Developing fundamental tools and insight into biomaterial designs for predictive functional outcomes remains critical for the field. In our current U01 grant we have made significant progress in many areas related to this need, starting from the overarching goal of integrating experimental-modeling-processing approaches into a synergistic approach for protein biomaterial design, as viewed from a hierarchical perspective and with a focus on mechanical outcomes. This approach has resulted in specific insights into the role of molecular weight, domain sizes and distributions, hydrophobic/hydrophilic partitioning and charged termini, on protein polymer assembly and the resulting properties, all informed via this integrated modeling-experimental feedback loop. These insights provide the foundation upon which we plan to build in this renewal application. The key features of our proposed approach remain to integrate modeling and experimentation at multiple scales to reach enhanced, predictive material functions out of simple protein building blocks though the exploitation of the accessibility and control afforded by genetically-encoded protein polymer designs. Our hypothesis in this renewal proposal is that predictions of biomaterial performance can be attained by the combined use of suitable experimental models to cover polymer features (chemistry, molecular weight, sequence control), processing (to modulate hierarchical structures) and modeling at different length scales of materials structural hierarchy (from nano- to macroscopic scales). Our goal is to further develop predictive assessments of biomaterials to save time, animals and costs, while accelerating translation of such biomaterials for repair and regenerative systems. In the renewal we will specifically focus on the use of modeling tools to further design and optimize protein-based materials to achieve specific functional outcomes (Aim 1), develop dynamic, shape-changing, protein materials (Aim 2), and address biomaterial interfaces with respect to mineralization of protein biomaterials (Aim 3). In total, these three aims build off of our progress in the current grant, but move the tools, experimental approaches and predictive capabilities to a new set of biomaterial challenges. Importantly, we also have established a strong, interdisciplinary team under the current grant to continue to foster this planned new insight, outcomes and contributions to the broader needs in the field of biomaterials.
The ability to predict biomaterial performance by the combined use of suitable experimental models to cover polymer features (chemistry, molecular weight), processing (e.g., fibers, films, sponges, hierarchical structure) and modeling at different length scales of materials structural hierarchy (from nano- to macroscopic) has broad implications for many types of biomaterials. For example, the plans to focus on protein-based materials has broad impact for synthetic and hybrid polymer systems, as well as inorganic/composite biomaterial needs, such as for bone repair, blood vessel designs and many related medical needs.
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