2. Academic Validation
  3. Computational identification of RNA functional determinants by three-dimensional quantitative structure-activity relationships

Computational identification of RNA functional determinants by three-dimensional quantitative structure-activity relationships

  • Nucleic Acids Res. 2014;42(17):11261-71. doi: 10.1093/nar/gku816.
Marc-Frédérick Blanchet 1,  Karine St-Onge 1,  Véronique Lisi 2,  Julie Robitaille 2,  Sylvie Hamel 3,  François Major 4
Affiliations

Affiliations

  • 1 Institute for Research in Immunology and Cancer, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada Department of Computer Science and Operations Research, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada.
  • 2 Institute for Research in Immunology and Cancer, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada.
  • 3 Department of Computer Science and Operations Research, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada.
  • 4 Institute for Research in Immunology and Cancer, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada Department of Computer Science and Operations Research, Université de Montréal, PO Box 6128, Downtown Station, Montréal, Québec H3C 3J7, Canada [email protected].
PMID: 25200082 DOI: 10.1093/nar/gku816
Abstract

Anti-infection drugs target vital functions of infectious agents, including their ribosome and Other essential non-coding RNAs. One of the reasons infectious agents become resistant to drugs is due to mutations that eliminate drug-binding affinity while maintaining vital elements. Identifying these elements is based on the determination of viable and lethal mutants and associated structures. However, determining the structure of enough mutants at high resolution is not always possible. Here, we introduce a new computational method, MC-3DQSAR, to determine the vital elements of target RNA structure from mutagenesis and available high-resolution data. We applied the method to further characterize the structural determinants of the Bacterial 23S ribosomal RNA sarcin-ricin loop (SRL), as well as those of the lead-activated and hammerhead ribozymes. The method was accurate in confirming experimentally determined essential structural elements and predicting the viability of new SRL variants, which were either observed in bacteria or validated in Bacterial growth assays. Our results indicate that MC-3DQSAR could be used systematically to evaluate the drug-target potentials of any RNA sites using current high-resolution structural data.

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