s and calculation of the active conformers inside the active site and equilibration by MD simulations; c) generation of the molecular descriptors for the couples of enantiomers by means of GRID analysis and dMIFs calculation; d) multivariate statistical analysis of the data and generation of the mathematical predictive model by PLS analysis (Fig. 5). The model was tested against a validation set of couples of enantiomers demonstrating a predictivity coefficient q2 of 0.78 (generally, a q2 > 0.6 is considered an indicator of acceptable predictivity). From the inherent nature of the regression models, it derives that they are able to predict the effect of a variable (e.g., a specific structural feature of a molecule) as long as such a variable is somehow represented in the training set. Consequently, models that are based on training set of structurally homogeneous molecules are expected to have an excellent predictivity but only with respect to molecules that fall within the structural features accounted by the training set.

Concerning the time scale of the whole computational procedure, a whole PLS model including a data set of about 20 compounds, can be developed in about one week using standard low-end computational facilities; once the model is available, screening of substrates requires approximately one hour per molecule. However, times can be heavily reduced by increasing the computational power, since the conformational analysis represents the most time-consuming step of the protocol. A similar approach was also applied in a study aiming at the evaluation of the acyl donor contribution to CaLB enantiodiscrimination [51]. As in the above described methodology, each enantiomer was accommodated into the CaLB active site and the TI’s were generated for the different substrates. Molecular descriptors were used for analyzing and merging the information contained in each couple of enantiomers. Finally, structural features were correlated with the enantiomeric ratio E to obtain a QSAR model. Results indicated that the role of acyl donors in CaLB enantiodiscrimination remains less defined as compared to nucleophilic counterpart [51]. Nevertheless, the QSAR statistical model allowed for the identification of variables

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and interactions affecting the enantiodiscrimination inside the CaLB structure. Residues responsible for these specific interactions were localized and suggested as possible hot spot targets for rational mutagenesis of CaLB. 6. ENTROPIC CONTRIBUTION TO CALB ENANTIODISCRIMINATION: SUBSTRATE EFFECTS As discussed in section 4, entropic contribution plays an important role in determining enantiodiscrimination especially when steric constraints are involved in the binding of the substrates. However, computational evaluation of entropic contribution to enzymatic catalysis still appears a quite complex task. Some studies supported the idea that the binding of a substrate in the enzyme active site freezes the motion of the reacting fragments and minimizes their entropic contributions to the energy of activation. Villa et al. [52] confuted this approach by demonstrating that the reacting moieties of substrates maintained some mobility even after the formation of the enzyme-substrate complex. Although the inclusion of entropy in protein modelling remains a challenge, some very rigorous approaches have been published [42, 52] which are based on the comparison of the enzymatic reaction with the same reaction in solution without any catalyst. The contributions of differential activation enthalpy and entropy to enantioselectivity can be experimentally evaluated by calculating the dependence of E on temperature, namely by carrying out each resolution reaction at different temperatures. Phillips and coworkers [53] had investigated the effect of temperature on enzyme enantioselectivity already in the late ‘80s but, more recently, the group of Karl Hult focused attention on entropic contribution to enantiodiscrimination in different reactions catalyzed by CaLB. In some pioneering works [21,28,35,54-56] the enantioselectivity of CaLB was studied by analyzing the substrate- and solvent-related component of activation entropy. More specifically, a series of secondary alcohols were examined in transesterification reactions with vinyl octanoate to understand the spatial freedom of the substrate in transition state as well as the roles of enthalpy and entropy on a molecular level. The five substrates investigated all showed entropic terms of differential activation free energy, whose values are 25% to 60% of the enthalpic term, thus confirming the importance of entropic contribution. The experimental data indicated a temperature dependence of the enantiomeric ratio E, showing that the enthalpic and entropic components of the differential activation free energy are both important to the success of the kinetic resolution catalyzed by CaLB. The molecular dynamics (MD) simulations performed during 500 ps allowed an evaluation of the tetrahedral intermediate fast-reactive and slow-reactive structures. Their number varied dramatically between enantiomers as well as between different substrates. The accumulated volumes in the active site that the tetrahedral intermediate of the R-enantiomer occupied during the MD simulations were larger when compared to those of the Senantiomer. In another approach, the volume within the CaLB active site accessible for the substrate was systematically searched

