Network-based tools for the identification of novel drug targets

Abstract

In the past few years, network-based tools have become increasingly important in the identification of novel molecular targets for drug development. Systems-based approaches to predict signal transduction-related drug targets have developed into an especially promising field. Here, we summarize our studies, which indicate that modular bridges and overlaps of protein-protein interaction and signaling networks may be of key importance in future drug design. Intermodular nodes are very efficient in mediating the transmission of perturbations between signaling modules and are important in network cooperation. The analysis of stress-induced rearrangements of the yeast interactome by the ModuLand modularization algorithm indicated that components of modular overlap are key players in cellular adaptation to stress. Signaling crosstalk was much more pronounced in humans than in Caenorhabditis elegans or Drosophila melanogaster in the SignaLink (http://www.SignaLink.org) database, a uniformly curated database of eight major signaling pathways. We also showed that signaling proteins that participate in multiple pathways included multiple established drug targets and drug target candidates. Lastly, we caution that the pervasive overlap of cellular network modules implies that wider use of multitarget drugs to partially inhibit multiple individual proteins will be necessary to modify specific cellular functions, because targeting single proteins for complete disruption usually affects multiple cellular functions with little specificity for a particular process. Tools for analyzing network topology and especially network dynamics have great potential to identify alternative sets of targets for developing multitarget drugs.