Since we were on the topic of kinases a few days back, it is worth pointing out a recent paper by Alex Aronov, Mark Murcko and others at Vertex on kinase-likeness.
One of the most common questions asked by medicinal chemists is about how to identify "privileged scaffolds", either generally among molecules that could bind to proteins, or among a subset of molecules. It would be useful indeed to identify, for example, common scaffolds among kinase inhibitors, which could help to pick out putative kinase inhibitors from a large dataset of molecules.
Aronov's group sets out to do just this. They do a statistical study in which they identify rings and linkers that are commonly found among kinase inhibitors. For this, they looked at three different databases. The important one was a database of molecules obtained from GVK Biosciences, which contains inhibitors from J. Med. Chem. published between 1959-2003. Naturally, there is a preponderance of kinase inhibitor-like molecules in the later publications. As controls, they also used two other databases which were underrepresented in kinase inhibitors.
Now any kinase lover worth his or her salt should not be surprised at their database-fishing results- they find that amino (NH) linkers are among the most common, along with rings containing one or two nitrogens. Cyano groups are also pretty common in side chains. They find that biaryl amines are extremely common among kinase inhibitors, another not very surprising conclusion. Anilines, pyridines and pyrimidines as well as pyrroles are also better represented among kinase inhibitors.
But the authors do something more valuable and generally applicable. After making these observations, they come up with what they call the "2-0 rule" for kinase likeness prediction. The rule needs putative kinase inhibitors to have an aromatic pyridine like (N) or pyrrole like (NH) nitrogen, or an aniline NH and/or a cyano group. Simply put, the rule for kinase-likeness is represented as:
When they applied this simple rule to the GVK database, they found that four out of five kinases inhibitors were flagged with this rule. In case of the kinase-inhibitor underrepresented database obviously, there were very few compounds that emerged through this rule.
∑ (N aromatic) + ∑ (NH aromatic) > 2
∑ (Ar-NH) + ∑ (R-CN) > 0
The paper also went one step further and documented the locations in the ATP-binding pocket of kinases where these commonly identified fragments fit and found most probable locations for the fragments. However, it should be remembered that allosteric kinase inhibitors can have some of the most valuable functions for selectively targeting kinases, and this rule may not help in identifying them. But in any case, not too many allosteric inhibitors are known relative to ATP-site binding inhibitors.
Such a rule, while not completely exhaustive, can serve some valuable purposes. For one thing as the authors demonstrate, it can be used to fish out kinase inhibitor-like molecule hits/leads from a database of existing drugs. This is of course a well-known strategy, to use a drug prescribed for one ailment to treat a different one, and one of the big advantages of this is that because the drug has been on the market its PK/ADME-TOX properties are already well-established. But it's not easy to do in general, and it's nice to have a structural rule that could weed out such drugs and "redeploy" them for targeting kinases. In this case, the fished-out drugs that originally bound to totally different targets did show broad-spectrum kinase activity experimentally.
In general, such a rule can be used both ways. More commonly, it can be used to fish out kinase inhibitors. But in a more novel application, it can be used to exclude kinase inhibitors and then screen other moelcules for novel scaffolds, albeit with a lower hit rate.
There is a caveat in this study which the authors note; the scaffolds for kinase inhibitors probably also reflect the ease of access to these inhibitors through existing synthetic chemistry. For example, one of the reasons anilines and biarylanilines are predominant among kinase inhibitors is because they are easy to synthesize through coupling reactions like Suzuki coupling. Ready availability of starting materials also drives the structures of kinase inhibitors. Thus, the existing structures should not be taken as representative of the most commonly possible scaffolds for kinase inhibition. The search should certainly continue.
Aronov, A.M., McClain, B., Moody, C.S., Murcko, M.A. (2008). Kinase-likeness and Kinase-Privileged Fragments: Toward Virtual Polypharmacology. Journal of Medicinal Chemistry DOI: 10.1021/jm701021b