Quantitative structure-activity relationship (QSAR) models for predicting organophosphate inhibition of acetylcholinesterase.

Abstract

Quantitative structure-activity relationship (QSAR) models are a tool for linking chemical activities with molecular structure and compositions. A large number of dicrotophos analogous organophosphate compounds acting as Acetylcholinesterase inhibitors whose toxicity towards mouse ( pLD50 ) value ranged between 0.3 to 4.5 has been studied. Molecules are separated into two categories test and training set. Different type of descriptors like quantum-chemical, physico-chemical, molecular descriptors used to get a quantitative relationship between biological activity and chemical properties of pesticide. The QSAR model developed using CCG's unique Binary-QSAR method for Dicrotophos organophosphate revealed good predictability, with the coefficient of determination r2 values of 0.84 as well as leave-one-out (LOO) cross-validation q2 values of 0.77, and the corresponding standard deviation of error 0.25 and 0.33 respectively. In addition, a linear correlation was observed between the experimental and predicted LD50 values for the test set data with r2 of 0.84  for the dicrotophos organophosphate group, indicating that the prediction accuracy of the QSAR model was acceptable. The model is also tested successfully from external validation criteria. A prediction of new pesticides using this QSAR model for the design of new organophosphate pesticides is presented and studied using a molecular docking method against the target AChE protein of mouse. A model developed in this QSAR study should help the further design of novel potent pesticides which has good pesticide property but lower toxicity in non-targeted organisms.