Abstract
Post-translational modification (PTM)(1) plays an important role in regulating the functions of proteins. PTMs of multiple residues on one protein may work together to determine a functional outcome, which is known as PTM cross-talk. Identification of PTM cross-talks is an emerging theme in proteomics and has elicited great interest, but their properties remain to be systematically characterized. To this end, we collected 193 PTM cross-talk pairs in 77 human proteins from the literature and then tested location preference and co-evolution at the residue and modification levels. We found that cross-talk events preferentially occurred among nearby PTM sites, especially in disordered protein regions, and cross-talk pairs tended to co-evolve. Given the properties of PTM cross-talk pairs, a naïve Bayes classifier integrating different features was built to predict cross-talks for pairwise combination of PTM sites. By using a 10-fold cross-validation, the integrated prediction model showed an area under the receiver operating characteristic (ROC) curve of 0.833, superior to using any individual feature alone. The prediction performance was also demonstrated to be robust to the biases in the collected PTM cross-talk pairs. The integrated approach has the potential for large-scale prioritization of PTM cross-talk candidates for functional validation and was implemented as a web server available at http://bioinfo.bjmu.edu.cn/ptm-x/.
Highlights
To find out whether the 81 computationally identified motifs were enriched in the sequence context of the cross-talk pairs, only Post-translational modification (PTM) pairs that had compatible residues and PTM types with the motifs and were located within five amino acids were selected as candidates
Structural proximity, and residue co-evolution were presumed to imply the functional association between PTM sites in previous studies [8, 26]; here, we systematically tested the effectiveness of these features to predict the PTM cross-talk using by far the largest collection of validated cross-talk data sets
130 of 193 (67.4%) PTM cross-talks in our data were located within 20 amino acids
Summary
Systematic Characterization and Prediction of Post-Translational Modification Cross-Talk*□S. Identification of PTM cross-talks is an emerging theme in proteomics and has elicited great interest, but their properties remain to be systematically characterized To this end, we collected 193 PTM cross-talk pairs in 77 human proteins from the literature and tested location preference and co-evolution at the residue and modification levels. Peng et al [26] globally identified 81 putative PTM cross-talk motifs enriched in the sequence context of PTM sites occurring in proximity These studies suggested that several different features could be used to predict functional associations between PTM sites, to what extent do those associations represent PTM crosstalks remains to be evaluated on a gold-standard data set. Our method called PTM-X was implemented as a web-based tool available at http://bioinfo.bjmu.edu.cn/ptm-x/
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