In Silico Identification of Antiviral Peptides as Potential Leads Against Sudan Ebolavirus VP-40
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BioMed Research International
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The continued reemergence of Ebola virus epidemics remains a global health concern, largely due to limited therapeutic interventions. This study is aimed at identifying and characterizing antiviral peptides as potential lead candidates against the Sudan Ebola virus. We retrieved antiviral peptides from the AVPdb and designed novel peptides from them using support vector machine, RF, and discriminant analysis algorithms. The toxicity and allergenicity predictions were performed using ToxinPred, ADMETLab 3.0, Allertop, and AllergenFP web servers, respectively. The 3D structures of selected peptides were modeled using PEP-FOLD and I-TASSER and validated using ProSA and PROCHECK web servers.The best peptide models were docked against the Sudan Ebola virus VP-40 protein using HDOCK and ClusPro. Molecular dynamics (MD) simulations were then carried out in GROMACS 2024.2. Out of 170 designed motifs, 30 exhibited antiviral potential with antiviral scores ranging from 0.506 to 1.000. Among the predicted antiviral peptides, five demonstrated favorable stabilities, nontoxicity, and non-allergenic properties. PEP-FOLD produced more stable peptide structures than I-TASSER, with over 84.6% of their amino acids in the most favorable region. Binding energies ranged from −252.39 to −145.83 kcal/mol (HDOCK) and from −887.7 to −538.7 units (ClusPro). The MD simulations confirmed high stability, with motif A10_M showing the strongest binding and structural compactness. Five peptides show strong potential as therapeutic leads against Sudan Ebola virus; however, further experimental validation is recommended.
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Omara, B., Kiyimba, K., Fofana, F. G., Diabaté, O., Odur, W., Jjingo, D., ... & Odongo, S. (2026). In Silico Identification of Antiviral Peptides as Potential Leads Against Sudan Ebolavirus VP‐40. BioMed Research International, 2026(1), 2204127.
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Except where otherwised noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States
