ArticleJournal of biomolecular NMR2016
Amino acid recognition for automatic resonance assignment of intrinsically disordered proteins.
Article in Journal of biomolecular NMR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Using temperature coefficients to support resonance assignment of intrinsically disordered proteins.Journal of biomolecular NMR · 2025Article
- Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes.Journal of biomolecular NMR · 2023Article
- Interaction patterns of methoprene-tolerant and germ cell-expressedFrontiers in molecular biosciences · 2023Article
- Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins.PLoS computational biology · 2022Article
- Review
- Enhancing Compression Level for More Efficient Compressed Sensing and Other Lessons from NMR Spectroscopy.Sensors (Basel, Switzerland) · 2020Article
- POTENCI: prediction of temperature, neighbor and pH-corrected chemical shifts for intrinsically disordered proteins.Journal of biomolecular NMR · 2018Article
- NMR assignments of sparsely labeled proteins using a genetic algorithm.Journal of biomolecular NMR · 2017Article
- Resonance assignment of disordered protein with repetitive and overlapping sequence using combinatorial approach reveals initial structural propensities and local restrictions in the denatured state.Journal of biomolecular NMR · 2016Article
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Authors and funding
8 authors.
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Abstract
Resonance assignment is a prerequisite for almost any NMR-based study of proteins. It can be very challenging in some cases, however, due to the nature of the protein under investigation. This is the case with intrinsically disordered proteins, for example, whose NMR spectra suffer from low chemical shifts dispersion and generally low resolution. For these systems, sequence specific assignment is highly time-consuming, so the prospect of using automatic strategies for their assignment is very attractive. In this article we present a new version of the automatic assignment program TSAR dedicated to intrinsically disordered proteins. In particular, we demonstrate how the automatic procedure can be improved by incorporating methods for amino acid recognition and information on chemical shifts in selected amino acids. The approach was tested in silico on 16 disordered proteins and experimentally on α-synuclein, with remarkably good results.
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