Epigenetic drug discovery is a promising avenue to find therapeutic agents for treating several diseases and developing novel chemical probes for research. In order to identify hit and lead compounds, the chemical space has been explored and screened, generating valuable bioactivity information that can be used for multiple purposes such as prediction of the activity of existing chemicals, e.g., small molecules, guiding the design or optimization of compounds, and expanding the epigenetic relevant chemical space. Herein, we review the chemical spaces explored for epigenetic drug discovery and discuss the advances in using structure–activity relationships stored in public chemogenomic databases. We also review current efforts to chart and identify novel regions of the epigenetic relevant chemical space. In particular, we discuss the development and accessibility of two significant types of compound libraries focused on epigenetic targets: commercially available libraries for screening and targeted chemical libraries using de novo design. In this mini-review, we emphasize inhibitors of DNA methyltransferases.

The manuscript discusses recent advances on computer-aided drug discovery (CADD) with focus on data-dependent drug discovery. Herein, we do not intend to review the many CADD methodologies comprehensively. Instead, the review discusses progress on selected concepts, methodologies, resources, and applications that are part of multidisciplinary efforts: the manuscript covers advances in artificial intelligence, machine learning, virtual screening, and chemical space including the concept of chemical multiverses, and novel extended similarity methods for chemical space exploration. Throughout the review, we emphasize public resources and open-source code available to the scientific community working in academia and non-profit institutions.