DRUG-seq Provides Unbiased Biological Activity Readouts for Neuroscience Drug Discovery.
ACS Chem Biol
; 17(6): 1401-1414, 2022 06 17.
Article
em En
| MEDLINE
| ID: mdl-35508359
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Descoberta de Drogas
/
Transcriptoma
Tipo de estudo:
Guideline
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article