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Updated: May 29, 2026

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling
Published on: October 7, 2021
Key intermolecular interactions in the E. coli 70S ribosome revealed by coarse-grained analysis
Zhiyong Zhang1, Karissa Y Sanbonmatsu, Gregory A Voth
1Department of Chemistry, James Franck Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, USA.
None:
The ribosome is a very large complex that consists of many RNA and protein molecules and plays a central role in protein biosynthesis in all organisms. Extensive interactions between different molecules are critical to ribosomal functional dynamics. In this work, intermolecular interactions in the Escherichia coli 70S ribosome are investigated by coarse-grained (CG) analysis. CG models are defined to preserve dynamic domains in RNAs and proteins and to capture functional motions in the ribosome, and then the CG sites are connected by harmonic springs, and spring constants are obtained by matching the computed fluctuations to those of an all-atom molecular dynamics (MD) simulation. Those spring constants indicate how strong the interactions are between the ribosomal components, and they are in good agreement with various experimental data. Nearly all the bridges between the small and large ribosomal subunits are indicated by CG interactions with large spring constants. The head of the small subunit is very mobile because it has minimal CG interactions with the rest of the subunit; however, a large number of small subunit proteins bind to maintain the internal structure of the head. The results show a clear connection between the intermolecular interactions and the structural and functional properties of the ribosome because of the reduced complexity in domain-based CG models. The present approach also provides a useful strategy to map interactions between molecules within large biomolecular complexes since it is not straightforward to investigate these by either atomistic MD simulations or residue-based elastic network models.
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