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超越均一性:评估米氏动力学定律在空间异质环境中的有效性。

Beyond homogeneity: Assessing the validity of the Michaelis-Menten rate law in spatially heterogeneous environments.

机构信息

Department of Applied Mathematics, Korea University, Sejong, Republic of Korea.

Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, Republic of Korea.

出版信息

PLoS Comput Biol. 2024 Jun 6;20(6):e1012205. doi: 10.1371/journal.pcbi.1012205. eCollection 2024 Jun.

Abstract

The Michaelis-Menten (MM) rate law has been a fundamental tool in describing enzyme-catalyzed reactions for over a century. When substrates and enzymes are homogeneously distributed, the validity of the MM rate law can be easily assessed based on relative concentrations: the substrate is in large excess over the enzyme-substrate complex. However, the applicability of this conventional criterion remains unclear when species exhibit spatial heterogeneity, a prevailing scenario in biological systems. Here, we explore the MM rate law's applicability under spatial heterogeneity by using partial differential equations. In this study, molecules diffuse very slowly, allowing them to locally reach quasi-steady states. We find that the conventional criterion for the validity of the MM rate law cannot be readily extended to heterogeneous environments solely through spatial averages of molecular concentrations. That is, even when the conventional criterion for the spatial averages is satisfied, the MM rate law fails to capture the enzyme catalytic rate under spatial heterogeneity. In contrast, a slightly modified form of the MM rate law, based on the total quasi-steady state approximation (tQSSA), is accurate. Specifically, the tQSSA-based modified form, but not the original MM rate law, accurately predicts the drug clearance via cytochrome P450 enzymes and the ultrasensitive phosphorylation in heterogeneous environments. Our findings shed light on how to simplify spatiotemporal models for enzyme-catalyzed reactions in the right context, ensuring accurate conclusions and avoiding misinterpretations in in silico simulations.

摘要

米氏(Michaelis-Menten)动力学定律在描述酶催化反应方面已经有一个多世纪的历史了。当底物和酶均匀分布时,基于相对浓度,即底物大大过量于酶-底物复合物,米氏动力学定律的有效性可以很容易地得到评估。然而,当物种表现出空间异质性时,这种传统的标准在生物系统中普遍存在,其适用性仍然不清楚。在这里,我们通过偏微分方程来探索空间异质性下米氏动力学定律的适用性。在这项研究中,分子扩散非常缓慢,允许它们在局部达到准稳态。我们发现,仅通过分子浓度的空间平均值,不能轻易地将米氏动力学定律的有效性的传统标准扩展到不均匀的环境中。也就是说,即使满足了传统的空间平均值标准,米氏动力学定律也不能在空间异质性下捕捉到酶的催化速率。相比之下,一种基于总准稳态近似(tQSSA)的略微修改形式的米氏动力学定律是准确的。具体来说,基于 tQSSA 的修改形式,但不是原始的米氏动力学定律,准确地预测了在不均匀环境中通过细胞色素 P450 酶的药物清除率和超敏磷酸化。我们的发现揭示了在正确的背景下如何简化酶催化反应的时空模型,以确保在计算机模拟中得出准确的结论并避免误解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113e/11185478/c2920830df43/pcbi.1012205.g001.jpg

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