BRCA2 Polymorphisms and Breast Cancer Susceptibility: a Multi-Tools Bioinformatics Approach.

IF 2.5 Q3 CELL BIOLOGY

Cellular Physiology and Biochemistry Pub Date : 2024-03-24 DOI:10.33594/000000689

Haris Jan, Najeeb Ullah Khan, Ayman M Al-Qaaneh, Munazzah Tasleem, Mikhlid H Almutairi, Ijaz Ali

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引用次数: 0

Abstract

Background/aims: The main focus of this investigation is to identify deleterious single nucleotide polymorphisms (SNPs) located in the BRCA2 gene through in silico approach, thereby,providing an understanding of potential consequences regarding the susceptibility to breast cancer.

Methods: The GenomAD database was used to identify SNPs. To determine the potential adverse consequences, our study employed various prediction tools, including SIFT, PolyPhen, PredictSNP, SNAP2, PhD-SNP, and ClinVar. The pathogenicity associated with the deleterious snSNPs was evaluated bu MutPred and Fathmm. Additionally, I-Mutant and MuPro were used to assess the stability, followed by conservation and protein-protein interaction analysis using robust computational tools. The 3D structure of BRCA2 protein was generated by SwissModel, followed by validation using PROCHECK and Errat.

Results: The GenomAD database was used to identify a total of 7, 921 SNPs, including 1940 missense SNPs. A set of 69 SNPs predicted by consensus to be damaging across all platforms was identified. Mutpred and Fathmm identified 48 and 38 SNPs, respectively to be associated with cancer. While I- Mutant and MuPro assays suggested 22 SNPs to decrease protein stability. Additionally, these 22 SNPs reside within highly conserved regions of the BRCA2 protein. Domain analysis, utilizing InterPro, pinpointed 18 deleterious mutations within crucial DNA binding domains and one in the BRC repeat region.

Conclusion: This study establishes a foundation for future experimental validations and the creation of breast cancer-targeted treatment approaches.

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BRCA2 多态性与乳腺癌易感性：一种多工具生物信息学方法。

背景/目的：本研究的重点是通过硅学方法识别 BRCA2 基因中的有害单核苷酸多态性（SNPs），从而了解其对乳腺癌易感性的潜在影响：方法：利用 GenomAD 数据库识别 SNPs。为了确定潜在的不良后果，我们的研究采用了多种预测工具，包括 SIFT、PolyPhen、PredictSNP、SNAP2、PhD-SNP 和 ClinVar。通过 MutPred 和 Fathmm 评估了与有害 snSNPs 相关的致病性。此外，还使用了 I-Mutant 和 MuPro 来评估稳定性，然后使用强大的计算工具进行保护和蛋白质-蛋白质相互作用分析。用 SwissModel 生成了 BRCA2 蛋白的三维结构，然后用 PROCHECK 和 Errat.Results 进行了验证：利用 GenomAD 数据库共鉴定出 7,921 个 SNPs，其中包括 1940 个错义 SNPs。根据共识预测，69 个 SNP 在所有平台上都具有损伤性。Mutpred 和 Fathmm 分别鉴定出 48 和 38 个与癌症相关的 SNPs。而 I- Mutant 和 MuPro 检测表明，22 个 SNP 会降低蛋白质的稳定性。此外，这 22 个 SNP 位于 BRCA2 蛋白的高度保守区域。利用 InterPro 进行的结构域分析确定了关键 DNA 结合结构域中的 18 个有害突变和 BRC 重复区域中的一个有害突变：这项研究为未来的实验验证和乳腺癌靶向治疗方法的开发奠定了基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cellular Physiology and Biochemistry 生物-生理学

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

1 months

期刊介绍： Cellular Physiology and Biochemistry is a multidisciplinary scientific forum dedicated to advancing the frontiers of basic cellular research. It addresses scientists from both the physiological and biochemical disciplines as well as related fields such as genetics, molecular biology, pathophysiology, pathobiochemistry and cellular toxicology & pharmacology. Original papers and reviews on the mechanisms of intracellular transmission, cellular metabolism, cell growth, differentiation and death, ion channels and carriers, and the maintenance, regulation and disturbances of cell volume are presented. Appearing monthly under peer review, Cellular Physiology and Biochemistry takes an active role in the concerted international effort to unravel the mechanisms of cellular function.