ArticleJournal of magnetic resonance (San Diego, Calif. : 1997)2010
A Monte Carlo/simulated annealing algorithm for sequential resonance assignment in solid state NMR of uniformly labeled proteins with magic-angle spinning.
Article in Journal of magnetic resonance (San Diego, Calif. : 1997), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed.
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- Automated fibril structure calculations in Xplor-NIH.Structure (London, England : 1993) · 2025Article
- Solid-state NMR studies of proteins in condensed phases.Magnetic resonance letters · 2024Review
- Structure of Amyloid Peptide Ribbons Characterized by Electron Microscopy, Atomic Force Microscopy, and Solid-State Nuclear Magnetic Resonance.The journal of physical chemistry. B · 2024Article
- Liquid Droplet Aging and Seeded Fibril Formation of the Cytotoxic Granule Associated RNA Binding Protein TIA1 Low Complexity Domain.Journal of the American Chemical Society · 2023Article
- Solid-state NMR spectroscopy.Nature reviews. Methods primers · 2021Article
- Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.Journal of biomolecular NMR · 2017Article
- Cellulose Structural Polymorphism in Plant Primary Cell Walls Investigated by High-Field 2D Solid-State NMR Spectroscopy and Density Functional Theory Calculations.Biomacromolecules · 2016Article
- Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria.Journal of biomolecular NMR · 2016Article
- Aromatic spectral editing techniques for magic-angle-spinning solid-state NMR spectroscopy of uniformly (13)C-labeled proteins.Solid state nuclear magnetic resonance · 2015Article
- Successive Stages of Amyloid-β Self-Assembly Characterized by Solid-State Nuclear Magnetic Resonance with Dynamic Nuclear Polarization.Journal of the American Chemical Society · 2015Article
- On the problem of resonance assignments in solid state NMR of uniformly ¹⁵N,¹³C-labeled proteins.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2015Article
- MAS NMR of HIV-1 protein assemblies.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2015Article
- Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra.Scientific reports · 2015Article
- VirtualSpectrum, a tool for simulating peak list for multi-dimensional NMR spectra.Journal of biomolecular NMR · 2014Article
- An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming.Journal of biomolecular NMR · 2014Article
- Automated robust and accurate assignment of protein resonances for solid state NMR.Journal of biomolecular NMR · 2014Article
- Resonance assignment of the NMR spectra of disordered proteins using a multi-objective non-dominated sorting genetic algorithm.Journal of biomolecular NMR · 2013Article
- Automated solid-state NMR resonance assignment of protein microcrystals and amyloids.Journal of biomolecular NMR · 2013Article
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2 authors.
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Abstract
We describe a computational approach to sequential resonance assignment in solid state NMR studies of uniformly (15)N,(13)C-labeled proteins with magic-angle spinning. As input, the algorithm uses only the protein sequence and lists of (15)N/(13)C(alpha) crosspeaks from 2D NCACX and NCOCX spectra that include possible residue-type assignments of each crosspeak. Assignment of crosspeaks to specific residues is carried out by a Monte Carlo/simulated annealing algorithm, implemented in the program MC_ASSIGN1. The algorithm tolerates substantial ambiguity in residue-type assignments and coexistence of visible and invisible segments in the protein sequence. We use MC_ASSIGN1 and our own 2D spectra to replicate and extend the sequential assignments for uniformly-labeled HET-s(218-289) fibrils previously determined manually by Siemer et al. (J. Biomol. NMR, 34 (2006) 75-87) from a more extensive set of 2D and 3D spectra. Accurate assignments by MC_ASSIGN1 do not require data that are of exceptionally high quality. Use of MC_ASSIGN1 (and its extensions to other types of 2D and 3D data) is likely to alleviate many of the difficulties and uncertainties associated with manual resonance assignments in solid state NMR studies of uniformly labeled proteins, where spectral resolution and signal-to-noise are often sub-optimal.
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