RESUMO
Tumor suppressor cylindromatosis protein (CYLD) regulates NF-κB and JNK signaling pathways by cleaving K63-linked poly-ubiquitin chain from its substrate molecules and thus preventing the progression of tumorigenesis and metastasis of the cancer cells. Mutations in CYLD can cause aberrant structure and abnormal functionality leading to tumor formation. In this study, we utilized several computational tools such as PANTHER, PROVEAN, PredictSNP, PolyPhen-2, PhD-SNP, PON-P2, and SIFT to find out deleterious nsSNPs. We also highlighted the damaging impact of those deleterious nsSNPs on the structure and function of the CYLD utilizing ConSurf, I-Mutant, SDM, Phyre2, HOPE, Swiss-PdbViewer, and Mutation 3D. We shortlisted 18 high-risk nsSNPs from a total of 446 nsSNPs recorded in the NCBI database. Based on the conservation profile, stability status, and structural impact analysis, we finalized 13 nsSNPs. Molecular docking analysis and molecular dynamic simulation concluded the study with the findings of two significant nsSNPs (R830K, H827R) which have a remarkable impact on binding affinity, RMSD, RMSF, radius of gyration, and hydrogen bond formation during CYLD-ubiquitin interaction. The principal component analysis compared native and two mutants R830K and H827R of CYLD that signify structural and energy profile fluctuations during molecular dynamic (MD) simulation. Finally, the protein-protein interaction network showed CYLD interacts with 20 proteins involved in several biological pathways that mutations can impair. Considering all these in silico analyses, our study recommended conducting large-scale association studies of nsSNPs of CYLD with cancer as well as designing precise medications against diseases associated with these polymorphisms.
RESUMO
Obesity is a chronic condition which is identified by the buildup of excess body fat caused by a combination of various factors, including genetic predisposition and lifestyle choices. rs1137101 (A > G) polymorphism in the CHR1 domain of LEPR protein linked to different diseases including obesity. Nevertheless, the connection between this polymorphism and the likelihood of developing obesity has not been determined definitively. Therefore, a meta-analysis was conducted to assess the relationship between rs1137101 and the risk of obesity. The meta-analysis included all studies meeting pre-defined criteria, found through searching databases up until February 2023. A combined odds ratio with a 95% confidence interval was estimated as overall and in continent subgroups for homozygous, heterozygous, recessive, dominant and allelic models using the fixed or the random-effects model. The meta-analysis identified 39 eligible studies with cases and controls (6099 cases/6711 controls) in 38 articles under different ethnic backgrounds. The results indicated a significant relationship between rs1137101 and the likelihood of developing obesity in each of the genetic models [the homozygous model (GG vs. AA: 95% Confidence Interval = 1.12-1.73, Odds Ratio = 1.39, P value = 0.003); the heterozygous model (AG vs. AA: 95% Confidence Interval = 1.07-1.42, Odds Ratio = 1.23, P value = 0.005); the dominant model (AG/GG vs AA: 95% Confidence Interval = 1.10-1.49, Odds Ratio = 1.28, P value = 0.001); the recessive model (GG vs AA/AG: 95% Confidence Interval = 1.02-1.45, Odds Ratio = 1.21, P value = 0.03); and the allelic model (G vs A; 95% Confidence Interval = 1.07-1.33, Odds Ratio = 1.19, P value = 0.002)] tested. Additionally, with an FDR <0.05, all genotypic models demonstrated statistical significance. The association remained significant among subgroups of Asian and Caucasian populations, although analysis in some genetic models did not show a significant association. Begg's and Egger's tests did not show publication biases. In sensitivity analysis, one particular study was found to have an impact on the Recessive model's significance, but other models remained unaffected. The current meta-analysis found significant indications supporting the association between rs1137101 and obesity. To avail a deeper understanding of this association, future research should include large-scale studies conducted in diverse ethnic populations.