The entire set of kinases in a given organism is called its kinome. The human kinome consists of 518 kinases. Unsurprisingly, biologists and pharmaceutical companies are intensely interested in understanding how these enzymes work and developing drugs that control their behaviour.

So it may come as a surprise to find that three quarters of the research in this area focuses on just 10 per cent of these enzymes, as measured by the number of times the kinases are cited in research papers. By contrast, 60 per cent of the kinome, some 300 kinases, is virtually ignored by the community and mentioned in only 5 per cent of the work.

This is known as the Harlow-Knapp effect after the researchers that discovered it a couple of years ago. The question it raises is why biologists ignore most of the kinome when there is good reason to think that careful study should pay off in silver dollars

Today, Ruth Isserlin at the University of Toronto in Canada and a few buddies take a more detailed look at the effect. They say it is more widespread than previously thought and also affects the study of other biological molecules too.

Kinases have been well studied since the 1950s but the publication of the human genome in 2000 was an important watershed in this area. All of a sudden, it become possible to identify the entire family of kinases, the whole kinome, work which was published in 2002.

Consequently, research in this area exploded. Between 1950 and 2002, there were some 80,000 papers citing kinases, say Isserlin and co. But in the ten years since then, there have been 120,000.

What’s strange is that publication of the human kinome didn’t change the distribution of citations. “Interestingly, the very same kinases continued to garner most of the citations even long after the genome information became widely available,” say Isserlin and co.

In some ways, the Harlow Knapp effect is unsurprising. It has all the hallmarks of the classic power laws that physicists have been finding everywhere in the last couple of decades. Famous examples include the distribution of wealth in which 20 per cent of the population have 80 per cent of the wealth, the frequency of words in most languages, and the size distribution of cities, epidemics, wars and so on.

Humanity seems to be primed to generate power laws. But the ubiquity of this effect raises another question: is there some deeper underlying reason why so many phenomena follow this law?

Nobody is quite sure but there’s no shortage of work in this area, particularly in the study of networks. And understanding the processes that generate these distributions is important.

One common idea is the Matthew effect–from the biblical reference that the rich get richer and poor get poorer. For example, it is common for well-known scientists to be awarded prizes, making them more famous, even if all the work was done by a graduate student who is ignored.

At first glance, it’s easy to imagine that the Harlow Knapp effect is good example of this. Isserlin and co point out that current molecular biology is so rich that it is possible to ask important questions even of the most well-studied systems. And since its easier to get grants, to do good science and to get published in higher impact journals by sticking to well known systems, that’s exactly what scientists do. So the best known systems become better studied.

That alone might explain this distribution. But there is something else going on too, say Isserlin and co. Biologists commonly screen the entire genome of an organism looking for interesting proteins. But when they find one, the amount of work they can do with it depends on the chemical tools available to interact with it.

In many cases, these tools are not available. And when that happens, the proteins are ignored. This, say Isserlin and co, is one of the important underlying reasons why so many kinases and other interesting biomolecules are so poorly studied.

The solution then is clear: provide incentive for chemists to develop these tools.

That may be easier said than done. But there’s clearly a great deal of low-hanging fruit for anybody able to develop the tools to reach it. That should provide at least some motivation.

More broadly, something similar to the Harlow Knapp effect probably occurs in all areas of science: that most research is done on a small subset of interesting or important problems.

The difference in biology is that its easier to see where the gaps lie because the bigger picture is clearer: the treatment of disease and the ultimate understanding of the human body and life itself.

Ref: arxiv.org/abs/1102.0448: The Human Genome And Drug Discovery After A Decade. Roads (Still) Not Taken