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Colloid-Like Solution Behavior of Computationally Designed Coiled Coil Bundlemers

Published

Author(s)

Nairiti J. Sinha, Rui Guo, Rajkumar Misra, Jeffrey Fagan, Antonio Faraone, Christopher J. Kloxin, Jeffery G. Saven, Grethe V. Jensen, Darrin J. Pochan

Abstract

The use of colloidal theory for describing protein-protein interactions is a topic of ongoing debate in the biophysical community. This contention stems from the unavailability of synthetic protein-like model particles that are amenable to systematic experimental characterization. In this article, we test the utility of colloidal theory to capture the solution structure, interactions and dynamics of new globular protein-mimicking computationally designed peptide assemblies called bundlemers that are programmable model systems at the intersection of colloids and proteins. Small-Angle Neutron Scattering (SANS) measurements of dilute bundlemer solutions in low and high ionic strength solution indicate that bundlemers interact locally via repulsive interactions that can be described by either a long-range repulsive potential or an effective hard sphere potential. Importantly, formation of soluble aggregate clusters of bundlemers due to transient short-range attractive contacts is also observed in SANS even at probed low bundlemer concentrations. We also present Neutron Spin Echo (NSE) results that corroborate freely-diffusive dynamics of locally-repulsive bundlemers. Systematic computational design of bundlemer peptides can yield insights into the similarities and differences between simple colloidal and complex protein-protein interactions.
Citation
Journal of Colloid and Interface Science
Volume
606
Issue
Part 2

Keywords

Colloid, protein-protein interactions, bundlemer, computational design

Citation

Sinha, N. , Guo, R. , Misra, R. , Fagan, J. , Faraone, A. , Kloxin, C. , Saven, J. , Jensen, G. and Pochan, D. (2022), Colloid-Like Solution Behavior of Computationally Designed Coiled Coil Bundlemers, Journal of Colloid and Interface Science (Accessed March 28, 2024)
Created January 14, 2022, Updated September 20, 2022