DEVELOPMENT OF EXPERIMENTAL METHODS TO ASSESS ADSORPTION FREE ENERGY FOR PEPTIDE-SURFACE INTERACTIONS

Because of its governing role in cellular response to implants and substrates for biomedical applications, the understanding and control of protein adsorption to material surfaces has been one of the major topics of research in the field of biomaterials. Unfortunately, it has proven to be extremely difficult to quantitatively understand and control these types of interactions because of the complexities involved, and existing methods that have been developed and used to characterize protein-surface interactions have proved to be inadequate to provide the level of detail necessary to achieve this understanding. New, more fundamental methods, both experimental and computational, are needed to overcome the current limitations. At a fundamental level, protein adsorption behavior can be considered to be represented by the combination of the individual interactions between the amino acid residues making up a protein, the solvent environment, and the functional groups presented by a surface. These interactions can be best characterized by the standard state adsorption free energy associated with their adsorption to a functionalized surface, and this information could be potentially very useful for understanding the sub-molecular events that govern protein adsorption behavior. In this dissertation, we specifically develop experimental methods for the determination of free energy to quantitatively characterize peptide adsorption behavior to well-defined surfaces presenting functional groups common to many types of polymeric biomaterials using surface plasmon resonance (SPR) spectroscopy. Also, because SPR is primarily limited to the types of surfaces that can readily be formed as thin layers in nanometer scale on gold biosensor substrates, methods are further developed and applied to enable values of free energy to be determined for peptide adsorption to any microscopically flat surface. The development and application of these methods enables the fundamental aspects underlying protein adsorption behavior to be characterized and provides data that can be used for the evaluation, modification, and validation of computational models that may be used to accurately predict protein adsorption behavior