Analysis of signaling networks using reverse protein arrays

Significant progress has been made during the last dec-ade in linking pathological conditions to defects inmolecular pathway components. Most prominent hasbeen the linkage of signalling pathway dysregulationto conditions such as cancer [1] and inflammatory dis-orders [2]. Understanding the information flowthrough the various pathways within a signalingnetwork, and how these pathways can best be manipu-lated to redirect signal transduction, is a challengingendeavor. A first step would be to describe the fullcomplexity of signaling networks at a molecular level,including activities specific to a particular cell type,dynamic feedback mechanisms, pathway cross-talk,signaling kinetics and, of course, pathway activationstates in normal and disease situations [3]. Eventhough both kinases and phosphatases are key regula-tors in signaling pathways, across the pharmaceuticalindustry it is primarily kinases on which a substantialpercentage of drug-discovery efforts are currentlyfocused.For a ‘kinase pathway’, the information flow (orpathway flux) mostly depends on the ratio of phos-phorylated and nonphosphorylated protein species,reflecting the activation state of the biological system.Comparing cellular activity over time, at various stagesof disease progression or before or after drug treat-ment, provides an opportunity to find a correlationbetween the activation state, on the one hand, and thebiological or disease state, on the other hand.Small molecules that modulate the activity of signal-ing proteins are useful tools for dissecting the func-tional roles and connections of the individual nodes ina pathway [4]. Using such a ‘systems approach’, onecan begin to build a model that will not only provide