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Turkish Journal of Biology

DOI

10.3906/biy-1501-11

Abstract

The recent progress in DNA sequencing and computational algorithms dramatically heightened the value of single nucleotide polymorphism (SNP) databases. The experimental studies of mutation for the particular gene of interest are laborious and time-consuming. In this study, we used several computational algorithms to investigate the structural and functional consequences of SNPs on the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene of zebrafish (Danio rerio). The GAPDH gene is involved in multiple cellular activities, in addition to its association with classical glycolytic pathway. It has most commonly been used as the housekeeping gene for differential gene expression profiling, including western blots. The computational analysis, which used sequence-based tools such as SIFT, PANTHER, PROVEAN, and I-Mutant2.0, predicted deleterious nonsynonymous SNPs (nsSNPs) at p.W194R in the GAPDH gene. The SWISS Model tool generated a homology-modeled 3D structure of GAPDH by applying homologous protein structures retrieved from the RCSB PDB databank (PDB ID: 1U8F_O, 1ZNQ_O, 1J0X_O, 3GPD_R, and 1SZJ_G). The sequence identities of the above selected models were 86%, 86%, 86%, 83%, and 75%, respectively. The Procheck quality assessment in the Ramachandran plot showed that the incorporated mutation (p.W194R) led to a shifting of amino acid residues from the most favored regions towards the disallowed region, as compared to the native counterpart. The lowered ERRAT and PROSA Z scores in the mutant confirmed the overall deteriorating quality of mutant GAPDH. We also predicted an effect of mutation on increased H-bonding patterns due to mutant residue. The molecular docking analysis, while binding GAPDH to its ligand (NAD+), also revealed elevated global energy in the mutant. Altogether, this study demonstrated the impact of nsSNPs on the protein structure and function. The results of work provide an insight/roadmap for future investigations with regard to the pathological consequences of nsSNPs using in vivo methods.

First Page

43

Last Page

54

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