Computational Methods for Epigenetic Drug Discovery: A Focus on Activity Landscape Modeling

Adv Protein Chem Struct Biol. 2018;113:65-83. doi: 10.1016/bs.apcsb.2018.01.001. Epub 2018 Mar 5.

Abstract

Epigenetic drug discovery is an emerging strategy against several chronic and complex diseases. The increased interest in epigenetics has boosted the development and maintenance of large information on structure-epigenetic activity relationships for several epigenetic targets. In turn, such large databases-many in the public domain-are a rich source of information to explore their structure-activity relationships (SARs). Herein, we conducted a large-scale analysis of the SAR of epigenetic targets using the concept of activity landscape modeling. A comprehensive quantitative analysis and a novel visual representation of the epigenetic activity landscape enabled the rapid identification of regions of targets with continuous and discontinuous SAR. This information led to the identification of epigenetic targets for which it is anticipated an easier or a more difficult drug-discovery program using conventional hit-to-lead approaches. The insights of this work also enabled the identification of specific structural changes associated with a large shift in biological activity. To the best of our knowledge, this work represents the largest comprehensive SAR analysis of several epigenetic targets and contributes to the better understanding of the epigenetic activity landscape.

Keywords: Activity cliffs; Chemical space; Chemoinformatics; Docking; Epi-informatics; SALI; SAS maps; Structure–activity relationships.

Publication types

  • Review

MeSH terms

  • Drug Discovery*
  • Epigenesis, Genetic / drug effects*
  • Epigenesis, Genetic / genetics
  • Models, Molecular
  • Structure-Activity Relationship