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.
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
Abstract
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.
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