In silico study of selective inhibition mechanism of S-adenosyl-L-methionine analogs for human DNA methyltransferase 3A. (February 2023)

• Record Type: Journal Article
• Authors: Stillson, Nathaniel J.; Anderson, Kyle E.; Reich, Norbert O.
• Is Part Of: Computational biology and chemistry. Volume 102(2023)
• Publication Date: 2023-02
• Subjects: DNA methyltransferase inhibitors -- Epigenetic protein targets -- MM/GBSA -- S-adenosyl-L-methionine derivatives -- In silico based drug design; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2022.107796
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: Epigenetic mechanisms leading to transcriptional regulation, including DNA methylation, are frequently dysregulated in diverse cancers. Interfering with aberrant DNA methylation performed by DNA cytosine methyltransferases (DNMTs) is a clinically validated approach. In particular, the selective inhibition of the de novo DNMT3A and DNMT3B enzymes, whose expression is limited to early embryogenesis, adult stem cells, and in cancers, is particularly attractive; such selectivity is likely to attenuate the dose limiting toxicity shown by current, non-selective DNMT inhibitors. We use molecular dynamics (MD) based computational analysis to study known small molecule binders of DNMT3A, then propose reversible, tight binding, and selective inhibitors that exploit the Asn 1192 /Arg 688 difference between the maintenance DNMT1 and DNMT3A near the active site. A similar strategy exploiting the presence of a unique active site cysteine Cys 666 is used to propose DNMT3A-selective irreversible inhibitors. We report our results of relative binding energies of the known and proposed compounds estimated using MM/GBSA and umbrella sampling (US) techniques, and our evaluation of other end-point binding free energy calculation methods for these receptors. These calculations offer insight into the potential for small molecules to selectively target the active site of DNMT3A. Graphical Abstract: ga1 Highlights: MM/GBSA methods predict relative binding affinities in DNMTs. Conserved Asp residue protein-ligand H bond drives selective binding. Non-conserved Asn/Arg difference is predicted to drive further selectivity. Novel proposed inhibitors exploit this difference by MM/GBSA and US.