Protein synthesis by ribosomes: agent-based modeling of mRNA translation rates incorporating tRNA modification effects

Translational regulation through synonymous codon usage has been recently shown to play an important role in health and disease. Modified tRNAs are important actors involved in regulating protein expression levels by optimizing the decoding of differentially used codons, nevertheless their contribution in protein synthesis dynamics remain unclear. Agent Based Models such as the Totally Asymmetric Simple Exclusion Process (TASEP) models have been used to quantify the transcripts translation rates by ribosomes. Our work aims at extending ABM and TASEP modeling to accommodate for tRNA modifications effects. We implemented a computational stochastic model quantifying protein synthesis rates. The algorithm uses ribosome residence time per codon from transcripts codons sequences, relative transcripts abundance and tables of (modified or not) tRNA accommodation, peptide bond formation and translocation rates. Important features in the model include the elongation rate variation caused by charged amino-acids in the ribosomal exit tunnel, proline transpeptidation at the peptide transfer center and transcript secondary structure slow down effects. The model allows to compare relative protein expression levels as well as polysome profiling and RiboSeq profiles in different scenarios with a controllable pool of ribosomes and initiation rates. We intend to use our model to help understand how codon usage and tRNA modifications dynamically interact and impact on protein synthesis. The ultimate purpose of the work is to understand how the translational control through codon usage and tRNA tuning influence the proteome, local protein structure possibly linked to changes in functional specific activity, aggregation, ribophagy, autophagy or proteasomal degradation. The results of this work will possibly help the development of targeted therapies against cancers (melanoma and lung cancers).