Al Mahdi Hadiah Bassam, Shaik Noor Ahmad, Banaganapalli Babajan, Edris Sherif, Zahed Rawabi, ElSokary Hanan Abdelhalim, Daghistani Hussam, Almoghrabi Yousef, Bayashut Safa, Edrees Alaa Y, Mujalli Abdulrahman, Alefishat Eman, Elango Ramu, Awan Zuhier
Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Department of Research and Development, Al Borg Diagnostics, Jeddah, Saudi Arabia.
Comput Struct Biotechnol J. 2025 Aug 25;27:3770-3784. doi: 10.1016/j.csbj.2025.08.029. eCollection 2025.
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 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.