Molecular Consequences of PCOS-Linked Aromatase Variants: Structural Modeling and Inhibitor Docking
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Submission Date
Fall 2025
Abstract
Polycystic ovary syndrome (PCOS) affects approximately 10% of women of reproductive age and involves hormonal imbalances partly driven by disrupted estrogen synthesis. Aromatase (CYP19A1) catalyzes the conversion of testosterone and androstenedione into estrogen, making it essential for maintaining estrogen–androgen balance. The structural consequences of disease-associated aromatase mutations remain poorly understood. We investigated the Val161Asp substitution, a PCOS-linked variant in which a nonpolar valine is replaced by a negatively charged aspartate within a hydrophobic helical region of aromatase. Using the wild-type structure from PDB ID 3EQM, we generated a 3D-printed model highlighting the mutation and identified key catalytic features, including the heme prosthetic group, substrate-binding channel, and conserved monooxygenase motifs. We then produced a Val161Asp structural model with AlphaFold and compared it to the wild-type enzyme using Jmol to assess mutation-specific disruptions. Our modeling indicates that introducing a charged residue at position 161 destabilizes local helix packing, alters substrate channel geometry, and may interfere with androstenedione positioning in the active site. These structural changes suggest reduced catalytic efficiency, which provides a potential mechanism for impaired estrogen production in PCOS. High-confidence structural models of additional variants were generated with AlphaFold and refined in PyMOL to align with the wild-type structure. Molecular docking simulations in SwissDock assessed the predicted binding affinities of three non-steroidal aromatase inhibitors: Anastrozole, Letrozole, and Fadrozole (steroidal structures did not perform favorably under simulation). Across all inhibitors, R264C consistently caused the largest reduction in predicted binding affinity, likely due to disruption of critical hydrogen bonds and ionic interactions, whereas V161D and R375C had moderate or minimal effects. This integrative workflow demonstrates how computational and predicted molecular modeling can systematically evaluate the effects of PCOS-associated mutations on inhibitor interactions, identifying Arg264 as a potential focus for reduced drug efficacy and providing a foundation for future experimental validation and therapeutic investigation.
Recommended Citation
Sajnani, Kiran S.; Burri, Bharath Kumar Reddy; Milukuri, Yuktha; Patel, Preya; Colón, Marqus; Schmitt Lavin, Emily Ph.D.; and Sikora, Arthur Ph.D., "Molecular Consequences of PCOS-Linked Aromatase Variants: Structural Modeling and Inhibitor Docking" (2025). Protein Modeling Reports. 24.
https://nsuworks.nova.edu/protein_modeling_reports/24
Jmol Script
G3_25_poster.pdf (447 kB)
Poster
G3_25_Presentation.pptx (3857 kB)
Presentation