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The Ebola virus is a highly infectious pathogen with no effective antiviral treatments currently available, prompting ongoing research into potential therapeutic options. This study evaluated the inhibitory effects of licensed non-viral drugs on Ebola virus entry and replication using bioinformatic tools. A descriptive-analytical approach was used, in which the chemical structures of selected drugs were first generated in ChemDraw Ultra 10.0 and then energy-optimized in Hyperchem 8.0. Molecular docking was performed using AutoDock4.2 to simulate interactions between the drugs and viral proteins. The analysis revealed that the interactions involved primarily hydrophobic, π-π stacking, hydrogen bonding, and cation-π interactions. Chloroquine, diphenoxylate, and amodiaquine showed the strongest binding affinity, with the most negative docking energies, indicating their potential as effective inhibitors of the GP and VP40 proteins. Conversely, erythromycin and dirithromycin, due to their high hydrophilicity, exhibited weaker binding results. Overall, the study highlighted that drugs with hydrophobic components, effective hydrogen bonding, and tertiary amines tend to show enhanced anti-Ebola properties. The bioinformatic analysis suggests that these drugs could serve as promising candidates for inhibiting Ebola virus entry and replication.

The global impact of the COVID-19 pandemic continues, driven by the emergence of various SARS-CoV-2 variants and the limited availability of effective therapeutic options. The viral entry process requires the SARS-CoV-2 spike protein to be activated by host cell proteases, particularly TMPRSS2 and CTSL. These proteases facilitate viral membrane fusion and support the endocytic uptake of the virus. In this study, a computational approach using virtual screening was applied to discover compounds that could simultaneously inhibit both TMPRSS2 and CTSL. Two pharmacophore models were constructed from the binding pockets of these proteases, each in complex with its respective ligand. These models were employed to screen a library containing 41,775 compounds, including 10,849 drugs from the ChEMBL database and 30,926 natural products from the NPASS database. This process identified 115 compounds—54 pharmaceutical drugs and 61 natural products—that matched both the TMPRSS2 and CTSL pharmacophore models. The identified compounds were then docked into the protease structures to further refine the list. Molecular docking simulations identified 17 top candidates (5 drugs and 12 natural products) with stronger binding energies than the reference ligands and known inhibitors of these proteases. These candidates were then evaluated using various filters, including ADMET predictions, drug-likeness assessments, and synthetic accessibility. Among the drugs, silibinin emerged as the leading repurposed candidate, showing promise as a dual inhibitor for SARS-CoV-2 treatment. Additionally, the natural product barettin was highlighted as a strong contender for development into a novel dual-target inhibitor of TMPRSS2 and CTSL.