By analyzing the stability data of wild-type MnP (wtMnP) that we have measured in the early stage, we found that wtMnP has good activity at room temperature lower than 37℃, but has poor activity in acidic, methanol or ethanol environments.
In order to make the molecular machines we manufactured better be put into practical use, we need to improve the adaptability of MnP to the complex environment in reality.
Therefore, we designed a semi-rational directed evolution scheme based on molecular dynamics simulation, deep learning and machine learning, followed by constructing and screening the MnP mutants library. Afterwards, we selected the best 10 mutants for heterologous expression and stability assay, with the hope to obtain mutants with enhanced even excellent performance.