Computational Design of Helical Peptide Bundle Variants Spanning a Wide Range of Charge States

Published

March 1, 2022

Author(s)

Jeffrey Fagan, Nairiti Sinha, rui gui, Darrin Pochan, Grethe Vestergaard Jensen, Jeffery Saven, matthew Langenstein, Rajkumar Misra, Christopher Kloxin, yan tang

Abstract

Peptides can be computationally designed and engineered to achieve various functionalities and structures. Herein computational design was used to identify a set of 17 peptides having a wide range of putative charge states but the same tetrameric coiled-coil bundle structure. Calculations were performed to identify suitable locations for ionizable residues (D, E, K and R) at the bundle's exterior sites, while interior hydrophobic interactions are retained. The designed bundle structures span putative charge states of -32 to +32 in units of electron charge. The peptides were experimentally investigated using spectroscopic and scattering techniques. Thermal stabilities of the bundles were assessed using circular dichroism. Molecular dynamics simulations assessed structural fluctuations within the bundles. The 4 nm cylindrical peptide bundles were covalently linked to form rigid micron-scale polymers and characterized using transmission electron microscopy. The resulting suite of sequences provides a set of readily realized nanometer-scale structures of tunable charge that can also be polymerized to yield rigid-rod polyelectrolytes.

Citation

Journal of Colloid and Interface Science

Volume

23

Issue

4

Pub Type

Journals

Download Paper

https://doi.org/10.1021/acs.biomac.1c01539

Local Download

Keywords

polyelectrolyte, analytical ultracentrifugation, small angle neutron scattering, peptide

Citation

Fagan, J. , Sinha, N. , gui, R. , Pochan, D. , Jensen, G. , Saven, J. , Langenstein, M. , Misra, R. , Kloxin, C. and tang, Y. (2022), Computational Design of Helical Peptide Bundle Variants Spanning a Wide Range of Charge States, Journal of Colloid and Interface Science, [online], https://doi.org/10.1021/acs.biomac.1c01539, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933823 (Accessed December 26, 2024)