title: Validity conditions for moment closure approximations in stochastic chemical kinetics.
abstract: Approximations based on moment-closure (MA) are commonly used to obtain estimates of the mean molecule numbers and of the variance of fluctuations in the number of molecules of chemical systems. The advantage of this approach is that it can be far less computationally expensive than exact stochastic simulations of the chemical master equation. Here, we numerically study the conditions under which the MA equations yield results reflecting the true stochastic dynamics of the system. We show that for bistable and oscillatory chemical systems with deterministic initial conditions, the solution of the MA equations can be interpreted as a valid approximation to the true moments of the chemical master equation, only when the steady-state mean molecule numbers obtained from the chemical master equation fall within a certain finite range. The same validity criterion for monostable systems implies that the steady-state mean molecule numbers obtained from the chemical master equation must be above a certain threshold. For mean molecule numbers outside of this range of validity, the MA equations lead to either qualitatively wrong oscillatory dynamics or to unphysical predictions such as negative variances in the molecule numbers or multiple steady-state moments of the stationary distribution as the initial conditions are varied. Our results clarify the range of validity of the MA approach and show that pitfalls in the interpretation of the results can only be overcome through the systematic comparison of the solutions of the MA equations of a certain order with those of higher orders.
authors.affiliation: School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Schnoerr
authors.affiliation: School of Informatics, University of Edinburgh, Edinburgh EH8 9LE, United Kingdom.
authors.forename: Guido
authors.initials: G
authors.lastname: Sanguinetti
authors.affiliation: School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, United Kingdom.
authors.forename: Ramon
authors.initials: R
authors.lastname: Grima
mesh_terms: D003198:Computer Simulation; D007700:Kinetics; D008956:Models, Chemical; D011336:Probability; D013269:Stochastic Processes