Has AlphaFold 3 reached its success for RNAs?

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.

Through an extensive benchmark over four different test sets, we discuss the performances and limitations of AlphaFold 3. We also compare its performances with ten existing state-of-the-art ab initio, template-based and deep-learning approaches