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DRUG-seq Provides Unbiased Biological Activity Readouts for Neuroscience Drug Discovery

[Image: see text] Unbiased transcriptomic RNA-seq data has provided deep insights into biological processes. However, its impact in drug discovery has been narrow given high costs and low throughput. Proof-of-concept studies with Digital RNA with pertUrbation of Genes (DRUG)-seq demonstrated the pot...

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Detalles Bibliográficos
Autores principales: Li, Jingyao, Ho, Daniel J., Henault, Martin, Yang, Chian, Neri, Marilisa, Ge, Robin, Renner, Steffen, Mansur, Leandra, Lindeman, Alicia, Kelly, Brian, Tumkaya, Tayfun, Ke, Xiaoling, Soler-Llavina, Gilberto, Shanker, Gopi, Russ, Carsten, Hild, Marc, Gubser Keller, Caroline, Jenkins, Jeremy L., Worringer, Kathleen A., Sigoillot, Frederic D., Ihry, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207813/
https://www.ncbi.nlm.nih.gov/pubmed/35508359
http://dx.doi.org/10.1021/acschembio.1c00920
Descripción
Sumario:[Image: see text] Unbiased transcriptomic RNA-seq data has provided deep insights into biological processes. However, its impact in drug discovery has been narrow given high costs and low throughput. Proof-of-concept studies with Digital RNA with pertUrbation of Genes (DRUG)-seq demonstrated the potential to address this gap. We extended the DRUG-seq platform by subjecting it to rigorous testing and by adding an open-source analysis pipeline. The results demonstrate high reproducibility and ability to resolve the mechanism(s) of action for a diverse set of compounds. Furthermore, we demonstrate how this data can be incorporated into a drug discovery project aiming to develop therapeutics for schizophrenia using human stem cell-derived neurons. We identified both an on-target activation signature, induced by a set of chemically distinct positive allosteric modulators of the N-methyl-d-aspartate (NMDA) receptor, and independent off-target effects. Overall, the protocol and open-source analysis pipeline are a step toward industrializing RNA-seq for high-complexity transcriptomics studies performed at a saturating scale.