Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human...

Area of Science:

• Genetics and Molecular Biology
• Bioinformatics
• Neuroscience

Background:

• Alterations in nuclear retinoid X receptor (RXR) signaling are implicated in neurodegenerative disorders.
• Single nucleotide polymorphisms (SNPs) contribute to genetic variations and disease susceptibility.

Purpose of the Study:

• To identify deleterious SNPs affecting RXR isoforms using computational and molecular modeling.
• To investigate the impact of these SNPs on RXR protein structure and function.

Main Methods:

• Bioinformatic retrieval and analysis of 1,813 SNPs.
• In silico prediction of pathogenicity and protein stability using multiple tools (SIFT, PolyPhen, PROVEAN, etc.).
• Molecular modeling and structural assessment of RXR variants using DynaMut.

Main Results:

• Several deleterious SNPs were identified, with rs140464195_G139R, rs368400425_R358W, and rs368586400_L383F in RXRα being particularly detrimental.
• Seven missense mutations were found across RXRα/β/γ isoforms, including two novel mutations in RXRα (rs1588299621, rs1057519958).
• Structural analysis indicated affected interatomic interactions, reduced protein flexibility, and altered stability in mutant RXR variants.

Conclusions:

• Computational analysis is crucial for understanding the impact of RXR variants on protein function.
• The identified deleterious SNPs and mutations provide insights into potential genotype-phenotype correlations in neurodegenerative diseases.
• Further sophisticated computational approaches are suggested for studying RXR variants and their role in disease.