Dawn Cohen, Kumar Vadaparty, Bill Dickinson and Hemanth Salem
Databases of macromoleo,lar structures allow reaeaxchers to identify genera] principles of molecular behavior. They do this by providing a variety of data obtained under a number of different experimental conditions. Many new tools have been developed recently to aid in exploratory analysis of structural data. However, some queries of interest still require considerable manual filtering of data. In particular, studies attempting to make generalizations about complex axrangements of atoms or building blocks in macromolecular structures cannot be approached directly with existing tools. Such studies are frequently carried out on only a few structures or else require a laborintensive process. To address this problem, we have developed a visual language, VQLM (Visual Query Language for Macromolecules). A query is formulated in this language by drawing aa abstract picture of substructures to be searched for in the database and specifying constraints on the objects in them. To illustrate the usefuinesl of our language, we show how to encode a number of queries that were found scientifically interesting in the published literature in molecular biology. VQLM relies on VQL, a new database language, as its underlying engine for database retrieval and computation. We believe that VQLM will make maeromolecular structural data more accessible to scientists, enabling faster and deeper data analysis.