In silico profiling of non-synonymous SNPs in IDS gene for early diagnosis of Hunter syndrome

Background Single amino acid substitutions in the Iduronate-2-sulfatase enzyme result in destabilization of the protein and cause a genetic disorder called Hunter syndrome. To gain functional insight into the mutations causing Hunter syndrome, various bioinformatics tools were employed, and special...

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Bibliographic Details
Published in:Egyptian Journal of Medical Human Genetics 2022-03, Vol.23 (1), p.53-9
Main Authors: Sivakumar, Adarshan, Dinakarkumar, Yuvaraj, Al-Qahtani, Wahidah H, Karnan, Muthusamy, Rajabathar, Jothiramalingam, Charumathi, Arokiyaraj, Sadhaasivam, Elakiya
Format: Article
Language:English
Subjects:
Amino acids
Analysis
Bioinformatics
Chromosomes
Diagnosis
Enzymes
Genetic disorders
Genetic markers
Hunter syndrome
IDS gene
Molecular docking
Mucopolysaccharidosis
Mutation
Ns-SNPs
RMSF
Single nucleotide polymorphisms
Single-nucleotide polymorphism
Trajectory analysis
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Summary:Background Single amino acid substitutions in the Iduronate-2-sulfatase enzyme result in destabilization of the protein and cause a genetic disorder called Hunter syndrome. To gain functional insight into the mutations causing Hunter syndrome, various bioinformatics tools were employed, and special significance is given to molecular docking. Results In-silico tools available online for preliminary analysis including SIFT, PolyPhen 2.0, etc., were primarily employed and have identified 51 Non-synonymous Single Nucleotide Polymorphisms (ns-SNPs) as possibly deleterious. Further, modelling and energy minimization followed by Root Mean Square Deviation (RMSD) calculation has labelled 42 mutations as probably deleterious ns-SNPs. Later, trajectory analysis was performed using online tools like PSIPRED, SRide, etc., and has predicted six ns-SNPs as potentially deleterious. Additionally, docking was performed, and three candidate ns-SNPs were identified. Finally, these three ns-SNPs were confirmed to play a significant role in causing syndrome through root mean square fluctuation (RMSF) calculations. Conclusion From the observed results, G134E, V503D, and E521D were predicted to be candidate ns-SNPs in comparison with other in-silico tools and confirmed by RMSF calculations. Thus, the identified candidate ns-SNPs can be employed as a potential genetic marker in the early diagnosis of Hunter syndrome after clinical validation.
ISSN:1110-8630
2090-2441
DOI:10.1186/s43042-022-00271-3