ConStruct: a tool for thermodynamic controlled prediction of conserved secondary structure

Area of Science:

• Computational Biology
• Bioinformatics
• Molecular Biology

Background:

• Predicting RNA secondary structure is crucial for understanding RNA function.
• Homologous RNAs often share conserved structural elements.
• Accurate prediction requires robust handling of sequence alignments and structural information.

Purpose of the Study:

• To present a novel computational tool for predicting conserved secondary structures in sets of homologous single-stranded RNAs.
• To enable the identification and visualization of conserved structural elements within RNA families.
• To improve the accuracy of RNA structure prediction by optimizing sequence alignments based on structural information.

Main Methods:

• Calculation and storage of structure distribution in base pair probability matrices for individual RNAs.
• Introduction and alignment of gaps from multiple sequence alignment into probability matrices.
• Summation of aligned probability matrices to create a consensus probability matrix.
• Utilizing a graphical user interface to refine sequence alignments by removing disruptive gaps.
• Extraction and visualization of consensus secondary structure from the consensus probability matrix.

Main Results:

• Development of a tool that generates a consensus probability matrix highlighting conserved structural elements.
• Demonstration of the tool's functionality using a set of U7 RNAs involved in histone mRNA processing.
• Identification of conserved secondary structures within the tested RNA set.
• Provision of three distinct graphical representations for the predicted consensus structure.

Conclusions:

• The presented tool effectively predicts conserved secondary structures in homologous RNAs.
• The ability to optimize sequence alignments improves the accuracy of structure prediction.
• The tool offers valuable insights into RNA structural conservation and function.
• The graphical interface facilitates the recognition and correction of alignment artifacts impacting structure prediction.