8rd6
the C-terminal domain of TonB protein from Salmonella enterica.
Structural highlights
FunctionTONB_SALTY Interacts with outer membrane receptor proteins that carry out high-affinity binding and energy dependent uptake into the periplasmic space of specific substrates such as cobalamin, and various iron compounds (such as iron dicitrate, enterochelin, aerobactin, etc.). In the absence of TonB these receptors bind their substrates but do not carry out active transport. TonB also interacts with some colicins and is involved in the energy-dependent, irreversible steps of bacteriophages phi 80 and T1 infection. It could act to transduce energy from the cytoplasmic membrane to specific energy-requiring processes in the outer membrane, resulting in the release into the periplasm of ligands bound by these outer membrane proteins. Publication Abstract from PubMedMultidimensional NMR spectra are the basis for studying proteins by NMR spectroscopy and crucial for the development and evaluation of methods for biomolecular NMR data analysis. Nevertheless, in contrast to derived data such as chemical shift assignments in the BMRB and protein structures in the PDB databases, this primary data is in general not publicly archived. To change this unsatisfactory situation, we present a standardized set of solution NMR data comprising 1329 2-4-dimensional NMR spectra and associated reference (chemical shift assignments, structures) and derived (peak lists, restraints for structure calculation, etc.) annotations. With the 100-protein NMR spectra dataset that was originally compiled for the development of the ARTINA deep learning-based spectra analysis method, 100 protein structures can be reproduced from their original experimental data. The 100-protein NMR spectra dataset is expected to help the development of computational methods for NMR spectroscopy, in particular machine learning approaches, and enable consistent and objective comparisons of these methods. The 100-protein NMR spectra dataset: A resource for biomolecular NMR data analysis.,Klukowski P, Damberger FF, Allain FH, Iwai H, Kadavath H, Ramelot TA, Montelione GT, Riek R, Guntert P Sci Data. 2024 Jan 4;11(1):30. doi: 10.1038/s41597-023-02879-5. PMID:38177162[1] From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine. References
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