INTRODUCTION
Epigenetic drug discovery remains a promising drug discovery strategy that has long been driven by advances in computational approaches. The subfield of epi-informatics, established more than a decade ago, continues to evolve rapidly as emerging machine learning methodologies reshape and expand its applications.
AREAS COVERED
The authors provide an updated overview of bioinformatics, chemoinformatics, and machine learning methodologies used to identify, design, and optimize compounds, primarily small-molecules, that modulate epigenetic processes with therapeutic potential. The discussion is based on a comprehensive literature analysis of peer-reviewed literature, encompassing 7,185 unique research articles published between 2000 up to 2025. The article also examines the epigenetic drug discovery landscape by analyzing the most extensively investigated epigenetic targets and emerging research trends.
EXPERT OPINION
Epi-informatics has evolved into a distinct interdisciplinary field integrating bioinformatics, chemoinformatics, and artificial intelligence to advance epigenetic drug discovery. Although rapid progress in multi-omics integration, molecular modeling, and generative artificial intelligence is accelerating the identification of drug candidates, future success will depend on high-quality, standardized data, interpretable machine learning models, and rigorous experimental validation that ensure reproducibility. Addressing these challenges will further advance epi-informatics in oncology research and an expanding range of complex diseases.
Aylin del Moral-Morales, Erik D. Díaz-Dionisio, José L. Medina-Franco· Expert Opinion on Drug Disco...· 0 citations
FOXM1 is a cell proliferation-driving transcription factor activated by phosphorylation-induced conformational changes. In its inactive state, an intramolecular β-hairpin within the transactivation domain (TAD) binds the N-terminal repressor domain (NRD), forming a composite β-sheet that locks the protein in an autoinhibited conformation. Despite the known importance of this regulatory switch, the molecular events that unlock FOXM1 remain poorly characterized. Here, we performed 5 μs all-atom molecular dynamics simulations of human FOXM1b NRD-TAD complexes in both unphosphorylated and tetra-phosphorylated states, modeling four experimentally validated regulatory phosphosites. Our results showed that phosphorylation induces local unfolding of the β-hairpin beginning at Ser715, located at the hairpin turn, and propagates to global disruption of the NRD interface through hydrogen bond loss, salt bridge rupture, and secondary structure collapse. In contrast, the unphosphorylated complex maintains stable hairpin geometry and interdomain contacts. Additional replicate tetra-phosphorylated simulations and a monophosphorylated Ser715 simulation reproduced the β-hairpin unfolding event, supporting both reproducibility and the sufficiency of Ser715 phosphorylation in initiating this transition. Per-residue MM-PBSA energy decomposition further reveals that phosphorylation redistributes interdomain interaction energetics, with Ser715 emerging as the dominant locus of energetic perturbation despite the presence of multiple phosphosites. Together, these findings support a phosphorylation-triggered order-to-disorder transition that relieves FOXM1 autoinhibition and highlight Ser715 as a key structural and energetic switch. Our study provides a dynamic molecular framework for targeting FOXM1 activation via its regulatory fold.
Sara Alrawashdeh, Raghd Obidat, Aylin Del Moral-Morales et al.· Journal of Chemical Informat...· 0 citations
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