Exploration of 3,6-dihydroimidazo(4,5-d)pyrrolo(2,3-b)pyridin-2(1H)-one derivatives as JAK inhibitors using various in silico techniques

Jisha, Radhakrishnan S; Aswathy, Lilly; Masand, Vijay H.; Gajbhiye, Jayant M.; Shibi, Indira G.

doi:10.1007/s40203-017-0029-x

Cited by 6 publications

(1 citation statement)

References 72 publications

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“…During the generation of 3D-QSAR models, the molecular alignments of the compounds was considered as the most crucial step for the robustness and predictive power of CoMFA and CoMSIA models [24]. The most potent compound of the dataset, 36r, was chosen as the template on which all molecules of the training set were aligned according to the largest common substructure.…”

Section: Molecular Modeling and Alignmentmentioning

confidence: 99%

Research on the Anti-tumor Activity of Novel Histone Deacetylase Inhibitors based on 3D QSAR Model

Meng,

Yang,

Yao

et al. 2023

Preprint

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Background Histone deacetylases (HDACs) pertain to the category of Zn2+ or nicotinamide adenine dinucleotide (NAD+)-dependent proteolytic enzymes. While the antitumor effect of HDAC inhibitors alone has been demonstrated and the effect of HDAC inhibitors on solid tumors is not ideal, which considerably limits their clinical use. Therefore, the search for novel HDAC inhibitors equipped with specific inhibitors is extremely urgent and necessary. Methods 3D-QSAR was employed to investigate insights into the crucial structural element that effect the activity of novel HDAC small molecule inhibitors. The best saliency CoMFA and CoMSIA models are obtained using 55 molecules in the training set and 16 molecules in the test set. Results The statistical quality of the generated model is demonstrated by internal and external cross-validations. The CoMFA model obtained satisfactory values (q2 = 0.664, r2 = 0.917, SEE = 0.217) while optimized CoMSIA model exceed with (q2 = 0.672, r2 = 0.948, SEE = 0.175). Conclusion The statistical parameters from 3D-QSAR models reveal that the results are reliable and significant with strong predictive ability. These theoretical results may contribute to the design of novel HDAC small molecule inhibitors with enhanced activity for the treatment of cancer.

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Section: Molecular Modeling and Alignmentmentioning

confidence: 99%

Research on the Anti-tumor Activity of Novel Histone Deacetylase Inhibitors based on 3D QSAR Model

Meng,

Yang,

Yao

et al. 2023

Preprint

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Identification of prodigious and under-privileged structural features for RG7834 analogs as Hepatitis B virus expression inhibitor

Masand¹,

El-Sayed

Rastija

et al. 2019

Med Chem Res

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Design of novel amyloid β aggregation inhibitors using QSAR, pharmacophore modeling, molecular docking and ADME prediction

Aswathy¹,

Jisha²,

Masand³

et al. 2018

In Silico Pharmacol.

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The inhibition of abnormal amyloid β (Aβ) aggregation has been regarded as a good target to control Alzheimer's disease. The present study adopted 2D-QSAR, HQSAR and 3D QSAR (CoMFA & CoMSIA) modeling approaches to identify the structural and physicochemical requirements for the potential Aβ aggregation inhibition. A structure-based molecular docking technique is utilized to approve the features that are obtained from the ligand-based techniques on 30 curcumin derivatives. The combined outputs were then used to screen the modified 10 compounds. The 2D QSAR model on curcumin derivatives gave statistical values R 2 = 0.9086 and SEE = 0.1837. The model was further confirmed by Y-randomization test and Applicability domain analysis by the standardization approach. The HQSAR study (Q 2 = 0.615, R 2 ncv = 0.931, R 2 pred = 0.956) illustrated the important molecular fingerprints for inhibition. Contour maps of 3D QSAR models, CoMFA (Q 2 = 0.687, R 2 ncv = 0.787, R 2 pred = 0.731) and CoMSIA (Q 2 = 0.743, R 2 ncv = 0.972, R 2 pred = 0.713), depict that the models are robust and provide explanation of the important features, like steric, electrostatic and hydrogen bond acceptor, which play important role for interaction with the receptor site cavity. The molecular docking study of the curcumin derivatives elucidates the important interactions between the amino acid residues at the catalytic site of the receptor and the ligands, indicating the structural requirements of the inhibitors. The ligand-receptor interactions of top hits were analyzed to explore the pharmacophore features of Aβ aggregation inhibition. The Aβ aggregation inhibitory activities of novel chemical entities were then obtained through inverse QSAR. The newly designed molecules were further screened through machine learning, prediction of toxicity and nature of metabolism to get the proposed six lead compounds.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Exploration of 3,6-dihydroimidazo(4,5-d)pyrrolo(2,3-b)pyridin-2(1H)-one derivatives as JAK inhibitors using various in silico techniques

Cited by 6 publications

References 72 publications

Research on the Anti-tumor Activity of Novel Histone Deacetylase Inhibitors based on 3D QSAR Model

Research on the Anti-tumor Activity of Novel Histone Deacetylase Inhibitors based on 3D QSAR Model

Identification of prodigious and under-privileged structural features for RG7834 analogs as Hepatitis B virus expression inhibitor

Design of novel amyloid β aggregation inhibitors using QSAR, pharmacophore modeling, molecular docking and ADME prediction

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