DNA methyltransferases (DNMTs) are a family of epigenetic enzymes for which inhibition is an attractive strategy for the treatment of cancer and other diseases. In synergy with experimental approaches, computational methods are increasingly being used to identify and optimize the activity
of inhibitors of DNMTs as well as to rationalize at the molecular level of the mechanism of established inhibitors. Recently, a crystallographic structure of the methyltransferase domain of human DNMT1 bound to unmethylated DNA was published encouraging the application of structure-based approaches
to design and optimize the activity of currently known inhibitors. Herein, we review the progress in the discovery and optimization of inhibitors of DNMTs using computational approaches including homology modeling, docking, pharmacophore modeling, molecular dynamics, and virtual screening.
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