Design of Potential Inhibitors and Prediction of their Activity by the Structural Insight of VEGFR2 Inhibitors: Atom‐based 3D‐QSAR, Fingerprint‐based 2D QSAR and Off‐target analysis.

Rathi, Ekta; Kumar, Avinash; Suvarna,; Kini, Suvarna G.

doi:10.1002/slct.201903898

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…Several potential kinase inhibitors, such as a dual ALX/FLT3 inhibitor and a CDK9 inhibitor, were reported on the basis of LBVS methodology. 180 , 181 There are many cases of QSAR models used in the design of kinase inhibitors for VEGFR2, 182 EGFR, 183 MCL-1, 184 IKK-β, 185 , 186 LYN, 187 and MER, 188 and so on. 177 , 178 …”

Section: Advances In Efficacy Assessment Models and Technologymentioning

confidence: 99%

An overview of kinase downregulators and recent advances in discovery approaches

Wang

et al. 2021

Sig Transduct Target Ther

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Since the clinical approval of imatinib, the discovery of protein kinase downregulators entered a prosperous age. However, challenges still exist in the discovery of kinase downregulator drugs, such as the high failure rate during development, side effects, and drug-resistance problems. With the progress made through multidisciplinary efforts, an increasing number of new approaches have been applied to solve the above problems during the discovery process of kinase downregulators. In terms of in vitro and in vivo drug evaluation, progress was also made in cellular and animal model platforms for better and more clinically relevant drug assessment. Here, we review the advances in drug design strategies, drug property evaluation technologies, and efficacy evaluation models and technologies. Finally, we discuss the challenges and perspectives in the development of kinase downregulator drugs.

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Section: Advances In Efficacy Assessment Models and Technologymentioning

confidence: 99%

An overview of kinase downregulators and recent advances in discovery approaches

Wang

et al. 2021

Sig Transduct Target Ther

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Identification of DprE1 inhibitors for tuberculosis through integrated in-silico approaches

Dash,

Rathi,

Kumar

et al. 2024

Sci Rep

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Decaprenylphosphoryl-β-D-ribose-2′-epimerase (DprE1), a crucial enzyme in the process of arabinogalactan and lipoarabinomannan biosynthesis, has become the target of choice for anti-TB drug discovery in the recent past. The current study aims to find the potential DprE1 inhibitors through in-silico approaches. Here, we built the pharmacophore and 3D-QSAR model using the reported 40 azaindole derivatives of DprE1 inhibitors. The best pharmacophore hypothesis (ADRRR_1) was employed for the virtual screening of the chEMBL database. To identify prospective hits, molecules with good phase scores (> 2.000) were further evaluated by molecular docking studies for their ability to bind to the DprE1 enzyme (PDB: 4KW5). Based on their binding affinities (< − 9.0 kcal/mole), the best hits were subjected to the calculation of free-binding energies (Prime/MM-GBSA), pharmacokinetic, and druglikeness evaluations. The top 10 hits retrieved from these results were selected to predict their inhibitory activities via the developed 3D-QSAR model with a regression coefficient (R2) value of 0.9608 and predictive coefficient (Q2) value of 0.7313. The induced fit docking (IFD) studies and in-silico prediction of anti-TB sensitivity for these top 10 hits were also implemented. Molecular dynamics simulations (MDS) were performed for the top 5 hit molecules for 200 ns to check the stability of the hits with DprE1. Based on their conformational stability throughout the 200 ns simulation, hit 2 (chEMBL_SDF:357100) was identified as the best hit against DprE1 with an accepted safety profile. The MD results were also in accordance with the docking score, MM-GBSA value, and 3D-QSAR predicted activity. The hit 2 molecule, (N-(3-((2-(((1r,4r)-4-(dimethylamino)cyclohexyl)amino)-9-isopropyl-9H-purin-6-yl)amino)phenyl)acrylamide) could serve as a lead for the discovery of a novel DprE1 inhibiting anti-TB drug.

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Design of Potential Inhibitors and Prediction of their Activity by the Structural Insight of VEGFR2 Inhibitors: Atom‐based 3D‐QSAR, Fingerprint‐based 2D QSAR and Off‐target analysis.

Cited by 2 publications

References 32 publications

An overview of kinase downregulators and recent advances in discovery approaches

An overview of kinase downregulators and recent advances in discovery approaches

Identification of DprE1 inhibitors for tuberculosis through integrated in-silico approaches

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