journal article·2017-11-01Open access

Understanding diffusion of intrinsically disordered proteins in polymer solutions: A disorder plus collapse model

Juan Wang, Yukun Bian, Xiuli Cao, Nanrong Zhao

AIP Advances· Volume 7· Issue 11

Abstract

Understanding diffusion of intrinsically disordered proteins (IDPs) under crowded environments is of ubiquitous importance to modelling related dynamics in biological systems. In the present work, we proposed a theoretical framework to study the diffusion behavior of IDPs in polymer solutions. IDP is modeled as an ensemble of particles with a wide range of gyration radius subject to Flory-Fisk distribution, where the collapse effect which leads to the shrink of IDP due to polymer crowding is included. The diffusion coefficient of IDP is calculated as the average, denoted by 〈D〉, over the values of the particle samples. By properly incorporating the scaling relations for diffusion coefficient of nanoparticle (NP) in polymer solutions, we are able to evaluate 〈D〉 straightforwardly and reveal the disorder and collapse effects on IDP’s diffusion in an explicit manner. Particular attentions are paid on comparison between the diffusion coefficient of an IDP and that of a NP. Results demonstrate that both disorder and collapse can enhance IDP diffusion rate. Our analysis shows that the crossover behavior reported by experiments can be actually a general phenomenon, namely, while a NP with smaller size than that of an IDP diffuses faster in simple solutions, the IDP may become the faster one under crowded conditions. We apply our theory to analyze the diffusion of several types of IDP in a few different polymer solutions. Good agreements between the theoretical results and the experimental data are obtained.
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Research context

OpenAlex topics: Stochastic processes and statistical mechanics · Material Dynamics and Properties · Theoretical and Computational Physics

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Affiliations

College of Chemistry, Sichuan University , Chengdu 610064, China

Funding

National Natural Science Foundation of China

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