Transitions States of Stochastic Chemical Kinetic Systems

Based on Transition Path Theory (TPT) for Markov jump processes [1, 2], we develop a general approach for identifying and calculating Transition States (TS) stochastic chemical reacting networks. We first extend the concept of probability current, originally defined on edges connecting different nodes in the configuration space [2], to each sub-network. To locate sub-networks with maximal probability current on the separatrix between reactive and non-reactive events, which will give the Transition States of the reaction, constraint optimization is conducted. We further introduce an alternative scheme to compute the transition pathways by topological sorting, which is shown to be highly efficient through analysis.

Automated summary

Based on Transition Path Theory, a general approach is developed to identify and calculate Transition States in stochastic chemical reacting networks using probability currents and constraint optimization. An alternative scheme for computing transition pathways through topological sorting is introduced, which is proven to be highly efficient.