Sampling rare switching events in biochemical networks

TL;DR

This paper introduces a novel simulation method to efficiently predict the rate and mechanism of rare switching events in biochemical networks, overcoming limitations of traditional approaches.

Contribution

The authors develop a phase space interface-based simulation technique to accurately and efficiently analyze rare switching events in biochemical systems.

Findings

The method accurately predicts switching rates orders of magnitude faster than brute-force simulations.

Switching mechanisms depend critically on regulatory protein binding interactions.

The technique is applicable to non-equilibrium processes in soft matter systems.

Abstract

Bistable biochemical switches are ubiquitous in gene regulatory networks and signal transduction pathways. Their switching dynamics, however, are difficult to study directly in experiments or conventional computer simulations, because switching events are rapid, yet infrequent. We present a simulation technique that makes it possible to predict the rate and mechanism of flipping of biochemical switches. The method uses a series of interfaces in phase space between the two stable steady states of the switch to generate transition trajectories in a ratchet-like manner. We demonstrate its use by calculating the spontaneous flipping rate of a symmetric model of a genetic switch consisting of two mutually repressing genes. The rate constant can be obtained orders of magnitude more efficiently than using brute-force simulations. For this model switch, we show that the switching mechanism, and consequently the switching rate, depends crucially on whether the binding of one regulatory protein to the DNA excludes the binding of the other one. Our technique could also be used to study rare events and non-equilibrium processes in soft condensed matter systems.