The invention belongs to the technical field of biological information, and relates to an acetylcholin
esterase inhibitor prediction method based on Stacking
ensemble learning and molecular
feature fusion, which comprises the steps of data collection and preparation,
data annotation and optimization,
feature extraction and analysis, construction of a Stacking model, result
verification and feedback and construction of a prediction platform. The molecular fingerprints and the property descriptors are used as features, and an acetylcholin
esterase inhibitor classifier is successfully constructed by adopting a Stacking
algorithm. According to the method, the problems that the efficiency of finding the acetylcholin
esterase inhibitor by a traditional experimental method is low, and a common
quantitative structure-function relationship method is high in complexity and poor in generalization ability can be solved, the new
drug finding speed is increased, experimental candidates are accurately positioned, and resource waste is reduced.