Anna Lewicka

The paper describes a Kaggle competition for RNA 3D structure prediction, showing that template-based methods can outperform deep learning approaches.

Structure providers for 18 CASP16 nucleic acid targets find blind predictions capture secondary structure but miss non-canonical interactions, backbone kinks, ligand sites, and intermolecular interfaces.

This study identifies coumarin derivatives that selectively bind RNA single G bulges, revealing key structural features and using computational and experimental methods to guide rational ligand design.

The paper shows that specific RNA sequences can be nonenzymatically aminoacylated and ligated to form amino acid-bridged stem-loop RNAs, with structural and functional similarities to modern tRNA.