沙特家族性高胆固醇血症配体结合和细胞质结构域的致病性LDLR变异(C .103 C . >T和C .2416dup):分子表征和计算见解。

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-08-25 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.08.029
Hadiah Bassam Al Mahdi, Noor Ahmad Shaik, Babajan Banaganapalli, Sherif Edris, Rawabi Zahed, Hanan Abdelhalim ElSokary, Hussam Daghistani, Yousef Almoghrabi, Safa Bayashut, Alaa Y Edrees, Abdulrahman Mujalli, Eman Alefishat, Ramu Elango, Zuhier Awan
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引用次数: 0

摘要

家族性高胆固醇血症(FH)导致LDL-C水平升高,增加患心血管疾病的风险。本研究旨在确定沙特FH患者的遗传原因,并检查遗传变异与由此产生的基因型-蛋白表型之间的联系。采用全外显子组测序(WES)和Sanger测序检测受影响的沙特FH家族及其健康亲属的致病变异。包括RNA稳定性分析、分子动力学模拟和分子对接在内的计算工具被用来评估这些变异对mRNA稳定性和蛋白质结构的影响,特别是LDLR-LDLRAP1相互作用。WES在两个沙特阿拉伯FH家族中发现了LDLR基因的两个致病变异:C .103 C . b> p.(Gln35Ter)和C .2416dup p.(Val806GlyfsTer11),这两个基因在健康亲属和区域数据库中都不存在。C .103 C>T变异改变了LDLR的二级RNA结构,可能影响其稳定性和功能。c.2416dupG变异体截断LDLR细胞质尾部,破坏NPXY-LDLRAP1相互作用并损害受体内化。Desmond的分子动力学模拟显示,由于c.2416dup变异,LDLR蛋白的结构灵活性增加,相互作用动力学改变,这表明对蛋白质功能完整性的进一步影响。总之,本研究在沙特阿拉伯家族的LDLR中发现了罕见的致病变异C .2416dup和C .103 C . >T。它展示了生物信息学方法与测序数据的整合,以表征和阐明遗传变异的致病作用,为LDLR遗传变异及其在FH患者中的分子影响之间复杂的相互作用提供了全面的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pathogenic LDLR Variants (c.103 C>T and c.2416dup) in ligand-binding and cytosolic domains in Saudi familial hypercholesterolemia: Molecular characterization and computational insights.

Familial hypercholesterolemia (FH) results in elevated levels of LDL-C, increasing the risk of developing cardiovascular disease. This study aims to identify genetic causes and examine the connection between genetic variants and the resulting genotype-protein phenotype in Saudi FH patients. Whole-exome sequencing (WES) and Sanger sequencing were employed to detect causative variants in affected Saudi FH families and their healthy relatives. Computational tools, including RNA stability analysis, molecular dynamics simulations, and molecular docking were used to assess the impact of these variants on mRNA stability and protein structure, particularly LDLR-LDLRAP1 interactions. WES identified two pathogenic variants in the LDLR gene in two Saudi FH families: c.103 C>T p.(Gln35Ter) and c.2416dup p.(Val806GlyfsTer11), both absent in healthy relatives and regional databases. The c.103 C>T variant alters the secondary RNA structure of LDLR, potentially affecting its stability and function. The c.2416dupG variant truncates the LDLR cytoplasmic tail, disrupting the NPXY-LDLRAP1 interaction and impairing receptor internalization. Molecular dynamics simulations using Desmond revealed increased structural flexibility and altered interaction dynamics in the LDLR protein due to the c.2416dup variant, suggesting further impacts on the protein's functional integrity. In conclusion, this study identifies rare pathogenic variants c.2416dup and c.103 C>T in LDLR in extended Saudi Arabian families. It demonstrates the integration of bioinformatics methods with sequencing data to characterize and elucidate the pathogenic effects of genetic variants, providing comprehensive insights into the intricate interplay between LDLR genetic variants and their molecular impacts in FH patients.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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