The development of a knowledge base for basic active structures: an example case of dopamine agonists

This paper presents a BAS knowledge base, BASiC, which currently covers 46 activities and is available on the Internet. We use the dopamine agonists D1, D2, and Dauto as examples and illustrate the process of BAS extraction. The resulting BASs were reasonably interpreted after proposing a few template structures.The knowledge base is useful for drug design. Proposed BASs and their supporting structures in the knowledge base will facilitate the development of new template structures for other activities, and will be useful in the design of new lead compounds via reasonable interpretations of active structures.The bioactivity of chemical compounds can usually be explained in terms of common structural features, and the recognition of these features is the starting point in drug design processes. For example, if a group of compounds shares a large carbon skeleton, then recognition of this aspect is relatively straightforward at the structural formula and three-dimensional (3D) levels. However, structural aspects of drugs are very diverse, and no catalog or database of characteristic substructures exists that includes most known active compounds.The concept of a basic active structure (BAS) is described herein and applied at the structural formula level to express characteristic features shared by a group of active compounds. This expression is similar to a combination of the pharmacophore, or the component indispensable to binding and biological activity, and the scaffold, which consists of secondary components that assist in ligand coordination. However, a BAS cannot always be divided into these two components. Active compounds are usually categorized into groups with a BAS.Many papers and reviews have been published that propose relationships among characteristic substructures, structural modifications, and associated biological activity. One typical approach is employed in the commercial system LHASA [1], which compiles empirical knowledge with QSAR results in toxic