Advanced Computational Techniques for Structure Determination of Membrane Proteins by Solid-state NMR.

LAPIN, JOEL. Advanced Computational Techniques for Structure Determination of Membrane Proteins by Solid-state NMR. (Under the direction of Dr. Alexander Nevzorov). Utilizing solid-state NMR spectroscopy of aligned membrane proteins has the potential to yield high-resolution structures for these important biological constituents. Generally, upon acquisition of their NMR spectra, the resonances must be 1) assigned and then 2) the structure must be calculated while satisfying the experimental NMR restraints. Both processes are, in general, affected by ambiguity and degeneracy in the interpretation of the spectra, owing in part to broad linewidths and an insufficient number of NMR measurements. For spectroscopic assignment we have developed an automated algorithm that can assign 2D homonuclear and heteronuclear spectra based on the crosspeak pattern from the spin-exchange experiments. By treating the spectral contours as a “pseudopotential”, the main peak assignment can be scored based on how well the calculated crosspeaks match the experimental intensity. The best score yields the most plausible assignment which best fits the spectra. The developed Monte Carlo/Simulated annealing algorithm to find the highest-scoring main peak order is first exemplified on synthetic spectra, and then demonstrated on two experimental datasets, i.e. Pf1 coat protein reconstituted in magnetically aligned bicelles and within the entire Pf1 bacteriophage supramolecular assembly. In the former case the previous assignment that was established via selective labeling experiments was recovered in an automated fashion. For the latter dataset, a new assignment was suggested by the algorithm, simultaneously satisfying both the selective labeling spectra and the assumed helical pattern for the crosspeaks. For structure determination we have significantly improved a previous algorithm which has resulted in more accurate structures, as well as developed a protocol to utilize Rosetta bioinformatics scoring functions to screen the fitted solutions yielding the most plausible structures. Since 3D NMR spectra are not yet routinely available, this protocol was demonstrated on synthetic spectra generated from PDBs 2gb1, a soluble protein, and 4a2n, a membrane protein. The results provide a road map for future structure calculations. Based on the trials with the synthetic spectra, and using a new pulse sequence for correlating HαCα dipolar couplings with N CSA, the protocol has been applied on the dataset derived from triple-resonance NMR spectra of Pf1 coat protein in magnetically aligned bicelles. Structure calculations were carried out without biasing the φ,ψ torsion search, as was previously necessary for 2D spectra, and produced a consensus alpha-helical solution. Finally, simulations were utilized for NMR pulse sequence optimization, producing spectra with superior H-N dipolar coupling linewidths. A Monte Carlo search protocol implemented on a GPU computer was used to extensively simulate NMR experiments in order to optimize the pulse phases and durations that make up a pulse sequence. Predicted pulse sequences were tested on an NAL crystal and Leucine labeled Pf1 coat protein in magnetically aligned bicelles. The resulting pulse sequence, termed ROULETTE-1, resulted in linewidths 18% sharper than the SAMPI4 pulse sequence on the crystal, and 14% sharper for the