Title: Validity of the total quasi-steady-state approximation in stochastic biochemical reaction networks Show Chinese title

Title: 总准稳态近似在随机生化反应网络中的有效性

Abstract: Stochastic models for biochemical reaction networks are widely used to explore their complex dynamics but face significant challenges, including difficulties in determining rate constants and high computational costs. To address these issues, model reduction approaches based on deterministic quasi-steady-state approximations (QSSA) have been employed, resulting in propensity functions in the form of deterministic non-elementary reaction functions, such as the Michaelis-Menten equation. In particular, the total QSSA (tQSSA), known for its accuracy in deterministic frameworks, has been perceived as universally valid for stochastic model reduction. However, recent studies have challenged this perception. In this review, we demonstrate that applying tQSSA in stochastic model reduction can distort dynamics, even in cases where the deterministic tQSSA is rigorously valid. This highlights the need for caution when using deterministic QSSA in stochastic model reduction to avoid erroneous conclusions from model simulations. Show Chinese abstract

Abstract: 随机模型用于生化反应网络的建模被广泛用来探索其复杂的动态特性，但面临诸多挑战，包括确定速率常数的困难和计算成本高昂。 为解决这些问题，基于确定性拟稳态近似（QSSA）的模型简化方法已被采用，从而得到形式为确定性非初等反应函数的倾向函数，例如米氏方程。 特别是总QSSA（tQSSA），因其在确定性框架中的准确性而广为人知，曾被认为在随机模型简化中普遍适用。 然而，最近的研究对此观点提出了质疑。 在本综述中，我们表明，在随机模型简化中应用tQSSA可能会扭曲动态特性，即使在确定性tQSSA严格有效的情况下也是如此。 这突显了在使用确定性QSSA进行随机模型简化时需要谨慎，以避免从模型模拟中得出错误结论。