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 identi?cation 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 ef?cient 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 ?rst time, provide a suf?ciently 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), starting with the ?rst crystallographic structure of an archetype RNA-cleaving DNAzyme (8-17 DNAzyme), published than a year ago, Detailed study of the 8-17 DNAzyme using our computational enzymology approach will complement our ongoing studies of the mechanisms of RNA enzymes and their protein enzyme analogs such as RNase.

Public Health Relevance

Computational Enzymology to Study Diverse Catalytic Strategies of RNA PI: Darrin M. York, Rutgers University, Piscataway, NJ 08854-8087 USA. The goal of this proposal is to use a novel computational RNA enzymology approach to study diverse catalytic strategies exhibited by RNA enzymes. Powerful computational tools and insightful guiding principles for ribozyme engineering are likely to emerge through the proposed work that enable the rational design of new biomedical technology and facilitate discovery.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM062248-19
Application #
9660717
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lyster, Peter
Project Start
2001-06-01
Project End
2022-08-31
Budget Start
2018-09-20
Budget End
2019-08-31
Support Year
19
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Rutgers University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
001912864
City
Piscataway
State
NJ
Country
United States
Zip Code
Lee, Tai-Sung; Cerutti, David S; Mermelstein, Dan et al. (2018) GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features. J Chem Inf Model 58:2043-2050
Giese, Timothy J; York, Darrin M (2018) A GPU-Accelerated Parameter Interpolation Thermodynamic Integration Free Energy Method. J Chem Theory Comput 14:1564-1582
Gaines, Colin S; York, Darrin M (2017) Model for the Functional Active State of the TS Ribozyme from Molecular Simulation. Angew Chem Int Ed Engl 56:13392-13395
Chen, Haoyuan; Giese, Timothy J; Golden, Barbara L et al. (2017) Divalent Metal Ion Activation of a Guanine General Base in the Hammerhead Ribozyme: Insights from Molecular Simulations. Biochemistry 56:2985-2994
Lee, Tai-Sung; Radak, Brian K; Harris, Michael E et al. (2016) A Two-Metal-Ion-Mediated Conformational Switching Pathway for HDV Ribozyme Activation. ACS Catal 6:1853-1869
Sengupta, Raghuvir N; Van Schie, Sabine N S; Giamba?u, George et al. (2016) An active site rearrangement within the Tetrahymena group I ribozyme releases nonproductive interactions and allows formation of catalytic interactions. RNA 22:32-48
Zhang, Shuming; Gu, Hong; Chen, Haoyuan et al. (2016) Isotope effect analyses provide evidence for an altered transition state for RNA 2'-O-transphosphorylation catalyzed by Zn(2+). Chem Commun (Camb) 52:4462-5
Gaines, Colin S; York, Darrin M (2016) Ribozyme Catalysis with a Twist: Active State of the Twister Ribozyme in Solution Predicted from Molecular Simulation. J Am Chem Soc 138:3058-65
Giamba?u, George M; York, Darrin M; Case, David A (2015) Structural fidelity and NMR relaxation analysis in a prototype RNA hairpin. RNA 21:963-74
Weissman, Benjamin P; Li, Nan-Sheng; York, Darrin et al. (2015) Heavy atom labeled nucleotides for measurement of kinetic isotope effects. Biochim Biophys Acta 1854:1737-45

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