Computational Enzymology to Study Diverse Catalytic Strategies of RNA

Information

  • Research Project
  • 10241436
  • ApplicationId
    10241436
  • Core Project Number
    R01GM062248
  • Full Project Number
    5R01GM062248-22
  • Serial Number
    062248
  • FOA Number
    PA-18-484
  • Sub Project Id
  • Project Start Date
    6/1/2001 - 23 years ago
  • Project End Date
    8/31/2022 - 2 years ago
  • Program Officer Name
    LYSTER, PETER
  • Budget Start Date
    9/1/2021 - 3 years ago
  • Budget End Date
    8/31/2022 - 2 years ago
  • Fiscal Year
    2021
  • Support Year
    22
  • Suffix
  • Award Notice Date
    8/22/2021 - 3 years ago

Computational Enzymology to Study Diverse Catalytic Strategies of RNA

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.

IC Name
NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
  • Activity
    R01
  • Administering IC
    GM
  • Application Type
    5
  • Direct Cost Amount
    215327
  • Indirect Cost Amount
    115304
  • Total Cost
    330631
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    859
  • Ed Inst. Type
    SCHOOLS OF ARTS AND SCIENCES
  • Funding ICs
    NIGMS:330631\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    RUTGERS, THE STATE UNIV OF N.J.
  • Organization Department
    CHEMISTRY
  • Organization DUNS
    001912864
  • Organization City
    PISCATAWAY
  • Organization State
    NJ
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    088543925
  • Organization District
    UNITED STATES