Also, 15 external test set 18A molecules which were used to validate the pharmacophore developed from ligand-based methodology were also used as a screening validation dataset on the five-feature structure-based pharmacophore. All the 15 external test set molecules exhibited good estimated activities and fit values explaining the accuracy of our developed pharmacophore. The most active compounds of both non-cyclic and cyclic urea derivatives showed the best fit values. In order to validate the pharmacophoric pattern of above mentioned four database compounds, their ACPT-II conformations were generated and mapped onto the pharmacophore derived from structure-based strategy. Out of different conformations of four compounds, 19 hits were obtained and three hits exhibited a perfect five-feature mapping and rest all showed a four-feature interaction. Analysis of the best five feature hit exhibited by highest estimated compound BTB01434, revealed that two HBA and two HY features were mapped exactly on the same groups as that of mapping obtained onto the pharmacophore obtained from HypoGen study. An additional feature i.e. hydrogen bond donor which was additionally retrieved through receptor-based approach was mapped onto the �CNH group of suphonamide moiety. This similar pattern of accurate mapping was seen, when rest of three database compounds were mapped onto the structure-based pharmacophore, hence proving the precision of our predicted database compounds. In this study, we described the development of highly selective pharmacophore models for inhibitors of HIV-1 protease. The generated pharmacophore reflects the binding mode and the important interactions of the ligands with certain amino acids in the active site of HIV-1 protease enzyme. In our ligand-oriented study, efforts were made to take multiple contributions of ligand features to build a quantitative pharmacophore models from a training set of 33 HIV-1 protease inhibitor analogs. The best pharmacophore consisted of four pharmacophore features, including two hydrogen bond acceptor and two hydrophobic features, having a correlation coefficient of 0.90. Besides, this hypothesis was further validated by an external test of 15 compounds. The type and spatial location of the chemical feature agree perfectly with the pattern of enzyme inhibitor interactions identified from crystallography. In our structure-oriented study, another 3D pharmacophore model from HIV-1 protease enzyme was developed and was used to screen compound library comprising of for HIV-1 protease inhibitors as validation step.