In-Silico Analysis and Identification of functional Single Nucleotide Polymorphism (SNPs) of the DISC1 gene

SNPs (Single-nucleotide polymorphisms) are essential for understanding the genetic origin of various complex human diseases. The identification of the functional SNPs responsible for the disease is still a challenge so there is an urgent need for identification of functional SNPs. In this work, analysis was made on the genetic variations which can alter both the function and expression of the DISC1 gene using computational approaches. The total of 23 SNPs was found, out of which 12 are missense (non-synonymous or nsSNPs), 8 occurred in 3’UTR region and 3 are synonymous SNPs. The 2 nsSNPs (rs6675281 and rs821616) were found to be damaging by PolyPhen and SIFT servers. I-mutant server showed decrease in the stability of rs6675281 and increase in the stability of rs821616 protein upon mutations. Structural analysis of proteins with mutations was done using SPDBV (Swiss PDB viewer), MUSTER (MUlti—Sources ThreadER) and PyMol tools for the detection of molecular dynamics and energy minimization calculations. This study revealed that L607F and S704C variants could indirectly or directly destabilize the amino acid interactions.