人类TUFT1基因中非同义SNPs的计算机筛选。

IF 3.6 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Athira Ajith, Usha Subbiah
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摘要

背景:Tuftelin 1(TUFT1)基因在牙釉质的发育和矿化中具有重要作用。该研究旨在通过使用不同的计算机工具来识别TUFT1基因中潜在的功能有害的非同义SNPs(nsSNPs)。从SIFT、PolyPhen-2、PROVEAN、SNPs&GO、PANTHER和SNAP2中鉴定出有害的错义SNPs。分别通过I-mutant 3.0、Consurf和Project HOPE分析突变蛋白的稳定性、保守性和三维建模。蛋白质-蛋白质相互作用,使用STRING、基因-基因相互作用的GeneMANIA和用于评估突变对蛋白质稳定性、构象和灵活性的影响的DynaMut。结果:使用6种硅工具,304种有害nsSNPs中有8种(E242A、R303W、K182N、K123N、R117W、H289Q、R203W和Q107R)具有高风险损伤作用。其中,基于DDG值,单独的K182N和K123N具有增加的稳定性,而E242A、R303W、R117W、H289Q、Q107R和R203W表现出蛋白质稳定性的降低。同时,所有八种有害的nsSNPs都改变了氨基酸的大小、电荷、疏水性和空间组织,并且主要具有α螺旋结构域。这些有害变体位于除R203W以外的高度保守区域。蛋白质-蛋白质相互作用预测TUFT1与10种参与牙釉质矿化和牙齿形成的蛋白质相互作用。基因-基因相互作用网络表明,TUFT1参与物理相互作用、基因共定位和通路相互作用。DynaMutΔΔG值预测5个nsSNPs正在破坏蛋白质的稳定,ΔΔG ENCoM值对所有突变体都显示出破坏稳定的作用,7个nsSNP增加了TUFT1的分子灵活性。结论:我们的研究预测了8个功能性SNPs对TUFT1基因的结构和功能有不利影响。这将有助于开发候选有害标志物,作为疾病诊断和治疗干预的潜在靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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.

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