DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.

Convolutional neural network Nuclear magnetic resonance Structure prediction

Journal

Journal of cheminformatics
ISSN: 1758-2946
Titre abrégé: J Cheminform
Pays: England
ID NLM: 101516718

Informations de publication

Date de publication:
07 Aug 2023
Historique:
received: 01 05 2023
accepted: 19 07 2023
medline: 8 8 2023
pubmed: 8 8 2023
entrez: 7 8 2023
Statut: epublish

Résumé

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 that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra. However, the number of reference NMR spectra available is limited and has mostly facilitated annotation of commercially available derivatives. Here, we introduce DeepSAT, a neural network-based structure annotation and scaffold prediction system that directly extracts the chemical features associated with molecular structures from their NMR spectra. Using only the

Identifiants

pubmed: 37550756
doi: 10.1186/s13321-023-00738-4
pii: 10.1186/s13321-023-00738-4
pmc: PMC10406729
doi:

Types de publication

Journal Article

Langues

eng

Pagination

71

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM107550
Pays : United States
Organisme : NIH HHS
ID : GM107550
Pays : United States

Informations de copyright

© 2023. Springer Nature Switzerland AG.

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Auteurs

Hyun Woo Kim (HW)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
College of Pharmacy and Integrated Research Institute for Drug Development, Dongguk University-Seoul, Gyeonggi-Do, Republic of Korea.

Chen Zhang (C)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
Department of Computer Science and Engineering, University of California, La Jolla, San Diego, CA, USA.

Raphael Reher (R)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
Institute of Pharmaceutical Biology and Biotechnology, University of Marburg, Marburg, Germany.

Mingxun Wang (M)

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Ometa Labs LLC, San Diego, CA, USA.
Department of Computer Science, University of California Riverside, Riverside, CA, USA.

Kelsey L Alexander (KL)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, USA.

Louis-Félix Nothias (LF)

Institut de Chimie de Nice, UMR 7272, Université Côte d'Azur, CNRS, 06108, Nice, France.

Yoo Kyong Han (YK)

College of Pharmacy, Korea University, Sejong, Republic of Korea.

Hyeji Shin (H)

College of Pharmacy, Korea University, Sejong, Republic of Korea.

Ki Yong Lee (KY)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
College of Pharmacy, Korea University, Sejong, Republic of Korea.

Kyu Hyeong Lee (KH)

College of Pharmacy and Integrated Research Institute for Drug Development, Dongguk University-Seoul, Gyeonggi-Do, Republic of Korea.

Myeong Ji Kim (MJ)

College of Pharmacy and Integrated Research Institute for Drug Development, Dongguk University-Seoul, Gyeonggi-Do, Republic of Korea.

Pieter C Dorrestein (PC)

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.

William H Gerwick (WH)

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA. wgerwick@ucsd.edu.
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA. wgerwick@ucsd.edu.

Garrison W Cottrell (GW)

Department of Computer Science and Engineering, University of California, La Jolla, San Diego, CA, USA. gary@ucsd.edu.

Classifications MeSH