Integrating at-line nanofractionation platform with GNPS for unveiling neuraminidase inhibitors from ethanolic extract of Smilax china L.

Influenza is a highly transmissible airborne disease that causes acute febrile respiratory illness, ranging from mild fatigue to fatal respiratory failure. Neuraminidase (NA) serves as a primary drug target for both the prevention and treatment of influenza. In this study, an efficient strategy integrating an at-line nanofractionation (ANF) platform with Global Natural Products Social Molecular Networking (GNPS) was employed for the rapid discovery of neuraminidase inhibitors (NAIs) from the Traditional Chinese medicine (TCM) Smilax china L. High-throughput screening of a self-constructed TCM extract library revealed that the ethanolic extract of Smilax china L. exhibited over 90% inhibitory activity against oseltamivir-sensitive neuraminidase (NAS), with an IC50 value of 88.78 ± 13.26 μg/mL. The NAS-based ANF platform was then applied, and 21 compounds were prioritized as candidate NAIs based on their association with bioactive ANF fractions. By combining GNPS molecular networking with manual interpretation (mass errors <5 ppm), a total of 97 compounds were annotated (Confidence level II), covering six major classes, including 47 flavonoids, 20 cinnamic acid derivatives, 16 polyphenolic compounds, and 14 others. Among these, the 21 bioactive constituents included chlorogenic acid, astilbin, procyanidin B, and smilaside A. Molecular docking and molecular dynamics simulations were used to explore potential binding interactions and possible structural determinants of candidate binding. The results suggest that these compounds may interact with key residues in the NAS active site, including the 150-loop, the Arg cluster (residues 118, 292, 371), and Glu119. Notably, the 150-loop region is relatively conserved, suggesting a potential structural basis for hypothesizing activity against drug-resistant variants that warrants further experimental investigation. However, docking scores and MD stability are computational predictions and do not establish experimental inhibitory potency; biochemical and antiviral validation is required. The integrated ANF-GNPS platform established in this study provides an efficient and reliable technical approach for the rapid screening and structural annotation of bioactive constituents from TCM. It lays a solid chemical foundation for the discovery of novel NAIs.