Protein Structural Information Derived from NMR Chemical Shift with the Neural Network Program TALOS-N

By Yang Shen, A. Bax. 2015

245 citations recorded by the source corpus.

Summary Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors and the artificial neural network based TALOS-N program has been trained to extract backbone and sidechain torsion angles from 1H, 15N and 13C shifts. The program is quite robust, and typically yields backbone torsion angles for more than 90% of the residues, and sidechain χ1 rotamer information for about half of these, in addition to reliably predicting secondary structure. The use of TALOS-N is illustrated for the protein DinI, and torsion angles obtained by TALOS-N analysis from the measured chemical shifts of its backbone and 13Cβ nuclei are compared to those seen in a prior, experimentally determined structure. The program is also particularly useful for generating torsion angle restraints, which then can be used during standard NMR protein structure calculations.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

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Citations in the corpus

Predicting multiple conformations via sequence clustering and AlphaFold2 (2023, positive): “We followed this with automated NOE assignments by AUDANA 77 (which uses X-PLOR-NIH for simulated annealing and TALOS-N for calculation of torsion angle constraints).”
Assessment of Prediction Methods for Protein Structures Determined by NMR in CASP14: Impact of AlphaFold2 (2021, unknown): “Model agreement with backbone chemical shift data deposited in the BioMagResDatabase was assessed using the Talos_N program.(16)”