Related Experiment Video
Updated: Jun 25, 2025

13:42
RNA Secondary Structure Prediction Using High-throughput SHAPE
Published on: May 31, 2013
31.5K
RNA Secondary Structure Modeling Following the IPANEMAP Workflow
Delphine Allouche1,2, Grégoire De Bisschop1,3, Afaf Saaidi4
1CiTCOM, Cibles Thérapeutiques et conception de médicaments, UMR8038 CNRS, Université de PARIS, Paris, France.
Methods in Molecular Biology (Clifton, N.J.)
|May 23, 2024
Summary
Predicting RNA secondary structure is challenging but improves with experimental data. The IPANEMAP workflow integrates multiple data types for accurate RNA structure modeling.
Area of Science:
- Molecular Biology
- Structural Biology
- Bioinformatics
Background:
- RNA structure is fundamental to molecular biology, underpinning functions like gene regulation and catalysis.
- Accurate RNA secondary structure prediction is essential for 3D modeling and understanding RNA function.
- Current prediction software performance can be enhanced by integrating experimental RNA structure probing data.
Purpose of the Study:
- To detail methods for popular chemical probing techniques (DMS, CMCT, SHAPE-CE, SHAPE-Map).
- To describe the subsequent analysis of probing data.
- To present the IPANEMAP workflow for RNA secondary structure prediction using multiple quantitative and qualitative datasets.
Main Methods:
- Utilized chemical probing methods including dimethyl sulfate (DMS), cyclic carbodiimide (CMCT), and selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE-CE, SHAPE-Map).
- Employed the IPANEMAP workflow, a RNAfold-based approach.
- Integrated multiple sets of quantitative or qualitative experimental data as constraints for computational modeling.
Main Results:
- Demonstrated the application of IPANEMAP for RNA secondary structure prediction.
- Showcased the integration of diverse chemical probing data to improve prediction accuracy.
- Provided a detailed methodological guide for researchers.
Conclusions:
- The IPANEMAP workflow significantly improves RNA secondary structure prediction by incorporating multiple experimental probing datasets.
- This approach offers a powerful tool for advancing the understanding of RNA structure-mediated functions.
- Accurate RNA structure modeling is achievable through the synergistic use of computational tools and experimental data.
Related Concept Videos
Newman Projections
16.8K
Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as...
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as...
16.8K
Protein Organization
6.4K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
The primary structure of a protein is its amino acid sequence....
6.4K

