Computational Assessment of nsSNPs Associated with FGFR2 Gene

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ID: 312601
2026
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Abstract
The fibroblast growth factor receptor 2 (FGFR2) controls cell proliferation, differentiation, angiogenesis, and wound healing. Single nucleotide polymorphisms (SNPs) of the FGFR2 gene are linked with Pfeiffer syndrome, Crouzon syndrome, and Jackson-Weiss syndrome. Missense mutations in FGFR2 have also been reported in breast, gastric, and lung cancer. Objective: This study aimed to systematically analyze missense SNPs (nsSNPs) in FGFR2 using an integrative computational pipeline to identify variants with the strongest predicted pathogenic impact. Methods: FGFR2 gene data and protein sequence were retrieved from the NCBI dbSNP [build 153 (March 2020)] and UniProt database [release 2020_02; UniProt ID: P21802]. A total of eleven bioinformatics tools—SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, PANTHER, PhD-SNP, PMut, I-Mutant3.0, ConSurf server, and Project HOPE—were used to examine the deleterious potential of nsSNPs. The interaction of FGFR2 with different genes was analyzed using GeneMANIA. Results: We investigated 28,027 total SNPs from dbSNP, of which 701 were coding variants: 294 synonymous and 407 non-synonymous. Among the latter, 393 were missense mutations, 7 frameshift mutations, and 7 nonsense mutations. Only missense nsSNPs were retained for further analysis. Stepwise filtering identified 90 consensus-deleterious variants (≥ 6/8 predictors), 54 extremely damaging variants (all 8 predictors), and 38 unstable variants (ΔΔG ≤ −0.5 kcal/mol). A final set of 24 highly conserved and damaging variants (ConSurf score ≥7) was prioritized. Conclusion: A total of 24 nsSNPs (L757S, G690R, P666S, R664W, D644N, Y616C, L572F, L550P, L550V, I547M, V514M, G502E, G502R, E489K, R450C, P286S, C278Y, G271R, P263L, P256S, D225E, S224P, E219G, and Y105C) were predicted to have the most damaging and disease-causing effects on FGFR2 protein function and structure. Thus, the early prediction of FGFR2 gene functions could aid in disease prognosis. The results of our study provide beneficial information for devising early diagnostic and therapeutic measures.
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Authors Anum Munir
Journal Journal of Computing & Biomedical Informatics
Year 2026
DOI
10.56979/1101/2026/1067
URL
https://jcbi.org/index.php/Main/article/view/1067
Keywords Keywords not found

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