Predicting the 3D structure of RNA is a significant challenge despite ongoing advancements in the field.
Although AlphaFold has successfully addressed this problem for proteins, RNA structure prediction raises difficulties due to fundamental differences between proteins and RNAs, which hinder direct adaptation.
The latest release of AlphaFold, AlphaFold 3, has broadened its scope to include multiple different molecules like DNA, ligands and RNA.
In this article, we provide a comprehensive analysis of the performances of AlphaFold 3 in the prediction of RNA 3D structures.
Through an extensive benchmark over five different test sets, we discuss the performances and limitations of AlphaFold 3.