Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery. Issue 5 (18th May 2017) - Drawnel, Faye Marie; Zhang, Jitao David; Küng, Erich; Aoyama, Natsuyo; Benmansour, Fethallah; Araujo Del Rosario, Andrea; Jensen Zoffmann, Sannah; Delobel, Frédéric; Prummer, Michael; Weibel, Franziska; Carlson, Coby; Anson, Blake; et al.
Summary: Today, novel therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping was applicable to compounds with a range of binding specificities and triaged false positives derived from high-content screening assays. The technique identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. Our results advocate for application of molecular phenotyping in early drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade. Graphical Abstract: Highlights: Molecular phenotyping stratifies compounds based on pathway profiles Molecular phenotyping detects false-positive hits in a phenotypic screen Molecular phenotyping correlates pathway activity patterns with phenotypic readouts Molecular phenotyping can be powered by preclinical and clinical data Abstract : Drawnel and Zhang et al. show that quantitative mRNA sequencing of pathway reporter genes can be powered by translational information and classifies compound responses. Adopting this technique in drug discovery could permit biomedically relevant compound screening, increasing likelihood of clinical impact.