Data Sheet 1_Identification of natural TLR4 modulators through network pharmacology and molecular modeling in SARS-CoV-2 Acinetobacter baumannii co-infection.docx

Using network pharmacology, an integrated protein–protein 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 −10.46, −10.02, and −9.58 kcal/mol, respectively, compared with −9.10 kcal/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.