The invention discloses a prediction method, and particularly relates to a
protein DNA binding tendency prediction method based on a multi-
modal biomolecular model, which comprises the following steps: S1, inputting a
protein sequence; s2, predicting a three-dimensional structure; s3, secondary structure calculation is carried out; s4, calculating the
accessibility of the
solvent; s5, performing
protein function
annotation; s6, generating feature representation; step S7, sample representation; s8, obtaining a
training set; s9, generating all protein residue samples; step S10, constructing a protein map; step S11, building a graph neural network; step S12, adjusting through a convolutional layer; step S13, training and storing the model; and step S14, outputting a PWM matrix. The invention relates to a
protein DNA binding tendency prediction method based on a multi-
modal biomolecular model, which can reduce the calculation cost of the existing
protein DNA binding tendency prediction method and improve the recognition accuracy.