Abstract: Background: Dengue, a vector borne disease has become a crucial health concern globally. The search for a suitable dengue vaccine has been going on for the last few decades due to unavailability of any effective treatment. An efficient medication strategy is required to overcome the devastating effects of dengue. Now, computational biology has emerged as a novel tool to improve the domain of computer aided drug designing. The present study reports a complex-based pharmacophore computational modeling that elucidates important pharmacophoric features helpful for the inhibition of protease activity of NS2B/NS3 protein of Dengue Virus (DV). Materials and Methods: A seven featured pharmacophore model of DV NS2B/NS3 protease has been developed via crystal structure of NS2B/NS3 protease and its inhibitor complex in Molecular Operating Environment (MOE) pharmacophore constructing tool. The developed pharmacophore model was validated by a test database of the published inhibitors. Validated pharmacophore model was then used to virtually screen the potential compounds from ZINC database. The screened compounds were filtered by Lipinski’s rule of five and further evaluated through molecular docking studies. The results of docking and interaction studies were validated through binding affinity analysis and ADMET profiling. Results: Six hits (ZINC ID’s: 75163069, 59170698, 06395655, 32933073, 13728171 and 65395833) of different scaffolds having interactions with important active site residues (His51, Asp75, Ser135) were predicted. Conclusion: It can be concluded from the finding of the present study that predicted hits could serve as potential candidates to act as starting point in the development of novel and potent NS2B/NS3 protease inhibitors. The present modeling explores the significant role of the predicted hits towards blocking the replication of DV.