NAD(P)H: quinone oxidoreductase 1 (NQO1) inhibitors are proved as promising therapeutic agents against cancer. This study is to determine potent NAD(P)H-dependent NQO1 inhibitors with new scaffold. Pharmacophore-based three-dimensional (3D) QSAR model has been built based on 45 NQO1 inhibitors reported in the literature. The structure-function correlation coefficient graph represents the relationship between phase activity and phase predicted activity for training and test sets. A QSAR model statistics shows the excellent correlation of the generated model. Pharmacophore hypothesis (AARR) yielded a statistically significant 3D QSASR model with a correlation coefficient of r 2 = 0.99 as well as an excellent predictive power. From the analysis of pharmacophore-based virtual screening using by SPEC database, 4093 hits were obtained and were further filtered using virtual screening filters (HTVS, SP, XP) through structure based molecular docking. Based on glide energy and docking score, seven lead compounds show better binding affinity compared to the co-crystal inhibitor. The results of induced fit docking and prime/MM-GBSA suggest that leads AN-153/J117103 and AT-138/KB09997 binding with the catalytic site. Further, to understanding the stability of identified lead compounds MD simulations were done. The lead AN-153/J117103 showed the strong binding stable of the protein-ligand complex. Also the computed drug likeness reveals potential of this compound to treat cancer. AbbreviationsNQO1 NAD(P)H-quinine oxidoreductase 1CPH common pharmacophore hypothesisPLS partial least squireHBD hydrogen bond donorSD standard deviationXP extra precisionIFD induced fit dockingMM-GBSA molecular mechanics generalized born surface areaMDS molecular dynamics simulationRMSD root mean square deviationRMSF root mean square fluctuationRMSE root mean square errorADME absorption distribution metabolism excretions Communicated by Ramaswamy H. Sarma. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.