Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery

Drug Discovery is an active research area that demands great investments and generates low returns due to its inherent complexity and great costs. To identify potential therapeutic candidates more effectively, we propose protein–ligand with adversarial augmentations network (PLA-Net), a deep learnin...

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Detalles Bibliográficos
Autores principales: Ruiz Puentes, Paola, Rueda-Gensini, Laura, Valderrama, Natalia, Hernández, Isabela, González, Cristina, Daza, Laura, Muñoz-Camargo, Carolina, Cruz, Juan C., Arbeláez, Pablo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119967/
https://www.ncbi.nlm.nih.gov/pubmed/35589824
http://dx.doi.org/10.1038/s41598-022-12180-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119967/
https://www.ncbi.nlm.nih.gov/pubmed/35589824
http://dx.doi.org/10.1038/s41598-022-12180-x

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