Estimating peptide-major histocompatibility complex (pMHC) binding using structural computational methods has an impact on understanding overall immune function triggering adaptive immune responses in MHC class II molecules. We developed a strategy for optimizing pMHC structure interacting with water molecules and for calculating the binding energy of receptor + ligand systems, such as HLA-DR1 + HA, HLA-DR1 + CLIP, HLA-DR2 + MBP, and HLA-DR3 + CLIP, as well as a monosubstitution panel. Taking pMHC's structural properties, we assumed that ΔH ≫ -TΔS would generate a linear model for estimating relative free energy change, using three semiempirical quantum methods (PM6, PM7, and FMO-SCC-DFTB3) along with the implicit solvent models, and considering proteins in neutral and charged states. Likewise, we confirmed our approach's effectiveness in calculating binding energies having high correlation with experimental data and low root-mean-square error (<2 kcal/mol). All in all, our pipeline differentiates weak from strong peptide binders as a reliable method for studying pMHC interactions.