Quantitative Structure-Activity Relationship (QSAR) Models for Predicting Organophosphate Inhibition of Acetylcholinesterase in Mous

Quantitative structure-activity relationship (QSAR) models are a tool for linking biological activities with molecular structure and compositions. All of the organophosphate molecules bind the same way as acetylcholine and act as competitive inhibitors of acetylcholinesterase (AChE). A large number of organophosphate analogous compounds acting as acetylcholinesterase inhibitors whose toxicity towards mouse AChE pLD50 values ranged from 0.3 to 3.1 have been studied. Molecules were separated into two categories, the test and training set. Different types of descriptors such as quantum-chemical, physicochemical and molecular descriptors were used to obtain a quantitative relationship between biological activity and chemical properties of pesticides. The QSAR models were developed using the unique binary-QSAR module of MOE 2016. The models for the dicrotophos and omethoate organophosphate group revealed good predictability. The pLD50 of the dicrotophos group was predicted with a coefficient of determination R2 value of 0.84 and leave-one-out (LOO) cross-validation Q2 value of 0.77, and a corresponding root mean square error (RMSE) of 0.25 and 0.33, respectively. The omethoate group pLD50 was predicted with coefficient of determination R2 values of 0.82 and leave-one-out (LOO) cross-validation Q2 value of 0.77, and a corresponding root mean square error (RMSE) of 0.27 and 0.30, respectively. Also, a linear correlation was observed between the experimental and predicted LD50 values for the test set data with an R2 of 0.82 and 0.84 for the dicrotophos and omethoate organophosphate groups respectively, indicating that the prediction accuracy of the QSAR model was acceptable. A model developed in this QSAR study should help the further design of novel pesticides that have good pesticides that are effective for targeted species but safer on non-targeted species.