Microscopic Atomic Binding Model and Simulation Results | Different free energy landscapes give different free energy barrier heights between the non-na-tive and native states. |
Microscopic Atomic Binding Model and Simulation Results | As we can see the large intrinsic specificity characterized by high ISR gives smaller free energy barrier and lower ISR gives higher barrier. |
Summary and Conclusion | This might be due to the increase of the free energy barrier for escaping the binding from the increase of the affinity. |
Z‘A j§;~9.5 9=°a’ o | We plot the free energy barrier height and the kinetic time for binding of these three cases as shown in Fig 10D. |
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations | Assuming two-state unfolding kinetics [39—42] we can estimate the characteristic time required to cross the unfolding free energy barrier (in fact it is the time spent in the native state waiting for sufficient thermal fluctuation to cross the barrier) as: |
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations | Where T137 is first-passage time from the folded to the unfolded state, AG# is the free energy barrier between the folded state and the transition state for unfolding (see Fig. |
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations | In order to see this we note that the mutational effect on protein stability AAG is related to the change in the unfolding free energy barrier AAG#, the difference between the WT barrier height and the mutant barrier height, shown in Fig. |