Literature DB >> 24702656

Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer.

Manika Awasthi1, Swati Singh, Veda P Pandey, Upendra N Dwivedi.   

Abstract

Aromatase, catalyzing final step of estrogen biosynthesis, is considered a key target for the development of drug against estrogen-dependent breast cancer (EDBC). Identification and development of naturally occurring compounds, such as flavonoids, as drugs against EDBC is in demand due to their lesser toxicity when compared to those of synthetic ones. Thus, a three-dimensional quantitative structure-activity relationship, using comparative molecular field analysis (CoMFA) was done on a series of 45 flavonoids against human aromatase. A significant cross-validated correlation coefficient (q(2)) of 0.827 was obtained. The best predictive CoMFA model explaining the biological activity of the training and test sets with correlation coefficient values (r(2)) of 0.916 and 0.710, respectively, when used for virtual screening of a flavanoids database following molecular docking revealed a flavanone namely, 7-hydroxyflavanone beta-D-glucopyranoside showing highest predicted activity of 1.09 μM. In comparison to a well-established inhibitor of aromatase, namely 7-hydroxyflavanone (IC50: 3.8 μM), the derivative identified in the present study, namely 7-hydroxyflavanone beta-D-glucopyranoside exhibited about 3.5 folds higher inhibitory activity against aromatase. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 25 ns MD simulation analysis revealed high stability and effective binding of 7-hydroxyflavanone beta-D-glucopyranoside within the active site of aromatase. To the best of our knowledge, this is the first report of CoMFA-based QSAR model for virtual screening of flavonoids as inhibitors of aromatase.

Entities:  

Keywords:  3D-QSAR; 7-hydroxyflavanone beta-D-glucopyranoside; aromatase; breast cancer; flavonoids; molecular dynamics simulation

Mesh:

Substances:

Year:  2014        PMID: 24702656     DOI: 10.1080/07391102.2014.912152

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102


  7 in total

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2.  Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors.

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Review 3.  Towards understanding aromatase inhibitory activity via QSAR modeling.

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Journal:  EXCLI J       Date:  2018-07-20       Impact factor: 4.068

4.  Therapeutic Effects of Modified Gengnianchun Formula on Stress-Induced Diminished Ovarian Reserve Based on Experimental Approaches and Network Pharmacology.

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5.  A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening.

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Review 6.  Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens.

Authors:  Anna Helena Mazurek; Łukasz Szeleszczuk; Thomas Simonson; Dariusz Maciej Pisklak
Journal:  Int J Mol Sci       Date:  2020-09-03       Impact factor: 5.923

7.  In silico docking and ADME study of deketene curcumin derivatives (DKC) as an aromatase inhibitor or antagonist to the estrogen-alpha positive receptor (Erα+): potent application of breast cancer.

Authors:  Vraj Shah; Jaydip Bhaliya; Gautam M Patel
Journal:  Struct Chem       Date:  2022-01-28       Impact factor: 1.795

  7 in total

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