In-silico analysis unravels the structural and functional consequences of non-synonymous SNPs in the human IL-10 gene

Abstract

Background Interleukin-10 (IL-10) is an anti-inflammatory cytokine that affects different immune cells. It is also associated with the stimulation of the T and B cells for the production of antibodies. Several genetic polymorphisms in the IL-10 gene have been reported to cause or aggravate certain diseases like inflammatory bowel disease, rheumatoid arthritis, systemic sclerosis, asthma, etc. However, the disease susceptibility and abnormal function of the mutated IL-10 variants remain obscure. Results In this study, we used seven bioinformatics tools (SIFT, PROVEAN, PMut, PANTHER, PolyPhen-2, PHD-SNP, and SNPs&GO) to predict the disease susceptible non-synonymous SNPs (nsSNPs) of IL-10. Nine nsSNPs of IL-10 were predicted to be potentially deleterious: R42G, R45Q, F48L, E72G, M95T, A98D, R125S, Y155C, and I168T. Except two, all of the putative deleterious mutations are found in the highly conserved region of IL-10 protein structure, thus affecting the protein's stability. The 3-D structure of mutant proteins was modeled by project HOPE, and the protein–protein interactions were assessed with STRING. The predicted nsSNPs: R42Q, R45Q, F48L, E72G, and I168T are situated in the binding site region of the IL-10R1 receptor. Disruption of binding affinity with its receptor leads to deregulation of the JAK-STAT pathway and results in enhanced inflammation that imbalance in cellular signaling. Finally, Kaplan–Meier Plotter analysis displayed that deregulation of IL-10 expression affects gastric and ovarian cancer patients' survival rate. Thus, IL-10 could be useful as a potential prognostic marker gene for some cancers. Conclusion This study has determined the deleterious nsSNPs of IL-10 that might contribute to the malfunction of IL-10 protein and ultimately lead to the IL-10 associated diseases.

Role of single nucleotide polymorphisms of the HSD3B1 gene (rs6203 and rs33937873) in the prediction of prostate cancer risk

“…SNPs can affect the binding interaction of RNA-protein by modification of secondary structure of RNA ( 52 , 53 ). Additionally, SNPs can affect both gene expression level of the specific protein or its binding with transcription factors ( 54 , 55 ). In all previously mentioned mechanisms, these can lead to modifications in either function or structure of the translated proteins (folding) and related metabolic pathways such as increased cell proliferation, protein dimerization and activation of a number of mediators ( 56 ).…”

An In silico Approach towards Finding the Cancer-Causing Mutations in Human MET Gene

“…Rate of Different Cancer Patients. The Kaplan-Meier Plot (https://kmplot.com/analysis/) [51] is an online tool that estimates the time of death, and this event may have a substantial inference while using these analytics for clinical decisions, medical policies, and also resource provision [52]. This plot is able to perform proportional survival analysis utilizing the data produced by genomic, transcriptomic, or proteomic investigations [51].…”

“…Proteins. Protein-protein interactions were investigated to interpret all functional interactions among cellular proteins [52]. The STRING database prediction showed that MET protein has interaction with other 10 proteins (Figure 10, Table 4) whose functions also might be interrupted by these mutations.…”