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by incremental rotation of bonds. From a conceptual point of view, the volume in the active site occupied by the substrate during an MD simulation is an indication of the spatial restrictions suffered by the substrate that, ultimately, translate into entropy variations. Therefore, the calculation of the accessible volumes by systematic searches allowed for the identification of the preferred enantiomer, which was characterized by larger accessible volume and higher TS entropy. However, a lack of correlation between TS entropy and substrate accessible volume could also mean that simulation times were not sufficient to fully explore the entire conformational space accessible to the substrate. The same studies inspired the development of new molecular descriptors for the quantitative description of entropic contribution to enzyme enantioselectivity, which were validated [57] using experimental data previously produced by Vallin et al. [33] using a CaLB mutant [33]. That study reported about the CaLB mutant W104A where the bulky Trp residue was replaced by the smaller Ala. Data on the kinetic resolution of bulky secondary alcohols catalyzed by CaLB mutant W104A are available from the same study. The mutation causes an enlargement of the socalled stereospecificity pocket and, consequently, an increase of the conformational freedom of substrates inside the active site (Fig. 6). According to Villa et al. [52], the entropic contribution to catalysis is related to the mobility of the reacting fragments of substrates after the enzyme-substrate binding. The new molecular descriptors (“differential Hybrid Molecular Interaction Fields” or dH-MIFs) developed in the study of Ferrario et al. [57] are based on the concept that entropy is correlated with the conformational freedom of the tetrahedral intermediate (TI) of the reaction catalyzed by CaLB. Molecular dynamic simulations (MD) provided the information on the conformational freedom of the tetrahedral intermediate (TI) of the reactions and GRID analysis gave a description of the chemical features of each relevant conformer in terms of Molecular Interaction Fields (MIFs). Finally, for each enantiomer the “average” MIFs were calculated obtaining the H-MIF descriptor that summarizes the information coming from the relevant conformers. Partial Least Square analysis was used to correlate the descriptors to the experimental data available from the literature and the good fitting and predictivity of the mathematical models (one for each temperature) demonstrate that the new molecular descriptors can be used effectively for correlating the structure of substrates with CaLB enantioselectivity. Variables responsible for the differential free energy of activation were visualized into the CaLB mutant active site: interestingly, all variables were localized in the tunnel that leads to the stereospecificity pocket whereas the oxyanion hole and the acylic pocket [8] play a secondary role in enantiodiscrimination. Therefore, the localization of the variables allows identification of mutation hotspots that will affect stereoselectivity by changing g the entropic contribution and ultimately E. Another interesting aspect is the presence of several variables inside the stereospecificity pocket, which suggests the possibility of establishing interactions with a water molecule.



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residual mobility, reducing the enthalpic advantage of the fast-reacting substrate and leading to a reduced enantiopreference. 7. SOLVENT EFFECT ON CALB ENANTIOSELECTIVITY

Fig. (6). The entrance of the stereospecificity pocket. The enzyme surface of the CaLB mutant W104A is highlighted in pink. The tryptophane 104 of the wild type CaLB (highlighted in green stick mode) restricts the space available in the pocket. The figure illustrates how the mutation W104A increases the space for bulkier nucleophiles.

The role of water molecules inside CaLB active site was also mentioned in the study of Leonard et al. [58, 59], who discussed the possibility that water molecules cause a reduction in degree of freedom of the system and, ultimately, a difference in entropy. A rigorous example of investigation employing TI definition is reported by Bocola et al. [60], who studied the resolution of 1-phenylethylamine using a CaLB that had been preacylated with an ethoxyacetyl group. Under nonaqueous conditions, the amine nucleophile attacks the acyl enzyme to produce the corresponding amide. Combined kinetic and crystallographic investigations together with computer simulations allowed the elucidation of factors responsible for enantiodiscrimination. A study on the temperature dependence of the enantiomeric ratio E between 20 and 90 °C revealed that the fast-reacting substrate is enthalpically favored over the slow reactive one. Methyl phosphonate analogs of the transition states of the reactions were co-crystallized with CaLB and the accessible space for each of the enantiomers was explored within the binding pocket [60]. The crystallographic observations explained the enthalpic advantage of the fast-reacting (R)-amine as a result of the nearly perfect fit into the binding pocket of CaLB. Numerous favorable van der Waals contacts and the formation of ideal hydrogen bonds immobilize and stabilize the TS in an orientation productive for the reaction. On the other hand, the interactions that stabilize the TS induce a pronounced decrease in motional degrees of freedom, so that binding of the TS would be entropically disfavored. The slow-reacting substrate shows significant residual mobility in its transition state so that less entropy is lost upon binding. However, the residual mobility in the binding pocket corresponds to less stabilizing contacts in the transition state. Accordingly, the substrate resides less frequently in an orientation productive for the enzyme reaction and profits less from favorable enthalpic interactions. Consequently, an increase in the reaction temperature would result in higher

