In Silico Analysis of Collagens Missense SNPs and Human Abnormalities

Collagens are the most abundant proteins in the extra cellular matrix/ECM of human tissues that are encoded by different genes. There are single nucleotide polymorphisms/SNPs which are considered as the most useful biomarkers for some disease diagnosis or prognosis. The aim of this study is screening and identifying the functional missense SNPs of human ECM-collagens and investigating their correlation with human abnormalities. All of the missense SNPs were retrieved from the NCBI SNP database and screened for a global frequency of more than 0.1. Seventy missense SNPs that met the screening criteria were characterized for functional and stability impact using six and three protein analysis tools, respectively. Next, HOPE and geneMANIA analysis tools were used to show the effect of SNPs on three-dimensional structure (3D) and physical interaction of proteins. Results showed that 13 missense SNPs (rs2070739, rs28381984, rs13424243, rs1800517, rs73868680, rs12488457, rs1353613, rs59021909, rs9830253, rs2228547, rs3753841, rs2855430, and rs970547), which are in nine different collagen genes, affect the structure and function of different collagen proteins. Among these polymorphisms, COL4A3- rs13424243 and COL6A6- rs59021909 were predicted as the most effective ones. On the other hand, designed mutated and native 3D of rs13424243 variant illustrated that it can disturb the protein motifs. Also, geneMANIA predicted that COL4A3 and COL6A6 are interacting with some proteins including: DDR1, COL6A1, COL11A2 and so on. Based on our findings, ECM-collagens functional SNPs are important and may be considered as a risk factor or molecular marker for human disorders in the future studies.