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Proteome-wide Prediction of Lysine Methylation Reveals Novel Histone Marks and Outlines the Methyllysine Proteome

Biggar, K. K.; Charih, F.; Liu, H.; Ruiz-Blanco, Y. B.; Stalker, L.; Chopra, A.; Connolly, J.; Adhikary, H.; Frensemier, K.; Galka, M.; Fang, Q.; Wynder, C.; Standford, W.; Green, J. R.; Li, S. S. C.

2020-03-01 biochemistry
10.1101/274688 bioRxiv
Show abstract

Protein Lys methylation plays a critical role in numerous cellular processes, yet it has been challenging to identify Lys methylation in a systematic manner. We present here an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We have developed MethylSight, a program that predicts Kme events solely on physicochemical and biochemical properties of putative methylation sites, which can then be validated by targeted MS. Using this approach, we have identified 70 new histone Kme marks with a 90% validation rate. H2BK43me2, which undergoes dynamic changes during stem cell differentiation, is found to be a substrate of KDM5b. Furthermore, MethylSight predicts ~50,000 Kme sites in non-histone proteins with high confidence, suggesting that Lys methylation is a prevalent post-translational modification. Our work provides a useful resource for systematic exploration of the role of Lys methylation in human health and disease.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.