When enzymes are stable and active in organic solvents this choice may be an alternative to classical chemistry. Actually, this is the case of many lipases, among which CaLB [61, 62]. However, since the solvent strongly affects enzyme properties, such as specificity and stereopreference [56, 63-66], solvent engineering can be regarded as a valid alternative to other more uncertain and expensive methods such as, for instance, protein engineering. The most studied solvent feature, which is considered to affect enzyme enantioselectivity, is solvent hydrophobicity, measured as logP, where P is the partition coefficient of the solvent between octanol and water. However, this correlation is not always predictable. In addition to this, dipole moment and dielectric constant [67] have been found to be correlated with E. An accurate investigation on the CaLB catalyzed resolution of 3-methyl-2-butanol in eight liquid organic solvents and supercritical carbon dioxide allowed K. Hult and coworkers [54] to conclude that the size of the solvent molecules might be one of the parameters that governs the enzymatic resolution of a chiral reagent. Actually, the discrimination between the enantiomers by the enzyme is determined by the steric difference between the enantiomers in their respective transition state. The interactions of enantiomers with solvent molecules are quite different for the enantiomers in the transition state and that translates into entropic and enthalpic activation energy differences. Consequently, ΔΔS of activation between the enantiomers can in part result from different displacement of solvent from the active site. The number of solvent molecules involved in the solvation of the active site may be different for the enantiomers and entropic activation energy differences should depend on the size of the solvent molecules. The relevance of entropic contribution to enantiodiscrimination was also pointed out in studies of enantioselective synthesis of caffeic acid esters catalyzed by immobilized CaLB (Novozym® 435) [68]. Kinetic, thermodynamic and chemometrics were combined in an interesting study of the reaction between caffeic acid and racemic alcohols. Kinetic investigations were performed using the Ping Pong Bi−Bi mechanism. Thermodynamic analyses were aimed at investigating the enzyme-catalyzed enantioselective mechanism and the effect of the alcohol on enantioselectivity. The solvent parameter considered was hydrophobicity measured as logP and the resolution succeeded with all solvents characterized by logP > 2.5. Results indicated that both −ΔΔH and −ΔΔS were important for enantiomer discrimination, and −ΔΔH was dominant in the reaction. These differential parameters varied with the chain length of alcohols, showing a decrease in amount with increase of carbon chain, effect also confirmed by kinetic studies. KM and kcat values for (R)- and (S)-alcohols were also different. The data indicated a higher affinity of the CaLB active site for (R)-alcohols, so that (R)-caffeic acid esters were the main products. Interestingly, the Authors used Response Surface Methodology (RSM) with a central

10


composite rotatable design (5-level-4-factor CCRD), to evaluate the effect of major independent parameters (reaction temperature, reaction time, substrate molar ratio of caffeic acid to (R,S)-2-pentanol and the enzyme additive amount) on two dependent variables (conversion (%) and e.e. (%)). The RSM procedure and Design-Expert 7.0 software were employed for the calculations. As an example, predicted optimal values for the above mentioned parameters were: reaction time = 52 h; reaction temperature = 67 °C; molar ratio of caffeic acid/2-pentanol = 1:21; enzyme additive amount of 50.8 mg. By using this integrated methodology, Authors identified optimal experimental conditions corresponding to predicted values of > 99% e.e. and 31% of conversion, values in accordance with the experimental findings. The effects of solvent and other reaction parameters were studied in an investigation addressing the enantioselective esterification of racemic naproxen catalyzed by CaLB. [69] The study was aiming at verifying the advantages of Super Critical CO2 (SCCO2) over other solvent conditions (vacuum, water, hexane and supercritical carbon dioxide) using both experiments and simulations. In this study, the dielectric constant ε of solvents was used as a key property because of the exceptionally low ε value of SCCO2 when compared to those of organic solvents such as water and hexane. Thus, using different values of dielectric constants, the activation energy and conformational stability of the esterification reaction in supercritical carbon dioxide were compared with those of the molecular simulation in each solvent. The molecular dynamics simulation explained the (S)-enantioselectivity of the lipase on the basis of binding energy and structural characteristics and verified that under supercritical conditions yields and reaction time were higher as compared to other solvent conditions. A study of CaLB-catalyzed hydrolysis of racemic 2methylalkanoyl-3-(2-pyridyl)pyrazoles to obtain (R)- or (S)2-methylalkanoic acid demonstrated the importance of water content and solvent hydrophobicity on the enthalpic and entropic contributions [70]. Using the heptanoyl chain as a model system the Authors could find the best reaction condition of CaLB-catalyzed hydrolysis in water-saturated methyl t-butyl ether (MTBE) at 35 °C (enantioselectivity VR/VS > 100). Kinetic analysis for all substrates indicated that alkanoyl chain length was also critical for enantiomeric discrimination. A thermodynamic study of the CaLBcatalyzed methanolysis of (R,S)-β-butyrolactone led to the conclusion that the enantiomer discrimination for the TS’s of both enantiomers was entropy driven within the temperature range investigated [71]. In parallel, a kinetic study revealed that both the methyl ester product and methanol were inhibitors for the enzyme, which induced the Authors to follow a feed-batch procedure. 8. CALB APPLIED TO THE RESOLUTION OF RACEMIC CARBOXYLIC ACIDS As discussed so far, CaLB is largely employed for resolution of chiral secondary alcohols and primary amines and the alcohol pocket (or more generally the nucleophile pocket) is responsible for the enantiodiscrimination. Kazlauskas’s rule as well as all QM, MM, QM/MM studies

