Map conformational landscapes of intrinsically disordered proteins with polymer physics quantities

利用聚合物物理量绘制固有无序蛋白的构象景观图

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Abstract

Disordered proteins are conformationally flexible proteins that are biologically important and have been implicated in devastating diseases such as Alzheimer's disease and cancer. Unlike stably folded structured proteins, disordered proteins sample a range of different conformations that needs to be accounted for. Here, we treat disordered proteins as polymer chains, and compute a dimensionless quantity called instantaneous shape ratio (R(s)), as R(s) = R(ee)(2)/R(g)(2), where R(ee) is end-to-end distance and R(g) is radius of gyration. Extended protein conformations tend to have high R(ee) compared with R(g), and thus have high R(s) values, whereas compact conformations have smaller R(s) values. We use a scatter plot of R(s) (representing shape) against R(g) (representing size) as a simple map of conformational landscapes. We first examine the conformational landscape of simple polymer models such as Random Walk, Self-Avoiding Walk, and Gaussian Walk (GW), and we notice that all protein/polymer maps lie within the boundaries of the GW map. We thus use the GW map as a reference and, to assess conformational diversity, we compute the fraction of the GW conformations (f(C)) covered by each protein/polymer. Disordered proteins all have high f(C) scores, consistent with their disordered nature. Each disordered protein accesses a different region of the reference map, revealing differences in their conformational ensembles. We additionally examine the conformational maps of the nonviral gene delivery vector polyethyleneimine at various protonation states, and find that they resemble disordered proteins, with coverage of the reference map decreasing with increasing protonation state, indicating decreasing conformational diversity. We propose that our method of combining R(s) and R(g) in a scatter plot generates a simple, meaningful map of the conformational landscape of a disordered protein, which in turn can be used to assess conformational diversity of disordered proteins.

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