Suganya, Jeyabaskar and Radha, Mahendran and Sharanya, Manoharan and Poornima, Vasudevan (2018) IN-SILICO ANALYSIS OF SNPs FROM cAMP-GEFII GENE ASSOCIATED WITH POLYCYSTIC OVARIAN SYNDROME. International Journal of Pharmaceutical Sciences and Research, 9 (12). ISSN 23205148
![[thumbnail of 21-Vol.-9-Issue-12-Dec-2018-IJPSR-RA-10085.pdf]](https://ir.vistas.ac.in/style/images/fileicons/text.png)
21-Vol.-9-Issue-12-Dec-2018-IJPSR-RA-10085.pdf
Download (397kB)
Abstract
Polycystic ovary syndrome (PCOS) is one of the most common disorders that occur in women at any age due to the endocrine hormone imbalance. The cause for this disorder is still not identified, but on recent research provided that disorder may be caused by some genetic variation. Predicting and understanding the effects of genetic variation that occurred in the gene are becoming more important for single nucleotide polymorphism to understand the molecular basis of genetic disease. From the literature survey, the candidate gene which is responsible for causing genetic PCOS was identified. In this work using computational methods, this candidate gene was analyzed completely to find out the genetic variation which in charge for altering the expression and the functional of the gene. On analyzing the gene, it was predicted that the protein which was translated from the gene played a key role for causing the major alteration in the gene. Using SNP analysis tool, further investigation were carried out to the disease causing protein and were predicted that the particular mutation occurred in the protein altered the function and structure of the gene. By using bioinformatics tool, an attempt was made to stop the mutation by replacing the original amino acid to the structure and sequence of the protein, which was suggested by the tools. Some clinical studies can be carried out further to confirm that the protein which was responsible for gene alteration in PCOS will function normally after some necessary modification are made in the protein which was suggested by computational methods.
Item Type: | Article |
---|---|
Subjects: | Bioinformatics > Gene Therapy |
Domains: | Bioinformatics |
Depositing User: | Mr IR Admin |
Date Deposited: | 31 Aug 2025 12:30 |
Last Modified: | 31 Aug 2025 12:30 |
URI: | https://ir.vistas.ac.in/id/eprint/10630 |