Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds

Deep generative neural networks have been used increasingly in computational chemistry for de novo design of molecules with desired properties. Many deep learning approaches employ reinforcement learning for optimizing the target properties of the generated molecules. However, the success of this ap...

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Detalles Bibliográficos
Autores principales: Korshunova, Maria, Huang, Niles, Capuzzi, Stephen, Radchenko, Dmytro S., Savych, Olena, Moroz, Yuriy S., Wells, Carrow I., Willson, Timothy M., Tropsha, Alexander, Isayev, Olexandr
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/PMC9814657/
https://www.ncbi.nlm.nih.gov/pubmed/36697952
http://dx.doi.org/10.1038/s42004-022-00733-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814657/
https://www.ncbi.nlm.nih.gov/pubmed/36697952
http://dx.doi.org/10.1038/s42004-022-00733-0

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