Stochastic Simulation to Visualize Gene Expression and Error Correction in Living Cells

Abstract

Stochastic simulation can make the molecular processes of cellular control more vivid than the traditional differential-equation approach by generating typical system histories instead of just statistical measures such as the mean and variance of a population. Simple simulations are now easy for students to construct from scratch, that is, without recourse to black-box packages. In some cases, their results can also be compared directly to single-molecule experimental data. After introducing the stochastic simulation algorithm, this article gives two case studies, involving gene expression and error correction, respectively. Code samples and resulting animations showing results are given in the online supplement. arXiv:1809.05619v1 [q-bio.SC]

Allostery and Kinetic Proofreading

“…In the presentation of the piston model, we focused on the thermodynamic consistency of the framework for managing the energy dissipation and did not consider strategies for improving the performance of the mechanism. One such possibility that can be considered in future work is to use a more elaborate design for the ratchet and pawl engine with alternating activation barriers for pawl hopping, which would allow the use of different rates of piston compression and expansion, analogous to how hydrolysis and condensation reactions generally occur with different rates in biological proofreading. , Another avenue would be to consider alternative ways of allocating the mechanical energy dissipation across the different ratchet transition steps, similar to how optimization schemes for allocating the free energy of ATP hydrolysis were studied for molecular machine cycles . Incorporating these additional features would allow us to probe the performance limits of the piston model and compare them with the fundamental limits set by thermodynamics …”