bioRxivSystems BiologyPreprint
Anticodon nucleotide modifications affect translational tuning by the ribosomal CAR surface
Mitsu RavaliD, Yancheng ZhouiD, Mia WichmaniD, Miki LynchiD, Daniel Krizanc, Kelly M. ThayeriD, Michael P. WeiriD
Abstract
Nucleotide modifications of the tRNA anticodon can affect protein translation fidelity and speed. Chemical modifications of the anticodon nucleotide 34 are regulated under cellular stress and associated with several translational defects and pathologies. Here, we investigate how these modifications influence A-site codon recognition interactions and their coupling to the CAR site that lies adjacent to nucleotide 34 in the ribosome. The conserved three-residue CAR interface hydrogen bonds in a sequence-dependent manner to the mRNA +1 codon 3-adjacent to the A-site codon and is implicated in tuning translational speed. The C of CAR is pi-stacked with the nucleotide 34 of the A site tRNA anticodon. The A site and the CAR site influence each others hydrogen bonding and stacking interactions, and these codon-adjacency effects potentially provide a layer of regulation affecting translational fidelity and kinetics. Through molecular dynamics simulations of a subsystem of a translocating ribosome IRES-model, we observed that nucleotide 34 modifications affect the hydrogen bonding and stacking interactions at the A site and CAR site as well as CARs influence on the A site interactions. Integrating these results with gene sequence and ribosome profiling analyses, we propose that nucleotide 34 modifications help modulate CARs sequence-dependent tuning of translation in response to cellular stress. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/740946v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1971867org.highwire.dtl.DTLVardef@c31822org.highwire.dtl.DTLVardef@6597f6org.highwire.dtl.DTLVardef@1dbd747_HPS_FORMAT_FIGEXP M_FIG C_FIG
- assay: proteomics
- assay: metagenomics
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: protein structure prediction
- approach: statistical model
- approach: simulation
- Citations
- 0
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