低聚受体模型的变构。

IF 0.8 4区 数学 Q4 BIOLOGY
Gregory Douglas Conradi Smith
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引用次数: 0

摘要

我们展示了受体同型二聚体的平衡结合曲线如何可以表示为组成单体的平衡结合曲线的有理多项式函数,而不需要近似和假设受体单体的独立性。该方法使用一种特殊的生成树构造来降低图的幂,适当地考虑了热力学约束和受体单体之间的变构相互作用(即构象耦合)。这种方法是完全通用的;它以表示单体状态转移图拓扑结构的任意无向图开始,并以由两个或多个相同且不可区分的单体组成的受体低聚物的平衡结合曲线的代数表达式结束。分析了几个具体的例子,包括鸟嘌呤核苷酸结合蛋白偶联受体二聚体和由多个“三元配合物”单体组成的四聚体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allostery in oligomeric receptor models.

We show how equilibrium binding curves of receptor homodimers can be expressed as rational polynomial functions of the equilibrium binding curves of the constituent monomers, without approximation and without assuming independence of receptor monomers. Using a distinguished spanning tree construction for reduced graph powers, the method properly accounts for thermodynamic constraints and allosteric interactions between receptor monomers (i.e. conformational coupling). The method is completely general; it begins with an arbitrary undirected graph representing the topology of a monomer state-transition diagram and ends with an algebraic expression for the equilibrium binding curve of a receptor oligomer composed of two or more identical and indistinguishable monomers. Several specific examples are analysed, including guanine nucleotide-binding protein-coupled receptor dimers and tetramers composed of multiple 'ternary complex' monomers.

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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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