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Configurational Entropy Components and Their Contribution to Biomolecular Complex Formation

机译:配置熵组分及其对生物分子复杂形成的贡献

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Configurational entropy change is a central constituent of the free energy change in noncovalent interactions between biomolecules. Due to both experimental and computational limitations, however, the impact of individual contributions to configurational entropy change remains underexplored. Here, we develop a novel, fully analytical framework to dissect the configurational entropy change of binding into contributions coming from molecular internal and external degrees of freedom. Importantly, this framework accounts for all coupled and uncoupled contributions in the absence of an external field. We employ our parallel implementation of the maximum information spanning tree algorithm to provide a comprehensive numerical analysis of the importance of the individual contributions to configurational entropy change on an extensive set of molecular dynamics simulations of protein binding processes. Contrary to commonly accepted assumptions, we show that different coupling terms contribute significantly to the overall configurational entropy change. Finally, while the magnitude of individual terms may be largely unpredictable a priori, the total configurational entropy change can be well approximated by rescaling the sum of uncoupled contributions from internal degrees of freedom only, providing support for NMR-based approaches for configurational entropy change estimation.
机译:配置熵改变是生物分子之间非共价相互作用的自由能变化的中央组成部分。然而,由于实验和计算限制,个别贡献对配置熵变的影响仍然是缺乏缺陷的。在这里,我们开发了一种新颖,完全分析的框架,解剖到来自分子内部和外部自由度的贡献的配置熵变化。重要的是,该框架在没有外部领域的情况下占所有耦合和解耦的贡献。我们采用我们的最大信息跨越树算法的平行实现,为各个贡献改变的各个贡献的重要性提供了全面的数值分析,对蛋白质结合过程的广泛的分子动力学模拟。与普遍接受的假设相反,我们表明不同的耦合术语对整体配置熵变化有显着贡献。最后,虽然各个术语的大小可能在很大程度上是不可预测的,但是通过重新加强来自内部自由度的非耦合贡献的总和,可以很好地逼近总配置熵变化,从而提供基于NMR的配置熵变化估计的方法。

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