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蛋白质-蛋白质复合物可能破坏依赖于超敏性的生物适应性。

Protein-protein complexes can undermine ultrasensitivity-dependent biological adaptation.

机构信息

School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.

出版信息

J R Soc Interface. 2023 Jan;20(198):20220553. doi: 10.1098/rsif.2022.0553. Epub 2023 Jan 4.

Abstract

Robust perfect adaptation (RPA) is a ubiquitously observed signalling response across all scales of biological organization. A major class of network architectures that drive RPA in complex networks is the Opposer module-a feedback-regulated network into which specialized integral-computing 'opposer node(s)' are embedded. Although ultrasensitivity-generating chemical reactions have long been considered a possible mechanism for such adaptation-conferring opposer nodes, this hypothesis has relied on simplified Michaelian models, which neglect the presence of protein-protein complexes. Here we develop models of interlinked covalent-modification cycles with embedded ultrasensitivity, explicitly capturing all molecular interactions and protein complexes. Strikingly, we demonstrate that the presence of protein-protein complexes thwarts the network's capacity for RPA in any 'free' active protein form, conferring RPA capacity instead on the concentration of a larger protein pool consisting of two distinct forms of a single protein. We further show that the presence of enzyme-substrate complexes, even at comparatively low concentrations, play a crucial and previously unrecognized role in controlling the RPA response-significantly reducing the range of network inputs for which RPA can obtain, and imposing greater parametric requirements on the RPA response. These surprising results raise fundamental new questions as to the biochemical requirements for adaptation-conferring Opposer modules within complex cellular networks.

摘要

稳健完美适应(RPA)是在所有生物组织规模上普遍观察到的信号响应。驱动复杂网络中 RPA 的主要网络架构类是反对派模块——一种反馈调节网络,其中嵌入了专门的积分计算“反对派节点”。尽管产生超敏反应的化学反应长期以来一直被认为是赋予适应能力的反对派节点的一种可能机制,但这一假设依赖于简化的迈克尔模型,该模型忽略了蛋白质-蛋白质复合物的存在。在这里,我们开发了具有嵌入式超敏反应的交联共价修饰循环模型,明确捕获了所有分子相互作用和蛋白质复合物。引人注目的是,我们证明了蛋白质-蛋白质复合物的存在会破坏网络在任何“自由”活性蛋白形式下的 RPA 能力,而是赋予由两种不同形式的单个蛋白质组成的更大蛋白质池的浓度以 RPA 能力。我们进一步表明,即使在相对较低的浓度下,酶-底物复合物的存在也在控制 RPA 反应中起着至关重要且以前未被认识的作用——显著减少了 RPA 可以获得的网络输入范围,并对 RPA 反应提出了更高的参数要求。这些令人惊讶的结果提出了关于复杂细胞网络中赋予适应能力的反对派模块的生化要求的基本新问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8209/9810431/101c3e7db913/rsif20220553f01.jpg

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