# Computational Enzymology to Study Diverse Catalytic Strategies of RNA > **NIH NIH R01** · RUTGERS, THE STATE UNIV OF N.J. · 2021 · $330,631 ## Abstract Computational Enzymology to Study Diverse Catalytic Strategies of RNA PI: Darrin M. York, Rutgers University, Piscataway, NJ 08854-8087 USA. This proposal is to bridge the gap between theory and experiment and contribute to a deeper understanding of more complex cellular catalytic RNA systems. Guiding principles for ribozyme engineering may emerge from the identification of conserved mechanistic features as well as elements that may tolerate variation. Establishing these principles will enable the rational design of new biomedical technology and facilitate discovery. Hence we propose to develop and apply a novel computational RNA enzymology approach to study a broad range of small nucleolytic ribozymes in order to reveal common themes and guiding principles in the diverse array of catalytic strategies exhibited by RNA. Complementing these studies, we propose to explore higher tiers of complexity in a model for group I introns, and an RNA-cleaving catalytic DNA system: 1. Develop a computational RNA enzymology toolkit to study ribozyme catalysis: We will build a suite of integrated computational tools to study RNA catalysis, to aid in the interpretation of experimental data, and to provide predictive mechanistic insight. This toolkit will enable the characterization of highly coupled catalytically relevant RNA conformations, metal binding modes, and nucleobase protonation states, and robust and efficient elucidation of catalytic chemical reaction pathways using new integrated multiscale quantum models and path methods, 2. Elucidate diverse catalytic strategies of small nucleolytic ribozyme classes. We will apply our computational RNA enzymology approach to study the array of catalytic mechanisms exhibited by a comprehensive series of self-cleaving ribozymes for which structural data is available. In close collaboration with key experimental groups, we will study various ribozymes for which structures have been determined recently. These new systems greatly expand the scope of known ribozymes, and for the first time, provide a sufficiently rich data set from which novel cross-cutting studies can be performed in order to gain a deep understanding of the guiding principles that underpin catalysis in small self-cleaving RNAs. 3. Explore higher-order RNA structure and function in Azoarcus ribozyme and investigate the mechanism of catalysis in an archetype RNA-cleaving DNA enzyme. We will initiate two new directions that enhance our fun- damental studies of self-cleaving ribozymes. First: we will engage in the study of Azoarcus ribozyme which recent crystallographic data is available. This system is considerably more complex than the small nucleolytic ribozymes, and we propose to focus on gaining insight into the mechanisms of group I introns usage of metal ions, and the origin of the stronger molecular recognition exhibited by Azoarcus ribozyme relative to Tetrahymena ribozyme. Second: we will explore the mechanism of an RNA-cleaving DNA enzyme (DNAzyme), ... ## Key facts - **NIH application ID:** 10241436 - **Project number:** 5R01GM062248-22 - **Recipient organization:** RUTGERS, THE STATE UNIV OF N.J. - **Principal Investigator:** Darrin M York - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $330,631 - **Award type:** 5 - **Project period:** 2001-06-01 → 2022-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10241436 ## Citation > US National Institutes of Health, RePORTER application 10241436, Computational Enzymology to Study Diverse Catalytic Strategies of RNA (5R01GM062248-22). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10241436. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*