An award is made to the University of Colorado Anschutz Medical Center to develop a Nuclear Magnetic Resonance (NMR) protocol to routinely determine high-resolution ribonucleic acid (RNA) structures and their dynamics based exclusively on empirical data with modest experimental effort. Although the conversion of the NMR data into interatomic distances requires in-depth understanding of the underlying physics and mathematics, the software to be developed will render this knowledge unnecessary. The project specifically concerns RNA, but some of the methods will boost the applicability to proteins as well. In combination with the anticipated reduction in measuring time, this will make the protocol attractive to the NMR spectroscopy and structural biology communities. Educationally, structural dynamics studies of RNA molecules have been largely unrepresented while the scientific communities' focus has centered on average structural representation. Macromolecules and their interactions are dynamic in nature and this is why it is critical to learn how to evaluate motions in parallel with structure. Thus, mentoring students on how to bridge this gap is a critical part of this proposed project, especially considering that the general field of macromolecular dynamics experimentation has moved quickly within recent years. A summer student from the RNA Bioscience Initiative Summer Internship Program at the University of Colorado will be recruited, which offers access to top-level research experience for students from institutions with limited research programs.

RNA not only is the template for translating the genetic code into proteins, but also carries out diverse important cellular functions. Understanding these functions absolutely depends on knowledge of the structural arrangement at atomic resolution, and, as is becoming increasingly evident, the conformational dynamics of RNA molecules. Almost one-half of the determined RNA structures have been solved by NMR. However, high-resolution RNA structures can rarely be obtained from the most popular and successful NMR probe alone, the Nuclear Overhauser Enhancement (NOE). Instead, many additional semi-empirical restraints and labor-intensive techniques only accessible to experts are required to obtain a structural average, and there are only a few experimentally derived ensembles of structures representing realistic spatial sampling. Therefore, the structural biology community is in need of novel methods that improve the pool of structural data that can be collected and used for RNA structure determination. In principle, the NOE directly depends on the distance between two atoms. However, the NOE is employed as a semi-quantitative upper limit distance restraint. The non-exact nature of this restraint means that important information about structure and dynamics is lost. It is our idea to measure the NOE exactly (eNOE), which can be converted into a tight distance limit. In ideal cases, such a distance can be measured to an accuracy of ca. 10-11 meters and can be obtained for hundreds of proton pairs in an RNA molecule. These project proposes to establish an efficient protocol to improve NMR structures of RNA of all sizes using the exact NOE (eNOE) approach, enabling RNA researchers to calculate multi-state structural ensembles for small RNAs, and improving average structures or specific local structural aspects for larger RNAs. It is the intellectual merit of this project that the eNOE distance will improve all types of determined NMR structures: i) structures of small RNAs (up to 20 nucleotides) may be defined at high resolution without any other restraints; the eNOE can also be used to calculate multi-state structural ensembles to realistically sample their conformational space, ii) larger RNA molecules will result in improved average structures. We will offer NMR pulse sequence codes and our eNOE analysis program eNORA for free download from our webpage. This protocol should help researchers to study RNA structures at higher resolution, a prerequisite for better understanding of RNA function.

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.

National Science Foundation (NSF)
Division of Biological Infrastructure (DBI)
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Jean Gao
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University of Colorado at Denver-Downtown Campus
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