Reed Michael C, Gamble Mary V, Hall Megan N, Nijhout H Frederik
Department of Mathematics, Duke University, Durham, 27708, NC, USA.
Mailman School of Public Health, Columbia University, New YorkNY, 10032, USA.
BMC Syst Biol. 2015 Oct 14;9:69. doi: 10.1186/s12918-015-0215-6.
Methyltransferase (MT) reactions, in which methyl groups are attached to substrates, are fundamental to many aspects of cell biology and human physiology. The universal methyl donor for these reactions is S-adenosylmethionine (SAM) and this presents the cell with an important regulatory problem. If the flux along one pathway is changed then the SAM concentration will change affecting all the other MT pathways, so it is difficult for the cell to regulate the pathways independently.
We created a mathematical model, based on the known biochemistry of the folate and methionine cycles, to study the regulatory mechanisms that enable the cell to overcome this difficulty. Some of the primary mechanisms are long-range allosteric interactions by which substrates in one part of the biochemical network affect the activity of enzymes at distant locations in the network (not distant in the cell). Because of these long-range allosteric interactions, the dynamic behavior of the network is very complicated, and so mathematical modeling is a useful tool for investigating the effects of the regulatory mechanisms and understanding the complicated underlying biochemistry and cell biology.
We study the allosteric binding of 5-methyltetrahydrofolate (5 mTHF) to glycine-N-methyltransferase (GNMT) and explain why data in the literature implies that when one molecule binds, GNMT retains half its activity. Using the model, we quantify the effects of different regulatory mechanisms and show how cell processes would be different if the regulatory mechanisms were eliminated. In addition, we use the model to interpret and understand data from studies in the literature. Finally, we explain why a full understanding of how competing MTs are regulated is important for designing intervention strategies to improve human health.
We give strong computational evidence that once bound GNMT retains half its activity. The long-range allosteric interactions enable the cell to regulate the MT reactions somewhat independently. The low K m values of many MTs also play a role because the reactions then run near saturation and changes in SAM have little effect. Finally, the inhibition of the MTs by the product S-adenosylhomocysteine also stabilizes reaction rates against changes in SAM.
甲基转移酶（MT）反应是指将甲基基团连接到底物上，这在细胞生物学和人类生理学的许多方面都至关重要。这些反应的通用甲基供体是S-腺苷甲硫氨酸（SAM），这给细胞带来了一个重要的调节问题。如果一条途径的通量发生变化，那么SAM浓度也会改变，从而影响所有其他MT途径，因此细胞很难独立调节这些途径。
我们基于叶酸和甲硫氨酸循环的已知生物化学知识创建了一个数学模型，以研究使细胞克服这一困难的调节机制。一些主要机制是远程变构相互作用，即生化网络一部分中的底物会影响网络中远处位置（在细胞中并非实际距离很远）的酶的活性。由于这些远程变构相互作用，网络的动态行为非常复杂，因此数学建模是研究调节机制的影响并理解复杂的基础生物化学和细胞生物学的有用工具。
我们研究了5-甲基四氢叶酸（5 mTHF）与甘氨酸-N-甲基转移酶（GNMT）的变构结合，并解释了为什么文献中的数据表明当一个分子结合时，GNMT仍保留其一半活性。使用该模型，我们量化了不同调节机制的影响，并展示了如果消除调节机制细胞过程会有何不同。此外，我们使用该模型来解释和理解文献研究中的数据。最后，我们解释了为什么全面了解竞争性MTs的调节方式对于设计改善人类健康的干预策略很重要。
我们提供了有力的计算证据，证明一旦结合，GNMT仍保留其一半活性。远程变构相互作用使细胞能够在一定程度上独立调节MT反应。许多MTs的低K m值也起到了作用，因为反应随后在接近饱和的状态下进行，SAM的变化影响很小。最后，产物S-腺苷同型半胱氨酸对MTs的抑制也使反应速率对SAM的变化保持稳定。
