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

Huijuan Feng, Xiang-Jun Lu, Suvrajit Maji, Linxi Liu, Dmytro Ustianenko, Noam D. Rudnick and Chaolin Zhang ()
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Huijuan Feng: School of Life Sciences, Fudan University
Xiang-Jun Lu: Columbia University
Suvrajit Maji: Columbia University
Linxi Liu: Columbia University
Dmytro Ustianenko: Columbia University
Noam D. Rudnick: Columbia University
Chaolin Zhang: Columbia University

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract UV-crosslinking of protein and RNA in direct contacts has been widely used to study protein-RNA complexes while our understanding of the photo-crosslinking mechanisms remains poor. This knowledge gap is due to the challenge of precisely mapping the crosslink sites in protein and RNA simultaneously in their native sequence and structural contexts. Here we systematically analyze protein-RNA interactions and photo-crosslinking by bridging crosslinked nucleotides and amino acids mapped using different assays with protein-RNA complex structures. We developed a computational method PxR3D-map which reliably predicts crosslink sites using structural information characterizing protein-RNA interaction interfaces. Analysis of the informative features revealed 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 RNA-binding domains. Our work suggests protein-RNA photo-crosslinking is highly selective in the cellular environment, which can guide data interpretation and further technology development for UV-crosslinking-based assays.

Date: 2024
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DOI: 10.1038/s41467-024-46429-y

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