Abstract
Polycystic ovarian syndrome (PCOS) is a multigenic endocrine disorder observed in women of reproductive age. Although the condition is characterized by the presence of polycystic ovaries and excess production of androgens, the exact aetiology has not been well deciphered due to the unavailability of a suitable model organism. Defects in the two prime biomarkers namely CYP11A and CYP19A1, have been found to play a role in disease progression. The objective of this study was to carry out an in-silico assessment of these two genes to identify a potential model organism for the efficacious study of PCOS. Bioinformatics tools such as BLAST and EMBOSS were used for local and global alignment respectively, to find sequence homology and thereby, establish a model organism. Sequence comparison was followed by phylogenetic analysis and secondary structure prediction of the enzymes encoded by the respective genes. Our in-silico study revealed Gorilla gorilla to be an ideal candidate for the study of PCOS owing to its high sequence and structural similarities with the human gene counterparts. Future prospects of the research include in-vitro analysis of the biomarkers on Gorilla gorilla ovarian theca cell line to pave the way for therapy.
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