DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

We address the problem of generating novel molecules with desired interaction properties as a multi-objective optimization problem. Interaction binding models are learned from binding data using graph convolution networks (GCNs). Since the experimentally obtained property scores are recognised as ha...

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Detalles Bibliográficos
Autores principales: Khemchandani, Yash, O’Hagan, Stephen, Samanta, Soumitra, Swainston, Neil, Roberts, Timothy J., Bollegala, Danushka, Kell, Douglas B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487898/
https://www.ncbi.nlm.nih.gov/pubmed/33431037
http://dx.doi.org/10.1186/s13321-020-00454-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487898/
https://www.ncbi.nlm.nih.gov/pubmed/33431037
http://dx.doi.org/10.1186/s13321-020-00454-3

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