Recent progress on cheminformatics approaches to epigenetic drug discovery

Abstract

The ability of epigenetic markers to affect genome function has enabled transformative changes in drug discovery, especially in cancer and other emerging therapeutic areas. Concordant with the introduction of the term 'epi-informatics', the size of the epigenetically relevant chemical space has grown substantially and so did the number of applications of cheminformatic methods to epigenetics. Recent progress in epi-informatics has improved our understanding of the structure-epigenetic activity relationships and boosted the development of models predicting novel epigenetic agents. Herein, we review the advances in computational approaches to drug discovery of small molecules with epigenetic modulation profiles, summarize the current chemogenomics data available for epigenetic targets, and provide a perspective on the greater utility of biomedical knowledge mining as a means to advance the epigenetic drug discovery.

Figure 1.

Title. (a) The number of papers in PubMed with the keyword ‘Epigenetics’ alone or co-occurring with multiple diseases (cancer, diabetes, neurodegenerative, cardiovascular, central nervous system, and rare disease) by year. (b) The number of papers in PubMed with the keywords ‘epigenetics drug discovery’ and ‘epigenetics + computer-aided drug discovery / computational drug discovery’ by year.

Figure 2.

Title. (a) Chemical structures of epigenetic drugs approved for clinical use. (b) Chemical structures of selected compounds in clinical development as epidrugs. Epigenetic targets are grouped as writers, erasers, and readers. A comprehensive review of compounds in clinical development the reader was recently provided by Ganesan et al. [4]. For definitions of abbreviations, please see the main text.

Figure 3.

Visual representation of the current epigenetics-relevant chemical space. The visualization was generated with the recent Tree Manifold Approximation and Projection method and Statistical-Based Database Fingerprints as condensed representations of compounds associated to the epigenetic targets [31]. Individual nodes of the tree are epigenetic targets, colored by their class. The nodes are clustered according to the pairwise similarity of their condensed representations. The branches represent the connection between the chemical space of two different targets. Proximal data sets can contribute to the discovery of compounds acting on multiple targets. For definitions of abbreviations, please see the main text.