Fragment-based drug discovery is an effective and efficient strategy for generating target-optimized drugs. Its success rests in part on careful design of the underlying fragment library. During my project, I formulated design rules of what constitutes a “good” fragment by harnessing information across diverse target groups. To do so, I developed statistical methods that combine structural modelling, machine learning and statistical filtering to identify relevant patterns in binding data; this also entailed making optimal use of ligand structure. The resulting algorithms and models provide deeper insight into molecular reactivity, will improve the composition of fragment libraries, and boost the in-silico aspects of fragment-based drug discovery.

Carl is currently working as an Associate Director in the Computational Chemistry & Informatics Department at Astex Pharmaceuticals.