We’ve been through this before. While it may be convenient to refer to Lipitor as an HMG-CoA reductase inhibitor, or aspirin as a cyclooxegenase inhibitor, or Tom Brady as an “athlete,” they are clearly much more than that. Hence, being too attached to that conception can be dangerous, especially for your drug development options or your top line results.
All drugs in clinical use, be it marketed or in trials, act on several if not hundreds of receptors in the human body or even in a single cell, albeit with highly variable intensities. Everyone would agree with that, but it is surprising how little that fact seems to be taken into account in developing and testing drugs. Part of this bias comes from the cancer field, where drugs are developed specifically using their effects on cancer cells in a dish as a guide. And in many cases, the drugs are developed specifically to target a gene/protein that a host of data has shown the cancer is dependent on. So, if the kinase MELK is overexpressed in some cancer, and knocking down MELK slowed the growth of that cancer’s cells in a dish, then BINGO!–a drug inhibiting MELK should be a great cancer drug, riiight? And we will call it: a MELK inhibitor! And so have been born hundreds of target-specific cancer drugs: JAK inhibitors, MELK inhibitors, Braf inhibitors, etc. Lost along the way, except by us!, was that every one of these drugs has other targets.
Now a group of scientists has shown that even in the target friendly world of cancer, that target shorthand for drugs is a disaster. A large number of cancer drugs developed for specific targets actually work via unknown targets: When the new technology was used to eliminate any trace of the drug target from the cancer cells, they kept on keeping on as if nothing had happened, proving that the effect of the drug was NOT due to what was in the drug’s very name! And every one of these drugs is a pillar of some biotech or company’s bottom line. Let’s hope not yours!
If only there was a tool to easily evaluate the polypharmacology of drugs! Better yet, imagine if it could re-weight the off-targets according to their level of expression in the cancer cells or tissues!