Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches.

TLDR: 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 suggests potential of this compound to treat cancer.

Abstract: 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 r2 = 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. AbbreviationsNQO1NAD(P)H-quinine oxidoreductase 1CPHcommon pharmacophore hypothesisPLSpartial least squireHBDhydrogen bond donorSDstandard deviationXPextra precisionIFDinduced fit dockingMM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSDroot mean square deviationRMSFroot mean square fluctuationRMSEroot mean square errorADMEabsorption distribution metabolism excretionsCommunicated by Ramaswamy H. Sarma.