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Mechanism-Based Analysis of Acetylcholinesterase Inhibitory Potency of Organophosphates, Carbamates, and Their Analogs
Citation:
Lee, S. AND M. Barron. Mechanism-Based Analysis of Acetylcholinesterase Inhibitory Potency of Organophosphates, Carbamates, and Their Analogs. 17th International Conference on QSAR in Environmental and Health Sciences, Miami Beach, FL, June 13 - 17, 2016.
Impact/Purpose:
The presentation will summarize research investigating the ability to predict acetylcholinesterase inhibition of pesticides and metabolites.
Description:
Acetylcholinesterase (AChE) is a key enzyme in the nervous system of animals, terminating impulse transmission by rapid hydrolysis of the neurotransmitter acetylcholine. Organophosphate (OP) and carbamate esters can inhibit acetylcholinesterase (AChE) by binding covalently to a serine residue in the enzyme active site, and their inhibitory potency depends largely on affinity for the enzyme and the reactivity of the ester. Despite this understanding, there has been no mechanism-based in silico approach for analysis of the inhibitory potency of ether OPs or carbamates. This prompted us to develop a comprehensive prediction framework for OPs, carbamates, and their analogs. Inhibitory structures of a compound that can form the covalent bond were identified through analysis of docked conformations of the compound and its metabolites. Inhibitory potencies of the selected structures were then predicted using a previously developed three dimensional quantitative structure-active relationship (3D-QSAR) [1]. This approach was validated with a large number of structurally diverse OP and carbamate compounds encompassing widely used insecticides and structural analogs including OP flame retardants and thio- and dithiocarbamate pesticides. Incorporation of metabolite information in the docking simulations substantially improved the binary classification (AChEI vs non-AChEI) results for OPs, but only minor improvements were observed for carbamates. Classification accuracy and Matthews correlation coefficient were 0.92 and 0.62, respectively, for OPs, and 0.87 and 0.58, respectively, for carbamates. A more detailed description of a hydrophobic feature interacting with Trp86 at the anionic site was incorporated into the 3D-QSAR based on observations in the original model development and findings in this study. The refined 3D-QSAR had mean absolute errors of 0.98 and 0.29 log units for the OPs and carbamates, respectively, and an R2 of 0.74 for all the compounds. The modeling revealed that: (1) in addition to classical OP metabolic activation, the toxicity of carbamate compounds can be dependent on biotransformation, (2) OP and carbamate analogs such as OP flame retardants and thiocarbamate herbicides can act as AChEI, (3) hydrogen bonds at the oxyanion hole is critical for AChE inhibition through the covalent bond, and (4) π-π interaction with Trp86 is necessary for strong inhibition of AChE. Our combined computational approach provided detailed understanding of the mechanism of action of OP and carbamate compounds and may be useful for screening a diversity of chemical structures for AChE inhibitory potency.