The BindingDB project was conceived in the mid-1990s, based upon recognition of the broad value of quantitative affinity data and the inadequacy of journal articles as a means of making these data accessible. A NIST-sponsored workshop in September 1997 validated the concept, and funding from the NSF and  NIST enabled initial development of the database with a collection of data for systems of many types, including protein-ligand, protein-protein, and host–guest binding.  However, hopes that the database would be populated primarily through depositions by experimentalists were not borne out, and it became clear that the project would have to take responsibility for extracting data from the literature.  Given the vastness of the molecular recognition literature and limitations in available resources, this meant that creating a useful database would require limiting attention to a well-defined set of high-value binding data.
The decision was taken to focus on binding data for small molecules with proteins that are drug-targets, or potential drug-targets, and for which the three-dimensional structure is available in the PDB or can potentially be modeled to high accuracy based upon the structure of a similar protein.  This choice would aid drug-discovery for the selected targets, as well as the development of both ligand-based and structure-based methods of computational ligand-design.  This is the current focus of BindingDB, which is led by [http://gilson.ucsd.edu/ Michael Gilson], based at UC San Diego's Skaggs School of Pharmacy and Pharmaceutical Sciences, and supported by a grant from the NIH.