Influence of protein charge patches on the structure of protein-polyelectrolyte complexes

Samanta, Rituparna; Ganesan, Venkat

Influence of protein charge patches on the structure of protein-polyelectrolyte complexes

Type

Article

Authors

Samanta, Rituparna
Ganesan, Venkat

KAUST Grant Number

OSR-2016-CRG5-2993-1

Date

2018-11-15

Abstract

We employ a combination of the single chain in mean field simulation approach with the solution of Poisson's equation to study the influence of charge heterogeneities on the structure of protein–polyelectrolyte complexes. By adopting a coarse-grained model of representing proteins as charged nanoparticles, we studied the influence of the pattern of charge heterogeneities, net charge, ratio of positive to negative charges on the patches, and the volume fraction of the particles on the structural and aggregation characteristics of proteins in polyelectrolyte solutions. Our results demonstrate that the pattern of charge heterogeneities can exert a significant influence on the resulting characteristics of the aggregates, in some cases leading to a transformation from polymer-bridged complexes into direct particle aggregates driven by the attraction between oppositely charged patches.

Citation

Samanta, R., & Ganesan, V. (2018). Influence of protein charge patches on the structure of protein–polyelectrolyte complexes. Soft Matter, 14(46), 9475–9488. doi:10.1039/c8sm01535j

Acknowledgements

We are grateful to Prof. Bradley Olsen for discussions which motivated this work. We also thank Justin Leung for performing some of the simulations on polyampholyte particles. We acknowledge funding in part by grants from the Robert A. Welch Foundation (Grant F1599), the National Science Foundation (DMR-1721512), King Abdullah University of Science and Technology (OSR-2016-CRG5-2993-1). Acknowledgment is also made to the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research (56715-ND9). We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for computing resources that contributed to the research results reported within this paper.