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Mapping Trofinetide Polypharmacology in Rett Syndrome: A Multi-Stage Computational Analysis
Luis Felipe Hernández-Ayala1, Gabriel Eduardo Guzmán-López1, Annia Galano1
1Departamento de Química, Universidad Autónoma Metropolitana Unidad Iztapalapa, Mexico City, Mexico.
Journal of Computational Chemistry
|July 30, 2026
Summary
Trofinetide, an FDA-approved drug for Rett syndrome (RTT), may work by interacting with multiple targets. This study used computational methods to identify potential drug targets and understand trofinetide
Area of Science:
- Neuroscience
- Pharmacology
- Computational Biology
Background:
- Rett syndrome (RTT) is a severe neurodevelopmental disorder linked to MECP2 gene mutations.
- Trofinetide is the first FDA-approved treatment for RTT, but its mechanism of action is not fully understood.
Purpose of the Study:
- To elucidate the pharmacological mechanism of trofinetide in Rett syndrome.
- To identify and prioritize potential molecular targets of trofinetide using a structure-based in silico workflow.
Main Methods:
- Integrated target prediction, molecular docking, and 100 ns molecular dynamics (MD) simulations.
- Candidate receptors were ranked using comparative pleiotropic score (PS) and interaction similarity index (SSI).
- Five high-priority targets (GAT1, GABA(A), CHRM1, AMPA, GSK3β) were further analyzed with MD simulations.
Main Results:
- MD simulations supported binding hypotheses for trofinetide at GAT1, CHRM1, and GSK3β, suggesting stable interactions at key sites.
- Dynamic, surface-associated binding modes were observed for GABA(A) and AMPA receptors.
- The proline fragment of trofinetide was identified as a key element for hydrophobic anchoring across different targets.
Conclusions:
- The study provides testable structural hypotheses for trofinetide's multi-target interactions in Rett syndrome.
- The developed computational framework can guide experimental validation and the design of future multi-target drugs for RTT.