Diverging co-translational protein complex assembly pathways are governed by interface energy distribution

Johannes Venezian, Hagit Bar-Yosef, Hila Ben-Arie Zilberman, Noam Cohen, Oded Kleifeld, Juan Fernandez-Recio, Fabian Glaser and Ayala Shiber ()
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Johannes Venezian: Technion Israel institute of Technology
Hagit Bar-Yosef: Technion Israel institute of Technology
Hila Ben-Arie Zilberman: Technion Israel institute of Technology
Noam Cohen: Technion Israel institute of Technology
Oded Kleifeld: Technion Israel institute of Technology
Juan Fernandez-Recio: CSIC-Universidad de La Rioja-Gobierno de La Rioja
Fabian Glaser: Lorry I. Lokey Interdisciplinary Center for Life Sciences & Engineering
Ayala Shiber: Technion Israel institute of Technology

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract Protein-protein interactions are at the heart of all cellular processes, with the ribosome emerging as a platform, orchestrating the nascent-chain interplay dynamics. Here, to study the characteristics governing co-translational protein folding and complex assembly, we combine selective ribosome profiling, imaging, and N-terminomics with all-atoms molecular dynamics. Focusing on conserved N-terminal acetyltransferases (NATs), we uncover diverging co-translational assembly pathways, where highly homologous subunits serve opposite functions. We find that only a few residues serve as “hotspots,” initiating co-translational assembly interactions upon exposure at the ribosome exit tunnel. These hotspots are characterized by high binding energy, anchoring the entire interface assembly. Alpha-helices harboring hotspots are highly thermolabile, folding and unfolding during simulations, depending on their partner subunit to avoid misfolding. In vivo hotspot mutations disrupted co-translational complexation, leading to aggregation. Accordingly, conservation analysis reveals that missense NATs variants, causing neurodevelopmental and neurodegenerative diseases, disrupt putative hotspot clusters. Expanding our study to include phosphofructokinase, anthranilate synthase, and nucleoporin subcomplex, we employ AlphaFold-Multimer to model the complexes’ complete structures. Computing MD-derived interface energy profiles, we find similar trends. Here, we propose a model based on the distribution of interface energy as a strong predictor of co-translational assembly.

Date: 2024
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DOI: 10.1038/s41467-024-46881-w

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