Mapping Trofinetide Polypharmacology in Rett Syndrome: A Multi-Stage Computational Analysis

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 drug 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 drug targets using a structure-based in silico workflow.

Main Methods:

• Integrated computational workflow: target prediction, molecular docking, and 100 ns molecular dynamics (MD) simulations.
• Candidate receptor prioritization using comparative pleiotropic score (PS) and interaction similarity index (SSI).
• Analysis of binding modes and interactions with key residues for high-priority targets.

Main Results:

• Five high-priority targets identified: GAT1, GABA(A), CHRM1, AMPA, and GSK3β.
• MD simulations supported binding hypotheses: stable orthosteric site occupation (GAT1, CHRM1), catalytic cleft binding (GSK3β), and dynamic surface binding (GABA(A), AMPA).
• The proline fragment of trofinetide was observed to contribute to hydrophobic anchoring across different targets.

Conclusions:

• The study provides testable structural hypotheses for trofinetide's multi-target interactions in RTT.
• The computational framework can guide experimental validation and the design of next-generation multi-target drugs for RTT.