Finding new scaffolds of JAK3 inhibitors in public database: 3D-QSAR models &amp; shape-based screening

Gadhe, Changdev G.; Lee, Eun-Hee; Kim, Mi‐Hyun

doi:10.1007/s12272-015-0607-6

Cited by 13 publications

(19 citation statements)

References 19 publications

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“…The GH score ranges between 0 and 1 and indicates null and ideal models, respectively. Pharmacophore model with GH score higher than 0.70 is considered as valid model for virtual screening of large databases [ 31 , 32 ]. The enrichment factor (EF) determines the specificity and selectivity of the model to identify active compounds during the screening of decoy test set.…”

Section: Methodsmentioning

confidence: 99%

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Zeb

Son

Yoon

et al. 2019

Computational and Structural Biotechnology Journal

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Deregulation of Cdk5 is a hallmark in neurodegenerative diseases and its complex with p25 forms Cdk5/p25, thereby causes severe neuropathological insults. Cdk5/p25 abnormally phosphorylates tau protein, and induces tau-associated neurofibrillary tangles in neurological disorders. Therefore, the pharmacological inhibition of Cdk5/p25 alleviates tau-associated neurological disorders. Herein, computational simulations probed two candidate inhibitors of Cdk5/p25. Structure-based pharmacophore investigated the essential complementary chemical features of ATP-binding site of Cdk5 in complex with roscovitine. Resultant pharmacophore harbored polar interactions with Cys83 and Asp86 residues and non-polar interactions with Ile10, Phe80, and Lys133 residues of Cdk5. The chemical space of selected pharmacophore was comprised of two hydrogen bond donors, one hydrogen bond acceptor, and three hydrophobic features. Decoy test validation of pharmacophore obtained highest Guner-Henry score (0.88) and enrichment factor score (7.23). The screening of natural product drug-like databases by validated pharmacophore retrieved 1126 compounds as candidate inhibitors of Cdk5/p25. The docking of candidate inhibitors filtered 10 molecules with docking score >80.00 and established polar and non-polar interactions with the ATP-binding site residues of Cdk5/p25. Finally, molecular dynamics simulation and binding free energy analyses identified two candidate inhibitors of Cdk5/p25. During 30 ns simulation, the candidate inhibitors established <3.0 Å root mean square deviation and stable hydrogen bond interactions with the ATP-binding site residues of Cdk5/p25. The final candidate inhibitors obtained lowest binding free energies of −122.18 kJ/mol and − 117.26 kJ/mol with Cdk5/p25. Overall, we recommend two natural product candidate inhibitors to target the pharmacological inhibition of Cdk5/p25 in tau-associated neurological disorders.

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Section: Methodsmentioning

confidence: 99%

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Zeb

Son

Yoon

et al. 2019

Computational and Structural Biotechnology Journal

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“…For in silico rational design of new scaffolds, we have conducted ‘de novo design/core-hopping’ 29 , ‘side-chain hopping’ 30 , in addition to prediction of binding mode through MD simulations 31 in structure-based prediction models. Similarly, like our previous shape-based QSAR model 32 , we could consider developing ligand-based predictive models to extract information regarding distinct structural features required for ligand-receptor interaction 33 . The database can be initially screened for drug-like molecules by applying different rational filters such as the Lipinski’s Rule of five 34 – 36 and drug-like adsorption, distribution, metabolism, excretion and toxicity (ADMET) properties 36 – 38 .…”

Section: Introductionmentioning

confidence: 99%

Identification of novel acetylcholinesterase inhibitors designed by pharmacophore-based virtual screening, molecular docking and bioassay

Jang

Yadav

Subedi

et al. 2018

Sci Rep

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In this study, pharmacophore based 3D QSAR models for human acetylcholinesterase (AChE) inhibitors were generated, with good significance, statistical values (r2training = 0.73) and predictability (q2training = 0.67). It was further validated by three methods (Fischer’s test, decoy set and Güner-Henry scoring method) to show that the models can be used to predict the biological activities of compounds without costly and time-consuming synthesis. The criteria for virtual screening were also validated by testing the selective AChE inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective AChE inhibitor. Thus, the findings reported herein may provide a new strategy for the discovery of selective AChE inhibitors. The IC50 value of compounds 5c and 6a presented selective inhibition of AChE without inhibiting butyrylcholinesterase (BChE) at uM level. Molecular docking studies were performed to explain the potent AChE inhibition of the target compounds studies to explain high affinity.

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“…Several statistical parameters in PHASE, such as R2 for the training set and Q2 for the test set, the standard deviation, root mean square error, and variance ratio (F), can be used to evaluate the robustness of a QSAR model [20][21][22][23]. To test the reliability of QSAR models, compounds that were not used for model development must be used: (1) test set (15 compounds), (2) 3 rd set (out of initial dataset).…”

Section: Materials and Methods Data Collection And Molecular Dockingmentioning

confidence: 99%

“…The screening identified in silico hit compounds with chemical features corresponding to those of the template [19, 23, and 26]. Some of these hits might be similar to known active compounds, while others might have more novel scaffolds [23,38]. The identification of hit compounds having different scaffolds was the primary aim of our research, development of novel D3R-selective antagonists.…”

Section: Identification Of Cns-like D3r Antagonist Through Virtual Scmentioning

confidence: 99%

Discovery of CNS-Like D3R- Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening

Lee

Cho²,

Kim

2018

Preprint

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The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R 2 training = 0.80; AHPRRR104: R 2 training = 0.82) and predictability (APRRR215: Q 2 test = 0.73, R 2 predictive = 0.82; AHPRRR104: Q 2 test = 0.86, R 2 predictive = 0.74) of their 3D-quantitative structure-activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (> 3 million compounds) using two optimal models expedited the search process 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNSlike properties as well as expected D3R antagonism.

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Finding new scaffolds of JAK3 inhibitors in public database: 3D-QSAR models & shape-based screening

Cited by 13 publications

References 19 publications

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Computational Simulations Identified Two Candidate Inhibitors of Cdk5/p25 to Abrogate Tau-associated Neurological Disorders

Identification of novel acetylcholinesterase inhibitors designed by pharmacophore-based virtual screening, molecular docking and bioassay

Discovery of CNS-Like D3R- Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening

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