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Stochastic thermodynamics of biochemical replication

CORDIS · observation · Publication date unknown

elation (TUR) or the thermodynamic speed limit (TSL). I then investigate how the topology and reaction rates of the KPR network can be optimized with respect to error rate and dissipation by means of machine learning, to deduce how close biological systems operate to these bounds. Subsequently, I will extend the results to the conformational proofreading (CPR) process, where an energy handicap is added to the free energy to increase binding specificity at the expense of binding affinity. The CPR is a proofreading scheme that does not consume energy by burning ATP/GTP, so the entropy production has its origin in the conformational change. Finally, I test the robustness of the aforementioned KPR and CPR networks. In realistic systems, the kinetic rates can fluctuate as a consequence of e.g., temperature or chemical density variations, which can possibly destabilize the network and lead to more errors in the replication process. This will be done by considering the networks as input-output systems that can be studied by control theory. This provides fundamental bounds such as Bode's se

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award

status

SIGNED

region

EU

value

230774.4

unit

EUR