Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME

Abstract

Today's large, public databases of protein-small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to custom scripting for informatics and data analysis. Here, we illustrate how the large protein-ligand database BindingDB may be incorporated into KNIME workflows as a step toward the integration of pharmacological data with broader biomolecular analyses. Thus, we describe a collection of KNIME workflows that access BindingDB data via RESTful webservices and, for more intensive queries, via a local distillation of the full BindingDB dataset. We focus in particular on the KNIME implementation of knowledge-based tools to generate informed hypotheses regarding protein targets of bioactive compounds, based on notions of chemical similarity. A number of variants of this basic approach are tested for seven existing drugs with relatively ill-defined therapeutic targets, leading to replication of some previously confirmed results and discovery of new, high-quality hits. Implications for future development are discussed.