Application of Agent-Based Modelling to Simulate Ribosome Translation

Translation is a key process in the cell that encompasses the formation of proteins. However, how the translation mechanisms are affected by physiological changes is yet to be determined. Saccharomyces cerevisiae is one of the most used microorganisms to express recombinant proteins, showing great industrial/commercial value. Modelling the translation process in this yeast can thus bring forward novel insights into its mechanisms and how they are affected by changes in the environment. The present work introduces an agent-based model describing the elongation step of the translation process in the yeast. The simulated and theoretical elongation times were almost identical, with a standard deviation of 0.0018%, demonstrating the usefulness of the model to simulate this type of scenarios. Results also show a negative correlation between tRNA levels and estimated decoding times of codons, in accordance with biological knowledge. The model holds considerable potential to help unveil new ways of manipulation and thus increase the production of economically relevant yeast-derived products, namely biopharmaceuticals. Further development will address more complex scenarios, such as ribosome queuing or all the phases in the translation process.