Computational profiling of vernomenin from Vernonia amygdalina via network pharmacology and molecular modeling: a preliminary assessment for fever targeting.

This study aimed to computationally evaluate the anti-fever potential of vernomenin from Vernonia amygdalina and its interactions with critical molecular targets. Network pharmacology was employed to screen bioactive compounds and identify fever-related targets (SIRT1, TP53, HDAC1), followed by molecular docking and 100-ns molecular dynamics (MD) simulations to assess binding affinities, interaction modes, and complex stability. Network analysis highlighted vernomenin as uniquely linked to all three targets, with the strongest binding affinity to SIRT1. MD simulations showed stable dynamics of the vernomenin-SIRT1 complex, with ligand-RMSD at ∼4.0 Å, while PCA revealed ligand-induced conformational stabilization that reduced protein flexibility and may suggest allosteric modulation. This work provides computational evidence that vernomenin could exert anti-fever effects, offering a mechanistic basis for the traditional use of Vernonia amygdalina and identifying vernomenin as a promising candidate for fever therapy requiring further experimental validation.