Understanding biological phenomena at atomic resolution is one of the keys to modern drug design. In particular, knowledge of 3D structures of proteins and their interactions with other macromolecules are necessary for designing chemical compounds that modify biological processes. Conventional methods for protein structure determinations comprise X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. These techniques can also determine the binding mode of chemical compounds. Either technique can be slow and costly, making it highly relevant to explore alternative strategies. Paramagnetic NMR spectroscopy is emerging as such an alternative technique. In order to measure the paramagnetic effects, two NMR spectra are compared that have been measured with and without a bound paramagnetic metal ion. In particular, pseudocontact shifts (PCS) of nuclear spins are easily measured as the difference (in ppm) of the chemical shifts between the two spectra. PCSs provide long range and orientation dependent restraints, allowing positioning of the spin with respect to the magnetic susceptibility tensor anisotropy (Δχ-tensor) of the metal ion. In this thesis, I used the PCS effect to computationally extract information from NMR spectra. I developed (i) a tool (called Possum) to automatically assign diamagnetic and paramagnetic spectra of the methyl groups of amino acid side chains, given structural information of the protein studied and prior knowledge of the Δχ-tensor; (ii) I designed a comprehensive software package (called Numbat) to extract Δχ-tensor parameters from assigned PCS values and the available 3D structure; and (iii) I incorporated PCS-based restraints into the protein structure prediction software CS-ROSETTA and demonstrated that this combination (PCS-ROSETTA) presents a significant improvement for de novo structure determination. The three projects serve different purposes at different stages of protein NMR studies. They could be combined in the following manner: Starting from assigned backbone PCSs, PCS-Rosetta could be used to determine the 3D structure of the protein. Possum can then be used to automatically assign the NMR resonances of the methyl groups using PCSs. Finally, Numbat can be used to fit improved Δχ-tensors to all the PCS data, analyze the quality of the Δχ-tensors and identify possible wrong assignments. Iterative repetition of this protocol would give a 3D structural model of the protein with a minimum of data. Alternatively, the Δχ-tensor parameters and PCSs could be used as input for a traditional software package such as Xplor-NIH to compute a 3D structure of the protein.
| Identifer | oai:union.ndltd.org:ADTP/286555 |
| Creators | Christophe Schmitz |
| Source Sets | Australiasian Digital Theses Program |
| Detected Language | English |
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