Pharmacoinformatics approaches are widely used in the field of drug discovery as it saves time, invest-ment and animal sacrifice. In the present study, pharmacore-based virtual screening was adopted toidentify potential HIV-protease ligands as anti-HIV agents. Pharmacophore is the 3D orientation andspatial arrangement of functional groups that are critical for binding at the active site cavity. Virtualscreening retrieves potential hit molecules from databases based on imposed criteria. A set of 30 com-pounds were selected with inhibition constant as training set from 129 compounds of dataset set andsubsequently the pharmacophore model was developed. The selected best model consists of hydrogenbond acceptor and donor, hydrophobic and aromatic ring, features critical for HIV-protease inhibitors. Themodel exhibits high correlation (R = 0.933), less rmsd (1.014), high cross validated correlation coefficient(Q2= 0.872) among the ten models examined and validated by Fischer’s randomization test at 95% con-fidence level. The acceptable parameters of test set prediction, such as R2pred= 0.768 and r2m(test)= 0.711suggested that external predictivity of the model was significant. The pharmacophore model was usedto perform a virtual screening employing the NCI database. Initial hits were sorted using a number ofparameters and finally seven compounds were proposed as potential HIV-protease molecules. One poten-tial HIV-protease ligand is reportedly confirmed as an active agent for anti-HIV screening, validating thecurrent approach. It can be postulated that the pharmacophore model facilitates the selection of novelscaffold of HIV-protease inhibitors and can also allow the design of new chemical entities.