Evaluating Functional and Structural Consequences of the most Deleterious Single Nucleotide Polymorphisms of Human C-X-C Motif Chemokine 10 (CXCL10) Using in silico Analyses

Document Type : Research Article

Authors

1 Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran

2 Biotechnology Research Institute, Shahrekord University, Shahrekord, Iran

Abstract

Single Nucleotide Polymorphisms, especially non-synonymous single-nucleotide polymorphisms (nsSNPs), which are the cause of various diseases, are a major issue in genetics. NsSNPs in protein-coding genes can cause functional and structural variations in the altered protein. The human CXCL10 gene, localized on chromosome 4q21, is a pro-inflammatory cytokine and plays a role in diverse and critical biological mechanisms. Despite its significance, there is not any document about the impact of variations mapped to this protein. Accordingly, we gathered data about SNPs on the CXCL10 protein and examined the diverse effects of deleterious ones on the function and structure of the protein using various web-based tools. Our analyses indicated that 9 most deleterious nsSNPs (identified by SIFT, PROVEAN, PolyPhen-2, SNPs&GO, PhD-SNP, SNAP2, and PMut) in the conserved region of the CXCL10 affect the molecular function and stability of the protein. By utilizing RMSD values, we concluded that these substitutions in the native structure cause several changes in the protein, including in the N-terminal end, which is vital for binding to the receptor, and finally results in altered regulation, expression, function, and consequently leads to different diseases. Furthermore, some SNPs on the 3′ UTR site showed pattern alterations in the upstream open reading frames (uORFs) and BRD-BOX; moreover, SNPs in this area result in significant changes in miRNA binding sites consequently. Finally, by some analyses, we identified that the CXCL10 deregulation might be a proper prognostic marker in gastric and ovarian cancer. These types of studies help scientists determine whether SNPs are worth following for additional experimental studies to maximize the outcome while studying human health.

Keywords


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