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Cited by 26Advanced NMR Techniques and ApplicationsProtein Structure and DynamicsMolecular spectroscopy and chirality

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Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks

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Karunanithy, Gogulan, Shukla, Vaibhav Kumar, Hansen, D. Flemming·2024·Nature Communications
DOI 10.1038/s41467-024-49378-8PMC PMC11176362

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Abstract

Methyl-TROSY nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for characterising large biomolecules in solution. However, preparing samples for these experiments is demanding and entails deuteration, limiting its use. Here we demonstrate that NMR spectra recorded on protonated, uniformly 13 C labelled samples can be processed using deep neural networks to yield spectra that are of similar quality to typical deuterated methyl-TROSY spectra, potentially providing information for proteins that cannot be produced in bacterial systems. We validate the methodology experimentally on three proteins with molecular weights in the range 42–360 kDa. We further demonstrate the applicability of our methodology to 3D NOESY spectra of Escherichia coli Malate Synthase G (81 kDa), where observed NOE cross-peaks are in good agreement with the available structure. The method represents an advance in the field of using deep learning to analyse complex magnetic resonance data and could have an impact on the study of large biomolecules in years to come.

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Metadata

Authors
Karunanithy, G., Shukla, V. K., & Hansen, D. F.
Affiliations
  • University College London (GB)
  • The Francis Crick Institute (GB)
Corresponding author
Hansen, D. Flemming
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2024-06-13
Volume
15
Issue
1
Pages
5073-5073
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-024-49378-8
PMC
PMC11176362
OpenAlex
W4399604318
Cited by
26
References
4
Citations by year
2026: 14 · 2025: 8 · 2024: 4
FWCI
3.23
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • RCUK | Biotechnology and Biological Sciences Research Council (BB/R000255/1)
  • Wellcome Trust (101569/z/13/z)
  • RCUK | Engineering and Physical Sciences Research Council (EP/X036782/1)
  • Cancer Research UK (FC001029)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced NMR Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Chemistry › Spectroscopy › Molecular spectroscopy and chirality
Keywords
deep neural network, large proteins, solution NMR, NOESY, malate synthase G
MeSH terms
Deep Learning, Carbon Isotopes, Escherichia coli, Malate Synthase, Magnetic Resonance Spectroscopy, Proteins, Neural Networks, Computer, Nuclear Magnetic Resonance, Biomolecular, Escherichia coli Proteins

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