Vfold2D-MC: A Physics-Based Hybrid Model for Predicting RNA Secondary Structure Folding.

ABSTRACT: Accurate prediction of RNA structure and folding stability has a far-reaching impact on our understanding of RNA functions. Here we develop Vfold2D-MC, a new physics-based model, to predict RNA structure and folding thermodynamics from the sequence. The model employs virtual bond-based coarse-graining of RNA backbone conformation and generates RNA conformations through Monte Carlo sampling of the bond angles and torsional angles of the virtual bonds. Using a coarse-grained statistical potential derived from the known structures, we assign each conformation with a statistical weight. The weighted average over the conformational ensemble gives the entropy and free energy parameters for the hairpin, bulge, and internal loops, and multiway junctions. From the thermodynamic parameters, we predi

SUBMITTER: Cheng Y 

PROVIDER: S-EPMC8903033 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature