Virtual screening for small molecule pathway regulators by image profile matching

Abstract

Identifying 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 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.

Competing Interest Statement

AEC has ownership interest in Recursion, a publicly-traded biotech company using images for drug discovery. JTG reports receiving a commercial research grant from Bayer AG. SMC reports receiving research funding from Bayer and Calico Life Sciences.

Footnotes

* Revised manuscript, including new experimental data in Figure 4j

* https://github.com/carpenterlab/2021_Rohban_submitted