p300 and CREB-binding protein (CBP) are ubiquitously expressed pleiotropic lysine acetyltransferases and play a key role as transcriptional co-activators that are essential for a multitude of cellular processes. Despite great importance, there is a lack of highly selective, potent, druglike p300/CBP inhibitors. Through the artificial-intelligence-assisted drug discovery pipeline and further optimization, we reported the discovery of novel, highly selective, potent small-molecule inhibitors of p300/CBP histone acetyltransferases (HAT) with desired druglike properties, exemplified by B026. Our data demonstrated that B026, with half maximal inhibitory concentration (IC50) values of 1.8 nM to p300 and 9.5 nM to CBP enzyme inhibitory activity, is the most potent, selective p300/CBP HAT inhibitor. Moreover, B026 achieves significant and dose-dependent tumor growth inhibition in an animal model of human cancer, suggesting that B026 is a highly promising p300/CBP HAT inhibitor and warrants extensive preclinical investigation as a potential clinical development candidate.

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

DNA methyltransferase-1 (DNMT1) plays a crucial role in the maintenance of genomic methylation patterns. The crystal structure of DNMT1 was determined in two different states in which the helix that follows the catalytic loop was either kinked (designated helix-kinked) or well folded (designated helix-straight state). Here, we show that the proper structural transition between these two states is required for DNMT1 activity. The mutations of N1248A and R1279D, which did not affect interactions between DNMT1 and substrates or cofactors, allosterically reduced enzymatic activities in vitro by decreasing k/ K for AdoMet. The crystallographic data combined with molecular dynamic (MD) simulations indicated that the N1248A and R1279D mutants bias the catalytic helix to either the kinked or straight conformation. In addition, genetic complementation assays for the two mutants suggested that disturbing the conformational transition reduced DNMT1 activity in cells, which could act additively with existing DNMT inhibitors to decrease DNA methylation. Collectively, our studies provide molecular insights into conformational changes of the catalytic helix, which is essential for DNMT1 catalytic activity, and thus aid in better understanding the relationship between DNMT1 dynamic switching and enzymatic activity.