Abstract
A major benefit of proteomic and genomic data is the potential for developing thousands of novel diagnostic and analytical tests of cells, tissues, and clinical samples. Monoclonal antibody technologies, phage display and mRNA display, are methods that could be used to generate affinity ligands against each member of the proteome. Increasingly, the challenge is not ligand generation, rather the analysis and affinity rank-ordering of the many ligands generated by these methods. Here, we developed a quantitative method to analyze protein interactions using in vitro translated ligands. In this assay, in vitro translated ligands generate a signal by simultaneously binding to a target immobilized on a magnetic bead and to a sensor surface in a commercial acoustic sensing device. We then normalize the binding of each ligand with its relative translation efficiency in order to rank-order the different ligands. We demonstrate the method with peptides directed against the cancer marker Bcl-xL. Our method has 4- to 10-fold higher sensitivity, using 100-fold less protein and 5-fold less antibody per sample, as compared directly with ELISA. Additionally, all analysis can be conducted in complex mixtures at physiological ionic strength. Lastly, we demonstrate the ability to use peptides as ultrahigh affinity reagents that function in complex matrices, as would be needed in diagnostic applications.