Identification of neoechinulin B metabolites in vivo by UPLC Q/TOF MS and exploration of its anti HCV mechanism based on network pharmacology and molecular docking.

Fungal secondary metabolites, owing to their structural diversity and broad spectrum of bioactivities, have become a vital source for the discovery of microbial drugs and antiviral lead compounds. Fungi of the genus Aspergillus, which are ubiquitous filamentous microorganisms, are capable of producing structurally novel and functionally diverse secondary metabolites, thus representing a rich reservoir for drug lead discovery. Neoechinulin B (NeoB), an isoprenyl indole diketopiperazine alkaloid isolated from Aspergillus strains, exhibits potent antiviral activity. However, its poor characterization in terms of in vivo metabolism has hindered further development. In this work, we systematically explored the metabolic profile of NeoB in Sprague-Dawley rats, and combined network pharmacology with molecular docking to generate hypotheses regarding its potential anti‑HCV mechanism. These computational results are predictive and require future experimental validation. Following oral administration of NeoB to rats at 20 mg/kg/day, a total of 18 compounds, including NeoB and its metabolites, were identified in plasma, urine, faeces, heart, and liver. The proposed major metabolic pathways involved demethylation, sulfation, and glucuronidation. Network pharmacology and molecular docking were then used to generate hypotheses regarding potential anti-HCV targets. These computational results are predictive and require future experimental validation. Network pharmacology suggested that NeoB and its representative metabolites may potentially modulate targets such as SRC and EGFR, and by interfering with signalling pathways including "Proteoglycans in cancer" and "Hepatitis C". Molecular docking results suggested a potential preference for SRC over EGFR based on docking scores. However, because redocking validation for EGFR and SRC did not meets the 2.0 Å threshold, theses docking scores are considered computational estimates only. They cannot be used to infer target selectivity or differences in binding affinity. The parent compound P0 showed lowest docking score with SRC (-10.5 kcal/mol)), but this value is a computational estimate and does not represent experimental binding affinity. Overall, the docking outcomes were consistent with the network pharmacology predictions. This study qualitatively characterizes the in vivo metabolic profile of NeoB and provides computational hypotheses for future research. Any therapeutic implications remain speculative.