Dynamics of Protein Synthesis Initiation

Abstract

In this thesis I investigate the underlying physical mechanisms by which cells optimize their rates of protein synthesis and thus their growth and function, targeting specifically the role of relative tRNA availabilities in limiting the rate of amino acid incorporation during translation. Although extensive literature focuses on maximizing the amino acid incorporation rate, the physical importance of additionally maximizing the entropy of a system remains unexplored. To shed light on this, I develop a maximum entropy model that predicts the distribution of likely sets of tRNA abundances required to produce the essential proteins of a given cell type for an initial set of codon frequencies. Further analytical work reveals, among other critical implications, the necessity of a tradeoff between entropy and maximization of the protein synthesis rate, and defines the minimum information required to achieve a given mean synthesis rate.

With the theoretical framework established, I then utilize numerical methods and Monte Carlo simulations to characterize and manipulate the selectivity of the solution space for tRNA abundance sets of the model system \textit{E. coli} under different experimental settings, thereby demonstrating the feasibility of achieving the predicted minimum incorporation time. At the localization limit, I also show that optimal tRNA abundance solutions involve largely mid-range concentration levels but are distinctly nonuniform, with individual tRNAs varying by the importance of the corresponding cognate codon in the production of essential proteins. The model accurately predicts and fine-tunes a quantitative description of tRNA abundance optimization, and also provides, from appropriate experimental data, a direct diagnostic on the priorities of natural cell states when optimizing along the spectrum of the entropy-synthesis rate tradeoff.