Comprehensive analysis of the deleterious nonsynonymous, non-coding SNPs and cancer variants of human aldo-keto reductase type 1 (AKR1C1) protein and their probable association with disease risk and progression: a computational study.

Aldo-keto reductase family 1 member C1 (AKR1C1) is a key enzyme involved in steroid hormone and xenobiotic metabolism and has been implicated in hormone-dependent cancers, chemoresistance, and inflammatory disorders. Genetic variation in AKR1C1 may influence enzyme structure and regulatory properties. In this study, we conducted a comprehensive in silico analysis to identify and characterize potentially deleterious nonsynonymous, non-coding, and cancer-associated single nucleotide polymorphisms (SNPs) in the human AKR1C1 gene. Missense, 3'-UTR, 5'-UTR, and intronic variants were systematically screened using multiple computational tools to evaluate their predicted functional, structural, and regulatory effects, incorporating residue conservation, domain mapping, post-translational modification sites, protein stability predictions, mutation clustering, and secondary and three-dimensional structural analyses. Among 301 missense variants analyzed, G20R and G62R were consistently prioritized as the most deleterious based on concordant predictions from 12 tools. Structural modeling suggested destabilization near the catalytic region, while conservation analysis indicated potential disruption of functionally important residues. Molecular dynamics simulations (200 ns) revealed minimal differences in overall structural deviation, flexibility, compactness, and solvent accessibility between the mutant and wild-type proteins, suggesting localized structural perturbations rather than widespread conformational instability. Analysis of non-coding variants identified several SNPs, including rs1163624611, rs1169939032, and rs1329563998, with predicted regulatory effects, and five 3'-UTR SNPs with potential to alter miRNA binding. From cBioPortal, 57 cancer-associated variants were retrieved, of which 43 unique missense SNPs remained after removing duplicates and synonymous or noncoding entries. Among these, 12 variants were classified as highly deleterious, including three predicted to affect post-translational modification sites. All were classified as passenger mutations, with Y55C and Y110H showing the strongest predicted structural impact. Overall, this comprehensive computational analysis highlights previously uncharacterized deleterious coding and regulatory variants of AKR1C1 with potential relevance to disease susceptibility and cancer progression. These findings provide a valuable framework for future experimental validation and risk assessment studies involving AKR1C1.