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

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.

Fucoidan serves a neuroprotective effect in an Alzheimer's disease model.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that causes memory and cognitive deficits. The present study was carried out to evaluate the protective effects of fucoidan in monocrotophos induced AD in Drosophila melanogaster. In silico studies showed that fucoidan exhibited binding energy of -9.3 kcal with proteins. Consistent with this, fucoidan, in a dose and time-dependent fashion, had inhibitory activity against cholinergic and monoamine-metabolized enzymes in vitro. Fucoidan inhibited the increase in total mRNA and protein in monocrotophos fed flies and prevented changes in biochemicals, neurochemicals and latency time of locomotor, learning and memory induced by monocrotophos. Together, the findings show that fucoidan serves a neuroprotective effect in Alzheimer's disease model in D. melanogaster.

Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.

Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease.

Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques.

c-Yes kinase is considered as one of the attractive targets for anti-cancer drug design. The DFG (Asp-Phe-Gly) motif present in most of the kinases will adopt active and inactive conformations, known as DFG-in and DFG-out and their inhibitors are classified into type I and type II, respectively. In the present study, two screening protocols were followed for identification of c-Yes kinase inhibitors. (i) Structure-based virtual screening (SBVS) and (ii) Structure-based (SB) and Pharmacophore-based (PB) tandem screening. In SBVS, the c-Yes kinase structure was obtained from homology modeling and seven ensembles with different active site scaffolds through molecular dynamics (MD) simulations. For SB-PB tandem screening, we modeled ligand bound active and inactive conformations. Physicochemical properties of inhibitors of Src kinase family and c-Yes kinase were used to prepare target focused libraries for screenings. Our screening procedure along with docking showed 520 probable hits in SBVS and tandem screening (120 and 400, respectively). Out of 5000 compounds identified from different computational methods, 2410 were examined using kinase inhibition assays. It includes 266 compounds (5.32%) identified from our method. We observed that 14 compounds (12%) are identified by the present method out of 168 that showed > 30% inhibition. Among them, three compounds are novel, unique, and showed good inhibition. Further, we have studied the binding of these compounds at the DFG-in and DFG-out conformations and reported the probable class (type I or type II). Hence, we suggest that these compounds could be novel drug leads for regulation of colorectal cancer.