Correlation between desorption force measured by atomic force microscopy and adsorption free energy measured by surface plasmon resonance spectroscopy for peptide-surface interactions.

Surface plasmon resonance (SPR) spectroscopy is a useful technique for thermodynamically characterizing peptide-surface interactions; however, its usefulness is limited to the types of surfaces that can readily be formed as thin layers on the nanometer scale on metallic biosensor substrates. Atomic force microscopy (AFM), on the other hand, can be used with any microscopically flat surface, thus making it more versatile for studying peptide-surface interactions. AFM, however, has the drawback of data interpretation due to questions regarding peptide-to-probe-tip density. This problem could be overcome if results from a standardized AFM method could be correlated with SPR results for a similar set of peptide-surface interactions so that AFM studies using the standardized method could be extended to characterize peptide-surface interactions for surfaces that are not amenable for characterization by SPR. In this article, we present the development and application of an AFM method to measure adsorption forces for host-guest peptides sequence on surfaces consisting of alkanethiol self-assembled monolayers (SAMs) with different functionality. The results from these studies show that a linear correlation exists between these data and the adsorption free energy (ΔG(o)(ads)) values associated with a similar set of peptide-surface systems available from SPR measurements. These methods will be extremely useful to characterize thermodynamically the adsorption behavior for peptides on a much broader range of surfaces than can be used with SPR to provide information related to understanding protein adsorption behavior to these surfaces and to provide an experimental database that can be used for the evaluation, modification, and validation of force field parameters that are needed to represent protein adsorption behavior accurately for molecular simulations.

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