Abstract
The biofabrication of structural proteins with controllable properties via amino acid sequence design is interesting for biomedicine and biotechnology, yet design rules that link amino acid sequence to material properties remain largely unknown. Molecular dynamics (MD) simulations can help in unveiling such rules, but the lack of a standardised framework to interpret the outcome of those simulation hinders their predictive value for the design of de novo structural proteins, To address this, we developed a model that unambiguously classifies a library of de novo elastin-like polypeptides (ELPs) with varying numbers and locations of hydrophobic/hydrophilic and physical/chemical-crosslinking blocks according to their thermoresponsiveness at physiological temperature. Our approach does not require long simulation times or advanced sampling methods. Instead, we apply (un)supervised data analysis methods to a dataset of molecular properties from relatively short MD simulations (150 ns). We also investigate the rheological properties and microstructure of ELP hydrogels, revealing handles to tune them: chain hydrophilicity/hydrophobicity or block distribution control the viscoelasticity and thermoresponsiveness, whereas ELP concentration defines the network permeability. Our findings provide an avenue to accelerate the design of de novo ELPs with bespoke material properties.
Supplementary materials
Title
Supporting Information
Description
Supporting information including supplementary figures and tables associated with the manuscript.
Actions