UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions
Abstract To extract information from NMR experiments, users need to identify the number of resonances in the spectrum, together with characteristic features such as chemical shifts and intensities. In many applications, particularly those involving biomolecules, this procedure is typically a manual...
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| Format: | Article |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54899-3 |
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| author | Charles Buchanan Gogulan Karunanithy Olga Tkachenko Michael Barber Michael T. Marty Timothy J. Nott Christina Redfield Andrew J. Baldwin |
| author_facet | Charles Buchanan Gogulan Karunanithy Olga Tkachenko Michael Barber Michael T. Marty Timothy J. Nott Christina Redfield Andrew J. Baldwin |
| author_sort | Charles Buchanan |
| collection | DOAJ |
| description | Abstract To extract information from NMR experiments, users need to identify the number of resonances in the spectrum, together with characteristic features such as chemical shifts and intensities. In many applications, particularly those involving biomolecules, this procedure is typically a manual and laborious process. While many algorithms are available to tackle this problem, their performance tends to be inferior to that of an experienced user. Here, we introduce UnidecNMR, which identifies resonances in NMR spectra using deconvolution. We demonstrate its favourable performance on 1 and 2D simulated spectra, strongly overlapped 1D spectra of oligosaccharides and 2D HSQC, 3D HNCO, 3D HNCA and 3/4D methyl-methyl NOE experimental spectra from a range of proteins. UnidecNMR outperforms a number of freely available algorithms and provides results comparable to those generated manually. Introducing additional restraints, such as a 2D peak list when analysing 3 and 4D data and incorporating reflection symmetry in NOE analysis further improves the results. UnidecNMR outputs a back-calculated spectrum and a peak list, both of which can be easily examined using the supplied GUI. The software allows interactive processing using nmrPipe, allowing users to go directly from raw data to processed spectra with picked peak lists. |
| format | Article |
| id | doaj-art-a0b3f975fc3a4a4f811c6aa196f02ace |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-a0b3f975fc3a4a4f811c6aa196f02ace2025-01-12T12:30:50ZengNature PortfolioNature Communications2041-17232025-01-0116111110.1038/s41467-024-54899-3UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensionsCharles Buchanan0Gogulan Karunanithy1Olga Tkachenko2Michael Barber3Michael T. Marty4Timothy J. Nott5Christina Redfield6Andrew J. Baldwin7Physical and Theoretical Chemistry, University of OxfordPhysical and Theoretical Chemistry, University of OxfordPhysical and Theoretical Chemistry, University of OxfordPhysical and Theoretical Chemistry, University of OxfordPhysical and Theoretical Chemistry, University of OxfordDepartment of Biochemistry, University of OxfordDepartment of Biochemistry, University of OxfordPhysical and Theoretical Chemistry, University of OxfordAbstract To extract information from NMR experiments, users need to identify the number of resonances in the spectrum, together with characteristic features such as chemical shifts and intensities. In many applications, particularly those involving biomolecules, this procedure is typically a manual and laborious process. While many algorithms are available to tackle this problem, their performance tends to be inferior to that of an experienced user. Here, we introduce UnidecNMR, which identifies resonances in NMR spectra using deconvolution. We demonstrate its favourable performance on 1 and 2D simulated spectra, strongly overlapped 1D spectra of oligosaccharides and 2D HSQC, 3D HNCO, 3D HNCA and 3/4D methyl-methyl NOE experimental spectra from a range of proteins. UnidecNMR outperforms a number of freely available algorithms and provides results comparable to those generated manually. Introducing additional restraints, such as a 2D peak list when analysing 3 and 4D data and incorporating reflection symmetry in NOE analysis further improves the results. UnidecNMR outputs a back-calculated spectrum and a peak list, both of which can be easily examined using the supplied GUI. The software allows interactive processing using nmrPipe, allowing users to go directly from raw data to processed spectra with picked peak lists.https://doi.org/10.1038/s41467-024-54899-3 |
| spellingShingle | Charles Buchanan Gogulan Karunanithy Olga Tkachenko Michael Barber Michael T. Marty Timothy J. Nott Christina Redfield Andrew J. Baldwin UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions Nature Communications |
| title | UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions |
| title_full | UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions |
| title_fullStr | UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions |
| title_full_unstemmed | UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions |
| title_short | UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions |
| title_sort | unidecnmr automatic peak detection for nmr spectra in 1 4 dimensions |
| url | https://doi.org/10.1038/s41467-024-54899-3 |
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