Literature DB >> 25298094

Plant-derived flavones as inhibitors of aurora B kinase and their quantitative structure-activity relationships.

Yearam Jung1, Soon Young Shin, Yeonjoong Yong, Hyeryoung Jung, Seunghyun Ahn, Young Han Lee, Yoongho Lim.   

Abstract

Although several plant-derived flavones inhibit aurora B kinase (aurB), quantitative relationships between the structural properties of plant-derived flavones and their inhibitory effects on aurB remain unclear. In this report, these quantitative structure-activity relationships were obtained. For quercetagetin, found in the Eriocaulon species, showing the best IC50 value among the flavone derivatives tested in this report, further biological tests were performed using cell-based assays, including Western blot analysis, flow cytometry, and immunofluorescence microscopy. In vitro cellular experiments demonstrated that quercetagetin inhibits aurB. The molecular-binding mode between quercetagetin and aurB was elucidated using in silico docking. Quercetagetin binds to aurB, aurA, and aurC and prevents the active phosphorylation of all three aurora kinases. In addition, quercetagetin triggers mitotic arrest and caspase-mediated apoptosis. These observations suggest that quercetagetin is an aurora kinase inhibitor. Induction of mitosis-associated tumor cell death by quercetagetin is a promising strategy for developing novel chemotherapeutic anticancer agents.
© 2014 John Wiley & Sons A/S.

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Keywords:  aurora B kinase; flavone; flow cytometry; immunofluorescence microscopy; in silico docking; quantitative structure-activity relationship; quercetagetin

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Year:  2014        PMID: 25298094     DOI: 10.1111/cbdd.12445

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  2 in total

1.  Design, synthesis, and biological evaluation of polyphenols with 4,6-diphenylpyrimidin-2-amine derivatives for inhibition of Aurora kinase A.

Authors:  Young Han Lee; Jihyun Park; Seunghyun Ahn; Youngshim Lee; Junho Lee; Soon Young Shin; Dongsoo Koh; Yoongho Lim
Journal:  Daru       Date:  2019-06-01       Impact factor: 3.117

2.  Ensemble learning method for the prediction of new bioactive molecules.

Authors:  Lateefat Temitope Afolabi; Faisal Saeed; Haslinda Hashim; Olutomilayo Olayemi Petinrin
Journal:  PLoS One       Date:  2018-01-12       Impact factor: 3.240

  2 in total

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