Browsing by Author "Kumar, Niraj"

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    Gaussian field-based comparative 3D QSAR modelling for the identification of favourable pharmacophoric features of chromene derivatives as selective inhibitors of ALR2 over ALR1
    (Springer, 2021-01-07T00:00:00) Verma, Sant Kumar; Kumar, Niraj; Thareja, Suresh
    Aldehyde reductase (ALR1) and aldose reductase (ALR2) are both oxo-reductase enzymes of aldo-keto reductase (AKR) superfamily involved in several cellular processes. ALR1 plays an important role in colorectal cancer, lungs, and hepatic carcinoma, while ALR2 is involved in diabetic complications like retinopathy, neuropathy, and nephropathy cataract. Both the enzymes take part in distinct physiological processes, however, share more > 70% structural homology. This is the major cause behind the unachieved target selectivity of molecules that entered the development pipeline as ALR2 inhibitors. Chromene analogues have been widely explored for diverse biological activities, including antioxidant and diabetic complication prevention potential. For the identification of spatial fingerprints of target-specific chromene bearing ALR2 inhibitors over ALR1, Gaussian field-based comparative 3D QSAR models were generated on a dataset having ALR1 and ALR2 inhibitory activity. Both the ALR1 and ALR2 3D QSAR models were statistically fit with good predictive ability concerning PLS generated validation constraints. The comparative steric, electrostatic, hydrophobic, HBA, and HBD features were elucidated using respective contour maps for selective target specific favourable activity against ALR2 over ALR1. In addition, the five-point pharmacophores for ALR1 and ALR2 favourable features were also generated using the DHHRR_1 hypothesis for better insight on the distinctive features of ALR2 inhibitors compared to ALR1. � 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
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    Pharmacophore derived 3D-QSAR, molecular docking, and simulation studies of quinoxaline derivatives as ALR2 inhibitors
    (Taylor and Francis Ltd., 2023-09-12T00:00:00) Singh, Yogesh; Kumar, Niraj; Kulkarni, Swanand; Singh, Satwinder; Thareja, Suresh
    Aldose Reductase 2 (ALR2), a key enzyme of the polyol pathway, plays a crucial role in the pathogenesis of diabetic complications. Quinoxaline scaffold-based compounds have been identified as potential ALR2 inhibitors for the management of diabetic complications. In the present work, molecular dynamic simulation studies in conjugation with pharmacophore mapping and atom-based 3D-QSAR were performed on a dataset of 99 molecules in comparison with Epalrestat (reference) to mark the desirable structural features of quinoxaline analogs to generate a probable template for designing novel and effective ALR2 inhibitors. The most potent compound 81 was subjected to MD simulation studies and found to be stable, with better interactions with the binding pocket as compared to Epalrestat. The MM-GBSA and MM-PBSA calculations showed that compound 81 possessed binding free energies of ?35.96 and ?4.92 kcal/mol, respectively. Atom-based 3D-QSAR yielded various pharmacophoric features with excellent statistical measures, such as correlation coefficient (R 2 value), F-value (Fischer ratio), Q 2 value (cross-validated correlation coefficient), and Pearson�s R-value for training and test sets. Furthermore, the pharmacophore mapping provided a five-point hypothesis (AADRR) and docking analysis revealed the active ligand-binding orientations on the active site�s amino acid residues TYR 48, HIE 110, TRP 111, and TRP 219. The results of this study will help in designing potent inhibitors of ALR2 for the management of diabetic complications. Communicated by Ramaswamy H. Sarma. � 2023 Informa UK Limited, trading as Taylor & Francis Group.