Efficient identification of allergenic epitopes and analysis of the peptide recognition mechanism in tropomyosin of prawn (penaeus chinensis) through quantum chemistry computational framework.

This study aimed to identify allergenic epitopes of tropomyosin by characterizing peptide interactions with major histocompatibility complex class II (pMHC-II) using semiempirical quantum computation (Geometry, Frequency, Noncovalent, extended Tight Binding, GFN2-xTB), Molecular Mechanics Poisson Boltzmann surface area (MMPBSA) and GFN-FF, and verified their correlation with experimental allergenicity. The results clarified that nine species-conserved peptides were identified, six of which were validated as antigenic epitopes. Interactive interface within pMHC-II complexes identified critical residue pairs and structural motifs for antigen presentation mechanism. By capturing electronic and dispersion effects, GFN2-xTB performed better than MMPBSA and GFN-FF in charged-ligand system, exhibiting a Pearson correlation of -0.74 between ΔGbind and IgE inhibition. Furthermore, partial least squares regression using interactive isosurface areas in GFN2-xTB revealed a correlation between MHC-II' anchors and IgE binding (R2 = 0.77). Conclusively, molecular dynamics combined with GFN2-xTB can elucidate epitope peptides' distribution, specific anchors, and correlation between ΔGbind and IgE.