Molecular dynamics simulations and bioinformatics’ analysis of deleterious missense single nucleotide polymorphisms in Glyoxalase-1 gene

Abstract

Glyoxalase-1 (Glo-1) is a key member of the Glyoxalase system, the primary line of defense against dicarbonyl stress which, in tandem, with reduced levels of expression or activity of Glyoxalase-1 enzyme, has been implicated in various human diseases like type 2 diabetes mellitus (T2DM) and its vascular complications. The association of Glo-1 single nucleotide polymorphisms with genetic susceptibility to T2DM and its vascular complications is yet to be explored. Therefore, in this study, we have employed a computational approach to identify the most damaging missense or nonsynonymous SNPs (nsSNPs) in Glo-1 gene. Initially, we characterized missense SNPs that are damaging to the structural and functional integrity of Glo-1 using various bioinformatic tools. These tools included SIFT, PolyPhen-2, SNAP, PANTHER, PROVEAN, PhD-SNP, SNPs&GO, I-Mutant, MUpro and MutPred2. One of these missense SNPs (rs1038747749; corresponding to amino acid change Arginine to Glutamine at position 38) was found to be highly conserved in evolution and is an important part of the enzyme’s active site, glutathione binding site, as well as the dimeric interface based on the results obtained from ConSurf and NCBI Conserved Domain Search tools. Project HOPE reported that this mutation replaces a positively charged polar amino acid (Arginine) with a small, neutrally charged amino acid (Glutamine). Comparative modelling of wildtype and mutant (R38Q) Glo-1 proteins was performed in the run up to molecular dynamics simulation analysis which showed that rs1038747749 adversely impacts Glo-1 protein’s stability, rigidity, compactness, hydrogen bonds/interactions as demonstrated by the results of various parameters computed during the analysis.

Communicated by Ramaswamy H. Sarma

Keywords:

• Missense mutation
• high-risk SNPs
• Glyoxalase-1
• methylglyoxal
• in silico
• dicarbonyl stress
• computational
• molecular dynamics

Acknowledgments

The authors wish to thank Dr Bibi Sabiha and Dr Zaira Rehman for their guidance in the utilization of various computational tools.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

All the datasets generated and analyzed during the course of this study are available from authors.

Additional information

Funding

This research work was supported by the Higher Education Commission 5000 Indigenous Scholarship Scheme.