Quantitative Deciphering of Mammalian Histamine Receptors through Mathematical Genomics

Histamine receptors (HRH1-HRH4) are G-protein coupled receptors (GPCRs) that mediate essential physiological functions, including neurotransmission, gastric acid secretion, immune regulation, and presynaptic autoregulation. Despite their importance, systematic comparative analyses across mammalian histamine receptor sequences remain scarce. In this study, we performed a comprehensive evaluation of HRH1-HRH4 across multiple mammalian species, integrating sequence homology, invariant residue mapping, amino acid substitutions, compositional frequencies, Shannon entropy, polystring distributions, intrinsic disorder profiling, and phylogenetic clustering. HRH2 and HRH1 were highly conserved among primates, HRH3 showed strong cohesion within rodents, while HRH4 exhibited pronounced divergence consistent with immune-related specialization. Invariant residues localized to transmembrane helices and activation motifs (D107, W428/Y431, NPxxY), underscoring strict evolutionary constraints on ligand binding, receptor stability, and G-protein coupling. Substitutions were confined to non-essential lipid-facing and loop regions, predominantly conservative in nature, enabling diversification without disrupting the GPCR fold. Amino acid frequency and entropy analyses revealed hydrophobic dominance with subtype-specific enrichment of polar residues, while disorder profiling identified HRH1 as the most dynamic and HRH2 as the most structurally constrained. Polystring analysis highlighted conserved motifs (WWW, PP) alongside subtype- and species-specific repeats, reflecting evolutionary strategies balancing receptor stability with adaptive flexibility. Phylogenetic clustering confirmed subtype-specific cohesion, with HRH3 and HRH4 forming compact clades, HRH1 showing moderate dispersion, and HRH2 forming the most isolated cluster. Collectively, these findings demonstrate that mammalian histamine receptor evolution is governed by conserved biophysical cores and selective variability, offering insights into structural conservation, functional diversification, and translational relevance for drug design and model selection.