Ferrario et al.

and 3D-QSAR models have been mainly focused on the structural features of the nucleophile pocket. CaLB shows low to modest enantioselectivity toward carboxylic acids, and this issue has been extensively reviewed by Tsai [72]. Its behavior has been attributed to fewer and/or weaker interactions between the substrates and the wider acyl-binding site, in contrast to the remarkable enantiopreference for secondary alcohols and primary amines displayed by the narrower nucleophile pocket. In that respect, it is of particular relevance the study of Kwon et al., who used simplified QM calculations to calculate the reaction pathway energies for the resolution of racemic cis-4-acetamidocyclopent-2-ene-1-alkyl esters, a precursor for the synthesis of aristereomycin that bears two chiral carbons (Fig. 7) [36]. The hydrolysis of esters having different alkyl chains (methyl to n-hexyl) was considered. The substrates were optimized through minimization and semiempirical PM3 method [73] was used to study the reaction pathway starting from a simplified model of the CaLB catalyzed reaction. Nevertheless, rigorous ab-initio calculations were performed using the GAUSSIAN software to validate the minimum and maximum energy points obtained through the simplified approach of the whole reaction pathway. Molecular Dynamics simulations were also performed starting from the transition state obtained through QM calculations. Ping-pong mechanism was applied and energies as well as binding configurations were computed. Calculations showed that the alkyl chain exerts a very small influence whereas the conformations played a major role. Results were validated by the experimental studies of the hydrolysis of (±)-cis-4-acetamido-cyclopent-2ene-1-ethyl acetate and showed a qualitative agreement with computational data since a higher formation of the (–)stereoisomer was detected.

Fig. (7). Representation of the racemic cis-4-acetamidocyclopent-2ene-1-alkyl esters.

In order to overcome the low enantiodiscrimiation of CaLB towards the acyl mojety, various approaches via substrate, medium, and/or enzyme engineering approaches have been used [74,75]. An experimental and computational study focused attention on the desymmetrization of diesters (prochiral dialkyl 3-isobutylglutarates) and evaluated the effect of the alkyl group [76]. The diallyl esters showed the highest selectivity leading to the monoester product (100% conversion) with 93% e.e (Fig. 8). To determine the role of the olefinic chain in the binding at the active site of the CaLB enzyme, the first tetrahedral intermediate (subsequent to the attack of Ser105 to the acyl groups) for both diallyl and dipropyl 3-isobutylglutarate was investigated by MD simulations. Four different tetrahedral intermediates (for the fast and slow enantiomers) were generated and the study focused attention on atomic distances, bond angles, and hydrogen bonds. Interestingly, new descriptors including the non-bonding interaction distances and the T1 torsional angle



11

Fig. (8). Resolution of dialkyl 3-isobutylglutarates catalysed by CaLB.

