Structural Bioinformatics and QSAR Analysis Applied to the Acetylcholinesterase and Bispyridinium Aldoximes

Exploring the physicochemical properties of oxime-reactivation therapeutics for cyclosarin, sarin, tabun, and VX inactivated acetylcholinesterase

The inactivation of acetylcholinesterase (AChE) by organophosphorus agent (OP) compounds is a serious problem regardless of how the individual was exposed. The reactivation of OP-inactivated AChE is dependent on the OP conjugate, and commonly a specific oxime is better at reactivating a specific OP conjugate than several diverse OP conjugates. The presented research explores the physicochemical properties needed for the reactivation of OP-inactivated AChE. Four different OPs, cyclosarin, sarin, tabun, and VX, were analyzed using the same set of oxime reactivators. A trial descriptor pool of semiempirical, traditional, and molecular interaction field descriptors was used to construct an ensemble of QSAR models for each OP-conjugate pair. Based on the molecular information and the cross-validation ability, individual QSAR models were selected to be part of an OP-conjugate consensus model. The OP-conjugate specific models provide important insight into the physicochemical properties required to reactivate the OP conjugates of interest. The reactivation of AChE inactivated with either cyclosarin or tabun requires the oxime therapeutic to possess an overall polar-positive surface area. Oxime therapeutics for the reactivation of sarin-inactivated AChE are conformationally dependent while oxime reverse therapeutics for VX require a compact region with a highly hydrophilic region and two positively charged pyridine rings.

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

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.

para- andortho-Pyridinium aldoximes in reaction with acetylthiocholine

In the oximolysis reaction para-aldoximes K027 and TMB-4 react faster with ATCh than ortho-aldoximes HI-6 and K033. The reaction rate constants at 25 degrees C were 22 M(-1) min(-1) for HI-6 and K033, 230 M(-1) min(-1) for TMB-4 and 306 M(-1) min(-1) for K027. Semi-empirical calculations showed that differences in rates do not origin from different electron density on the oxygen of the oxime group, but can be explained by the steric hindrance of the oxime group within the molecule. Thermodynamic parameters, DeltaG#, DeltaH# and DeltaS#, were also determined for oximolysis reaction.