In-silico characterization of deleterious non-synonymous SNPs in the human S1PR1 gene reveals structural instability...

S1PR1 is a G protein-coupled receptor that plays a key role in regulating lymphocyte trafficking, immune response, cardiovascular system function, cell proliferation and survival, tumor angiogenesis, and metastasis. It is also recognized as a pharmacotherapeutic target for the treatment of autoimmune diseases like relapsing multiple sclerosis and ulcerative colitis. This study aimed to identify deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the S1PR1 gene that may impact its functional properties and pharmacotherapeutic responses though in-silico approaches. A total of 3,259 SNPs were identified in the human S1PR1 gene, with 6.51% being non-synonymous (nsSNPs). Functional predictions from eight computational tools prioritized 25 deleterious variants. Further structural and evolutionary evaluation highlighted R120P, F125S, C184Y, Y198C, and L275P as the most damaging nsSNPs. These mutations were found to cluster within the seven-transmembrane (7-TM) domain (residues 46-322), directly affecting receptor stability and signaling. Structural modeling revealed disrupted hydrogen bonds, void formations, and loss of critical disulfide bonding (C184Y), severely compromising folding. Conservation analysis confirmed R120P, F125S, and C184Y as highly conserved (score 9), underscoring their functional importance. Molecular docking and dynamics simulations showed that R120P and F125S weaken binding affinity for natural agonist sphingosine-1-phosphate (S1P) and FTY720P, while antagonist W146 retained strong binding. Our analysis further revealed significant changes in binding interactions and protein-ligand complex stability under simulated physiological conditions. Collectively, these findings identified high-risk nsSNPs in S1PR1 gene with potential structural and functional implications, particularly in diseases involving impaired receptor signaling. These findings enhanced our understanding of how specific nsSNPs can influence disease susceptibility, drug response, and receptor function, paving the way for precision medicine approaches in treating autoimmune and inflammatory disorders.