3D-QSAR, Docking, ADME/Tox studies on Flavone analogs reveal anticancer activity through Tankyrase inhibition.
Sci Rep
; 9(1): 5414, 2019 04 01.
Article
em En
| MEDLINE
| ID: mdl-30932078
Flavones are known as an inhibitor of tankyrase, a potential drug target of cancer. We here expedited the use of different computational approaches and presented a fast, easy, cost-effective and high throughput screening method to identify flavones analogs as potential tankyrase inhibitors. For this, we developed a field point based (3D-QSAR) quantitative structure-activity relationship model. The developed model showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 (0.89) and q2 (0.67). This model may help to explain SAR data and illustrated the key descriptors which were firmly related with the anticancer activity. Using the QSAR model a dataset of 8000 flavonoids were evaluated to classify the bioactivity, which resulted in the identification of 1480 compounds with the IC50 value of less than 5 µM. Further, these compounds were scrutinized through molecular docking and ADMET risk assessment. Total of 25 compounds identified which further analyzed for drug-likeness, oral bioavailability, synthetic accessibility, lead-likeness, and alerts for PAINS & Brenk. Besides, metabolites of screened compounds were also analyzed for pharmacokinetics compliance. Finally, compounds F2, F3, F8, F11, F13, F20, F21 and F25 with predicted activity (IC50) of 1.59, 1, 0.62, 0.79, 3.98, 0.79, 0.63 and 0.64, respectively were find as top hit leads. This study is offering the first example of a computationally-driven tool for prioritization and discovery of novel flavone scaffold for tankyrase receptor affinity with high therapeutic windows.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Relação Quantitativa Estrutura-Atividade
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Tanquirases
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Flavonas
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Ensaios de Triagem em Larga Escala
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Simulação de Acoplamento Molecular
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Neoplasias
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2019
Tipo de documento:
Article