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Conversion of DNA methyltransferases into azidonucleosidyl transferases via synthetic cofactors.

ABSTRACT: Aziridine-based cofactor mimics have been synthesized and are shown to undergo methyltransferase-dependent DNA alkylation. Notably, each cofactor mimic possesses an azide functionality, to which can be attached an assortment of unnatural groups following methyltransferase-dependent DNA delivery. DNA duplexes modified with these cofactor mimics are capable of undergoing the Staudinger ligation with phosphines tethered to biological functionalities following enzymatic modification. This methodology provides a new tool by which to selectively modify DNA in a methyltransferase-dependent way. The conversion of biological methyltransferases into azidonucleosidyl transferases demonstrated here also holds tremendous promise as a means of identifying, as yet, unknown substrates of methylation.

SUBMITTER: Comstock LR

PROVIDER: S-EPMC1067524 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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Conversion of DNA methyltransferases into azidonucleosidyl transferases via synthetic cofactors.

Comstock Lindsay R LR Rajski Scott R SR

Nucleic acids research 20050318 5

Aziridine-based cofactor mimics have been synthesized and are shown to undergo methyltransferase-dependent DNA alkylation. Notably, each cofactor mimic possesses an azide functionality, to which can be attached an assortment of unnatural groups following methyltransferase-dependent DNA delivery. DNA duplexes modified with these cofactor mimics are capable of undergoing the Staudinger ligation with phosphines tethered to biological functionalities following enzymatic modification. This methodolog ...[more]

PMID: 15778434

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Project description:Methylation of DNA and histone proteins are mutually involved in the epigenetic regulation of gene expression mediated by DNA methyltransferases (DNMTs) and histone methyltransferases (HMTs). DNMTs methylate cytosine residues within gene promoters, whereas HMTs catalyze the transfer of methyl groups to lysine and arginine residues of histone proteins, thus causing chromatin condensation and transcriptional repression, which play an important role in the pathogenesis of cancer. The potential reversibility of epigenetic alterations has encouraged the development of dual pharmacologic inhibitors of DNA and histone methylation as anticancer therapeutics. Dietary flavones can affect epigenetic modifications that accumulate over time and have shown anticancer properties, which are undefined. Through DNA binding and in silico protein-ligand docking studies with plant flavones viz. Apigenin, Chrysin and Luteolin, the effect of flavones on DNA and histone methylation was assessed. Spectroscopic analysis of flavones with calf-thymus DNA revealed intercalation as the dominant binding mode, with specific binding to a GC-rich sequence in the DNA duplex. A virtual screening approach using a model of the catalytic site of DNMT and EZH2 demonstrated that plant flavones are tethered at both ends inside the catalytic pocket of DNMT and EZH2 by means of hydrogen bonding. Epigenetic studies performed with flavones exhibited a decrease in DNMT enzyme activity and a reversal of the hypermethylation of cytosine bases in the DNA and prevented cytosine methylation in the GC-rich promoter sequence incubated with the M.SssI enzyme. Furthermore, a marked decrease in HMT activity and a decrease in EZH2 protein expression and trimethylation of H3K27 were noted in histones isolated from cancer cells treated with plant flavones. Our results suggest that dietary flavones can alter DNMT and HMT activities and the methylation of DNA and histone proteins that regulate epigenetic modifications, thus providing a significant anticancer effect by altering epigenetic processes involved in the development of cancer.

Dataset Information

Conversion of DNA methyltransferases into azidonucleosidyl transferases via synthetic cofactors.

Publications

Conversion of DNA methyltransferases into azidonucleosidyl transferases via synthetic cofactors.

Similar Datasets

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