Mathematical Sequence Analyses of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR): Cross-Species Skeletal Frameworks in Cystic Fibrosis

Rare diseases, though individually uncommon, collectively represent a major global health challenge, affecting millions worldwide and increasingly recognized in India as a significant contributor to pediatric and adult morbidity. Cystic fibrosis (CF), a multisystem autosomal recessive disorder caused by pathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator (\textit{CFTR}) gene, exemplifies this burden, with delayed diagnosis and diverse mutational spectra complicating clinical management in South Asian populations. To advance rare disease genomics, quantitative analysis of CFTR sequences across multiple species is essential, as evolutionary conservation highlights residues and motifs critical for channel function, while divergence reveals lineage-specific adaptations relevant to disease mechanisms. In the present study, we performed integrative analyses encompassing amino acid composition, sequence homology, frequency-dominant residue patterns, hydropathy-based n‑gram distributions, hydropathy profile continuity, and intrinsic disorder architectures across various CFTR sequences from multiple species. The quantitative signatures derived from amino acid composition, sequence homology, hydropathy-based n‑grams, hydropathy profiles, and intrinsic disorder analyses carry significant translational impact, as they provide a unified framework for identifying conserved motifs, resolving disorder-prone domains, and guiding the precise mapping of pathogenic mutations and their functional consequences. Collectively, our findings demonstrate how cross-species quantitative protein analysis of CFTR bridges evolutionary biology with clinical investigation, providing translational insights that strengthen rare disease research and therapeutic development in cystic fibrosis.