Vfold: a web server for RNA structure and folding thermodynamics prediction

Area of Science:

• Computational Biology
• Biophysics
• Bioinformatics

Background:

• The discovery of non-coding RNAs necessitates accurate RNA folding predictions for understanding their functions and developing therapeutics.
• Accurate modeling of RNA structure and stability is crucial for human health and RNA-based therapeutic strategies.

Purpose of the Study:

• To develop a user-friendly web server for predicting RNA folding structures and stability.
• To provide accurate predictions of RNA two-dimensional (base pair) and three-dimensional all-atom structures.

Main Methods:

• The Vfold server predicts 2D RNA structures by evaluating free energies of various loop structures and base mismatches using experimental parameters and a coarse-grained model.
• 3D RNA structures are predicted by assembling motif scaffolds from PDB templates and refining them with all-atom energy minimization.
• Folding thermodynamics, including heat capacity melting curves, are predicted from the nucleotide sequence.

Main Results:

• The Vfold server accurately predicts RNA two-dimensional structures, including loop structures with intra-loop mismatches.
• The server generates three-dimensional all-atom structures from predicted two-dimensional structures and sequences.
• Folding thermodynamics, such as heat capacity melting curves, can be predicted from the RNA sequence.

Conclusions:

• The Vfold web server offers a user-friendly tool for predicting RNA structure and stability.
• The Vfold server provides accessible predictions for RNA 2D and 3D structures and folding thermodynamics.
• The Vfold web server and source code are publicly available for research purposes.