Computational Screening of Flavonoids for the Inhibition of Ebola: Admet, Dft and Molecular Docking

Ebola virus disease (EVD) remains a significant global health threat due to its high mortality rate and limited therapeutic options. Natural products such as flavonoids have attracted attention as potential antiviral agents because of their structural diversity, bioactivity, and favorable safety profiles. This study employed a comprehensive in silico approach to screen selected flavonoids for their potential inhibitory activity against Ebola virus targets.
Drug-likeness and pharmacokinetic profiles were first assessed using ADMET prediction tools to evaluate absorption, distribution, metabolism, excretion, and toxicity. The compounds were further analyzed using the PKCSM server to predict physicochemical properties, gastrointestinal absorption, blood–brain barrier permeability, cytochrome P450 interactions, and potential toxicological risks. These evaluations ensured that only flavonoids with favorable pharmacokinetic behavior and minimal toxicity concerns were advanced for subsequent analysis.
To explore electronic properties and stability, Density Functional Theory (DFT) calculations were performed. Parameters such as HOMO–LUMO gap, molecular electrostatic potential, and frontier orbital distributions provided insights into the compounds’ reactivity and potential binding affinity. These descriptors highlighted the structural features that may contribute to antiviral activity.
Finally, molecular docking studies were carried out to investigate the binding interactions of the screened flavonoids with key Ebola viral proteins. Overall, this integrated computational workflow combining ADMET analysis, PKCSM predictions, DFT calculations, and molecular docking suggests that flavonoids possess promising drug-like properties and binding capabilities against Ebola virus targets.