Abstract
To understand and predict protein adsorption behavior, we must first understand the fundamental interactions between the functional groups presented by the amino acid residues making up a protein and the functional groups presented by the surface. Limited quantitative information is available, however, on these types of submolecular interactions. The objective of this study was therefore to develop a reliable method to determine the standard state adsorption free energy (delta Go ads) of amino acid residue-surface interactions using surface plasma resonance (SPR) spectroscopy. Two problems are commonly encountered when using SPR for peptide adsorption studies: the need to account for "bulk-shift" effects and the influence of peptide-peptide interactions at the surface. Bulk-shift effects represent the contribution of the bulk solute concentration to the SPR response that occurs in addition to the response due to adsorption. Peptide-peptide interactions, which are assumed to be zero for Langmuir adsorption, can greatly skew the isotherm shape and result in erroneous calculated values of delta Go ads. To address these issues, we have developed a new approach for the determination of delta Go ads using SPR that is based on the chemical potential. In this article, we present the development of this new approach and its application for the calculation of delta Go ads for a set of peptide-surface systems where the peptide has a host-guest amino acid sequence of TGTG-X-GTGT (where G and T are glycine and threonine residues and X represents a variable residue) and the surface consists of alkanethiol self-assembled monolayers (SAMs) with methyl (CH 3) and hydroxyl (OH) functionality. This new approach enables bulk-shift effects to be directly determined from the raw SPR versus peptide concentration data plots and the influence of peptide-peptide interaction effects to be minimized, thus providing a very straightforward and accurate method for the determination of delta Go ads for peptide adsorption. Further studies are underway to characterize delta Go ads for a large library of peptide-SAM combinations.