Download or read book Protein Structure Determination by Paramagnetic NMR and Computational Hybrid Approach written by Kala Bharath Pilla and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modelling of proteins that rely on either de novo or evolutionary based approaches often produce poor quality structures, primarily due to the limitations in their algorithms or forcefields. Traditional experimental techniques such as X-ray crystallography depend on narrow set of crystallographic conditions while solution/solid state nuclear magnetic resonance (NMR) spectroscopy relies on cumbersome spectral analysis and complete resonance assignments. These traditional approaches are slow and costly endeavours. Computational/experimental hybrid approaches on the other hand provide a new avenue for reliable, rapid and cost-effective structure determination. Paramagnetic NMR offers easy generation of useful and sparse structural information which can be implemented as restraints in structure prediction algorithms. Pseudocontact shifts (PCS) are the most powerful of structural restraints generated by paramagnetic NMR which are long range in nature and can be easily obtained by simple 2D NMR experiments. This thesis demonstrates different approaches involved in protein structure calculations using PCS restraints in Rosetta. Chapter 2 demonstrates structure determination using PCS restraints exclusively obtained from protein samples in microcrystalline state by magic angle spinning (MAS) NMR spectroscopy. Chapter 3 discusses the implementation of using PCS data from multiple metal centres to precisely determine the location of spins in space in a manner analogues to GPS-satellites. Chapter 4 extends the usage of PCS data from multiple metal centres to capture distinct conformational states in proteins. Chapter 5 demonstrates new techniques especially developed for structure determination of large proteins involving super secondary structure motifs (Smotifs) and data driven iterative resampling. These different computational techniques serve the goal of determining accurate 3D models using minimal experimental data, which are applicable to proteins systems that are currently beyond the realm of traditional experimental approaches.