Sign in
BioinformaticsbioRxiv
Preprint

Computational Assessment of Aromatase: Unmasking Therapeutic Avenues for Female Hormonal Disorders

Sandesh P. KoiralaiD, Bhawana S. MagariD, Amit Kumar YadaviD, A Regmi, A PokhareliD, Samiran SubediiD, Pramod AryaliD

Abstract

Women of reproductive age widely experience the physical, mental, and emotional effects of hormonal imbalances. The levels of two hormones, estrogen, and progesterone, were particularly high. When these two hormones are unbalanced, symptoms such as irregular menstrual cycles, pelvic pain, and uterine fibroids can appear. Statistics show that 80 percent of women have hormonal imbalances. The creation of novel disease-containing drug candidates may be facilitated by computer-aided drug design (CADD), as many drugs and surgical treatments have unique adverse effects. Achieving good data coverage requires an optimized process for protein identification and enhanced selection techniques for medicinal compounds, including their metabolic characterization. In this study, aromatase is the prioritized protein that acted as a rate-limiting enzyme in steroidogenesis. To maintain its expression and regulation to control estrogen production, natural compounds were retrieved from the ZINC15 database through ADME/TOX property filtration. Compound B, specifically designated as (1R,3S,6S,7S,10S,11R)-7-[(dimethylamino)methyl]-3,12-dimethyl-2,9-dioxatetracyclo [9.3.0.01,3.06,10] tetradec-12-en-8-one, exhibits remarkable therapeutic potential, as evidenced by its inability to inhibit S-adenosyl methionine (SAM) biosynthesis, the observed stability of molecular interactions based on Density Functional Theory (DFT), and a favorable energy gap between molecular orbital stages. This research can be employed as a utility module for fast screening of drug-like molecules and taking these leads forward to clinical trials, assessing their value as potential suitors for drug repurposing against female hormonal disorders.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMallur '24Souza '20Rudovich '22Sharma '23Zhao '25Perina '22
66% semantic matchBioinformatics
Dhrithi Jayasimha Mallur, B. Lavanya, Sheshadri S. Temkar+2 more·Journal of Biomolecular Structure and Dynamics·Jun 17, 2024· 7 citations