GABA

New Chemical Entities (NCEs) were designed using information from pharmacophore profile of known anticonvulsants. Binding affinities of designed NCEs were studied on gamma-aminobutyric acid (GABA-alpha) using docking studies. Two Dimensional (2D) Quantitative Structure–Activity Relationship (QSAR) studies were performed for correlating the chemical composition of triazolethione analogs and estimation of their anticonvulsant activity using Multiple Linear Regression (MLR) Analysis.  ADMET properties were also predicted. These four basic strategies (pharmacophore mapping, QSAR, docking & ADMET screening) were implemented to evaluate the performance of derivatives. Although predicted Ki through QSAR model showed significant mild activity for GABA. Conclusively compounds, 2, 6, 7, 8, 9, 10, 11, and 20 were observed to be most feasible to activate GABA for anticonvulsant activity.