分子阻挫模型中的可调动力学校正
Tunable kinetic proofreading in a model with molecular frustration
摘要：
在复杂的系统中，反馈回路可以构建复杂的涌现现象，因此无法从单个部分的属性中轻松导出整个系统的描述。在这里，我们提出，分子间的挫折机制可以提供非平凡的反馈回路，可以发展非平凡的特异性放大。我们表明，这种机制可以被看作是一个更一般的形式的动力学校对机制，一个有趣的新的属性，即能够通过改变反应物的浓度来调整的特异性放大。这与经典的动力学校正机制形成对比，在经典的动力学校正机制中，特异性仅是化学途径中所涉及的反应速率常数的函数。这些结果也很有趣，因为它们表明，存在着广泛的一类挫折模型，它们具有相同的底层动力学校正机制，甚至具有更丰富的性质。这些模型可以在不同的领域，如进化生物学，免疫学和生物化学中找到应用。
英文摘要：
In complex systems, feedback loops can build intricate emergent phenomena, so that a description of the whole system cannot be easily derived from the properties of the individual parts. Here we propose that inter-molecular frustration mechanisms can provide non trivial feedback loops which can develop nontrivial specificity amplification. We show that this mechanism can be seen as a more general form of a kinetic proofreading mechanism, with an interesting new property, namely the ability to tune the specificity amplification by changing the reactants concentrations. This contrasts with the classical kinetic proofreading mechanism in which specificity is a function of only the reaction rate constants involved in a chemical pathway. These results are also interesting because they show that a wide class of frustration models exists that share the same underlining kinetic proofreading mechanisms, with even richer properties. These models can find applications in different areas such as evolutionary biology, immunology and biochemistry.
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