IUVSTA 15th International Vacuum Congress (IVC-15), AVS 48th International Symposium (AVS-48), 11th International Conference on Solid Surfaces (ICSS-11)
    Biomaterials Tuesday Sessions
       Session BI-TuA

Paper BI-TuA10
Theoretical Prediction of the Enthalpic and Entropic Contributions of the Change in Gibbs Free Energy for Peptide Residue Adsorption onto Functionalized SAM Surfaces

Tuesday, October 30, 2001, 5:00 pm, Room 102

Session: Non Fouling Surfaces and Theoretical Concepts
Presenter: R.A. Latour, Clemson University
Correspondent: Click to Email
The thermodynamic energy contributions of the change in enthalpy (dH) and entropy (dS), and their summation to calculate the change in Gibbs free energy (dG), provide a very useful tool to predict complex biomolecular behavior. This approach has been successfully applied to address a wide range of biomolecular problems such as the prediction of protein and RNA folding and ligand-receptor binding for rational drug design. A similar approach holds great potential to be applied to understand and predict the adsorption behavior of proteins to synthetic surfaces. A protein is composed of specific sequences of peptide residues arranged in a well-defined structural organization. Protein-surface adsorption can be expressed as a set of intermolecular (residue-surface) and intramolecular (residue-residue) interactions with the minimization of these energetic contributions determining the final conformation and orientation of adsorbed protein. In this study, computation chemistry (MOPAC/PM3/COSMO) was combined with wetting data to predict dH, dS, and dG contributions for the adsorption of individual peptide residues (alanine, serine, lysine) on functionalized SAM surfaces (methyl, hydroxyl, carboxyl) as a function of surface separation distance (SSD). The results are in close agreement with other more generalized continuum-based theories of adsorption and predict how dH and dS from residue/surface and solvent restructuring effects contribute uniquely for each residue/surface pair. These results will serve as the foundational building blocks of more advanced treatments to quantitatively predict protein adsorption behavior with subsequent application for biomaterials surface design.