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Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics 1/2019

01.12.2019 | Original Article

Computational simulation of inhibitory effects of curcumin, retinoic acid and their conjugates on GSK-3 beta

verfasst von: Hemanshi Mishra, Rajesh Kumar Kesharwani, Dev Bukhsh Singh, Sandeep Tripathi, Shiv Kumar Dubey, Krishna Misra

Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 1/2019

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Abstract

Turmeric, since in ancient Indian traditional medicinal system, has been implicated for its therapeutic and chemopreventive properties against a broad spectrum of diseases. Curcumin, the active polyphenol from turmeric, helps to obstruct the growth of many types of cancers at various stages which include prostrate, melanoma, breast, brain tumor, pancreatic, leukemia, etc. The initiation and recurrence of cancer have been attributed to few mutated cells in bulk of tumor called as cancer stem cells which have the capacity of self-renewal and differentiation. Glycogen synthase kinase-3 beta (GSK-3B) is a multifunctional serine/threonine protein kinase, originally found in mammals, an important component of diverse signaling pathways, dysregulation of which leads to affect the cancer stem cell properties. The nutritional- and phytochemical-based dietary interventions may complement current chemotherapy to prevent recurrence and relapse of cancer. The objective of present study is to investigate the effect of retinoic acid and curcumin–retinoic acid conjugates against GSK-3B protein. The in silico results indicate that molecule 3 (curcumin–retinoic acid conjugates) might be a potent inhibitor of GSK-3B and a novel future drug candidate for the treatment of cancer.

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Metadaten
Titel
Computational simulation of inhibitory effects of curcumin, retinoic acid and their conjugates on GSK-3 beta
verfasst von
Hemanshi Mishra
Rajesh Kumar Kesharwani
Dev Bukhsh Singh
Sandeep Tripathi
Shiv Kumar Dubey
Krishna Misra
Publikationsdatum
01.12.2019
Verlag
Springer Vienna
Erschienen in
Network Modeling Analysis in Health Informatics and Bioinformatics / Ausgabe 1/2019
Print ISSN: 2192-6662
Elektronische ISSN: 2192-6670
DOI
https://doi.org/10.1007/s13721-018-0177-x

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