Computational Prediction of Coiled-Coil Protein Gelation Dynamics and Structure

D Britton and LF Christians and CL Liu and J Legocki and YX Xiao and M Meleties and L Yang and M Cammer and SH Jia and ZH Zhang and F Mahmoudinobar and Z Kowalski and PD Renfrew and R Bonneau and DJ Pochan and AJ Pak and JK Montclare, BIOMACROMOLECULES, 25, 258-271 (2023).

DOI: 10.1021/acs.biomac.3c00968

Protein hydrogels represent an important and growing biomaterial for a multitude of applications, including diagnostics and drug delivery. We have previously explored the ability to engineer the thermoresponsive supramolecular assembly of coiled-coil proteins into hydrogels with varying gelation properties, where we have defined important parameters in the coiled-coil hydrogel design. Using Rosetta energy scores and Poisson-Boltzmann electrostatic energies, we iterate a computational design strategy to predict the gelation of coiled-coil proteins while simultaneously exploring five new coiled-coil protein hydrogel sequences. Provided this library, we explore the impact of in silico energies on structure and gelation kinetics, where we also reveal a range of blue autofluorescence that enables hydrogel disassembly and recovery. As a result of this library, we identify the new coiled-coil hydrogel sequence, Q5, capable of gelation within 24 h at 4 degrees C, a more than 2-fold increase over that of our previous iteration Q2. The fast gelation time of Q5 enables the assessment of structural transition in real time using small-angle X-ray scattering (SAXS) that is correlated to coarse-grained and atomistic molecular dynamics simulations revealing the supramolecular assembling behavior of coiled- coils toward nanofiber assembly and gelation. This work represents the first system of hydrogels with predictable self-assembly, autofluorescent capability, and a molecular model of coiled-coil fiber formation.

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