around the C=O carbon were considered. The MD study suggested that relevant π–π interactions between the olefin of the allyl derivative and Trp104 and His224 side chain are present. The differences of the torsional angles between the fast-reacting enantiomer and the slow-reacting enantiomer were much larger in the case of the allyl ester, thus confirming an “olefin effect” between the substrate and the enzyme. The role of the acylic pocket has been elucidated in different investigations, in some cases showing important effects on the reaction course. For instance, a study dealing with the resolution of 7-, 8-, 9-, and 10-hydroxystearic acids (HSAs) [77] in the presence of vinyl acetate demonstrated that the Kazlauskas’ rule cannot be applied to predict the enantioselectivity of the reactions. That is the consequence of the structural anomaly of hydroxystearic acids, which present the chiral carbon atom on a distal position with respect to the acyl moiety. By applying the 3D-QSAR approach cited in section 5 [19], the (R) enantiopreference was predicted but a quantitative reliable estimation of enantioselectivity was not possible due to extreme structural difference of hydroxystearic acids as compared to the training set used for the QSAR model. Interestingly, the docking of the substrate ground state into the alcohol pocket was unable to produce reliable poses consistent with catalysis because HSAs are characterized by a high number of rotatable bonds. The resulting conformational freedom caused the substrates to get coiled in the funnel shaped active site, thus producing no pose. Attempts to modify the placement algorithm failed basically because, in agreement with the CaLB biological role, the carboxylic group is better accommodated in the acylic pocket rather than in the alcohol pocket. It must be noted that both chains bound to the alcohol moiety are too long and bulky to be accommodated freely inside the stereospecificity pocket. Indeed, hydroxy fatty acids are acylated very slowly by CaLB due to the preferred fitting of the carboxyl group into the acyl pocket of the enzyme. Interestingly, the MD relaxation showed some enlargement and conformational adaptations of the active site funnel for accommodating such bulky substrates. Therefore, the substrate recognition occurs according to different criteria as compared with “normal” alcohols because in the case of HSAs the OH group can be accommodated in the right pocket. Nevertheless, (R)-7-HSA and (S)-9-HSA were obtained with an enantiomeric enrichment of about 55% e.e.

account the practical and economic impact of CaLB and its wide use for the synthesis of chiral chemicals, it is of major importance not only to model and explain the behavior of the enzyme but, ideally, also to predict quantitatively its selectivity. Such tools would be helpful in designing rational strategies for changing, tuning or optimizing the performance of the lipase, thus matching industrial and synthetic needs. Quantitative prediction of CaLB enantioselectivity still remains a challenging task: the accurate calculation of ∆∆G‡ of couples of enantiomers requires QM simulations that, however, are expensive in terms of computational power required because the system is too complex to be defined at high level of theory. Nevertheless, promising alternatives are represented by recent QM/MM approaches (EVB method) that involve extensive conformational sampling and a realistic relaxation of the active site. Consequently, these methods were successful in evaluating the actual activation free energies and in exploring entropic effects. Hybrid MM/statistical methods (3D-QSAR) represent a second class of methodologies that have proven to predict quantitatively CaLB enantioselectivity for a series of secondary alcohols and amines. However, these methodologies rely strongly on the robustness of experimental data used for generating and “training” the mathematical predicting models. Of course, the different experimental challenges must be overcome by selecting the most appropriate computational “aid”, being aware of the necessary computational cost and the time-scale for achieving the solution. Ideally, in order to be of practical large utility, effective in silico strategy should be user friendly, request moderate computational power, be competitive with experimental work in terms of time and costs, and work within a high throughput frame. On that respect, new computational procedures and software have proven able to integrate computational steps and software within working-flows, thus making the whole procedure automatic and fast [15]. New routes will face the challenge of integrating these powerful novel computational methodologies, hence generating innovative hybrid tools, accessible to a wider scientific audience. CONFLICT OF INTEREST

9. TOWARDS A FULL EXPLOITATION OF CALB ENANTIOSELECTIVITY: WHAT AID FROM IN SILICO METHODS? Recent advances in computational sciences have led to novel sophisticated and refined methods that are able to describe the bio-catalytic machinery in detail. Taken into

The authors confirm that this article content has no conflict of interest. ACKNOWLEDGEMENTS Lucia Gardossi acknowledges COST Action CM1303 System Biocatalysis for financial support.

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Valerio Ferrario is grateful to MIUR (Ministero dell’Istruzione, dell’Università e della Ricerca – Roma) and to Università degli Studi di Trieste for financial support. REFERENCES [1] [2] [3]

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Received: January 13, 2015

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Revised: March 21, 2015

Accepted: June 10, 2015