Protein synthesis is of paramount importance to every living cell. The major challenge in molecular biology is to understand how information that is encoded in an mRNA transcript affects the rate of mRNA translation and therefore the overall protein production (1). Computational models of mRNA translation that aim to address this challenge have a long history dating as back to 1960s (2,3). So far these models had very limited power in predicting determinants of translation efficiency, owning to the fact that ribosome dynamics operates out of equilibrium and is therefore beyond the realm of equilibrium statistical physics. I present here a novel mathematical method for solving a standard biophysical model of translation. The solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, together with the value of the initiation rate, are the main determinants of protein production rate. I also discuss potential experiments for testing these predictions.

(1) Gingold H, Pilpel Y. Determinants of translation efficiency and accuracy. Molecular Systems Biology. 2011;7: 481. Available from: doi:10.1038/msb.2011.14. (2) MacDonald CT, Gibbs JH, Pipkin AC. Kinetics of biopolymerization on nucleic acid templates. Biopolymers. 1968;6: 1-25. Available from: doi:10.1002/bip.1968.360060102. (3) Zur H, Tuller T. Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution. Nucleic Acids Research. 2016;44(19): 9031-9049. Availabe from doi:10.1093/nar/gkw764.

Financing: The Leverhulme Trust