A Data Driven Approach to Learning the Kinetics of Single Molecules: A Case Study of Single Inositol 1,4,5-Trisphosphate Receptor Channel

Abstract

The inositol 1,4,5-trisphosphate (IP3) receptor (IP3R) channel plays a central role in the generation and modulation of intracellular Ca2+ signals in animal cells. To gain insight into the crucial intricate ligand regulation of this ubiquitous channel, we constructed the simplest quantitative continuous-time Markov-chain model using a transparent iterative approach, which can be adopted to Markov chain models in general. Our model accounts for all experimentally observed gating behaviors of single native IP3R channels from insect Sf9 cells. Ligand (Ca2+ and IP3) dependencies of channel open probability (PO) established six main ligand-bound channel complexes, where a complex consists of one or more states with the same ligand stoichiometry and open or closed conformation. Channel gating in three distinct modes added one additional complex and indicated that three of the complexes can gate in two different modes. This also restricted the connectivity between channel complexes. Finally, channel responses to abrupt ligand concentration changes defined a model with 9 closed states and 3 open states, and its network topology. The model with 24 parameters can closely reproduce the equilibrium PO and channel gating statistics for all three gating modes for a broad range of ligand concentrations. It also captures the major features of channel response latency distributions. The model can generate falsifiable predictions of IP3R channel gating behaviors not yet explored, and provide insights to both guide future experiment development and improve IP3R channel gating analysis.