Introduction: Although the transition of a lead candidate into a drug is currently structured by
well-defined milestone, it is still most challenging and offers no guarantee in success to the end. In fact,
Ligand-based pharmacophore modeling has become a key motive force for retrieving potential leads across
several therapeutic areas.
Methods: An urgent need towards the development of novel antidepressant agents led us to generate a
pharmacophore model from an existing 44 compounds dataset. The best model with one hydrophobic, two
ring aromatic, and one positive ionization features was chosen on behalf of the correlation coefficient, sensitivity,
specificity, yield of actives and accuracy measures using HypoGen module of Discovery Studio. In
house library consisting of 10,000 substituted 1,3,5 triazine derivatives were shortlisted to select four insilico
hits. All shortlisted compounds were synthesized and characterized by FTIR, 1H-& 13C-NMR spectroscopy
and finally tested for antidepressant-like activity using behavioral models on rats viz Forced Swim Test (FST)
and Elevated Plus Maze (EPM).
Results: Two shortlisted compounds with optimal fit values showed a significant decrease in the duration
of immobility as compared to standard drug Imipramine in FST while time spent in open arm in enhanced
in case of EPM.