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核孔复合体中多价相互作用的物理建模。

Physical modeling of multivalent interactions in the nuclear pore complex.

机构信息

Department of Physics and Astronomy; Institute for the Physics of Living Systems; London Centre for Nanotechnology, University College London, London, United Kingdom.

Department of Physics and Astronomy; Institute for the Physics of Living Systems.

出版信息

Biophys J. 2021 May 4;120(9):1565-1577. doi: 10.1016/j.bpj.2021.01.039. Epub 2021 Feb 20.

Abstract

In the nuclear pore complex, intrinsically disordered proteins (FG Nups), along with their interactions with more globular proteins called nuclear transport receptors (NTRs), are vital to the selectivity of transport into and out of the cell nucleus. Although such interactions can be modeled at different levels of coarse graining, in vitro experimental data have been quantitatively described by minimal models that describe FG Nups as cohesive homogeneous polymers and NTRs as uniformly cohesive spheres, in which the heterogeneous effects have been smeared out. By definition, these minimal models do not account for the explicit heterogeneities in FG Nup sequences, essentially a string of cohesive and noncohesive polymer units, and at the NTR surface. Here, we develop computational and analytical models that do take into account such heterogeneity in a minimal fashion and compare them with experimental data on single-molecule interactions between FG Nups and NTRs. Overall, we find that the heterogeneous nature of FG Nups and NTRs does play a role in determining equilibrium binding properties but is of much greater significance when it comes to unbinding and binding kinetics. Using our models, we predict how binding equilibria and kinetics depend on the distribution of cohesive blocks in the FG Nup sequences and of the binding pockets at the NTR surface, with multivalency playing a key role. Finally, we observe that single-molecule binding kinetics has a rather minor influence on the diffusion of NTRs in polymer melts consisting of FG-Nup-like sequences.

摘要

在核孔复合物中,无序蛋白(FG Nups)及其与更多球状蛋白(核转运受体,NTR)的相互作用,对物质进出细胞核的选择性至关重要。尽管这些相互作用可以在不同的粗粒化水平上进行建模,但体外实验数据已被最小模型定量描述,这些模型将 FG Nups 描述为具有内聚性的均匀聚合物,而 NTR 则为具有均匀内聚性的球体,其中异质效应已被抹平。根据定义,这些最小模型并未考虑 FG Nup 序列中的明确异质性,实质上是一串具有内聚性和非内聚性的聚合物单元,以及 NTR 表面上的异质性。在这里,我们开发了计算和分析模型,以最小的方式考虑了这种异质性,并将其与 FG Nups 和 NTR 之间单分子相互作用的实验数据进行了比较。总体而言,我们发现 FG Nups 和 NTR 的异质性确实在确定平衡结合特性方面起着作用,但在解吸和结合动力学方面更为重要。使用我们的模型,我们预测了结合平衡和动力学如何取决于 FG Nup 序列中内聚块的分布以及 NTR 表面上的结合口袋的分布,其中多价性起着关键作用。最后,我们观察到单分子结合动力学对由 FG-Nup 样序列组成的聚合物熔体中 NTR 的扩散影响较小。

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3
Characterising the diffusion of biological nanoparticles on fluid and cross-linked membranes.
Soft Matter. 2020 Dec 16;16(47):10628-10639. doi: 10.1039/d0sm00712a.
4
Analytical Theory for Sequence-Specific Binary Fuzzy Complexes of Charged Intrinsically Disordered Proteins.
J Phys Chem B. 2020 Aug 6;124(31):6709-6720. doi: 10.1021/acs.jpcb.0c04575. Epub 2020 Jul 27.
5
Quantifying Protein-Protein Interactions in Molecular Simulations.
J Phys Chem B. 2020 Jun 11;124(23):4673-4685. doi: 10.1021/acs.jpcb.9b11802. Epub 2020 Jun 2.
6
Intrinsically disordered nuclear pore proteins show ideal-polymer morphologies and dynamics.
Phys Rev E. 2020 Feb;101(2-1):022420. doi: 10.1103/PhysRevE.101.022420.
7
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Biophys J. 2020 Jan 21;118(2):376-385. doi: 10.1016/j.bpj.2019.11.026. Epub 2019 Nov 26.
9
Computational Insights into Avidity of Polymeric Multivalent Binders.
Biophys J. 2019 Sep 3;117(5):892-902. doi: 10.1016/j.bpj.2019.07.026. Epub 2019 Jul 24.
10
Minimal coarse-grained models for molecular self-organisation in biology.
Curr Opin Struct Biol. 2019 Oct;58:43-52. doi: 10.1016/j.sbi.2019.05.018. Epub 2019 Jun 18.

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