Structure-guided optimization of ligands engaging with a specific molecular target is a key approach in drug discovery today. As a prerequisite, detailed knowledge of the types and quality of interactions, ligand and protein geometry, as well as available nearby space and interaction opportunities is necessary. Currently, X-ray crystallography is by far the most applied technique to elucidate protein-ligand co-structures; however, the success rate is often variable, in particular when working with dynamic proteins or weakly binding ligands. As a result, structural information is not routinely obtained in these situations and ligand optimization is often challenging or not pursued at all, representing a substantial limitation in the diversity of chemical scaffolds explored for a given target.<br/>To overcome this impediment, we have developed a robust NMR restraint-guided docking protocol to generate high quality models of protein-small molecule complexes. A comprehensive, experimentally determined and easily accessible set of protein-ligand intermolecular distances is used to drive the docking process and enables selection of the correct ligand conformation in the bound state. Using the antibacterial target CoaD as a model system, the method was first benchmarked with several compounds for which X-ray co-structures were available. Afterward, and for the first time according to our knowledge, the utility and performance of such a method was fully demonstrated by applying it to molecules with completely unknown binding mode. Data on two independent compound series is presented showing that the generated docking models could be employed for the successful, prospective optimization of crystallographically non-tractable hits into more potent binders. The improved molecules are shown to interact with the target as predicted and can serve as novel chemistry starting points.

High confidence protein-ligand complex modeling by NMR-guided docking enables early hit optimization

254th National Meeting (2017)

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