Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.

ABSTRACT: Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly wit

SUBMITTER: Nithin C 

PROVIDER: S-EPMC11260495 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature