Over 75% of disease-involved proteins cannot be readily targeted by conventional chemical biology approaches. New approaches are needed to increase the scope of molecular medicine. Cryptic binding pockets, i.e. pockets that transiently form in a folded protein, but are not apparent in the crystal structure of the unliganded apo-form, offer outstanding opportunities to target proteins otherwise deemed 'undruggable' and are thus of considerable interest in academia and the pharmaceutical industry. Unfortunately, not only they are notoriously difficult to identify, but also the molecular mechanism by which they form is still debated. The aim of this collaborative project is to address the knowledge gaps and develop an efficient computational platform based on atomistic molecular simulations to systematically detect druggable cryptic pockets in targets of biopharmaceutical interest. The platform will build on our successful experience in developing and applying enhanced-sampling simulation algorithms to molecular recognition, and will be extensively tested on validated drug targets harbouring cryptic sites. The computational results will be further validated on novel targets by a combination of experiments in collaboration with an industrial partner (UCB).