Your browser doesn't support javascript.
loading
Functional microRNA-targeting drug discovery by graph-based deep learning.
Keshavarzi Arshadi, Arash; Salem, Milad; Karner, Heather; Garcia, Kristle; Arab, Abolfazl; Yuan, Jiann Shiun; Goodarzi, Hani.
Afiliación
  • Keshavarzi Arshadi A; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
  • Salem M; Department of Urology, University of California, San Francisco, San Francisco, CA, USA.
  • Karner H; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
  • Garcia K; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
  • Arab A; Department of Computer Engineering, University of Central Florida, Orlando, FL, USA.
  • Yuan JS; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
  • Goodarzi H; Department of Urology, University of California, San Francisco, San Francisco, CA, USA.
Patterns (N Y) ; 5(1): 100909, 2024 Jan 12.
Article en En | MEDLINE | ID: mdl-38264717
ABSTRACT
MicroRNAs are recognized as key drivers in many cancers but targeting them with small molecules remains a challenge. We present RiboStrike, a deep-learning framework that identifies small molecules against specific microRNAs. To demonstrate its capabilities, we applied it to microRNA-21 (miR-21), a known driver of breast cancer. To ensure selectivity toward miR-21, we performed counter-screens against miR-122 and DICER. Auxiliary models were used to evaluate toxicity and rank the candidates. Learning from various datasets, we screened a pool of nine million molecules and identified eight, three of which showed anti-miR-21 activity in both reporter assays and RNA sequencing experiments. Target selectivity of these compounds was assessed using microRNA profiling and RNA sequencing analysis. The top candidate was tested in a xenograft mouse model of breast cancer metastasis, demonstrating a significant reduction in lung metastases. These results demonstrate RiboStrike's ability to nominate compounds that target the activity of miRNAs in cancer.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Patterns (N Y) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Patterns (N Y) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos