Identification of novel EED-EZH2 PPI inhibitors using an in silico fragment mapping method

Targeting EED as a key PRC2 complex mediator toward novel epigenetic therapeutics

EED within the PRC2 complex is crucial for chromatin regulation particularly in tumor development, making its inhibition a promising epigenetic therapeutic strategy. Significant advancement in PRC2 inhibitor development has been achieved with an approved EZH2 inhibitor in the market and with others in the clinical trials. However, current EZH2 inhibitors are limited to specific blood cancers and encounter therapeutic resistance. EED stabilizes PRC2 complex and enhances its activity through unique allosteric mechanisms, thereby acting as both a scaffold protein and a recognizer of H3K27me3 making it an attractive drug target. This review provides an overview of epigenetic therapeutic strategies targeting EED, including allosteric inhibitors, PPI inhibitors, and PROTACs, together with brief discussions on the relevant challenges, opportunities, and future directions.

EZH2 as a new therapeutic target in brain tumors: Molecular landscape, therapeutic targeting and future prospects

Brain tumors are responsible for high mortality and morbidity worldwide. The brain tumor treatment depends on identification of molecular pathways involved in progression and malignancy. Enhancer of zeste homolog 2 (EZH2) has obtained much attention in recent years in field of cancer therapy due to its aberrant expression and capacity in modulating expression of genes by binding to their promoter and affecting methylation status. The present review focuses on EZH2 signaling in brain tumors including glioma, glioblastoma, astrocytoma, ependymomas, medulloblastoma and brain rhabdoid tumors. EZH2 signaling mainly participates in increasing proliferation and invasion of cancer cells. However, in medulloblastoma, EZH2 demonstrates tumor-suppressor activity. Furthermore, EZH2 can regulate response of brain tumors to chemotherapy and radiotherapy. Various molecular pathways can function as upstream mediators of EZH2 in brain tumors including lncRNAs and miRNAs. Owing to its enzymatic activity, EZH2 can bind to promoter of target genes to induce methylation and affects their expression. EZH2 can be considered as an independent prognostic factor in brain tumors that its upregulation provides undesirable prognosis. Both anti-tumor agents and gene therapies such as siRNA have been developed for targeting EZH2 in cancer therapy.

Polycomb Repressive Complex 2 Modulation through the Development of EZH2-EED Interaction Inhibitors and EED Binders

Epigenetics is nowadays a well-accepted area of research. In the last years, tremendous progress was made regarding molecules targeting EZH2, directly or indirectly. Recently tazemetostat hit the market after FDA-approval for the treatment of lymphoma. However, the impairment of EZH2 activity by orthosteric intervention has proven to be effective only in a limited subset of cancers. Considering the multiproteic nature of the PRC2 complex and the marked dependence of EZH2 functions on the other core subunits such as EED, in recent years, a new targeting approach ascended to prominence. The possibility to cripple the function of the PRC2 complex by interfering with its multimeric integrity fueled the interest in developing EZH2–EED protein–protein interaction and EED inhibitors as indirect modulators of PRC2-dependent methyltransferase activity. In this Perspective, we aim to summarize the latest findings regarding the development and the biological activity of these emerging classes of PRC2 modulators from a medicinal chemist’s viewpoint.

Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer

Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is an important drug target for controlling cancer via epigenetic processes. In the present study, we have developed various predictive models for modeling the inhibitory activity of EZH2. Binary and multiclass models were built using SVM, random forest and XGBoost methods. Rigorous validation approaches including predictiveness curve, Y-randomization and applicability domain (AD) were employed for evaluation of the developed models. Eighteen descriptors selected from Boruta methods have been used for modeling. For binary classification, random forest and XGBoost achieved an accuracy of 0.80 and 0.82, respectively, on external test set. Contrastingly, for multiclass models, random forest and XGBoost achieved an accuracy of 0.73 and 0.75, respectively. 500 Y-randomization runs demonstrate that the models were robust and the correlations were not by chance. Evaluation metrics from predictiveness curve show that the selected eighteen descriptors predict active compounds with total gain (TG) of 0.79 and 0.59 for XGBoost and random forest, respectively. Validated models were further used for virtual screening and molecular docking in search of potential hits. A total of 221 compounds were commonly predicted as active with above the set probability threshold and also under the AD of training set. Molecular docking revealed that three compounds have reasonable binding energy and favorable interactions with critical residues in the active site of EZH2. In conclusion, we highlighted the potential of rigorously validated models for accurately predicting and ranking the activities of lead molecules against cancer epigenetic targets. The models presented in this study represent the platform for development of EZH2 inhibitors.