Comparative Bioinformatics Analysis of Physicochemical Properties of the Mouse Protein Epitopes

Major histocompatibility complex class I (MHC I) plays a crucial role in immune functions. This complex typically binds short fragments of protein chains, 8-9 amino acid residues in length, referred to as epitopes. In this study, we investigated differences between the peptides that bind to this complex (dataset N₁) and those that do not (dataset N₀). To compare the datasets N₁ and N₀, Z-score analysis using the Z-score function was applied to identify statistically significant differences in physicochemical properties under study: aliphatic index (α_i), charge (Z_i), hydrophobicity (H_i), isoelectric point (pI_i), molecular weight (M_i), and instability index (II_i). All properties except for the instability index depend solely on amino acid composition of the peptides and not on the sequence-specific features. For the evaluated physicochemical properties, the Z-score values indicated no significant differences between the datasets N₁ and N₀. Maximum Z-score values were 0.30 for the aliphatic index and 0.29 for hydrophobicity. The most robust and reliable separation between the datasets N₁ and N₀ was achieved using the r-value method, yielding classification accuracy of approximately 70% and Z-score of 0.63. This result is close to the separation accuracy of 75% obtained using the MHCflurry program. Analysis of amino acid distributions in the datasets N₁ and N₀ showed that the residues such as tyrosine, phenylalanine, isoleucine, leucine, and valine occur more frequently than cysteine, tryptophan, arginine, and lysine in the octa- and nonapeptide epitopes that noncovalently bind to MHC class I. Using bioinformatics analysis and artificial intelligence approaches, we demonstrated the extent to which binding and non-binding peptides can be discriminated based solely on amino acid composition.