Automatically Navigating Protein Interaction Networks with a Software Product Line Approach

Software Product Line Engineering (SPLE) would categorise protein-protein interaction (PPI) networks as highly configurable systems, and the main issue with those is the impracticability to manually analyse all network/system scenarios. SPLE solves this issue by means of automated reasoners - tools that analyse every solution of an SPLE system. Hence, if we apply and SPLE approach to analyse PPI networks, we can automatically navigate through every possible PPI pathway, including uncovering new ones with regards to the current literature, providing computer decision aid to both, bio-practitioners and researchers. While PPI networks are represented by the standard Systems Biological Graphical Notation (SBGN), product lines are represented by Variability Models (VMs). We present an approach where SBGN diagrams are transformed to SPLE VMs, providing compatibility between PPI networks and automated reasoners. We conjecture that protein artefacts are, in essence, variability features, and the signalling interactions are first-order logic relationships with certain cardinalities. We then analyse a reduced cell PPI (i.e., the Akt pathway) case study represented as a Clafer model with 9 features and 3 cross-tree constraints. The model is analysed with the chocosolver reasoner - the state-of-the-art multi-purpose and automated reasoner. The evaluation uncovered 84 pathways and was carried out in less than a millisecond using a RaspberryPI 3B+. We demonstrated how can be beneficial in biomedical research by supporting the creation, update, and re-usability of PPI network VMs.