SHAPER: A Web Server for Fast and Accurate SHAPE Reactivity Prediction.

Area of Science:

• Biochemistry
• Structural Biology
• Bioinformatics

Background:

• Selective 2 -hydroxyl acylation analyzed by primer extension (SHAPE) is an experimental technique for assessing RNA local flexibility.
• SHAPE reactivity data offers insights into RNA structural dynamics, crucial for accurate 2D/3D structure prediction.
• Integrating experimental SHAPE data with computational methods can refine RNA structure selection.

Purpose of the Study:

• To introduce SHAPE predictoR (SHAPER), a novel web server designed for rapid and precise prediction of SHAPE reactivity.
• To provide a user-friendly platform for refining RNA 2D/3D structure selection by integrating experimental SHAPE data.
• To facilitate the use of SHAPE reactivity data in computational RNA structure modeling.

Main Methods:

• Development of the SHAPER web server for SHAPE reactivity prediction.
• Acceptance of RNA structures from experimental or computational sources as input.
• Support for single or multiple RNA conformations within the input structures.
• Calculation and provision of predicted SHAPE profiles and correlations with experimental data.

Main Results:

• SHAPER enables fast and accurate prediction of SHAPE reactivity for given RNA structures.
• The server allows for the comparison of predicted SHAPE profiles with experimental data to assess structural models.
• Users can download predicted SHAPE profiles and correlation metrics for each submitted RNA conformation.

Conclusions:

• SHAPER serves as a valuable tool for leveraging SHAPE chemical probing data to improve RNA structure prediction accuracy.
• The web server facilitates the refinement of RNA structural models by integrating experimental flexibility information.
• SHAPER enhances the utility of SHAPE experiments in computational RNA biology research.