Non-equilibrium, stochastic model for tRNA binding time statistics

TL;DR

This paper presents a detailed stochastic model of tRNA binding during protein translation, revealing how non-equilibrium dynamics and fluctuations influence binding time distributions.

Contribution

It introduces a microscopic, non-equilibrium stochastic model that incorporates tRNA recharging, spatial inhomogeneity, and fluctuations, advancing understanding of translation kinetics.

Findings

Derived the distribution of tRNA binding times showing deviation from exponential behavior.

Identified the impact of charged and uncharged tRNA fluctuations on binding times.

Highlighted the importance of non-equilibrium effects in translation dynamics.

Abstract

Protein translation is one of the most important processes in cell life but, despite being well understood biochemically, the implications of its intrinsic stochastic nature have not been fully elucidated. In this paper we develop a microscopic and stochastic model which describes a crucial step in protein translation, namely the binding of the tRNA to the ribosome. Our model explicitly takes into consideration tRNA recharging dynamics, spatial inhomogeneity and stochastic fluctuations in the number of charged tRNAs around the ribosome. By analyzing this non-equilibrium system we are able to derive the statistical distribution of the times needed by the tRNAs to bind to the ribosome, and to show that it deviates from an exponential due to the coupling between the fluctuations of charged and uncharged populations of tRNA.