Comparative analysis is used to find the target of your compound. Or, to confirm the targeting. Your compound may be the result of a unique scaffold or may have emerged from phenotypical screens, in which case the biochemical target can be speculative. The intention to repurpose drugs may also trigger the need for target finding or confirmation. Clustering analysis of a broad range of anti cancer therapeutics will determine if your compound falls within a target group.
The clustering analysis via OncolinesProfiler™ compares your compound’s IC50 fingerprint against the cellular activity of 160 anti-cancer therapeutics. The latter include standards of care, clinical stage candidates and experimental therapeutics. The anti cancer drug list covers the wide variety of targets that is clinically applied or under investigation. Targets include tubulin, proteasome, topoisomerase, ubiquitin pathway, bromodomain, kinases, Wnt pathway, RNA synthesis, HDAC, EZH2, anti-apoptotic mechanisms and others.
The target for best in class inhibitors is confirmed when your compound shares a cluster with the relevant targeted therapeutics. For instance, it may fall within the cluster of selective PI3K inhibitors instead of pan-PI3K inhibitors. Its best in class properties emerge from improved potency, increased tissue selectivity, or selectivity for a genomic biomarker.
When you are working on a novel mechanism, your compound will be unique and located separately from all other therapeutics in the database. The exact targeting will be found by, for instance, knock-out experiments and zooming in on specific mechanisms via protein expression analysis.
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