Contribution of both catalytic constant and Michaelis constant to CALB enantioselectivity: Use of FEP calculations for prediction studies

Abstract

Candida antarctica lipase B (CALB) is characterised by its stability and ease of production and is widely used in the pharmaceutical industry. Here we report on the enantioselectivity of the enzyme using both experimental and computational methods. The apparent kinetic parameters were first experimentally determined for enantiopure butan-2-ol and pentan-2-ol substrates. We demonstrate that enantiopreference for the R form of butan-2-ol arises mainly from a lower apparent K M . This corresponds to a major contribution of ∆∆G ES , the free energy difference between the ES complex formed with the R and S enantiomers, to ∆∆G ‡ , the free energy difference between both transition states, in comparison with ∆∆G kcat , the activation free energy difference. In the case of pentan-2-ol, we show that the enantiopreference for the R form comes from both a lower K M and a higher k cat . In addition, we used, for the first time, the Free Energy Perturbation method to evaluate the free energy difference between tetrahedral intermediates formed with R and S alcohol enantiomers for a series of secondary alcohols . This is a valid model for ∆∆G ‡ . Computational results were found to be in good agreement with experimental data, and enable the determination of substrate orientation in the active site with fair confidence.

Enhancing the enantioselectivity of CALB by substrate imprinting: A combined experimental and molecular dynamics simulation model study

“…The time scale of Ile285 side chain rotation can thus be considered to be around 1 ms. Previously the same order of magnitude was obtained for pentan-2-ol transesterification in a solid-gas reactor [17]: k cat equal to 800 s −1 and 17 s −1 for (R)-and (S-pentan-2-ol respectively. The similarity of these two time scales namely, side chain rotation and substrate catalysis, is consistent with the hypothesis of "imprinting effect".…”

“…Thus, the enantiomeric form of the chiral ester substrate is essential for determining the enantioselectivity of the reaction. CALB displays enantiopreference for the R alcohol [9,17], and using an ester with the R chiral form for the alkyl part increases the enantioselectivity compared to the racemate. In contrast, an ester with the S chiral form for the alkyl part, results in decreased enantioselectivity.…”

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

“…CalB is a serine hydrolase whose catalytic mechanism has been studied extensively (for e.g., Refs. ). The CalB active site includes the catalytic triad of SER‐HIS‐ASP, which acts in the same way as the well‐studied serine proteases, where a proton transfer from serine is followed by a nucleophilic attack of the ester carbonyl by the deprotonated alcohol (see Fig.…”

Computational modelling of enzymes: predicting and understanding the selectivity of an epoxide hydrolase

“…Computational and statistical methods can predict the effects of mutations on enzyme selectivity from sparse sequence-activity data sets. Statistical and molecular modelling methods (see Chapter 5) have generally been used to model enantioselectivity [41][42][43][44][45][46][47][48][49][50][51][52], while machine learning has been under-utilised. Machine learning methods are described either as discriminative or generative (Figure 1.3) [53,54] and may be applied to classification, e.g.…”

“…Previous modelling studies predicting the preferred enantiomer and the degree of enantioselectivity have primarily used quantitative structure-activity relationship (QSAR) or molecular dynamics methods [41][42][43][44][45][46][47][48][49][50][51][52]. Such methods often require high-resolution protein structures, either derived from crystallography experiments or homology modelling, and need to explicitly model environmental variables that may influence enzyme enantioselectivity, e.g.…”