Circumventing the problems caused by protein diversity in microarrays: implications for protein interaction networks

Protein microarrays provide a well-controlled, high-throughput way to uncover protein-protein interactions. One problem with this and other standardized assays, however, is that proteins vary considerably with respect to their physical properties. If a simple threshold-based approach is used to define protein-protein interactions, the resulting binary networks can be strongly biased. Here, we investigate the extent to which even closely related protein interaction domains vary when printed as microarrays. We find that, when a collection of well behaved, monomeric Src homology 2 (SH2) domains are printed at the same concentration, they vary by up to 50-fold with respect to the resulting surface density of active protein. When a threshold-based binding assay is performed on these domains using fluorescently labeled phosphopeptides, a misleading picture of the underlying biophysical interactions emerges. This problem can be circumvented, however, by obtaining saturation binding curves for each protein-peptide interaction. Importantly, the equilibrium dissociation constants obtained from these curves are independent of the surface density of active protein. We submit that an increased emphasis should be placed on obtaining quantitative information from protein microarrays and that this should serve as a more general goal in all efforts to define large-scale protein interaction networks.