By Linda E. Cammish, Ph.D., NextGen Sciences, Ltd. and Mark N. Bobrow, Ph.D., PerkinElmer Life Sciences, Inc.
The use of DNA microarrays in scientific research and drug discovery has become very widespread. However, since it is proteins and not genes that are the vast majority of the true drug targets, there has been a fast growing interest in the use of functional protein microarrays, sometimes referred to as protein biochips. Unlike DNA molecules, functional proteins are not as easy to attach to a biochip substrate. Proteins also exhibit a wider range of physical characteristics, these being determined by the charged or non-charged functional side groups, regions of hydrophobicity or hydrophilicity and the manner in which the protein is folded via covalent or non-covalent interactions.
The production of protein microarrays is therefore fraught with many more problems than those encountered in the use of DNA microarrays. In addition, the use of protein microarrays requires that the assays performed be highly optimized due to the fact that there are many more variables to deal with including different pH conditions, buffer compositions, detergent types and concentrations, blocking reagents to prevent non-specific interactions and also the way in which the proteins are attached to substrates. All of these parameters have a significant impact on the affinity and specificity of protein-protein or protein-ligand interactions.
Despite these challenges, multiple protein assays that are performed in parallel, in miniature and in the format of a protein array hold great potential for target discovery and validation. To support this development process, there is a growing need to be able to automate these assays to improve sensitivity and reproducibility, and to make the optimization of each assay quicker and easier for the researcher to perform. To achieve