Mining impact of protein modifications on protein-protein interactions from literature

Identification of protein-protein interactions (PPIs) and downstream functional events is important to biologists because these are key to building protein networks and biological pathways. Of high relevance are the PPIs involving proteins with some post-translational modification (PTM), since PTMs constitute one way of regulating protein function. However, this type of PPIs is not yet well represented in public databases (such as UniProtKB and IntAct), which would link the PPI information to the unmodified forms of proteins. Hence, literature is still the primary source for PPI information linked to modified forms of proteins. In this work, we propose to automate the process that mines and combines PPI information and PTM information from the biomedical literature via a novel, rule-based system. Further, the results are ranked based on the relations between PPI and PTM information. Currently, we limit the scope of our system to phosphorylation, a common PTM.