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Automatic structure-based NMR methyl resonance assignment in large proteins
- Source :
- Nature Communications, Vol 10, Iss 1, Pp 1-12 (2019), Nature Communications, Nature Communications, 10 (1)
- Publication Year :
- 2019
- Publisher :
- Nature Publishing Group, 2019.
-
Abstract
- Isotopically labeled methyl groups provide NMR probes in large, otherwise deuterated proteins. However, the resonance assignment constitutes a bottleneck for broader applicability of methyl-based NMR. Here, we present the automated MethylFLYA method for the assignment of methyl groups that is based on methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. MethylFLYA is applied to five proteins (28–358 kDa) comprising a total of 708 isotope-labeled methyl groups, of which 612 contribute NOESY cross peaks. MethylFLYA confidently assigns 488 methyl groups, i.e. 80% of those with NOESY data. Of these, 459 agree with the reference, 6 were different, and 23 were without reference assignment. MethylFLYA assigns significantly more methyl groups than alternative algorithms, has an average error rate of 1%, modest runtimes of 0.4–1.2 h, and can handle arbitrary isotope labeling patterns and data from other types of NMR spectra.<br />Nature Communications, 10 (1)<br />ISSN:2041-1723
- Subjects :
- 0301 basic medicine
Models, Molecular
Stereochemistry
Science
Biophysics
General Physics and Astronomy
Nuclear Overhauser effect
010402 general chemistry
01 natural sciences
Resonance (particle physics)
Methylation
General Biochemistry, Genetics and Molecular Biology
Article
03 medical and health sciences
Automation
Spectroscopy
lcsh:Science
Nuclear Magnetic Resonance, Biomolecular
Multidisciplinary
Chemistry
Proteins
General Chemistry
0104 chemical sciences
Computational biology and bioinformatics
NMR spectra database
Molecular Weight
030104 developmental biology
Deuterium
Structure based
lcsh:Q
Structural biology
Two-dimensional nuclear magnetic resonance spectroscopy
Algorithms
Software
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 10
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Nature Communications
- Accession number :
- edsair.doi.dedup.....b153e8ae4395e41f74bcebb35de7a552
- Full Text :
- https://doi.org/10.1038/s41467-019-12837-8