Literature DB >> 32668242

Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome.

Kyle K Biggar1, Francois Charih2, Huadong Liu3, Yasser B Ruiz-Blanco4, Leanne Stalker5, Anand Chopra1, Justin Connolly1, Hemanta Adhikary1, Kristin Frensemier1, Matthew Hoekstra1, Marek Galka3, Qi Fang3, Christopher Wynder3, William L Stanford6, James R Green7, Shawn S-C Li8.   

Abstract

Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We develop MethylSight, a program that predicts Kme events solely on the physicochemical properties of residues surrounding the putative methylation sites, which then requires validation by targeted MS. Using this approach, we identify 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 that Lys methylation is a prevalent post-translational modification in the human proteome. Our work provides a useful resource for guiding systematic exploration of the role of Lys methylation in human health and disease.
Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  KDM5b; histone H1; histone H2B; histone marks; lysine methylation; machine learning; methyllysine proteome; non-histone methylation

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Substances:

Year:  2020        PMID: 32668242     DOI: 10.1016/j.celrep.2020.107896

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  3 in total

1.  Insights into a Cancer-Target Demethylase: Substrate Prediction through Systematic Specificity Analysis for KDM3A.

Authors:  Anand Chopra; William G Willmore; Kyle K Biggar
Journal:  Biomolecules       Date:  2022-04-27

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

Authors:  Francois Charih; James R Green; Kyle K Biggar
Journal:  STAR Protoc       Date:  2020-10-21

3.  PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein-Peptide and Protein-Protein Binding Affinity.

Authors:  Sandra Romero-Molina; Yasser B Ruiz-Blanco; Joel Mieres-Perez; Mirja Harms; Jan Münch; Michael Ehrmann; Elsa Sanchez-Garcia
Journal:  J Proteome Res       Date:  2022-06-02       Impact factor: 5.370

  3 in total

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