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Feline infectious peritonitis (FIP), a fatal disease caused by feline coronavirus (FCoV), poses a serious threat to feline health. Natural product-based virtual screening offers a promising avenue for identifying antiviral agents targeting FCoV. In this study, a structure-based computational approach was employed to discover potential inhibitors of the 3C-like protease (3CLpro) of FCoV.
A library of 96,677 natural compounds from the ZINC database was screened using molecular docking to assess their binding affinities to the protease. The initial hits were refined by evaluating ADMET properties and visually inspecting the binding poses, yielding 68 candidate molecules. These were further assessed through 100-nanosecond molecular dynamics simulations and binding free energy calculations.
Through computational filtering, 14 compounds were identified that exhibited strong interaction stability and minimal conformational fluctuation. An analysis of the binding modes revealed that key residues, such as His162, Glu165, and Cys144, formed crucial hydrogen bonds and hydrophobic contacts, contributing to the stability of the protein-ligand complexes.
The identified interactions highlighted the importance of specific residues in stabilizing the protein-ligand complex. Among the 14 compounds, eight maintained stable binding profiles throughout extended 500-nanosecond molecular dynamics simulations and also exhibited elevated binding free energy values, suggesting a stronger potential for antiviral development.
The findings indicated the compounds’ strong potential for further development as antiviral leads. The results also revealed several core molecular frameworks that may serve as an initial reference for designing FCoV 3CLpro inhibitors, laying the groundwork for structure-guided drug discovery efforts.
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