JOURNAL ARTICLE

Chemical characterization and evaluation of antiviral activity of two fucoidans extracted from Mediterranean brown seaweeds, Padina pavonica and Dictyopteris membranacea.

  • Published In: Letters in Applied Microbiology, 2025, v. 78, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Amri, Safa; Bouslama, Lamjed; Mzoughi, Zeineb; Nouira, Fatma; Majdoub, Hatem; Bouraoui, Abderrahman 3 of 3

Abstract

This article focuses on evaluating the antiviral activity of fucoidans—sulfated polysaccharides extracted from two Mediterranean brown seaweeds, Padina pavonica (Fuc-Pad) and Dictyopteris membranacea (Fuc-Dic)—against Herpes simplex virus type 2 (HSV-2) and coxsackievirus B3 (CVB-3). Both fucoidans demonstrated potent antiviral effects with high selectivity indexes, particularly against HSV-2, and exhibited distinct mechanisms of action: inhibiting HSV-2 by blocking viral adsorption and penetration via interaction with cellular receptors, and inhibiting CVB-3 by directly preventing viral ligand attachment to host cells. The antiviral efficacy is associated with their high sulfate content and molecular weight, and the compounds showed low cytotoxicity in vitro. These findings suggest fucoidans as promising candidates for developing new antiviral drugs, especially for CVB-3, which currently lacks treatment, and for HSV-2 strains resistant to existing therapies, though further in vivo and clinical studies are needed.

Additional Information

  • Source:Letters in Applied Microbiology. 2025/01, Vol. 78, Issue 1, p1
  • Document Type:Article
  • Subject Area:Botany
  • Publication Date:2025
  • ISSN:0266-8254
  • DOI:10.1093/lambio/ovaf002
  • Accession Number:182849329
  • Copyright Statement:Copyright of Letters in Applied Microbiology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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