RNA-TorsionBERT: leveraging language models for RNA 3D torsion angles prediction.

ABSTRACT:

Motivation

Predicting the 3D structure of RNA is an ongoing challenge that has yet to be completely addressed despite continuous advancements. RNA 3D structures rely on distances between residues and base interactions but also backbone torsional angles. Knowing the torsional angles for each residue could help reconstruct its global folding, which is what we tackle in this work. This paper presents a novel approach for directly predicting RNA torsional angles from raw sequence data. Our method draws inspiration from the successful application of language models in various domains and adapts them to RNA.

Results

We have developed a language-based model, RNA-TorsionBERT, incorporating better sequential interactions for predicting RNA torsional and pseudo-torsional angles from t

SUBMITTER: Bernard C 

PROVIDER: S-EPMC11758789 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature