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Pharmacology Research & Perspectives
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Pharmacology Research & Perspectives
Article
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Identification of an irreversible PPARγ antagonist with potent anticancer activity

Authors: Youyi Peng; Qiang Zhang; Robert M. Zielinski; Richard D. Howells; William J. Welsh;

Identification of an irreversible PPARγ antagonist with potent anticancer activity

Abstract

AbstractMelanoma is responsible for most skin cancer deaths, and its incidence continues to rise year after year. Different treatment options have been developed for melanoma depending on the stage of the disease. Despite recent advances in immuno‐ and targeted therapies, advanced melanoma remains incurable and thus an urgent need persists for safe and more effective melanoma therapeutics. In this study, we demonstrate that a novel compound MM902 (3‐(3‐(bromomethyl)‐5‐(4‐(tert‐butyl) phenyl)‐1H‐1,2,4‐triazol‐1‐yl) phenol) exhibited potent efficacies in inhibiting the growth of different cancer cells, and suppressed tumor growth in a mouse xenograft model of malignant melanoma. Beginning with MM902 instead of specific targets, computational similarity‐ and docking‐based approaches were conducted to search for known anticancer drugs whose structural features match MM902 and whose pharmacological target would accommodate an irreversible inhibitor. Peroxisome proliferator‐activated receptor (PPAR) was computationally identified as one of the pharmacological targets and confirmed by in vitro biochemical assays. MM902 was shown to bind to PPARγ in an irreversible mode of action and to function as a selective antagonist for PPARγ over PPARα and PPARδ. It is hoped that MM902 will serve as a valuable research probe to study the functions of PPARγ in tumorigenesis and other pathological processes.

Keywords

Skin Neoplasms, PPARγ, irreversible antagonist, Antineoplastic Agents, RM1-950, Mice, SCID, anticancer, Mice, Melanoma, Cutaneous Malignant, Cell Line, Tumor, melanoma, Animals, Humans, Invited Reviews, Melanoma, Dose-Response Relationship, Drug, Computational Biology, Xenograft Model Antitumor Assays, Molecular Docking Simulation, PPAR gamma, Female, Therapeutics. Pharmacology

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
Green
gold