Recent progress on cheminformatics approaches to epigenetic drug discovery

Area of Science:

• * Computational chemistry and epigenetics.

Background:

• * Epigenetic markers significantly influence genome function, driving innovation in drug discovery, particularly for cancer.
• * The field of epi-informatics has expanded, increasing the chemical space and computational applications for epigenetics.

Purpose of the Study:

• * To review computational approaches for discovering small molecules targeting epigenetic mechanisms.
• * To summarize available chemogenomics data for epigenetic targets.
• * To highlight the potential of biomedical knowledge mining in advancing epigenetic drug discovery.

Main Methods:

• * Review of computational strategies in small molecule epigenetic drug discovery.
• * Analysis of current chemogenomics databases for epigenetic targets.
• * Exploration of biomedical knowledge mining techniques.

Main Results:

• * Significant progress in understanding structure-epigenetic activity relationships.
• * Development of predictive models for novel epigenetic agents.
• * Growing availability of chemogenomics data for epigenetic targets.

Conclusions:

• * Computational approaches are crucial for advancing epigenetic drug discovery.
• * Integrating epi-informatics and chemogenomics enhances the identification of epigenetic modulators.
• * Biomedical knowledge mining offers a promising avenue for future epigenetic drug development.