Structure-based prediction and characterization of photo-crosslinking in native protein-RNA complexes

Abstract

UV-crosslinking of protein and RNA in direct contacts has been widely used to study protein-RNA complexes despite our poor understanding on the mechanisms of photo-crosslinking. This knowledge gap is due to the challenge to precisely map the crosslink sites in protein and RNA simultaneously in their native sequence and structural contexts. Here we developed PxR3D-map, a computational method to analyze protein-RNA interactions and photo-crosslinking by bridging crosslinked nucleotides and amino acids mapped using different assays with protein-RNA complex structures. PxR3D-map reliably predicts crosslink sites using structural information characterizing protein-RNA interaction interfaces. We found that photo-crosslinking is facilitated by base stacking with not only aromatic residues, but also dipeptide bonds that involve glycine, and distinct mechanisms are utilized by different types of RNA-binding domains. Our work suggests protein-RNA photocrosslinking is highly selective in the cellular environment, which can guide interpretation of data generated by UV-crosslinking-based assays and further technology development.