ChEMBL

One of the long-term projects we have been involved with is the prediction or assessment of the likelihood of success of a particular drug discovery program (this elusive, but seductive concept of druggability (or drugability if you prefer)). We have a specific focus on using sequence (and other related data such as 3-D structure, previous screening and pharmacology data, etc) to analyse and score a particular target or set of targets. One of the projects we shall run at the EBI is a 'druggability portal' (which will provide a per sequence view of a target, and also provide some tools to perform multiparametric scoring and ranking across a set of targets, up to genome scale). The intent is that this will be a 'learning' system, responsive to new data, disclosure and progress in the field. Hopefully, we will also be able to code various drug discovery strategies into the approach as well (biotherapeutics, prodrugs, orals, parenterals, fast-follower, HTS, etc). Finally, we will also aim to include 'proprietary' knowledge into the system as well, so that researchers can modify the scores for particular targets/genomes based on their own experiences or technological biases.

Continuing the use of (very) strained puns in project names, we will call this project drugEBIlity (I know the upper-case I and lower-case l look the same, but in the logo it looks OK).

As ever, anyone interested in collaborating or contributing to this program of work is very welcome. Finally, one of the web developer roles we have available at the moment in the group will optimise existing methods, and implement new approaches to target analysis within the web portal.