Identification and characterization of binding sites is key in the process of structure-based drug design. In some cases there may not be any information about the binding site for a target of interest. In other cases, a putative binding site has been identified by computational or experimental means, but the druggability of the target is not known. Even when a site for a given target is known, it may be desirable to find additional sites whose targeting could produce a desired biological response. A new program, called SiteMap, is presented for identifying and analyzing binding sites and for predicting target druggability. In a large-scale validation, SiteMap correctly identifies the known binding site as the top-ranked site in 86% of the cases, with best results (>98%) coming for sites that bind ligands with subnanomolar affinity. In addition, a modified version of the score employed for binding-site identification allows SiteMap to accurately classify the druggability of proteins as measured by their ability to bind passively absorbed small molecules tightly. In characterizing binding sites, SiteMap provides quantitative and graphical information that can help guide efforts to critically assess virtual hits in a lead-discovery application or to modify ligand structure to enhance potency or improve physical properties in a lead-optimization context.