X-ray crystallography, cryo-electron microscopy, and NMR spectroscopy are the leading methods for determining protein structures at atomic or near-atomic resolution. NMR spectroscopy is unique in its ability to support studies of protein structure and dynamics at the atomic level under a variety of physiologically relevant conditions. Solution NMR is suitable for investigations of small to moderate size proteins and does not require protein crystallization. However, solution NMR is unsuitable for studies of larger and less soluble proteins, such as nano/microcrystalline globular proteins, membrane proteins, and fibrils. These systems are of great interest because they are related to many diseases with no cure. Such systems are becoming increasingly amenable to solid-state NMR (ssNMR). This project aims to establish cyberinfrastructure for fast and reliable analysis of ssNMR data through the development and dissemination of intuitive software packages, algorithms for automated analysis, web services providing computational resources for structure calculations, and educational videos. The cyberinfrastructure will increase the efficiency and reproducibility of solid-state NMR studies, simplify the archiving or results in databases, and assist in the training of newcomers to the field. Solid-state NMR workshops are also planned to be developed, which provide hands-on training for student, postdocs, and junior faculties after completion of this project equivalent to the ones that we have carried longer than a decade for solution NMR.
Structural biology is benefiting greatly from recent advances in solid-state NMR instrumentation, such as ultra-high-speed MAS (magic angle spinning), and experimental technology, including proton or carbon-13 detection in N-dimensional experiments along with sparse sampling and spectral reconstruction. The data sets collected for solid-state NMR that lead to resonance assignments and structure determinations are quite different from those used in solution NMR. The objectives of this project are to develop a robust and efficient, end-to-end computational platform; a. To develop an automation platform for ssNMR-based protein research. b. To develop graphical user interfaces (GUIs) for the analysis of biomolecular ssNMR data. c. To produce web services and public resources for biomolecular ssNMR. The software and related educational materials will be freely disseminated by NMRFAM web services (www.nmrfam.wisc.edu), the NMRbox Project (www.nmrbox.org), and the SBGrid Consortium (www.sbgrid.org).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
