Tag! You're It!

The protein kinases are a sizable chunk of the human proteome (>500 members) and the subject of intense research. Some estimates peg about a quarter of all current small molecule drug discovery efforts as targeting kinases, and a lot of basic research remains to be done on the class.

A key question for a given kinase is what are the proteins it phosphorylates, its substrates. It turns out that this is a decidedly difficult problem. With mass spectrometry one can now read out lots of phosphorylation sites on proteins, but figuring out which kinase is phosphorylating which site remains difficult. A lot of methods have been proposed and successfully used, but while the mass spec folks are getting adept at churning out thousands of phosphorylation sites (here is another new one from PNAS), papers linking kinases to substrates typically have very small numbers of substrates (such as uno!) in them -- though there are some notable exceptions [not claiming this is an exhaustive list]. Which is too bad, as quite a few kinases have no known substrates (or none besides themselves; most kinases will trans-phosphorylate amongst themselves). Indeed, one hint that a breakthrough is needed is the fact that the number of methods keep proliferating; there's no one (or a few) good method to settle on yet.

A new report in Journal of the American Chemical Society is pretty intriguing in this light. I'll confess I haven't gotten past the abstract because my overdue ACS renewal is still riding in my backpack, but the abstract is tantalizing enough. The claim is that a biotin-ATP conglomerate will be accepted by a kinase and result in the kinase biotinylating the substrate. Since pulling down biotin-tagged proteins or peptides is truly old hat (heck, I did it as an undergraduate in the 80's -- and it was my all thumbs experience there that helped make me a computational biologist!), this is pretty exciting. If it proves to work with many (can we dare hope for most?) kinases, this could really revolutionize things.

Now, some previous tagging schemes had been developed, but they all required additional steps and perhaps even genetically modifying the kinase first. None of these methods has seemed to have caught on, at least from the standpoint of a growing pile of papers.

Clearly, the proof will be in the replication. If the next couple of years sees a flurry of papers reading out kinase substrates by biotinylation, that will be validation. If not, then let the next round of scheming begin!

Phosphopallooza.

Protein phosphorylation is a hot topic in signal transduction research. Kinases can add phosphate groups to serines, threonines & tyrosines (and very rarely histidines), and phosphatases can take them off. These phosphorylations can shift the shape of the protein directly, or create (or destroy) binding sites for other proteins. Such bindings can in turn cause the assembly/disassembly of protein complexes, trigger the transport of a protein to another part of the cell, or lead to the protein being destroyed (or prevent such) by the proteasome. This is hardly a comprehensive list of what can happen.

Furthermore, a large (by some estimates 1/4 to 1/5) amount of the pharmaceutical industries efforts, including those at my (soon to be ex-) employer Millennium, are targeting protein kinases. If you wish to drug kinases, you really want to know what the downstream biology is and that starts with what does your kinase phosphorylate, when does it do it, and what events do those phosphorylations trigger.

A large number of methods have been published for finding phosphorylation sites on proteins, but by far the most productive have been mass spectrometric ones (MS for short). Using various sample workup strategies, cleverer-and-cleverer instrument designs, and better software, the MS folks keep pushing the envelope in an impressive manner.

The latest Cell has the latest leap forward: a paper describing 6,600 phosphorylation sites (on 2,244 proteins). To put this in perspective, the total number of previously published human phosphorylation sites (by my count) was around 12,000 -- this paper has found 50% as many as were previously known! Some prior papers (such as these two examples) had found close to 2,000 sites.

Now some of this depth came from many MS runs -- but that in itself illustrates how this task is getting simpler; otherwise so many runs wouldn't be practical. The multiple runs also were used to gather more data: looking at phosphorylation changes (quantitatively!) over a timecourse.

One this this study wasn't designed to do is clearly assign the sites to kinases. Bioinformatic methods can be used to make guesses, but without some really painful work you can't really make a strong case. And if the site shouldn't look like any pattern for a known kinase -- good luck! There really aren't great methods for solving this (not to say there aren't some really clever tries).

Also interesting in this study is the low degree of overlap with previous studies. While the reference set they used is probably quite a bit lower than the 12K estimate I give, it is still quite large -- and most sites in the new paper weren't found in the older ones. There are in excess of 20 million Ser/Thr/Tyr in the proteome and many are probably not phosphorylated, but certainly a reasonable estimate would be north of 20K are.

For drug discovery, the sort of timecourse data in this paper is another proof-of-concept of the idea of discovering biomarkers for your kinase using high-throughput MS approaches (another case can be found in another paper). By pushing for so many sites, the number of candidates goes up substantially, since many sites found aren't modulated in an interesting way, at least in terms of pursuing a biomarker. This is noted in Figure 3 -- for the same protein, the temporal dynamics of phosphorylation at different sites can be quite different.

However, it remains to be seen how far into the process these MS approaches can be pushed. Most likely, the sites of interest will need to probed with immunologic assays, as previously discussed.