A recent, comprehensive pathway resource from our lab, SignaLink, applies uniform curation rules to keep the levels of details to be identical in all examined pathways for C. elegans, D. melanogaster and humans. Moreover, the structure of the SignaLink dataset allows the systematic transfer of pathway annotations between two species on the basis of LY294002 sequence orthology. Interestingly, in two different organisms the same signaling pathway is often known at different levels of detail. This may be due to evolutionary divergence or to differences between the current coverage of the two organisms�� interaction maps. Therefore, large-scale pathway annotation transfer between these 3 organisms can extend our current knowledge of their signaling pathways. Note that in cases of rapid evolution, orthology-based predictions are less reliable as even the orthologs exist, they no longer participate in the same signaling pathway. The topology of signaling pathways is important for selecting possible novel drug target candidates. As an example, drugs used for inhibiting a specific signaling protein in order to affect proliferation may actually activate the pathway by triggering an unknown negative feedback loop. Transferring signaling pathway annotations across species may alleviate such difficulties and can provide a more comprehensive signaling network. Identification of novel signaling components may help to discover drug targets as these signaling components can increase the applicability of model organisms for testing drugs and drug target candidates, in humans, they can serve as potential novel drug targets, and in the case of already used target proteins they can help to uncover possible side-effects. Here we introduce the concept of ��signalog�� to predict a protein as a novel component of a signaling pathway based on the signaling pathway membership of its ortholog in another organism. We identify signalogs on genomic scale in 8 signaling pathways, Cycloheximide abmole including the MAPK, TGF-b, and WNT pathways from 3 intensively investigated species: C. elegans, D. melanogaster and humans, and verify their novelty and predictive power, using both bioinformatics and experimental methods. We also show the utility of the signalog concept in drug target discovery. Sequence-based approaches, also in combination with interaction networks, have been frequently applied to detect orthology relationships between proteins. For example, the tool PathBLAST aligns an ordered list of proteins or pathways on the basis of their ortholog relations. In the Clusters of Orthologous Groups database, orthologous groups are defined through reciprocal best BLAST matches between proteins from at least three species. Furthermore, sequence clustering techniques incorporate a range of BLAST scores and can achieve a higher sensitivity.