Abstract
In this work, we analyze the structure-activity relationships (SAR) of epigenetic inhibitors (lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined activity landscape, molecular docking and molecular dynamics approach. The study was based on a set of 251 G9a inhibitors with reported experimental activity. The activity landscape analysis rapidly led to the identification of activity cliffs, scaffolds hops and other active an inactive molecules with distinct SAR. Structure-based analysis of activity cliffs, scaffold hops and other selected active and inactive G9a inhibitors by means of docking followed by molecular dynamics simulations led to the identification of interactions with key residues involved in activity against G9a, for instance with ASP 1083, LEU 1086, ASP 1088, TYR 1154 and PHE 1158. The outcome of this work is expected to further advance the development of G9a inhibitors.
Highlights
Technological-scientific advances have allowed to study the molecular machinery involved in the development of chronic diseases, as is the case of neoplastic hematological diseases
First we present and discuss the results of a qualitative exploration of the structure-activity relationship (SAR) of the data sets
Activity landscape modeling led to the identification of selective and dual compounds against G9a and DNA methyltransferase 1 (DNMT1), which will facilitate the generation of more robust SAR studies for both epigenetic targets
Summary
Technological-scientific advances have allowed to study the molecular machinery involved in the development of chronic diseases, as is the case of neoplastic hematological diseases. The work published by Rabal, et al serves as a key step forward in this analysis. They synthesized a novel series of 4-aminoquinolines as inhibitors of the enzymes lysine methyltransferase (G9a) and DNA methyltransferase 1 (DNMT1). DNMT1 is an enzyme that transfers methyl groups to cytosine nucleotides of genomic DNA. This protein is the major enzyme responsible for maintaining methylation patterns following DNA replication. Both epigenetic targets participate collaboratively in the development of neoplastic hematological diseases. Given that the compounds analyzed were obtained from a lead optimization process, the activity landscape modeling for the identification of “dual activity cliffs” and “dual activity switches”, along with their interpretation at the molecular level are Molecules 2018, 23, 3282; doi:10.3390/molecules23123282 www.mdpi.com/journal/molecules
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