
The NMR SPECTROSCOPY Team, headed by John Markley, PhD, is responsible for NMR condition optimization, data collection and processing, and structure determination. This group takes advantage of the facilities available at the National Magnetic Resonance Facility at Madison (NMRFAM) and the Medical College of Wisconsin (MCW) and has solved over 40 NMR structures.
The Teams' streamlined approach employs cryogenic probes and automated analysis to rapidly and efficiently determine three-dimensional protein structures by NMR. For proteins of up to 25 kDa in effective molecular weight that are soluble (> 0.5 mM), folded and stable, we acquire a complete data set consisting of 17 2D and 3D experiments in 10–14 days. Time-domain data are processed with NMR Pipe program, and converted to the XEASY format.
Data analysis is carried out in a semi-automated manner using software from various academic sources. Signals in all 3D experiments are detected
automatically and integrated using the SPSCAN program. GARANT or PINE is used for automated assignment of backbone and chemical shifts, and side chain
assignments are completed manually in XEASY or CARA. Backbone torsion angle restraints are predicted empirically from chemical shift values using the TALOS
package and included in the initial round of structure calculations.

Initial protein structures are generated using an iterative and fully automatic methodology for assignment of NOESY cross peaks provided by the NOEASSIGN module of CYANA. The final stages of structure refinement are accomplished through manual optimization of NOE assignments, NOE intensity-to-distance calibration functions, and backbone torsion angle restraints. Torsion angle dynamics structures that meet a set of objective criteria for agreement with experimental constraints and coordinate precision are subjected to molecular dynamics calculations in explicit solvent using the XPLOR-NIH package before final validation and deposition in the PDB and BMRB databases.
Structures are interrogated using bioinfomatic methods that utilize structure and sequence based comparison tools, such as FATCAT, VAST, FFAS03, and Pfam. Bioinformatic analysis can generate a testable functional hypothesis, and experimental validation of our findings led to the identification of a new family of membrane-associated ubiquitin fold proteins, the MUBs. This modular pipeline strategy relies on a predefined framework for data management that enables an efficient workflow even when multiple personnel participate at various stages of the process. The self-contained nature of individual steps allows for substitution of improved software tools as new technology becomes available.