(538g) Towards a Predictive Coarse-Grained Model for Computational Design of Bioadhesives

Strong and lasting adhesion to wet surfaces remains a challenge for synthetic glues. There are many applications (e.g., wound closure or integration of implantable devices onto wet tissues) where these adhesives have many potential advantages over alternative methods (i.e., sutures and staples). This has led to enormous interest in adhesives utilized by sea animals such as mussels or barnacles whose livelihood depend on their ability to bind to wet surfaces, despite facing turbulent and high salinity conditions. These animals utilize a collection of flexible unstructured proteins to maintain their adhesion. A good understanding of the surfaces forces unique for these proteins provides an avenue to designing biomimetic adhesives that can work well in aqueous environments. However, a thorough exploration of the parameter space is experimentally difficult; thus, theoretical insight into the essential physics behind the strong and lasting adhesion would greatly benefit bioadhesive design. Atomistic methods are not feasible because of the large system size and the extensive parameter space affiliated with the polypeptide sequence and the local solution environment (e.g., pH, salt types, and ionic strength). To solve this problem, we pursued the development of a coarse-grained model for amino acids that is computationally efficient and captures the important forces underlying surface-protein interactions. Importantly, by describing the polypeptides at the sequence level, we can better understand the role each residue plays when adhering to surfaces and how the polypeptides can be better designed (e.g., rearrangement of sequence) to take advantage of these characteristics. The coarse-grained model is able to account for the volume exclusion effects, electrostatic interactions, hydrophobic attractions, and other water-facilitated behavior in excellent agreement with experimental data. The adsorption of amino acids to inorganic surfaces requires careful consideration of the charge regulation of both the amino acids and the surface. Classical density functional theory (cDFT) provides a robust and efficient computational tool to describe the surface adhesion energy as well as the charge regulation and microscopic structure of polypeptides at various aqueous-solid interfaces. We demonstrate that that our coarse-grained model can semi-quantitatively describe the adsorption of amino acids and polypeptides to inorganic surfaces over a broad range of solution conditions. Importantly, the model provides insights into the important interfacial phenomena of polypeptides near inorganic surfaces. We then discuss the application of our model to investigate the bioadhesive behavior of polypeptides under various environmental conditions. The theoretical results for the surface force behavior of polypeptides can be directly compared with known experimental data for biomimetic surface forces. Of particular interest is the cooperativity between electrostatic and non-electrostatic (e.g., bidentate binding) through Lysine and DOPA residues in the polypeptide chain that promotes the adhesion. However, this cooperation between the two residues is highly dependent upon their placement (i.e., sequence) in the polypeptide chain and the surface and solution conditions (e.g., surface charge and salt concentration, respectively).