Aging of an increasing global population (with life expectancy predicted to reach 106 years for those born in the EU after 2030) is a serious challenge for public health systems, bringing along a rise in diseases caused by compromised tissues. To that end, the healthcare community is eagerly searching for new, smarter and more sustainable materials to treat those diseases. Developing such materials would contribute to a better health condition for citizens, while reducing the costs of healthcare (expected to rise to double-digit figures in the EU by 2050). In that regard, protein polymers are an interesting source of advanced medical materials, due to their natural abundance, sustainability, easy processability, cytocompatibility, tuneable degradation, bioresorbability, and controllable mechanical properties. These are all interesting features for materials for medical applications. The main hypothesis of the SUPERB (StructUral ProtEins foR Biomedical materials) project is that the discovery of new protein-based materials can be greatly accelerated by the use of computational modelling. The objective is to simulate and manufacture de novo fusion proteins for the synthesis of medical materials that incorporate, heal and regenerate in the body faster and better than current materials, like meshes based on polypropylene, polytetrafluoroethylene and polyethylene tereoxphthalate. These are aspects of great social and commercial relevance.
The research performed in this project sits at a crossover between computational modelling, bioprocess engineering and materials science. We first designed fusion proteins computationally through the modular assembly of simplified building block motifs from structural proteins like elastin or silk. These proteins were studied via molecular dynamics simulation to uncover how polymer building blocks (i.e. hydrophilic vs hydrophobic, charged vs uncharged, ordered vs disordered) and their distribution along the polymer chain affected the ability of these proteins to form macroscopic viscoelastic materials (Objective 1). Optimal protein sequences identified via simulations were then biosynthesised through fermentative processes (Objective 2), investigating processing routes to maximise their recovery from the fermentation broth. Finally, the purified proteins will be used to manufacture macroscopic materials (e.g. hydrogels) for biomedical applications (Objective 3). These materials were tested and characterised to validate the predictive power of the computational models.
