Predicting oxytocin binding dynamics in receptor genetic variants through computational modeling.
Preeti Dubey1, Yingye Fang1, K Lionel Tukei1
1Department of Bioengineering, University of Washington, Seattle, WA, USA.
Npj Women'S Health
|August 29, 2025
Summary
This study models how oxytocin receptor (OXT) genetic variants affect drug response. Mathematical modeling offers a framework for personalized Pitocin dosing in pregnant individuals.
Area of Science:
- Pharmacogenomics
- Molecular Pharmacology
- Computational Biology
Background:
- Pitocin (synthetic oxytocin) is widely used but optimal dosing is difficult due to patient variability.
- Genetic variations in the oxytocin receptor (OXTR) may influence individual responses to oxytocin.
- Understanding these genetic influences is crucial for improving obstetric care.
Purpose of the Study:
- To develop a mathematical model simulating oxytocin (OXT) and oxytocin receptor (OXTR) binding dynamics.
- To investigate the impact of five specific OXTR genetic variants on OXT-OXTR interactions.
- To explore how these variants affect OXT response in different cell types.
Main Methods:
- Developed a mathematical model of OXT-OXTR binding dynamics.
- Incorporated experimentally measured, cell-specific OXTR surface localization data.
- Utilized literature-reported OXT-OXTR binding kinetics for model parameterization.
- Simulated OXT-OXTR interactions in human embryonic kidney (HEK293T) and myometrial smooth muscle cells.
Main Results:
- The model identified differences in OXT-OXTR binding equilibrium times between HEK293T and myometrial cells.
- Distinct binding dynamics were observed across the five studied OXTR genetic variants.
- Early OXT administration showed potential to mitigate reduced responses in V281M and E339K variants.
Conclusions:
- Genetic variants in OXTR significantly influence OXT dose-response relationships.
- The developed mathematical model provides insights into OXT pharmacodynamics at a genetic level.
- This framework can potentially guide personalized Pitocin dosing strategies based on patient genetic profiles.
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