Predicting Functional Amino Acid Changes in Red Blood Cell Disorders
Author Information
Author(s): B Rajith C George, Priya Doss
Primary Institution: Vellore Institute of Technology University, Vellore, Tamil Nadu, India
Hypothesis
Amino acids conserved across species are more likely to be functionally significant.
Conclusion
The study identifies potential candidate SNPs that may contribute to red blood cell disorders and demonstrates the utility of bioinformatics tools in predicting deleterious mutations.
Supporting Evidence
- Bioinformatics tools can help identify mutations that affect protein function.
- 70% of non-synonymous SNPs were predicted to be deleterious by SIFT.
- PolyPhen predicted 43% of non-synonymous SNPs to be damaging.
- I-Mutant 2.0 predicted 80% of non-synonymous SNPs to be deleterious.
- PANTHER identified several SNPs with significant functional impacts.
- Combining different computational methods improved prediction accuracy.
- Identified SNPs may have implications for understanding red blood cell disorders.
- Functional significance of SNPs in untranslated regions was also assessed.
Takeaway
Scientists used computer tools to find changes in genes that might cause problems in red blood cells, helping to understand diseases better.
Methodology
The study involved analyzing deleterious SNPs using bioinformatics tools, including SIFT, PolyPhen, I-Mutant 2.0, and PANTHER.
Limitations
The study primarily focuses on computational predictions and may not account for all biological complexities.
Digital Object Identifier (DOI)
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