Chloé Quignot

This paper evaluates AlphaFold3's ability to predict protein-RNA interaction specificity using omics data and structural information, highlighting both its potential and limitations.

The paper analyzes conservation patterns in protein-RNA interface contacts using structural interologs, finding high conservation of distance-based and apolar contacts but versatility in hydrogen bonds and salt bridges.

DENSE is an automated pipeline for identifying de novo emerged genes, offering flexible strategies and a database of predictions across seven model organisms.

The paper improves protein-protein interface scoring by integrating atomic-level evolutionary information, achieving higher success rates in docking discrimination.