RNA Tertiary Structure Prediction and Analysis Using NuFold and the NuFold Database

Accurate prediction of RNA tertiary structure is critical for understanding the functions of diverse non-coding RNAs, yet experimental structure determination remains challenging and resource intensive. Inspired by advances in deep learning for protein structure prediction, NuFold was developed as an end-to-end framework that predicts all-atom RNA tertiary structures directly from sequence. NuFold integrates evolutionary information from multiple sequence alignments and predicted secondary structure features to construct 3D coordinates of RNA. To maximize accessibility, NuFold is available as open-source software, supported by a Google Colab notebook for browser-based prediction and NuFold DB, a large-scale repository of precomputed RNA structures. This chapter provides a practical guide to using these resources, enabling researchers to generate and interpret RNA structural models without extensive computational resources, and thereby facilitating structural and functional studies in RNA biology.