MHCBI: a pipeline for calculating peptide-MHC binding energy using semi-empirical quantum mechanical methods with explicit/implicit solvent models.

Experimentally estimating peptide-major histocompatibility complex (pMHC) binding affinity has been quite challenging due to the many receptors and the many potential ligands implicated in it. We have thus proposed a straightforward computational methodology considering the different mechanisms involved in pMHC binding to facilitate studying such receptor-ligand interactions. We have developed a pipeline using semi-empirical quantum mechanical methods for calculating pMHC class I and II molecules' binding energy (BE). This pipeline can systematize the methodology for calculating pMHC system BE, enabling the rational design of T-cell epitopes to be used as pharmaceuticals and vaccines.

Assessing Peptide Binding to MHC II: An Accurate Semiempirical Quantum Mechanics Based Proposal.

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.