An expectation/maximization nuclear vector replacement algorithm for automated NMR resonance assignments

We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of an homologous structure. Our algorithm performs Nuclear Vector Replacement (NVR) by Expectation/Maximization (EM) to compute assignments. NVR correlates experimentally-measured NH re...

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Vydáno v:Journal of biomolecular NMR Ročník 29; číslo 2; s. 111 - 138
Hlavní autoři: Langmead, Christopher James, Donald, Bruce Randall
Médium: Journal Article
Jazyk:angličtina
Vydáno: Netherlands Springer Nature B.V 01.06.2004
Témata:
Algorithms
Animals
Automation
Carbon Isotopes - chemistry
Computer Simulation
Crystallography
Crystallography, X-Ray
Humans
Magnetic Resonance Spectroscopy - methods
Molecular Structure
Muramidase - chemistry
Nitrogen Isotopes - chemistry
NMR
Nuclear magnetic resonance
Spectrum analysis
Streptococcus
Structural models
Ubiquitin - chemistry
ISSN:0925-2738, 1573-5001
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Shrnutí:We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of an homologous structure. Our algorithm performs Nuclear Vector Replacement (NVR) by Expectation/Maximization (EM) to compute assignments. NVR correlates experimentally-measured NH residual dipolar couplings (RDCs) and chemical shifts to a given a priori whole-protein 3D structural model. The algorithm requires only uniform (15)N-labelling of the protein, and processes unassigned H(N)-(15)N HSQC spectra, H(N)-(15)N RDCs, and sparse H(N)-H(N) NOE's (d(NN)s). NVR runs in minutes and efficiently assigns the (H(N),(15)N) backbone resonances as well as the sparse d(NN)s from the 3D (15)N-NOESY spectrum, in O (n(3)) time. The algorithm is demonstrated on NMR data from a 76-residue protein, human ubiquitin, matched to four structures, including one mutant (homolog), determined either by X-ray crystallography or by different NMR experiments (without RDCs). NVR achieves an average assignment accuracy of over 99%. We further demonstrate the feasibility of our algorithm for different and larger proteins, using different combinations of real and simulated NMR data for hen lysozyme (129 residues) and streptococcal protein G (56 residues), matched to a variety of 3D structural models.
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ISSN:0925-2738
1573-5001
DOI:10.1023/B:JNMR.0000019247.89110.e6