The invention relates to the field of
artificial intelligence, and particularly discloses an
antibody variable region structure prediction method based on structure prior evaluation, which comprises the following steps: S1, screening a high-resolution and high-integrity compound containing a complete
antigen and an
antibody H / L chain from PDB, and extracting
atomic coordinates after
processing; s2, calculating geometrical characteristics of a molecular structure and relative spherical polar coordinates of adjacent residues; s3, calculating a structure quality evaluation
score according to physical prior and a
dihedral angle-atomic spacing mapping formula; s4, screening training data according to scores, and removing low-
quality data; s5, constructing an
antigen-
antibody attribute isomeric graph and initializing a compound graph; s6, embedding related data as enhanced features when the model is initialized; s7, loading an RA-EGN
encoder to output a CDR sequence and a 3D coordinate, and splicing a
complete antibody structure; and S8, introducing a structure prior
loss function fine tuning model, and performing multi-index screening on an optimal result. According to the invention, the problems of low prediction precision and insufficient structure prior utilization of the existing antibody CDR region are solved, and the prediction accuracy of the
antibody variable region is improved.