Recognition of amino acid enrichments in ultra tolerant search results facilitates PTM crosstalk discovery in large scale proteomics

Post‐translational modifications (PTM) of proteins have been recognized to act in a concert to regulate protein function, cellular location and activity. However, experimental discovery and studying PTM crosstalks is challenging since few analytical strategies are available. One of the examples of PTMs’ interplay can be an occurrence of modification at a particular site conditioned by nearby presence of other modified amino acids. Reportedly, specificity of only a small part of existing enzymes is experimentally characterized. At the same time, the modification process can be catalyzed by enzymes that recognize the site of modification by an amino acid consensus motif containing a modified amino acid. To validate this hypothesis, we developed a workflow for identification and localization of PTMs and applied it for discovery of PTM co‐occurrence using mass spectrometry data from public repositories. Our workflow is based on using ultra‐tolerant database search complemented with effective post‐search mass shift interpretation and analysis of amino acid enrichments. To achieve that we developed a command‐line tool, MotiFF, that implements calculation of the binomial probabilities and χ2 criterion to discover the enriched amino acid patterns containing modified amino acids. Results demonstrated that χ2 ‐based statistics provides a higher sensitivity and reproducibility of the results in comparison with the widely applied binomial algorithm. The MotiFF tool is available at: https://github.com/lineva642/MotiFF .