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Andrew W Drake

Publications and source records attributed to Andrew W Drake.

3 recordsLinked to original sources

A rigorous multiple independent binding site model for determining cell-based equilibrium dissociation constants.

A new 4-parameter nonlinear equation based on the standard multiple independent binding site model (MIBS) is presented for fitting cell-based ligand titration data in order to calculate the ligand/cell receptor equilibrium dissociation constant and the number of receptors/cell. The most commonly used linear (Scatchard Plot) or nonlinear 2-parameter model (a single binding site model found in commercial programs like Prism(R)) used for analysis of ligand/receptor binding data assumes only the K(D) influences the shape of the titration curve. We demonstrate using simulated data sets that, depending upon the cell surface receptor expression level, the number of cells titrated, and the magnitude of the K(D) being measured, this assumption of always being under K(D)-controlled conditions can be erroneous and can lead to unreliable estimates for the binding parameters. We also compare and contrast the fitting of simulated data sets to the commonly used cell-based binding equation versus our more rigorous 4-parameter nonlinear MIBS model. It is shown through these simulations that the new 4-parameter MIBS model, when used for cell-based titrations under optimal conditions, yields highly accurate estimates of all binding parameters and hence should be the preferred model to fit cell-based experimental nonlinear titration data.

Algorithms↗

Screening antibody-antigen interactions in parallel using Biacore A100.

Label-free optical biosensor technology has become a standard tool for characterizing monoclonal antibodies for therapeutic and diagnostic applications. The availability of high-quality binding data at an early stage greatly improves the ability to select antibodies for further development. This article shows how Biacore A100, a protein interaction array system, is capable of providing high-quality data with increased throughput. In a 12-h automated run, we analyzed 386 crude hybridoma samples to identify those with the desired kinetic profiles. Selected antibodies were further characterized by higher resolution analysis, and binding interactions were studied under a range of buffer conditions. We demonstrate how this new parallel processing system significantly expands the throughput of protein interaction analysis while maintaining data quality.

Animals↗

Characterizing high-affinity antigen/antibody complexes by kinetic- and equilibrium-based methods.

Two biophysical methods, Biacore and KinExA, were used to kinetically and thermodynamically characterize high-affinity antigen/antibody complexes. Three to five independent experiments were performed on each platform with three different antigen/antibody complexes possessing nanomolar to picomolar equilibrium dissociation constants. By monitoring the dissociation phase on Biacore for 4 h, we were able to measure dissociation rate constants (kd) on the order of 1 x 10(-5)s(-1). To characterize high-affinity interactions by KinExA, samples needed to be equilibrated for up to 35 h to reach equilibrium. In the end, we show that similar kinetic rate constants and affinities were determined with both solution-phase and solid-phase methodologies. These results help further validate both interaction technologies and illustrate their suitability for characterizing extremely high-affinity interactions.

Animals↗