Virtual screening for small-molecule pathway regulators by image-profile matching

Identifying the chemical regulators of biological pathways is a time-consuming bottleneck in developing therapeutics and research compounds. Typically, thousands to millions of candidate small molecules are tested in target-based biochemical screens or phenotypic cell-based screens, both expensive experiments customized to each disease. Here, our uncustomized, virtual, profile-based screening approach instead identifies compounds that match to pathways based on the phenotypic information in public cell image data, created using the Cell Painting assay. Our straightforward correlation-based computational strategy retrospectively uncovered the expected, known small-molecule regulators for 32% of positive-control gene queries. In prospective, discovery mode, we efficiently identified new compounds related to three query genes and validated them in subsequent gene-relevant assays, including compounds that phenocopy or pheno-oppose YAP1 overexpression and kill a Yap1-dependent sarcoma cell line. This image-profile-based approach could replace many customized labor- and resource-intensive screens and accelerate the discovery of biologically and therapeutically useful compounds. [Display omitted] •Compounds impacting particular genes’ function are highly sought•Most chemicals and overexpressed genes impact cell morphology in the Cell Painting assay•Matching these image profiles can find chemicals that impact a particular gene’s function•This virtual screen using public data found new chemical regulators of several pathways If a chemical compound and a gene overexpression yield the same cell morphology in the microscopy-based assay Cell Painting, then they are likely to impact the same functions. This principle is exploited to retrieve useful compounds for particular query genes in public Cell Painting datasets.