Automatic assignment of protein backbone resonances by direct spectrum inspection in targeted acquisition of NMR data
- 105 Downloads
The necessity to acquire large multidimensional datasets, a basis for assignment of NMR resonances, results in long data acquisition times during which substantial degradation of a protein sample might occur. Here we propose a method applicable for such a protein for automatic assignment of backbone resonances by direct inspection of multidimensional NMR spectra. In order to establish an optimal balance between completeness of resonance assignment and losses of cross-peaks due to dynamic processes/degradation of protein, assignment of backbone resonances is set as a stirring criterion for dynamically controlled targeted nonlinear NMR data acquisition. The result is demonstrated with the 12 kDa 13C,15 N-labeled apo-form of heme chaperone protein CcmE, where hydrolytic cleavage of 29 C-terminal amino acids is detected. For this protein, 90 and 98% of manually assignable resonances are automatically assigned within 10 and 40 h of nonlinear sampling of five 3D NMR spectra, respectively, instead of 600 h needed to complete the full time domain grid. In addition, resonances stemming from degradation products are identified. This study indicates that automatic resonance assignment might serve as a guiding criterion for optimal run-time allocation of NMR resources in applications to proteins prone to degradation.
KeywordsMDD Automatic resonance assignment Nonlinear data sampling Targeted NMR data acquisition
2,2-Dimethyl-2-silapentane-5-sulfonate, sodium salt
Nuclear magnetic resonance
Relative hypothesis prioritization
This work was funded by the Academic Research Fund Tier-2 grant of Ministry of Education of Singapore to Konstantin Pervushin and Bruker BioSpin Group AG, Germany, grant to James E. Masse.
- Atreya HS, Chary KVR, Govil G (2002) Automated NMR assignments of proteins for high throughput structure determination: TATAPRO II. Curr Sci 83:1372–1376Google Scholar
- Bohm M, Stadlthanner K, Tome AM, Gruber P, Teixeira AR, Theis FJ, Puntonet CG, Lang EW (2005) AutoAssign—an automatic assignment tool for independent components. In: Proceedings of pattern recognition and image analysis, Pt. 2, vol. 3523. Springer, Berlin, pp 75–82Google Scholar
- Wu KP, Chang JM, Chen JB, Chang CF, Wu WJ, Huang TH, Sung TY, Hsu WL (2005) RIBRA—an error-tolerant algorithm for the NMR backbone assignment problem. In: Proceedings of research in computational molecular biology, vol. 3500. Springer, Berlin, pp 103–117Google Scholar