The ribosome catalyzes peptide bond formation by providing high ionic strength

Abstract

We performed QM/MM simulations based on density functional theory (DFT) and the density-functional tight binding method (DFTB) to investigate the reaction mechanism of the peptide-bond formation in the ribosome in atomistic detail. We found the key role of the ribosome in the increased availability of mobile ions, the counter-ions to the negatively charged RNA. To form the peptide bond, a C–N bond between the two amino acids is formed, a C–O bond between one amino acid and tRNA is broken, and a hydrogen atom is transferred from the N to the O atom. We found the hydrogen transfer to occur in two mechanisms in a competing manner with similar activation energies: a direct transfer, and a proton-shuttle mechanism via a ribose-2′-OH group. For this system it was found to be vital to calculate the energy barrier in numerous snapshots taken from molecular dynamics simulations and average them. Advantages and disadvantages of an exponential average compared with a direct average between the snapshots are discussed. An energy decomposition of the QM/MM results shows that the catalytic function is caused by the electrostatic influence of the environment rather than by mere positioning of the reactants. Analysis of the electrostatic influence residue-by-residue showed the importance of (sodium) ions near the active site. The free energy of activation for the direct proton-transfer mechanism was calculated by umbrella sampling. It confirmed a moderate entropic contribution to the activation free energy found in experiment. Overall, this study increases our understanding of the catalytic mechanism of the ribosome and probably also other ribozymes.

Keywords:

• ribosome
• catalytic activity
• QM/MM
• ionic strength
• umbrella sampling

Acknowledgements

We acknowledge support from HECToR, and CSED of STFC for access to its IBM Blue Gene/P system. J.K. thanks the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart.