Advances in in silico drug discovery for rabies virus: Innovations in ligand identification and therapeutic mechanisms (Review)

Abstract

Rabies remains a nearly universally fatal zoonotic disease once clinical symptoms manifest, despite the availability of effective vaccines. The lack of viable therapeutic interventions post‑symptom onset has fueled the exploration of novel strategies, particularly computational approaches. The present review highlights recent advancements in in silico drug discovery targeting rabies virus, focusing on structure‑based drug design, ligand screening, molecular dynamics and artificial intelligence‑assisted repurposing. Specific viral proteins, including nucleoprotein (N), glycoprotein (G) and RNA‑dependent RNA polymerase (L), have been computationally analyzed as promising therapeutic targets. Several FDA‑approved drugs, such as emtricitabine and micafungin, along with phytochemicals such as (+)‑catechin, have demonstrated strong binding affinities in docking simulations. Additionally, the development of multi‑epitope peptide vaccines and RNA‑based platforms, including mRNA vaccines and RNA interference, provides innovative preventive strategies. The integration of bioinformatics tools, such as AlphaFold, IEDB, CB‑Dock2 and PLIP has streamlined target identification and validation. Despite notable computational progress, translational gaps remain due to limited experimental validation. The present review emphasizes the importance of combining in silico predictions with laboratory research and clinical data to accelerate the development of effective rabies therapies. With an increasing global health burden, particularly in resource‑limited regions, computational drug discovery holds promise for bridging critical treatment gaps in rabies management.