Biological metabolites, substrates, cofactors, chemical probes, and drugs bind to flexible pockets in multiple biological macromolecules to exert their biological effect. The rapid growth of the structural databases and sequence data, including SNPs and disease-related genome modifications, complemented by the new cutting-edge 3D docking, scoring, and profiling methods has created a unique opportunity to develop a comprehensive structural map of interactions between any small molecule and biopolymers. Here we demonstrate that a comprehensive structural genomics engine can be built using multiple pocket conformations, experimentally determined or generated with a variety of modeling methods, and new efficient ensemble docking algorithms. In contrast to traditional ligand-activity-based engines trained on known chemical structures and their activities, the structural pocketome and docking engine will allow prediction of poses and activities for new, previously unknown, protein binding sites, and new, previously uncharacterized, chemical scaffolds. This de novo structure-based activity prediction engine may dramatically accelerate the discovery of potent and specific therapeutics with reduced side effects.