Abstract
Chemical shift prediction has an unappreciated power to guide backbone resonance assignment in cases where protein structure is known. Here we describe Resonance Assignment by chemical Shift Prediction (RASP), a method that exploits this power to derive protein backbone resonance assignments from chemical shift predictions. Robust assignments can be obtained from a minimal set of only the most sensitive triple-resonance experiments, even for spectroscopically challenging proteins. Over a test set of 154 proteins RASP assigns 88 % of residues with an accuracy of 99.7 %, using only information available from HNCO and HNCA spectra. Applied to experimental data from a challenging 34 kDa protein, RASP assigns 90 % of manually assigned residues using only 40 % of the experimental data required for the manual assignment. RASP has the potential to significantly accelerate the backbone assignment process for a wide range of proteins for which structural information is available, including those for which conventional assignment strategies are not feasible.
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Acknowledgments
We thank Stephen Headey and Martin Scanlon for sharing the KPR data, and David Chalmers for helpful discussions on optimization strategies. This work was supported in part by an Australian National Health and Medical Research Council project grant (1025150). RSN acknowledges fellowship support from the NHMRC.
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MacRaild, C.A., Norton, R.S. RASP: rapid and robust backbone chemical shift assignments from protein structure. J Biomol NMR 58, 155–163 (2014). https://doi.org/10.1007/s10858-014-9813-7
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DOI: https://doi.org/10.1007/s10858-014-9813-7