Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials

Cocrystal engineering have been widely applied in pharmaceutical, chemistry and material fields. However, how to effectively choose coformer has been a challenging task on experiments. Here we develop a graph neural network (GNN) based deep learning framework to quickly predict formation of the cocr...

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Detalles Bibliográficos
Autores principales: Jiang, Yuanyuan, Yang, Zongwei, Guo, Jiali, Li, Hongzhen, Liu, Yijing, Guo, Yanzhi, Li, Menglong, Pu, Xuemei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511140/
https://www.ncbi.nlm.nih.gov/pubmed/34642333
http://dx.doi.org/10.1038/s41467-021-26226-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511140/
https://www.ncbi.nlm.nih.gov/pubmed/34642333
http://dx.doi.org/10.1038/s41467-021-26226-7

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