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Although trofinetide is the first FDA\u2010approved drug for RTT, its pharmacological mechanism remains unclear. We present a structure\u2010based\n                    <jats:italic>in silico<\/jats:italic>\n                    workflow that integrates target prediction, molecular docking, and 100\u2009ns molecular dynamics (MD) simulations to prioritize potential RTT\u2010relevant targets. Candidate receptors were ranked using a comparative pleiotropic score\u00a0(\n                    <jats:italic>P<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>S<\/jats:italic>\n                    <\/jats:sub>\n                    ), as well as an interaction similarity index (\n                    <jats:italic>S<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>SI<\/jats:italic>\n                    <\/jats:sub>\n                    ) relative to endogenous substrates and reference modulators. Five targets emerged as high\u2010priority candidates (GAT1, GABA\n                    <jats:sub>A<\/jats:sub>\n                    , CHRM1, AMPA, and GSK3\u03b2) and were further examined using MD. The simulations supported several binding hypotheses: (i) stable occupation of the orthosteric site in GAT1 and CHRM1, with persistent contacts with ligand\u2010recognition\u2010associated residues (Tyr60 in GAT1 and Asp105 in CHRM1); (ii) sustained binding within the catalytic cleft of GSK3\u03b2 with recurrent interactions near key catalytic elements (including Lys85); and (iii) dynamic, surface\u2010associated binding modes in GABA\n                    <jats:sub>A<\/jats:sub>\n                    and AMPA, with peripheral residues. In different targets, the proline fragment frequently contributes to hydrophobic anchoring. Taken together, these results provide testable structural hypotheses for the multi\u2010target interaction of trofinetide in RTT and a computational framework to guide experimental validation and next\u2010generation multi\u2010target design.\n                  <\/jats:p>","DOI":"10.1002\/jcc.70468","type":"journal-article","created":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T12:18:43Z","timestamp":1785413923000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mapping Trofinetide Polypharmacology in Rett Syndrome: A Multi\u2010Stage Computational Analysis"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3387-763X","authenticated-orcid":false,"given":"Luis Felipe","family":"Hern\u00e1ndez\u2010Ayala","sequence":"first","affiliation":[{"name":"Departamento de Qu\u00edmica Universidad Aut\u00f3noma Metropolitana Unidad Iztapalapa  Mexico City 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