Fast high-resolution protein structure determination by using unassigned NMR data.

NMR spectroscopy provides high-resolution structural information of biomolecules in near-physiological conditions. Although significant improvements were achieved in NMR spectroscopy in the last 20 years, the increase in genome sequencing data has created a need for rapid and efficient methods of NMR-based structure determination. 3] NMR data acquisition can be accelerated significantly when sensitive spectrometers are combined with new methods for sampling chemical shifts in multidimensional NMR experiments. Therefore, data analysis and in particular the requirement to assign side-chain chemical shifts to specific atoms is the major bottleneck of rapid NMR-based structure determination. Herein, we present a method, termed FastNMR (fast structure determination by NMR) that enables automatic, high-resolution NMR structure determination of one-domain-sized proteins from unassigned NMR data. By using FastNMR, the de novo structure of the 65residue cone snail neurotoxin conkunitzin-S2 was determined automatically. Although good progress has been made towards prediction of 3D protein structures from amino acid sequences, the quality of the predictions is still limited. These problems may be overcome when a limited number of easily accessible NMR spectroscopic data is combined with ab initio methods. To obtain high-resolution protein structures, experimental distance information is required. The distance information can be extracted from NOE spectra with little manual intervention when assignment of NOE peaks and structure calculation are performed iteratively. To determine the correct structure, however, a nearly complete and error-free manual assignment of chemical shifts is essential. Alternatively, if excellent, unambiguously identified NOESY peak lists are available, it may be possible to obtain a 3D protein structure in the absence of any chemical-shift assignments from the distance information provided in NOESY spectra. FastNMR differs from these approaches in that it starts from unassigned chemical shifts, NOEs, and residual dipolar couplings (RDCs), avoids wrong structures by crossvalidation, works for experimental data, requires only a limited number of NMR spectra, and produces high-resolution (< 1 :) structures. The strategy of FastNMR is based on an approach that has proven to be robust in manual structure determination. This includes usage of information from triple-resonance experiments for sequential backbone assignment, use of iterative NOE assignment and structure calculation, and structure refinement by using RDCs (see the Supporting Information). The key to the success of FastNMR is, however, the simultaneous determination of the backbone assignment and the protein fold prior to analysis of NOE data. This is achieved by iterative RDC-enhanced backbone assignment and fold determination by using the assignment program Mars and the ab initio program Rosetta. The next step is to get from a protein backbone to a 3D structure including side chains. For this aim, side chains are built onto the protein backbone and proton and carbon chemical shifts are predicted from the ensemble of the 20 lowest-energy RosettaNMR structures by using empirical formulas and artificial neural networks. 18] Experimental chemical shifts are then matched to the predicted values and assigned based on the minimal chemical-shift difference. The structure of the protein backbone and the assignment of backbone and sidechain chemical shifts are subsequently used for automated NOE assignment by using the program Cyana. Cyana, however, is not only used for NOE assignment. All distance constraints involving proton chemical shifts, which could not be unambiguously assigned by comparison with predicted values, are treated as ambiguous NOEs. In this way, the assignment of side-chain chemical shifts is partially done as part of the automated NOE assignment. By using the NOEbased 3D structure, the prediction of chemical shifts is improved and a second round of automated NOE assignment is performed. Finally, all experimental data are combined and a high-resolution structure is obtained (see the Supporting Information). FastNMR is automatically performed; that is, FastNMR takes lists of unassigned NMR data as the input and outputs a high-resolution 3D structure. FastNMR was tested on the 60-residue conkunitzin-S1 (Conk-S1) and the 76-residue protein ubiquitin. For both proteins, 3D structures as well as chemical-shift assignments are known allowing evaluation of FastNMR. Furthermore, the high-resolution structure of the 65-residue toxin conkunitzin-S2 (72% sequence identity to Conk-S1) was determined by FastNMR. Neither NMR data nor a 3D [*] J. Korukottu, M. Bayrhuber, Dr. P. Montaville, V. Vijayan, Dr. Y. -S. Jung, Dr. S. Becker, Dr. M. Zweckstetter Department of NMR-Based Structural Biology Max Planck Institute for Biophysical Chemistry Am Fassberg 11, 37077 G9ttingen (Germany) Fax: (+49)551-201-2202 E-mail: mzwecks@gwdg.de