Rule-based modelling has already proved successful for taming the combinatorial complexity, typical of cellular signalling, caused by the combination of physical protein-protein interactions and modifications that may generate astronomical numbers of unique molecular species. However, traditional rule-based approaches, based on an unstructured space of agents and rules, remain susceptible to other combinatorial explosions such as those caused by mutated agents, that share most but not all rules

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... with their wild-type counterparts, and drugs, which must be distinguished from physiological ligands. We present here a syntactic extension of Kappa, an established rule-based modelling platform, that enables the expression of a structured space of agents and rules that simultaneously allows us to comfortably express mutated agents, splice variants, families of related proteins and drug interventions. This also enables a mode of model construction where, starting from our current consensus model, we attempt to reproduce in numero the mutational and more generally perturbational analyses that were used in the process of inferring those pathways-and in the light of this, we may need to upgrade our consensus model.