酶催化二氧化碳捕获与还原转化的量子-经典力学研究

项目旨在结合神经网络和机器学习方法，完善并发展低标度量子-经典力学自由能计算平台。开展碳酸酐酶和固氮酶分别催化二氧化碳捕获与还原转化过程的QM/MM计算与动力学模拟研究，探明两类酶催化二氧化碳转化过程的微观机理、电子转移与质子转移机制，以及调控酶催化活性与选择性的关键因素。探索碳酸酐酶和固氮酶复合体系的结构及其协同催化二氧化碳转化的分子机制，为单酶和多酶催化CO2转化体系的发展提供理论依据。

The project aims to improve and develop a low-cost QM/MM computational platform to predict the change of free energy of the enzymatic reaction, based on the neural network and machine learning methods. The enzymatic conversion of CO2 by the carbonic anhydrase and remodeled nitrogenase will be explored theoretically. On the basis of extensive QM/MM calculations and MD simulations, we try to elucidate the plausible mechanisms for electron and proton transfers involved in the enzymatic process and the regulating factors for the reactivity and selectivity, and provide a theoretical basis for the development of monomeric enzyme and multienzyme systems for the catalytic conversion of CO2.