The stochastic dynamics of chemical reactions can be accurately described by chemical
master equations. An approximated time-evolution equation of the Langevin type has been
proposed by Gillespie based on two explicit dynamical conditions. However, when
numerically solve these chemical Langevin equations, we often have a small stopping time–a
time point of having an unphysical solution–in the case of low molecular numbers. This
paper proposes an approach to simulate stochasticities in chemical reactions with
deterministic delay differential equations. We introduce a deterministic Brownian motion
described by delay differential equations, and replace the Gaussian noise in the chemical
Langevin equations by the solutions of these deterministic equations. This modification
can largely increase the stopping time in simulations and regain the accuracy as in the
chemical Langevin equations. The novel aspect of the present study is to apply the
deterministic Brownian motion to chemical reactions. It suggests a possible direction of
developing a hybrid method of simulating dynamic behaviours of complex gene regulation
networks.