ABSTRACT
The adsorption of proteins and other large molecules at the liquid-solid interface often involves a surface-induced transition in either internal conformation or molecular orientation. Recently, Van Tassel et al. modeled this adsorption/transition process as the sequential surface placement of spreading disks. In this work, we employ the scaled particle theory (SPT) to derive approximate analytical expressions for the probability functions appearing in the kinetic equations for this model system. Specifically, the probability functions governing the adsorption and spreading events are calculated in terms of the reversible work required to create cavities in a binary system of spread and unspread disks. Compared to those derived earlier via a density expansion theory (DET), the SPT approximated probability functions are simpler and more accurate (compared to simulation), and are applicable over a wider set of parameter values. Copyright 1999 Academic Press.
ABSTRACT
Modeling the kinetics of protein adsorption at solid surfaces is needed to predict protein separations, design biosensors, and determine the body's initial response to foreign objects. We develop, at the particle level, a kinetic model that accounts geometrically for the surface blockage due to adsorption and postadsorption conformational (or orientational) transitions. Proteins are modeled as disk-shaped particles of diameter final sigmaalpha that adsorb irreversibly at random positions onto a surface at a rate kac (c is the concentration of protein in the bulk solution). Adsorption occurs only where the surface is empty. Following adsorption, a particle attempts to spread (symmetrically) to a larger diameter final sigmabeta at a rate ks. Spreading only occurs if no overlap with any previously placed particle would result. A set of equations is developed for determining the time evolution of the adsorbed protein density. These predictions are compared to new experimental data for fibronectin onto silica-titania obtained using optical waveguide lightmode spectroscopy (OWLS). We also discuss the general application of this model to experimental data. Copyright 1998 Academic Press.
