Identification of functional SNPs in VEGF gene and <i>in silico</i> analysis of damaging SNPs based on data procured from dbSNP database

Abstract

VEGF (vascular endothelial growth factor) gene is known to cause angiogenesis and participate in many diseases like prostate cancer and diabetic retinopathy. Several single nucleotide polymorphisms (SNPs) have been described in the VEGF gene, some of which have been reported to be associated with differential expression of VEGF <em>in vitro</em>. In the present study, polymorphism of VEGF gene was studied in relation to damaging mutations. Of total SNPs in VEGF gene, 38 were non-synonymous SNPs (nsSNPs), 47 were synonymous SNPs, 66 were in non-coding regions, which comprised of 13 SNPs in 5'UTR region and 53 SNPs were in 3'UTR region. The rest were in the intronic region. SIFT (Sorting Intolerant from Tolerant) analysis showed that L163P, H200W, P312T, R288W and G365V mutations were damaging, whereas PolyPhen predicted P163L and H200W nsSNPs as damaging. Among the predicted nsSNPs, rs4645843, rs1800620 were identified as deleterious and damaging by the SIFT and PolyPhen programs. Protein structural analysis with these amino acid variants was performed by using I-Mutant, Swiss PDB viewer, ANOLEA (Atomic Non-Local Environment Assessment), MUSTER (MUlti-Sources ThreadER) and NOMAD-Ref servers to check their molecular dynamics and energy minimization calculations. This <em>in silico</em> analysis suggested that mutations in VEGF, such as, G365V, P312T and R288W, could directly or indirectly destabilize the amino acid interactions and hydrogen bond networks, thus explaining the functional deviations of protein to some extent. Thus screening for VEGF G365V, P312T and R288W variants in the population-based study may be useful to check disease susceptibility.