Enter fragments. Because fragments have lower complexity than lead-sized (let alone drug-sized) molecules, hit rates from fragment screens tend to be higher. If a binding pocket exists in a protein, a small library of just 1000 fragments or so should produce a good range of hits. In fact, Phil Hajduk and colleagues at Abbott found several years ago that fragment screens predict the success of lead discovery campaigns. In the new paper, Edfeldt and colleagues, all at AstraZeneca, analyzed 36 internal discovery projects where both fragment screens and HTS had been conducted. They used data from the fragment screens to categorize targets into three ligandability bins:
- Low: low hit rate, best affinities > 1 mM, low diversity of hits
- Medium: intermediate hit rate, best affinities 0.1 – 1 mM, some diversity of hits
- High: high hit rate, best affinities < 0.1 mM, high diversity of hits
AstraZeneca is now using fragment-based ligandability screening to help assess which targets to pursue: those with low ligandability are only pursued when the biology is truly compelling. On the flip side, targets that have failed conventional HTS but have high ligandability are reexamined using alternative hit discovery techniques, such as fragment-based methods. This seems like an appealing approach: fragments not only help drug hunters avoid throwing out the baby with the bathwater, but also to avoid drowning in dirty bathwater. I wonder how many other companies are using similar strategies.