Robust and predictive QSAR models for predicting the D2, 5-HT1A, and 5-HT2A inhibition activities of fused tricyclic heterocycle piperazine (piperidine) derivatives as atypical antipsychotic drugs

Abstract

In this research, QSAR models were developed for predicting the inhibition activities of tricyclic heterocycle piperazine (piperidine) derivatives against the D2, 5-HT1A, and 5-HT2A receptors. These develop 2D and 3D-QSAR models were use for determining chemical structural features that improve the activities of molecules. For the D2 inhibition activities of molecules, reliable MLR and CoMFA models and for their 5-HT2A inhibition activities, reliable MLR and ε-SVR were developed. For the 5-HT1A inhibition activities of molecules, three QSAR models (based on the application of CoMFA, MLR, and ε-SVR) were developed. For all models, the applicability domain of created models was investigated by calculating leverage. Residual plots show that there is no systematic error in creating all models and all QSAR models were validated by calculating several statistical parameters for both train and test sets. Based on the interpretation of developed QSAR models, new molecules with high activityis against all three receptors were designed. Finally, three molecules, including m5, m20, and m36, were docked to the binding site of the D2 receptor to investigate their binding pose and interaction with this binding site. The docking results show that m36 has the most negative binding energy, and molecular dynamics simulations results show that the binding of m36 to the D2 makes the receptor more stable with respect to risperidone.