Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Selection of antisense oligonucleotides based on multiple predicted target mRNA structures.

Xiaochen Bo1, Shaoke Lou, Daochun Sun

  • 1Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, P R China. boxc@bmi.ac.cn

BMC Bioinformatics
|March 11, 2006
PubMed
Summary

Integrating multiple predicted RNA structures improves antisense oligonucleotide (ODN) design. Key structural features predict ODN efficacy, enhancing reliability and efficiency in drug development.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Natural history of SPP1 signaling in NF1 tumors.

NPJ precision oncology·2025
Same author

The Combination of HSP90 Inhibitors and Selumetinib Reinforces the Inhibitory Effects on Plexiform Neurofibromas.

Cancers·2025
Same author

Hydroxychloroquine prevents resistance and potentiates the antitumor effect of SHP2 inhibition in NF1-associated malignant peripheral nerve sheath tumors.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Leveraging Neural Crest-Derived Tumors to Identify NF1 Cancer Stem Cell Signatures.

Cancers·2024
Same author

Glioblastoma functional heterogeneity and enrichment of cancer stem cells with tumor recurrence.

Neuron·2024
Same author

The 8th International RASopathies Symposium: Expanding research and care practice through global collaboration and advocacy.

American journal of medical genetics. Part A·2023

Area of Science:

  • Computational biology
  • RNA structure prediction
  • Antisense oligonucleotide (ODN) design

Background:

  • RNA secondary structures influence antisense oligonucleotide (ODN) efficacy.
  • Current structure-based ODN target selection methods face limitations due to RNA structure prediction uncertainties.
  • Utilizing multiple predicted mRNA structures simultaneously can enhance ODN target selection reliability and efficiency.

Purpose of the Study:

  • To systematically address challenges in ODN target selection using multiple predicted mRNA structures.
  • To develop improved methods for integrating diverse RNA structural predictions.
  • To identify key structural features predictive of ODN efficacy.

Main Methods:

  • Developed methods for merging topologically different RNA structures into integrated representations.

Related Experiment Videos

  • Derived parameters to characterize local target site structures.
  • Performed statistical analysis on a dataset of 448 ODNs against 28 mRNAs.
  • Utilized neural network efficacy predictors with features derived from integrated structures.

    • Main Results:

    • Identified 9 features quantitatively associated with ODN efficacy from statistical analysis.
    • Found structural consistency features to be more highly correlated with efficacy than single- or double-stranded region proportions.
    • Demonstrated the importance of local structures at the 5' and 3' termini of the target site.
    • Achieved good performance in cross-validation experiments using neural network predictors.

    Conclusions:

    • Topologically different mRNA structures can be merged into integrated representations for computer-aided ODN design.
    • Features derived from multiple predicted target site structures can effectively predict ODN efficacy.
    • This approach offers a more reliable and efficient strategy for ODN target selection.