{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T15:02:31Z","timestamp":1789570951407,"version":"build-2803163510"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Chem."],"abstract":"<jats:p>\n                    Viral\u2013bacterial co-infection with SARS-CoV-2 and\n                    <jats:italic>Acinetobacter baumannii<\/jats:italic>\n                    exacerbates hyperinflammation via Toll-like receptor 4 (TLR4)-mediated immune pathways. Using network pharmacology, an integrated protein\u2013protein interaction network identified 30 key inter-species hubs comprising viral, bacterial, and human host proteins, with TLR4 achieving a high MCC score (722), highlighting its high topological centrality as a host immune target. Virtual screen of 2,820 natural compounds against the TLR4\/MD-2 complex identified three top candidates, CID5898023, CID5403474, and CID74977829, with docking scores of \u221210.46, \u221210.02, and \u22129.58\u00a0kcal\/mol, respectively, compared with \u22129.10\u00a0kcal\/mol for the reference antagonist Eritoran. CID5898023 (curcumin-derived) exhibited a more favorable docking score and stable binding behavior during the molecular dynamics simulation compared with the reference antagonist Eritoran. CID74977829 (baicalin-derived) showed stable binding but lower intestinal absorption, while CID5403474 (chrysin-derived) lacked conformational stability despite favorable docking scores. These computational findings prioritize curcumin- and baicalin-derived scaffolds as potential TLR4\/MD-2 modulators for further experimental investigation in the context of co-infection-associated inflammation.\n                  <\/jats:p>","DOI":"10.3389\/fchem.2026.1916568","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T14:05:16Z","timestamp":1789567516000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of natural TLR4 modulators through network pharmacology and molecular modeling in SARS-CoV-2 Acinetobacter baumannii co-infection"],"prefix":"10.3389","volume":"14","author":[{"given":"Mebarka","family":"Ouassaf","sequence":"first","affiliation":[{"name":"Group of Computational and Medicinal Chemistry, LMCE Laboratory, University of Biskra","place":["Biskra, Algeria"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shafi Ullah","family":"Khan","sequence":"additional","affiliation":[{"name":"Independent Researcher","place":["H\u00e9rouville-Saint-Clair, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kannan R. 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