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Using Machine Learning and Targeted Mass Spectrometry to Explore the Methyl-Lys Proteome.

STAR protocols (2020-12-31)
Francois Charih, James R Green, Kyle K Biggar
ABSTRACT

Protein lysine methylation mediates a variety of biological processes, and their dysregulation has been established to play pivotal roles in human disease. A number of these sites constitute attractive drug targets. However, systematic identification of methylation sites is challenging and resource intensive. Here, we present a protocol combining MethylSight, a machine learning model trained to identify promising lysine methylation sites, and mass spectrometry for subsequent validation. Our approach can reduce the time and investment required to identify novel methylation sites. For complete information on the use and execution of this protocol, please refer to Biggar et al. (2020).

MATERIALS
Product Number
Brand
Product Description

Sigma-Aldrich
Guanidine hydrochloride, for molecular biology, ≥99%
Roche
Tris hydrochloride
Sigma-Aldrich
Iodoacetamide, ≥99% (NMR), crystalline