AIMS

Epigenomics has significantly advanced through the incorporation of Systems Biology approaches. This study aims to investigate the human lysine methylome as a system, using a data-science approach to reveal its emergent properties, particularly focusing on histone mimicry and the broader implications of lysine methylation across the proteome.

METHODS

We employed a data-science-driven OMICS approach, leveraging high-dimensional proteomic data to study the lysine methylome. The analysis focused on identifying sequence-based recognition motifs of lysine methyltransferases and evaluating the prevalence and distribution of lysine methylation across the human proteome.

RESULTS

Our analysis revealed that lysine methylation impacts 15% of the known proteome, with a notable bias toward mono-methylation. We identified sequence-based recognition motifs of 13 lysine methyltransferases, highlighting candidates for histone mimicry. These findings suggest that the selective inhibition of individual lysine methyltransferases could have systemic effects rather than merely targeting histone methylation.

CONCLUSIONS

The lysine methylome has significant mechanistic value and should be considered in the design and testing of therapeutic strategies, particularly in precision oncology. The study underscores the importance of considering non-histone proteins involved in DNA damage and repair, cell signaling, metabolism, and cell cycle pathways when targeting lysine methyltransferases.