ArticleInternational journal of molecular sciences2012
The three dimensional Quantitative Structure Activity Relationships (3D-QSAR) and docking studies of curcumin derivatives as androgen receptor antagonists.
Article in International journal of molecular sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Curcumin: A Potential Weapon in the Prevention and Treatment of Head and Neck Cancer.ACS pharmacology & translational science · 2024Review
- Molecular Modeling Studies of Natural Inhibitors of Androgen Signaling in Prostate Cancer.Cancer informatics · 2022Article
- Antitumoral Activities of Curcumin and Recent Advances to ImProve Its Oral Bioavailability.Biomedicines · 2021Review
- Natural Product-Based Studies for the Management of Castration-Resistant Prostate Cancer: Computational to Clinical Studies.Frontiers in pharmacology · 2021Review
- A Review of Curcumin and Its Derivatives as Anticancer Agents.International journal of molecular sciences · 2019Review
- Nature curing cancer - review on structural modification studies with natural active compounds having anti-tumor efficiency.Biotechnology reports (Amsterdam, Netherlands) · 2015Review
- Biological evaluation and 3D-QSAR studies of curcumin analogues as aldehyde dehydrogenase 1 inhibitors.International journal of molecular sciences · 2014Article
- The discovery of potentially selective human neuronal nitric oxide synthase (nNOS) Inhibitors: a combination of pharmacophore modelling, CoMFA, virtual screening and molecular docking studies.International journal of molecular sciences · 2014Article
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5 authors.
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Abstract
Androgen receptor antagonists have been proved to be effective anti-prostate cancer agents. 3D-QSAR and Molecular docking methods were performed on curcumin derivatives as androgen receptor antagonists. The bioactive conformation was explored by docking the potent compound 29 into the binding site of AR. The constructed Comparative Molecular Field Analysis (CoMFA) and Comparative Similarity Indices Analysis (CoMSIA) models produced statistically significant results with the cross-validated correlation coefficients q(2) of 0.658 and 0.567, non-cross-validated correlation coefficients r(2) of 0.988 and 0.978, and predicted correction coefficients r(2) (pred) of 0.715 and 0.793, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of novel potent AR antagonists. A set of 30 new analogs were proposed by utilizing the results revealed in the present study, and were predicted with potential activities in the developed models.
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