The invention provides an antibody-antigen molecular docking evaluating method based on artificial intelligence and a system, wherein the method comprises the steps of acquiring a plurality of antibody-antigen molecular docking samples; calculating an integrated value of each docking sample for representing an inter-sample difference condition; processing a plurality of abutting sample data and obtaining a score value of each abutting sample based on a convolutional neural network; calculating a loss value between two docking samples by means of a customized loss function according to the integrated value and the score value; calculating the loss average value of the plurality of docking samples according to the loss value between each two docking samples, and performing parameter updating on the convolutional neural network through an optimizing function according to the loss average value. According to the method, an excellent docking sample can be selected through comparing the differences of the input samples, thereby training the model which can directly determine a fact that the sample is good or bad, so that the sample better satisfies an actual experiment requirement for antibody-antigen molecular docking.
Antibody-antigen molecular docking evaluating method based on artificial intelligence and system