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Register a new userFidelity of bacterial translation initiation: a stochastic kinetic model
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Added by
Debashish Chowdhury
Publication date
2018
fields
Physics
and research's language is
English
Authors
Dipanwita Ghanti
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No Arabic abstract
During the initiation stage of protein synthesis, a ribosomal initiation complex (IC) is assembled on a messenger RNA (mRNA) template. In bacteria, the speed and accuracy of this assembly process are regulated by the complementary activities of three essential initiation factors (IFs). Selection of an authentic N-formylmethionyl-transfer RNA (fMet-tRNAtextsuperscript{fMet}) and the canonical, triplet-nucleotide mRNA start codon are crucial events during assembly of a canonical, ribosomal 70S IC. Mis-initiation due to the aberrant selection of an elongator tRNA or a non-canonical start codon are rare events that result in the assembly of a pseudo 70S IC or a non-canonical 70S IC, respectively. Here, we have developed a theoretical model for the stochastic kinetics of canonical-, pseudo-, and non-canonical 70S IC assembly that includes all of the major steps of the IC assembly process that have been observed and characterized in ensemble kinetic-, single-molecule kinetic-, and structural studies of the fidelity of translation initiation. Specifically, we use the rates of the individual steps in the IC assembly process and the formalism of first-passage times to derive exact analytical expressions for the probability distributions for the assembly of canonical-, pseudo- and non-canonical 70S ICs. In order to illustrate the power of this analytical approach, we compare the theoretically predicted first-passage time distributions with the corresponding computer simulation data. We also compare the mean times required for completion of these assemblies with experimental estimates. In addition to generating new, testable hypotheses, our theoretical model can also be easily extended as new experimental 70S IC assembly data become available, thereby providing a versatile tool for interpreting these data and developing advanced models of the mechanism and regulation of translation initiation.
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