A mutual information based activity labeling and scoring (MIBALS) approach to reverse fingerprint analysis is presented. Whole molecule scores produced by the method are shown to be capable of ranking compounds in virtual high-throughput screening (vHTS) experiments, while fragment scores produced by the method are able to identify pharmacophore moieties important for biological activity. The performance of MIBALS in vHTS experiments is assessed using reference ligands active against 40 different biological targets, and MIBALS retrieval rates are compared with those obtained using more traditional group fusion similarity search methods. The use of MIBALS to identify important pharmacophore fragments is demonstrated by comparing ligand fragment scores with known pharmacophores and known ligand/protein contacts. The ability of MIBALS to highlight beneficial and detrimental groups in a congeneric series is examined by comparing MIBALS fragment scores with features in known structure-activity relationships.