ArticleEnvironmental toxicology2014
Inhibition of polyisoprenylated methylated protein methyl esterase by synthetic musks induces cell degeneration.
Article in Environmental toxicology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals.International journal of environmental research and public health · 2022Article
- Polyisoprenylated Cysteinyl Amide Inhibitors: A Novel Approach to Controlling Cancers with Hyperactive Growth Signaling.Current medicinal chemistry · 2021Article
- Endocrine disruptors also function as nervous disruptors and can be renamed endocrine and nervous disruptors (ENDs).Toxicology reports · 2021Review
- Disruption of actin filaments and suppression of pancreatic cancer cell viability and migration following treatment with polyisoprenylated cysteinyl amides.American journal of cancer research · 2016Article
- Polyisoprenylated methylated protein methyl esterase: a putative biomarker and therapeutic target for pancreatic cancer.European journal of medicinal chemistry · 2014Article
- Polyisoprenylated methylated protein methyl esterase as a putative drug target for androgen-insensitive prostate cancer.Ecancermedicalscience · 2014Article
- Polyisoprenylated methylated protein methyl esterase is both sensitive to curcumin and overexpressed in colorectal cancer: implications for chemoprevention and treatment.BioMed research international · 2013Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Synthetic fragrances are persistent environmental pollutants that tend to bioaccumulate in animal tissues. They are widely used in personal care products and cleaning agents. Worldwide production of Galaxolide and Tonalide are in excess of 4500 tons annually. Because of their widespread production and use, they have been detected in surface waters and fish in the US and Europe. Consumption of contaminated water and fish from such sources leads to bioaccumulation and eventual toxicity. Since fragrances and flavors bear structural similarities to polyisoprenes, it was of interest to determine whether toxicity by Galaxolide and Tonalide may be linked with polyisoprenylated methylated protein methyl esterase (PMPMEase) inhibition. A concentration-dependent study of PMPMEase inhibition by Galaxolide and Tonalide as well as their effects on the degeneration of cultured cells were conducted. Galaxolide and Tonalide inhibited purified porcine liver PMPMEase with Ki values of 11 and 14 μM, respectively. Galaxolide and Tonalide also induced human cancer cell degeneration with EC50 values of 26 and 98 μM (neuroblastoma SH-SY5Y cells) and 58 and 14 μM (lung cancer A549 cells), respectively. The effects on cell viability correlate well with the inhibition of PMPMEase activity in the cultured cells. Molecular docking analysis revealed that the binding interactions are most likely between the fragrance molecules and hydrophobic amino acids in the active site of the enzyme. These results appear to suggest that the reported neurotoxicity of these compounds may be associated with their inhibition of PMPMEase. Exposure to fragrances may pose a significant risk to individuals predisposed to developing degenerative disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.