Cargando…
Empowering drug off-target discovery with metabolic and structural analysis
Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of...
Autores principales: | Chowdhury, Sourav, Zielinski, Daniel C., Dalldorf, Christopher, Rodrigues, Joao V., Palsson, Bernhard O., Shakhnovich, Eugene I. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256842/ https://www.ncbi.nlm.nih.gov/pubmed/37296102 http://dx.doi.org/10.1038/s41467-023-38859-x |
Ejemplares similares
-
Development of antibacterial compounds that constrain evolutionary pathways to resistance
por: Zhang, Yanmin, et al.
Publicado: (2021) -
Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model
por: Chang, Roger L., et al.
Publicado: (2010) -
The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions
por: Dalldorf, Christopher, et al.
Publicado: (2023) -
Pangenome Analytics Reveal Two-Component Systems as Conserved Targets in ESKAPEE Pathogens
por: Rajput, Akanksha, et al.
Publicado: (2021) -
Unveiling the Kinomes of Leishmania infantum and L. braziliensis Empowers the Discovery of New Kinase Targets and Antileishmanial Compounds
por: Borba, Joyce V.B., et al.
Publicado: (2019)