Diversity & tractability revisited in collaborative small molecule phenotypic screening library design.

Identification of purposeful chemical matter on a broad range of drug targets is of high importance to the pharmaceutical industry. However, disease-relevant but more complex hit-finding plans require flexibility regarding the subset of the compounds that we screen. Herein we describe a strategy to design high-quality small molecule screening subsets of two different sizes to cope with a rapidly changing early discovery portfolio. The approach taken balances chemical tractability, chemical diversity and biological target coverage. Furthermore, using surveys, we actively involved chemists within our company in the selection process of the diversity decks to ensure current medicinal chemistry principles were incorporated. The chemist surveys revealed that not all published PAINS substructure alerts are considered productive by the medicinal chemistry community and in agreement with previously published results from other institutions, QED scores tracked quite well with chemists' notions of chemical attractiveness.

Discovery of novel chemotypes to a G-protein-coupled receptor through ligand-steered homology modeling and structure-based virtual screening.

Melanin-concentrating hormone receptor 1 (MCH-R1) is a G-protein-coupled receptor (GPCR) and a target for the development of therapeutics for obesity. The structure-based development of MCH-R1 and other GPCR antagonists is hampered by the lack of an available experimentally determined atomic structure. A ligand-steered homology modeling approach has been developed (where information about existing ligands is used explicitly to shape and optimize the binding site) followed by docking-based virtual screening. Top scoring compounds identified virtually were tested experimentally in an MCH-R1 competitive binding assay, and six novel chemotypes as low micromolar affinity antagonist "hits" were identified. This success rate is more than a 10-fold improvement over random high-throughput screening, which supports our ligand-steered method. Clearly, the ligand-steered homology modeling method reduces the uncertainty of structure modeling for difficult targets like GPCRs.