(171t) Computational Modeling of the E. coli Ribosome L12 Complex and Impacts on mRNA Translation Rate

Modeling of colloidal-scale dynamics in a computational model of E. coli cytoplasm demonstrated that colloidal-scale transport regulates the speedup of mRNA translation during faster growth. Our physically-resolved voxel models of cytoplasm biomolecules, with first-principles Brownian motion and chemical reactions extracted from experimental literature, revealed that physics dominate this speedup via “stoichiometric crowding”, a coupling between improved physical proximity and advantageous chemical combinatorics. This qualitative recovery of experimentally observed speedup still left a quantitative gap in predicting absolute translation rate; we more recently represented the patchy attractions of the ribosomal L12 subunits, markedly improving quantitative agreement with in vivo experiments and prediction of absolute translation rate. This “pre-loading” of translation molecules onto the ribosome created favorable concentration for more efficient translation reactions. Here we seek to further improve absolute prediction of translation rate via detailed ribosomal morphology. We model the ribosomal L10 N-terminus domain (NTD), ribosomal L12 stalk, hinges, and ribosomal L12 C-terminus domain (CTD) as a set of flexible arms endowed with the shape and charge determined from the Protein Data Base and experimental reports of L12 mobility. The arms permit a larger search volume for translation molecules to bind to ribosomes, which can impact translation rate. Using this model, we probe the effects of cell growth-rate-mediated cellular stoichiometry, diffusive fluctuations of the L12 subunit, and combinatoric sampling efficiency on translation rate.