Cryptic pockets are ligand binding sites that form through protein dynamics. While cryptic pockets offer potential avenues in selectivity, competition, and tractability of challenging drug targets, their formation can involve extensive structural changes that evade experimental detection. This thesis addresses the identification of cryptic pockets and their ligands with two key contributions: i) a new simulation approach termed SLICE that can help explore extensive protein dynamics and find cryptic pockets within 100ns, and ii) a workflow integrating simulation-based approaches, docking, and co-folding to help find a cryptic pocket, a ligand binding it, and a protein-ligand complex in accordance with experiment. Since the methods described in this thesis do not rely on prior knowledge of the cryptic pocket or its ligand, they may be applicable to early stages of drug discovery. The insights gained by these approaches can in turn reduce the risk of inaccurately discarding relevant proteins as undruggable targets.