Sodium hydrogen exchanger (SHE) inhibitor is one of the most important targets 
in treatment of myocardial ischemia. In the course of our research into new 
types of non-acylguanidine, SHE inhibitory activities of 
5-tetrahydroquinolinylidine aminoguanidine derivatives were used to build 
pharmacophore and 3D-QSAR models. Genetic Algorithm Similarity Program (GASP) 
was used to derive a 3D pharmacophore model which was used in effective 
alignment of data set. Eight molecules were selected on the basis of structure 
diversity to build 10 different pharmacophore models. Model 1 was considered as 
the best model as it has highest fitness score compared to other nine models. 
The obtained model contained two acceptor sites, two donor atoms and one 
hydrophobic region. Pharmacophore modeling was followed by substructure 
searching and virtual screening. The best CoMFA model, representing steric and 
electrostatic fields, obtained for 30 training set molecules was statistically 
significant with cross-validated coefficient (q(2)) of 0.673 and conventional 
coefficient (r(2)) of 0.988. In addition to steric and electrostatic fields 
observed in CoMFA, CoMSIA also represents hydrophobic, hydrogen bond donor and 
hydrogen bond acceptor fields. CoMSIA model was also significant with 
cross-validated coefficient (q(2)) and conventional coefficient (r(2)) of 0.636 
and 0.986, respectively. Both models were validated by an external test set of 
eight compounds and gave satisfactory prediction (r(pred)(2)) of 0.772 and 0.701 
for CoMFA and CoMSIA models, respectively. This pharmacophore based 3D-QSAR 
approach provides significant insights that can be used to design novel, potent 
and selective SHE inhibitors.