Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays

Abstract

The wide variety of protein interactions in a cell comprises a biochemical wiring network that controls everything from growth and division to the cell's response to its environment. These interactions include metabolites, lipids, nucleic acids, carbohydrates, proteins (both self and other proteins) and drugs [1][2][3][4][5][6][7]. Understanding the dynamic nature of these interactions will reveal the functional responsibilities of proteins and the circuits in which they operate [8]. The complex milieu of the living cell has slowed many attempts at assaying for protein function in vivo. The broad dynamic range of protein abundance in biological samples [9,10], and the ability of proteins to undergo post-translational modifications (PTMs), such as phosphorylation, glycosylation and myristoylation, further encumber the ability to build sensitive and accurate assays for studying protein function. This is a result of the dependence of many protein interactions The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions -yeast twohybrid and immunoprecipitation with mass spectrometric detection -have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.

Label-free and dynamic detection of biomolecular interactions for high-throughput microarray applications

“…Thus, label-free measurement of binding events is a potentially powerful tool, simpler and more efficient than secondary probebased systems (3). Label-free detection has been demonstrated by using electrical, electromechanical, and optical detection methods (4). Especially notable is surface plasmon resonance (SPR), which has been the basis for such commercial biosensors as the Biacore instruments (GE Healthcare Life Sciences).…”

Large-Scale Protein-Protein Interaction Detection Approaches: Past, Present and Future

“…Labeling effi ciency varies from a protein to a protein (104) and labeling tends to be laborious and time consuming (33). Label-free detection systems can solve possible problems of steric hindrance associated with the use of labels and enable quantitative characterization of protein interactions (73). Current label-free detection technologies include mass spectrometry (MS), surface plasmon resonance imaging (SPRi), anomalous refl ections (AR) of gold surface and QCM, quartz-crystal microbalance analysis (95,104).…”

The use of proteomics to identify novel therapeutic targets for the treatment of disease

“…This method not only isolates the proteins that directly interact with the analyte-specific reagent but also the partner proteins that interact with them. The protein of interest also can be fused to a high affinity tag, introduced to a complex protein sample and subsequently isolated using the appropriate capture reagent (Ramachandran et al 2005). Both methods will isolate a number of proteins, making it difficult to determine whether a protein is interacting directly or indirectly with the protein of interest (Ramachandran et al 2005).…”