De Novo Design of Nurr1 Agonists via Fragment-Augmented Generative Deep Learning in Low-Data Regime

[Image: see text] Generative neural networks trained on SMILES can design innovative bioactive molecules de novo. These so-called chemical language models (CLMs) have typically been trained on tens of template molecules for fine-tuning. However, it is challenging to apply CLM to orphan targets with...

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Detalles Bibliográficos
Autores principales: Ballarotto, Marco, Willems, Sabine, Stiller, Tanja, Nawa, Felix, Marschner, Julian A., Grisoni, Francesca, Merk, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291550/
https://www.ncbi.nlm.nih.gov/pubmed/37256819
http://dx.doi.org/10.1021/acs.jmedchem.3c00485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291550/
https://www.ncbi.nlm.nih.gov/pubmed/37256819
http://dx.doi.org/10.1021/acs.jmedchem.3c00485

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