In silico screening of non-synonymous SNPs in human TUFT1 gene

Athira Ajith; Usha Subbiah

doi:10.1186/s43141-023-00551-4

In silico screening of non-synonymous SNPs in human TUFT1 gene

J Genet Eng Biotechnol. 2023 Oct 6;21(1):95. doi: 10.1186/s43141-023-00551-4.

Authors

Athira Ajith¹, Usha Subbiah²

Affiliations

¹ Human Genetics Research Centre, Sree Balaji Dental College and Hospital, Bharath Institute of Higher Education and Research, Chennai, 600 100, Tamil Nadu, India.
² Human Genetics Research Centre, Sree Balaji Dental College and Hospital, Bharath Institute of Higher Education and Research, Chennai, 600 100, Tamil Nadu, India. ushat75@yahoo.com.

Abstract

Background: Tuftelin 1 (TUFT1) gene is important in the development and mineralization of dental enamel. The study aimed to identify potential functionally deleterious non-synonymous SNPs (nsSNPs) in the TUFT1 gene by using different in silico tools. The deleterious missense SNPs were identified from SIFT, PolyPhen-2, PROVEAN, SNPs & GO, PANTHER, and SNAP2. The stabilization, conservation, and three-dimensional modeling of mutant proteins were analyzed by I-Mutant 3.0, Consurf, and Project HOPE, respectively. The protein-protein interaction using STRING, GeneMANIA for gene-gene interaction, and DynaMut for evaluating the impact of the mutation on protein stability, conformation, and flexibility.

Results: Eight deleterious nsSNPs (E242A, R303W, K182N, K123N, R117W, H289Q, R203W, and Q107R) out of 304 were found to have high-risk damaging effects using six in silico tools. Among them, K182N and K123N alone had increased stability, whereas E242A, R303W, R117W, H289Q, Q107R, and R203W exhibited a decrease in protein stability, based on DDG values. Meanwhile, all the eight deleterious nsSNPs altered the size, charge, hydrophobicity, and spatial organization of the amino acids and predominantly had alpha helix domains. These deleterious variants were located in highly conserved regions except R203W. Protein-protein interaction predicted that TUFT1 interacted with ten proteins that are involved in enamel mineralization and odontogenesis. Gene-gene interaction network showed that TUFT1 is involved in physical interactions, gene co-localization, and pathway interactions. DynaMut ΔΔG values predicted that five nsSNPs were destabilizing the protein, ΔΔG ENCoM values showed a destabilizing effect for all mutants, and seven nsSNPs increased the molecular flexibility of TUFT1.

Conclusion: Our study predicted eight functional SNPs that had detrimental effects on the structure and function of the TUFT1 gene. This will aid in the development of candidate deleterious markers as a potential target for disease diagnosis and therapeutic interventions.

Keywords: In silico analysis; SNPs; TUFT1 gene.