Computational Prediction of Coiled–Coil Protein Gelation Dynamics and Structure

Abstract

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 °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.