In Silico Identification of Antiviral Peptides as Potential Leads Against Sudan Ebolavirus VP‐40.

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 f...

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Publicado en:BioMed Research International Vol. 2026; pp. 1 - 19
Autores principales: Omara, Boniface, Kiyimba, Kenedy, Fofana, Fatoumata G., Diabaté, Oudou, Odur, Walter, Jjingo, Daudi, Iramiot, Jacob Stanley, Draleru, Peace, Achia, Joan, Shafiq, Muhammad, Ul-Haq, Zaheer, Okella, Hedmon, Odongo, Steven, Flora, Swaran J. S.
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 1/26/2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 1/26/2026
      vid: 2026
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        191137390
        191137390
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        10.1155/bmri/2204127
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        atl: In Silico Identification of Antiviral Peptides as Potential Leads Against Sudan Ebolavirus VP‐40.
      aug:
        au:
          Omara, Boniface
          Kiyimba, Kenedy
          Fofana, Fatoumata G.
          Diabaté, Oudou
          Odur, Walter
          Jjingo, Daudi
          Iramiot, Jacob Stanley
          Draleru, Peace
          Achia, Joan
          Shafiq, Muhammad
          Ul-Haq, Zaheer
          Okella, Hedmon
          Odongo, Steven
          Flora, Swaran J. S.
        affil: Department of Pathology,, Faculty of Health Sciences,, Busitema University,, Mbale, Uganda, busitema.ac.ug
      sug:
        subj:
          Ebola Virus Drug Effects
          Peptides Pharmacodynamics
          Peptides Analysis
          Antiviral Agents Pharmacodynamics
          Antiviral Agents Analysis
          Viral Proteins
          Computer Simulation
          Sudan
          Human
          Amino Acids
          Molecular Docking Simulation
          Drug Discovery
          Bioinformatics
          Support Vector Machine
          Discriminant Analysis
          Algorithms
          Descriptive Statistics
          Toxicity Tests
          Data Analysis Software
          Imaging, Three-Dimensional
          Molecular Structure
      ab: 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 stability, nontoxicity, and nonallergenic 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.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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