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DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data

Abstract The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process...

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Principais autores: Hyun Woo Kim, Chen Zhang, Raphael Reher, Mingxun Wang, Kelsey L. Alexander, Louis-Félix Nothias, Yoo Kyong Han, Hyeji Shin, Ki Yong Lee, Kyu Hyeong Lee, Myeong Ji Kim, Pieter C. Dorrestein, William H. Gerwick, Garrison W. Cottrell
Formato: Artigo
Idioma:Inglês
Publicado em: BMC 2023-08-01
coleção:Journal of Cheminformatics
Assuntos:
Convolutional neural network
Nuclear magnetic resonance
Structure prediction
Acesso em linha:https://doi.org/10.1186/s13321-023-00738-4
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