The invention belongs to the field of computer-aided
drug design, and discloses a
metal binding group extraction method based on chemical
informatics analysis and modeling. The method comprises the following steps: constructing a
metal binding compound
data set; training and optimizing a
metal combined compound prediction model by using a
decision tree-based model and a graph neural network
algorithm; using an SHAP interpretable method to analyze a relationship between the key features and a prediction result, and deriving a structure fragment with potential
metal binding capacity; according to the attention
score of the Attentive FP model, an atomic weight
heat map of molecules in the
test set is drawn, and key
metal binding fragments are determined; molecules in the
training set are fragmented, and representative substructures are extracted; a
metal binding fragment
chemistry library is compiled. According to the method, the problem that metal binding group extraction is limited to a
compound structure data set is solved, efficient extraction of any metal
ion binding group is realized, and discovery and research of metalloenzyme-related drugs are accelerated.