Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

We present machine learning (ML) models for hydrogen bond acceptor (HBA) and hydrogen bond donor (HBD) strengths. Quantum chemical (QC) free energies in solution for 1:1 hydrogen-bonded complex formation to the reference molecules 4-fluorophenol and acetone serve as our target values. Our acceptor a...

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Detalles Bibliográficos
Autores principales: Bauer, Christoph A., Schneider, Gisbert, Göller, Andreas H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737620/
https://www.ncbi.nlm.nih.gov/pubmed/33430967
http://dx.doi.org/10.1186/s13321-019-0381-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737620/
https://www.ncbi.nlm.nih.gov/pubmed/33430967
http://dx.doi.org/10.1186/s13321-019-0381-4

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