With the discovery of ribozymes and the multitude of regulatory functions performed by RNA, great effort is being directed toward high resolution characterization of RNA 3D structure. Because of the dynamic nature of RNA, static structures are not sufficient for the functional studies necessary for drug design. Nuclear Magnetic Resonance (NMR) is a tool that captures structural data across an ensemble of interchanging structures, and tools for converting this data into dynamic 3D models is in high demand across academic and industrial laboratories. We have developed a powerful software tool for predicting the NMR spectrum of computationally generated RNA structures, enabling the combination of empirical force fields and experimental data in determining the structure and dynamics of important RNAs.
NMR Chemical Shifts as Restraints in Molecular Dynamic Studies of RNA
Our technology allows for rapid and accurate prediction of 1H and 13C chemical shifts from 3D RNA structures generated in silico. This technology is the first of its kind to be readily coupled with molecular dynamics simulations. We have demonstrated straightforward integration of experimental NMR data into molecular dynamics scoring functions and shown that this data efficiently guides structural sampling toward more accurate structures. Not only is our technology extremely sensitive to changes in 3D structure, but we have also shown the unprecedented ability to detect 13C referencing errors in structures previously solved using NMR data, creating a tool for both structure prediction and validation.
- Assist in NMR assignment based on structure
- RNA structure prediction and determination
- RNA structure validation and assessment
- Detection of referencing errors in NMR chemical shifts
- Facile integration with Molecular Dynamics
- Increase speed and confidence in structure prediction
- Extreme sensitivity to subtle changes in 3D structure