TALOS+: A hybrid method for predicting protein backbone torsion angles from NMR chemical shifts

By Yang Shen, Frank Delaglio, Gabriel Cornilescu, A. Bax. Journal of Biomolecular NMR, 2009

2,596 citations recorded by the source corpus.

NMR chemical shifts in proteins depend strongly on local structure. The program TALOS establishes an empirical relation between 13C, 15N and 1H chemical shifts and backbone torsion angles ϕ and ψ (Cornilescu et al. J Biomol NMR 13 289–302, 1999). Extension of the original 20-protein database to 200 proteins increased the fraction of residues for which backbone angles could be predicted from 65 to 74%, while reducing the error rate from 3 to 2.5%. Addition of a two-layer neural network filter to the database fragment selection process forms the basis for a new program, TALOS+, which further enhances the prediction rate to 88.5%, without increasing the error rate. Excluding the 2.5% of residues for which TALOS+ makes predictions that strongly differ from those observed in the crystalline state, the accuracy of predicted ϕ and ψ angles, equals ±13°. Large discrepancies between predictions and crystal structures are primarily limited to loop regions, and for the few cases where multiple X-ray structures are available such residues are often found in different states in the different structures. The TALOS+ output includes predictions for individual residues with missing chemical shifts, and the neural network component of the program also predicts secondary structure with good accuracy.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/f616f35d32a4b5ff06dbb593178e2f235908e741

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In Materials Chemistry

1. Woonghee Lee
2. Santrupti Nerli
3. John L. Markley
4. Nikolaos G. Sgourakis
5. Yuanpeng Janet Huang
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In Molecular Biology

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In Spectroscopy

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2. Nikolaos G. Sgourakis
3. Gaetano T. Montelione
4. Yuanpeng Janet Huang
5. Julia Koehler Leman
6. Richard Bonneau
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8. Jens Meiler

Citations in the corpus

• Chemical shift-based methods in NMR structure determination (2018, background): “are expected to improve the accuracy and precision of torsion angle predictions even further [36,37].”
• Protein structure determination by combining sparse NMR data with evolutionary couplings (2015, positive): “A deuterium correction to 13 C chemical shifts was also applied in Talos+ calculations for perdeuterated proteins 33 .”
• PONDEROSA-C/S: client–server based software package for automated protein 3D structure determination (2014, background): “S1b), Ponderosa Server starts generating distance constraints from CYANA and angle constraints from TALOS-N (Shen and Bax 2013) or its relatives (Cornilescu et al. 1999; Shen et al. 2009).”
• Structural insights into the recruitment of SMRT by the corepressor SHARP under phosphorylative regulation. (2013, methodology): “Dihedral f and c angles derived from TALOS+ were also utilized (Shen et al., 2009).”
• Integrative protein modeling in RosettaNMR from sparse paramagnetic restraints (2019, methodology): “The second library was created using backbone CSs and secondary structure assignment predicted with the program TALOS+ (Shen et al., 2009).”
• Structure of the Bacterial Cytoskeleton Protein Bactofilin by NMR Chemical Shifts and Sequence Variation. (2016, background): “A previous analysis of the chemical shifts (9) using TALOSþ (13) suggested mostly b-sheet structure, but it was difficult to determine the exact location of loops and the number of strands.”