Pain Signaling-A Case Study of the Modular Petri Net Modeling Concept with Prospect to a Protein-Oriented Modeling Platform

The construction of monolithic pathway models, as well as their coupling, curation and the integration of new data is arduous and inconvenient. The modular Petri net modeling concept we present here shows one way to manage these difficulties. In our concept, proteins are represented as functional units by Petri net submodels with a defined structure and connection interface, called modules. Each module integrates all publicly available information about its intramolecular changes and interactions with other molecules. Hence, a module corresponds to an interactive review written in a formalized language. This allows to intuitively understand the functionality of a protein. Modules of interacting proteins communicate through matching subnets, which renders the automatic generation of molecular networks possible. Here, we demonstrate the applicability and advantages of our concept on pain signaling. The molecular mechanisms involved in pain signaling are complex and poorly understood. To enhance our understanding of the mechanisms and to get an impression of the functional interactions among the involved pathways, we systematically build a model from modules of pain-relevant proteins. We also offer a prospect of a platform to organize approved curated modules in order to generate molecular networks. Hopefully, our concept helps bridging the gap between experimental bioscientists and theoretically oriented systems biologists.