Objective Target Assessment
Computational Biology and Chemogenomics Team
Section:
Section of Cancer Therapeutics (including the Cancer Research UK Centre for Cancer Therapeutics)
A major problem often encountered in drug discovery is the abundance of biologically tantalizing targets that end up difficult to progress into useful drugs. These problems can be due to inherent ‘undruggability’ of a particular target, problems with the chemical matter that can be developed for it, or severe issues with selectivity.
‘Druggability’ is often assessed as membership of a previously drugged or likely successful family. This approach is limited as not all family members are equal in their suitability for drug development, and also, there are likely a large number of novel targets which are druggable. Most importantly, the evidence for or against a target can change as new knowledge becomes available.
The team is developing an objective target assessment pipeline. This pipeline employs machine-learning algorithms and methods in continuous target assessment. This will utilize target sequence, structure, natural ligands, screened compound, expression data, protein interaction information. This allows a multi-pronged approach to assess the likely success or risk associated with a target or a pathway. The pipeline will be live and target scores updated as new data become available.
Some of the methods employed are publicly available and some are being developed specifically for cancer drug development.
In the Section of Cancer Therapeutics (including the Cancer Research UK Centre for Cancer Therapeutics)
