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Communication Dans Un Congrès Année : 2022

From QM to coarse-grain, lessons from multiscale-modelling of redox enzymes

Résumé

The modeling of biological molecules requires to build on available structural information to obtain a clear understanding of the activity of these complex systems. Computational prediction of reactivity requires accurate physics-based models and suitable sampling. This task is particularly challenging for proteins due to their large size, making high-accuracy models especially costly from a computational point of view. This talk will present various strategies for modeling redox enzymes that are developed in french research groups, ranging from QM/MM approaches to coarse-grain models. In particular, I will address issues related to the immobilization of redox enzymes on the electrode surfaces, as the design of efficient devices comprising enzyme/solid interfaces requires to understand this interface on the molecular level. In this perspective, modeling can help us grasp details regarding several phenomena, such as the adsorbed enzyme orientation, the stability of the adsorption, and its impact on the catalytic activity.
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Dates et versions

hal-03790569 , version 1 (03-10-2022)

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  • HAL Id : hal-03790569 , version 1

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Sophie Sacquin-Mora. From QM to coarse-grain, lessons from multiscale-modelling of redox enzymes. XVIIth GFB (Groupe Français de Bioélectrochimie ) Conference, Sep 2022, Saint Dié-des-Vosges, France. ⟨hal-03790569⟩
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