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Reversing the relative time courses of the peptide bond reaction with oligopeptides of different lengths and charged amino acid distributions in the ribosome exit tunnel

Authors :
Marc Joiret
Frederic Kerff
Francesca Rapino
Pierre Close
Liesbet Geris
Source :
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2453-2464 (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

The kinetics of the protein elongation cycle by the ribosome depends on intertwined factors. One of these factors is the electrostatic interaction of the nascent protein with the ribosome exit tunnel. In this computational biology theoretical study, we focus on the rate of the peptide bond formation and its dependence on the ribosome exit tunnel electrostatic potential profile. We quantitatively predict how oligopeptides of variable lengths can affect the peptide bond formation rate. We applied the Michaelis-Menten model as previously extended to incorporate the mechano-biochemical effects of forces on the rate of reaction at the catalytic site of the ribosome. For a given pair of carboxy-terminal amino acid substrate at the P- and an aminoacyl-tRNA at the A-sites, the relative time courses of the peptide bond formation reaction can be reversed depending on the oligopeptide sequence embedded in the tunnel and their variable lengths from the P-site. The reversal is predicted to occur from a shift in positions of charged amino acids upstream in the oligopeptidyl-tRNA at the P-site. The position shift must be adjusted by clever design of the oligopeptide probes using the electrostatic potential profile along the exit tunnel axial path. These predicted quantitative results bring strong evidence of the importance and relative contribution of the electrostatic interaction of the ribosome exit tunnel with the nascent peptide chain during elongation.

Subjects

Subjects :
Biotechnology
TP248.13-248.65

Details

Language :
English
ISSN :
20010370
Volume :
23
Issue :
2453-2464
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.724f2b0efb594b5aa4ac512751a11362
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2024.05.045