Computational prediction of RNA 3D structure using low resolution data and a new

Information

  • Research Project
  • 8290972
  • ApplicationId
    8290972
  • Core Project Number
    R01GM088813
  • Full Project Number
    5R01GM088813-03
  • Serial Number
    088813
  • FOA Number
    PA-07-070
  • Sub Project Id
  • Project Start Date
    6/1/2010 - 14 years ago
  • Project End Date
    5/31/2013 - 11 years ago
  • Program Officer Name
    PREUSCH, PETER
  • Budget Start Date
    6/1/2012 - 12 years ago
  • Budget End Date
    5/31/2013 - 11 years ago
  • Fiscal Year
    2012
  • Support Year
    03
  • Suffix
  • Award Notice Date
    6/7/2012 - 12 years ago
Organizations

Computational prediction of RNA 3D structure using low resolution data and a new

DESCRIPTION (provided by applicant): Nature has developed mechanisms to protect living organisms against external intruders such as viruses, or internal dysfunction leading to diseases, such as cancer. One such security mechanism is gene silencing, which is at the heart of organisms< development and speciation. In particular, gene silencing is widely used to study human and model organisms' genetics. Increasing evidence suggests that diseases such as cancer are the result of multiple gene deregulations. A normal cellular reaction would be to shutting down these genes. However, in the case of diseases such as cancer, for unknown reasons the cell is unable to cope with the situation, leading to tumor development and progression. We need to understand better gene silencing mechanisms if we wish to discover why the cell cannot defends itself in these situations, or if we want to intervene efficiently in gene silencing to fight these diseases. Gene silencing is based on a class of ribonucleic acids called microRNAs. One of the aims of this research is to study the molecular basis of these microRNAs, and in particular the mechanism by which they bind the messenger RNAs of targeted genes. Predicting accurately the targeted genes of microRNAs is among the most important unresolved questions of gene silencing at this moment. Many in the field are hindered by their over-reliance on the secondary structures of ribonucleotide chains, which severely limits the usefulness and predictive value of the current computational models. Ribonucleotide chains' function is rather due to their tertiary structure. This is why it is crucial for all laboratories currently engaged in research on RNAs and microRNAs that modeling programs capable of rapidly and accurately producing RNA tertiary structures with atomic precision become available. In this research, I propose the development and application of an RNA computer-modeling framework that builds upon the one I developed over the last 20 years to obtain high-resolution tertiary structures of microRNAs and targeted messenger RNAs. These tertiary structures will help us get insights into how and where microRNAs bind their targets, and prepare biological assays to confirm these insights. We aim to put these new powerful tools in the hands of the experimentalists, since rapidly and reliably producing RNA structures will yield immense benefits to the biomedical field's ability to understand and experiment with these recently discovered gene-silencing pathways. PUBLIC HEALTH RELEVANCE: Accumulating evidence shows that RNA molecules are crucial players in the mechanisms that protect us against external intruders such as viruses, or internal dysfunction that leads to diseases. Determining RNA three-dimensional (3D) structures is key to study RNA function, but is costly and laborious using physical methods. In many ways, this situation hinders the RNA biomedical field, and the research here aims at providing to all computational tools to rapidly and reliably producing RNA 3D structures, yielding immense benefits to the researchers' ability to understand and manipulate RNAs including those in our own protection mechanisms.

IC Name
NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
  • Activity
    R01
  • Administering IC
    GM
  • Application Type
    5
  • Direct Cost Amount
    134187
  • Indirect Cost Amount
    10735
  • Total Cost
    144922
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    859
  • Ed Inst. Type
  • Funding ICs
    NIGMS:144922\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    MSFD
  • Study Section Name
    Macromolecular Structure and Function D Study Section
  • Organization Name
    UNIVERSITY OF MONTREAL
  • Organization Department
  • Organization DUNS
    207622838
  • Organization City
    MONTREAL
  • Organization State
    PQ
  • Organization Country
    CANADA
  • Organization Zip Code
    H3C 3J7
  • Organization District
    CANADA