ArticleJournal of biomolecular NMR2010
Robust structure-based resonance assignment for functional protein studies by NMR.
Article in Journal of biomolecular NMR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction.Science advances · 2023Article
- NMR Structure Determinations of Small Proteins Using only One Fractionally 20%Molecules (Basel, Switzerland) · 2021Article
- Automatic methyl assignment in large proteins by the MAGIC algorithm.Journal of biomolecular NMR · 2017Article
- Automated assignment of NMR chemical shifts based on a known structure and 4D spectra.Journal of biomolecular NMR · 2016Article
- Article
- Reliable resonance assignments of selected residues of proteins with known structure based on empirical NMR chemical shift prediction.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2015Article
- RASP: rapid and robust backbone chemical shift assignments from protein structure.Journal of biomolecular NMR · 2014Article
- RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts.Journal of biomolecular NMR · 2012Article
- Combining automated peak tracking in SAR by NMR with structure-based backbone assignment from 15N-NOESY.BMC bioinformatics · 2012Article
- RDC derived protein backbone resonance assignment using fragment assembly.Journal of biomolecular NMR · 2011Article
- SAGA: rapid automatic mainchain NMR assignment for large proteins.Journal of biomolecular NMR · 2010Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput functional protein NMR studies, like protein interactions or dynamics, require an automated approach for the assignment of the protein backbone. With the availability of a growing number of protein 3D structures, a new class of automated approaches, called structure-based assignment, has been developed quite recently. Structure-based approaches use primarily NMR input data that are not based on J-coupling and for which connections between residues are not limited by through bonds magnetization transfer efficiency. We present here a robust structure-based assignment approach using mainly H(N)-H(N) NOEs networks, as well as (1)H-(15) N residual dipolar couplings and chemical shifts. The NOEnet complete search algorithm is robust against assignment errors, even for sparse input data. Instead of a unique and partly erroneous assignment solution, an optimal assignment ensemble with an accuracy equal or near to 100% is given by NOEnet. We show that even low precision assignment ensembles give enough information for functional studies, like modeling of protein-complexes. Finally, the combination of NOEnet with a low number of ambiguous J-coupling sequential connectivities yields a high precision assignment ensemble. NOEnet will be available under: http://www.icsn.cnrs-gif.fr/download/nmr.
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