The present invention relates to a method for intelligently constructing a
list of preferred 5-hydroxytryptamine
reuptake inhibitors. The method comprises the following steps: constructing a functional
receptor protein of a 5-hydroxytryptamine
reuptake inhibitor by a homology modeling method, screening its key
protein of interference with
human health based on a harmful outcome pathway method, and calculating the
binding energy between it and the
receptor protein. The method further calculates the comprehensive effect value as the dependent variable by using an information weighting method, screening the main features of the target as the independent variable based on a variance filtering coupled Pearson
correlation coefficient method, realizing the establishment of a
data set, and
coupling a GRU neural network with a 1D-CNN neural network to realize the intelligent construction of a
list of preferred 5-hydroxytryptamine
reuptake inhibitors. The present invention aims to overcome the inability of current traditional methods to comprehensively evaluate the comprehensive selection effect of the functionality of 5-hydroxytryptamine reuptake inhibitors and interference with
human health, and to realize the intelligent construction of a
list of preferred 5-hydroxytryptamine reuptake inhibitors with high priority by establishing a
deep learning model.