PTM-X: A Web Server for PTM Cross-talk Prediction

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Post-translational modification (PTM) plays an important role in regulating the functions of proteins. PTM 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.

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This service can predict PTM crosstalk by inputting the Swiss-Prot accession number and the two candidate sites. The input data format was (columns are separated by Tab):

P04637	S15	phosphorylation	T18	phosphorylation

The first column is the Swiss-Prot accession number. The second column is the position of first candidate site. The third column is the PTM type of the first position. The forth column is the position of second candidate site. The fifth column is the PTM type of the second position. Unknown PTM type can be replaced by nan.


We investigated the location preference of cross-talk PTM pairs, and found that PTM cross-talk exhibits a proximity preference and prefers to co-localize within the same disordered region. In addition, we employed a normalized mutual information method to analyze residue co-evolution in Multiple Sequence Alignment (MSA) with approximately 50 vertebrates. We also defined the PTM co-evolution among H. sapiens, M. musculus and R. Norvegicus. The results indicated that PTM cross-talk co-evolved at both residue and modification levels. Finally, based on these features, a naive Bayes method was used to predict PTM cross-talk.


During the performance evaluation, we found that the area of under the overall receiver operating characteristic (ROC) curve in the cross-validation is 0.833.

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All comments, suggestions, questions, and bug reports are welcome. For inquiries, please send an e-mail to Tingting Li, Ph.D., Peking University Health Science Center via