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We give a review of the current state of the art of data-driven modelling ofthe inositol trisphosphate receptor (IPR). After explaining that the IPR playsa crucial role as a central regulator in calcium dynamics, several sources ofrelevant experimental data are introduced. Single ion channels are best studiedby recording single-channel currents under different ligand concentrations viathe patch-clamp technique. The particular relevance of modal gating, thespontaneous switching between different levels of channel activity that occureven at constant ligand concentrations, is highlighted. In order to investigatethe interactions of IPRs, calcium release from small clusters of channels,so-called calcium puffs, can be used. We then present the mathematicalframework common to all models based on single-channel data, aggregatedcontinuous-time Markov models, and give a short review of statisticalapproaches for parameterising these models with experimental data. The processof building a Markov model that integrates various sources of experimental datais illustrated using two recent examples, the model by Ullah et al. and the"Park-Drive" model by Siekmann et al., the only models that account for allsources of data currently available. Finally, it is demonstrated that theessential features of the Park-Drive model in different models of calciumdynamics are preserved after reducing it to a two-state model that onlyaccounts for the switching between the inactive "park" and the active "drive"mode. This highlights the fact that modal gating is the most importantmechanism of ligand regulation in the IPR. It also emphasises that data-drivenmodels of ion channels do not necessarily have to lead to detailed models butcan be constructed so that relevant data is selected to represent ion channelsat the appropriate level of complexity for a given application.

Data-driven modelling of the inositol trisphosphate receptor (IPR) and its role in calcium induced calcium release (CICR)