Current research status, databases and application of single nucleotide polymorphism

In silico analysis of non-synonymous single nucleotide polymorphisms of human DEFB1 gene

Background

Single nucleotide polymorphisms (SNPs) play a significant role in differences in individual’s susceptibility to diseases, and it is imperative to differentiate potentially harmful SNPs from neutral ones. Defensins are small cationic antimicrobial peptides that serve as antimicrobial and immunomodulatory molecules, and SNPs in β-defensin 1 (DEFB1 gene) have been associated with several diseases. In this study, we have determined deleterious SNPs of the DEFB1 gene that can affect the susceptibility to diseases by using different computational methods. Non-synonymous SNPs (nsSNPs) of the DEFB1 gene that have the ability to affect protein structure and functions were determined by several in silico tools—SIFT, PolyPhen v2, PROVEAN, SNAP, PhD-SNP, and SNPs&GO. Then, nsSNPs identified to be potentially deleterious were further analyzed by I-Mutant and ConSurf. Post-translational modifications mediated by nsSNPs were predicted by ModPred, and gene-gene interaction was studied by GeneMANIA. Finally, nsSNPs were submitted to Project HOPE analysis.

Results

Ten nsSNPs of the DEFB1 gene were found to be potentially deleterious: rs1800968, rs55874920, rs56270143, rs140503947, rs145468425, rs146603349, rs199581284, rs201260899, rs371897938, rs376876621. I-Mutant server showed that nsSNPs rs140503947 and rs146603349 decreased stability of the protein, and ConSurf analysis revealed that SNPs were located in conserved regions. The physiochemical properties of the polymorphic amino acid residues and their effect on structure were determined by Project HOPE.

Conclusion

This study has determined high-risk deleterious nsSNPs of β-defensin 1 and could increase the knowledge of nsSNPs towards the impact of mutations on structure and functions mediated by β-defensin 1 protein.

Structural and functional analysis of KIT gene encoding receptor tyrosine kinase and its interaction with sunitinib and HDAC inhibitors: an in silico approach

KIT is a growth factor receptor, important for normal germ cell migration and development. The malfunction of KIT gene results in constitutive activation of the tyrosine kinase activity of c-KIT which is believed to be the major oncogenic event in stomach, small intestine mastocytosis, acute leukemias, melanomas and colon tumors. The genetics of these diseases could be better understood by knowing the functional relevance of their SNP variation. In this study, a computational analysis to detect the most deleterious nonsynonymous SNPs of KIT gene was performed and investigated its binding affinity to native and predicted mutant protein structure (D816V) with sunitinib and HDAC (Trichostatin A and Panobinostat) inhibitors was investigated. Out of 1,288 SNPs retrieved from dbSNP database against KIT gene, 11 non-synonymous SNPs were detected to be damaging and deleterious by SIFT, PolyPhen and I-Mutant2.0 servers. Further, we modeled the mutant protein based on the deleterious nsSNP (rs121913507) and showed that the mutation from Aspartic acid to Valine at 816 position exhibit greatest impact on stability. The RMSD values of mutant and native structures are found to be 0.40 and 1.9 A, respectively. Furthermore, the binding affinity of sunitinib and HDAC inhibitors were compared with native and mutant protein. In this regard, it was found that trichostatin A has a high binding efficacy towards the mutant protein with a binding energy of -35.274 kcal mol(-1), as compared to the native structure which has a binding energy of -25.996 kcal mol(-1). Also, the FastSNP tool suggested that 3 SNPs found to affect protein splicing site and splicing regulation. From present results, it was clear that the non-synonymous SNP rs121913507 (D816V) could be the most deleterious SNP for KIT gene and HDAC inhibitors can serve as a best drug for the mutant protein.