Application of artificial neural networks and DFT-based parameters for prediction of reaction kinetics of ethylbenzene dehydrogenase

Abstract

Artificial neural networks (ANNs) are used for classification and prediction of enzymatic activity of ethylbenzene dehydrogenase from EbN1 Azoarcus sp. bacterium. Ethylbenzene dehydrogenase (EBDH) catalyzes stereo-specific oxidation of ethylbenzene and its derivates to alcohols, which find its application as building blocks in pharmaceutical industry. ANN systems are trained based on theoretical variables derived from Density Functional Theory (DFT) modeling, topological descriptors, and kinetic parameters measured with developed spectrophotometric assay. Obtained models exhibit high degree of accuracy (100% of correct classifications, correlation between predicted and experimental values of reaction rates on the 0.97 level). The applicability of ANNs is demonstrated as useful tool for the prediction of biochemical enzyme activity of new substrates basing only on quantum chemical calculations and simple structural characteristics. Multi Linear Regression and Molecular Field Analysis (MFA) are used in order to compare robustness of ANN and both classical and 3D-quantitative structure-activity relationship (QSAR) approaches.

Quantum chemical modeling studies of ethylbenzene dehydrogenase activity

“…We have shown in a previous QSAR modeling studies that steric factors may be detrimental on the reaction rate, especially regarding substituents in close proximity of the reacting ethyl substituent [5,18]. However, these factors cannot be probed with a small cluster model.…”

“…As a result, the pro-S-hydrogen atom is transferred to the Mo¼ ¼O group. In TS1, the modeled structure of the substratederived species is close to that of an ethylbenzyl radical, as indicated by an almost flat conformation around the radical carbon (alkyl-ring dihedral angle 18 ), a shortened bond between C1 and the aromatic/heterocyclic ring (from 1.52 to 1.46 Å ) and a characteristic deformation of the benzene ring [5]. The CAH and the Mo¼ ¼O bonds are elongated from 1.09 to 1.41 Å and from 1.74 to 1.88 Å , respectively [ Fig.…”

Substrate and Inhibitor Spectra of Ethylbenzene Dehydrogenase: Perspectives on Application Potential and Catalytic Mechanism

“…The reaction mechanism of EbDH consists of two alternating half-reactions: (i) hydroxylation of the substrate to the respective secondary alcohol, accompanied by reduction of the Mo-cofactor from the Mo(VI) to the Mo(IV) state, and (ii) reoxidation of the Mo-cofactor by transferring two electrons via the iron-sulfur clusters to the heme and then to an external electron acceptor (16). A hypothetical catalytic mechanism for substrate hydroxylation was recently proposed based on quantum chemical modeling and initial data on the reactivity with different substrate analogs (26,(28)(29)(30)(31). In short, two electrons and a proton at the C-1 position of the ethyl group are believed to be abstracted by the Mo-cofactor to form a transient carbocation intermediate, which reacts with a hydroxyl group derived from water to form the alcohol (Fig.…”

Ethylbenzene Dehydrogenase and Related Molybdenum Enzymes Involved in Oxygen-Independent Alkyl Chain Hydroxylation

“…The initial mechanistic hypothesis of EBDH was formulated based on the knowledge of the general reaction mechanisms postulated for Mo enzymes and quantitative analyses of EBDH kinetics with various substrates [Szaleniec et al, 2006[Szaleniec et al, , 2007[Szaleniec et al, , 2008. The overall mechanism of EBDH is divided into two parts: (1) a reductive half-cycle relative to the Mo cofactor, in which ethylbenzene is hydroxylated to (S) -1-phenylethanol and the cofactor is reduced from a six-coordinate Mo VI species to a five-coordinate Mo IV complex and (2) an oxidative half-cycle during which the Mo cofactor coordinates a water molecule and gets oxidized back to Mo VI by transferring electrons to external electron acceptors via the chain of Fe-S clusters and the heme b cofactor of EBDH ( fig.…”