Quantitative structure–activity relationships for organophosphates binding to acetylcholinesterase

Abstract

Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in physiologically based pharmacokinetic/pharmacodynamic models of organophosphate toxicity to determine the rate of acetylcholinesterase inhibition.

Monte Carlo QSAR models for predicting organophosphate inhibition of acetycholinesterase

“…In comparison with the published QSAR model with the same molecule data set [11], the QSAR model presented in this research showed better statistical parameter values and better productivity results. Furthermore, the descriptors used in this research were based just on a SMILES notation, completely ignoring the three-dimensional (3D) structure of OPs, which leads to faster computation time and reducing computation resources.…”

“…A diverse set of pentavalent OP oxon and CWNA compounds in their active phosphoryloxygen (P=O) form were taken from the literature [11]. These structures were used to generate canonical SMILES using OpenBabel software [27].…”

“…The experimental determination for stated rate constants for new OP is an expensive and time consuming process. For that reason, quantitative structure-activity relationships (QSAR) models are developed for predicting missing parameters [10,11]. There are a number of studies with values for AChE bimolecular rate constants for pentavalent OP oxons in the literature and this extensive experimental database allows the development of QSAR models for predicting k 1 for new OP oxon and CWNA compounds of interest [11].…”

Physiologically Based Pharmacokinetic Modeling of Chemical Warfare Agents

“…One significant area of needed validation from Chen and Seng's model is the assumption that tissue/blood partition coefficients for GD were identical across all species for all tissues, as well as other model parameter assumptions, which could have a critical impact on the broader application to more diverse simulation scenarios (Ruark et al, 2013). For the most significant step of extrapolation to the human species and making predictions about CWNA lethality, few of these parameter values are likely to be available, an area in which Quantitative Structure Activity Relationship (QSAR) analysis can provide a viable impact (Knaak et al, 2004;Ruark et al, 2013).…”

Toxicological and neurobehavioral effects of chlorpyrifos and deltamethrin insecticides in mice

“…Toxic effects of chlorpyrifos by affecting normal function of the insect nervous system (6) by irreversible inhibition of acetyl cholinesterase enzyme (AchE) that is responsible for the breakdown of acetylcholine (Ach) (7)(8)(9)(10). After exposure to the toxic doses, signs of poisoning appear within a few minutes or after few hours this depending on the degree of absorption, distribution, metabolism of insecticide inside the body and its excretion (11). Chlorpyrifos poisoning shows the cardinal signs of organophosphorus compounds that is represented by muscarinic signs, which appears early that includes: salivation, lacrimation, sweating, colic with diarrhea, dyspnea with profuse nasal discharges, urination, defecation, miosis and bradycardia (12,13), followed by nicotinic signs that includes: muscle fasciculation, muscle twitching, abnormal gait, in coordination and tremors (14), eventually nervous system effects which includes hyperactivity, anxiety, tremors followed by convulsions, depression and finally death as a result of respiratory failure (15,16).…”