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| Main Authors: | , , , , , , , , , |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
Journal of fish diseases
2026
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| Subjects: | |
| Online Access: | https://pubmed.ncbi.nlm.nih.gov/40751421/ |
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Table of Contents:
- Marine Drug Design for Epitheliocytis Rendering AI-Assisted Bioisosteric Replacement of Salicin. Naveed, Muhammad Javed, Khushbakht Aziz, Tariq Wazir, Rahmana Ali, Imran Khan, Ayaz Ali Shami, Ashwag Alwethaynani, Maher S Al-Asmari, Fahad Al-Joufi, Fakhria A Animals Fish Diseases Glucosides Molecular Docking Simulation Drug Design Benzyl Alcohols Micrococcaceae Anti-Bacterial Agents Epitheliocystis is a distinctive and relatively understudied bacterial infection of finfish skin and gill epithelia that occurs intracellularly and results in the enlargement of the host cells. The Candidatus Syngnamydia salmonis is a bacterial pathogen that affects fish, especially salmon species like trout and salmon. The production of Epitheliocystis by Candidatus Syngnamydia salmonis poses several challenges to the aquaculture industry. Currently, limited drugs and therapies are available to effectively manage and cease the spread of this disease. The goal of this study was to develop a potential drug target for the treatment of epitheliocystis. Salicin, an organic glucoside widely known for its anti-inflammatory characteristics, was chosen as the initial compound because of its pharmacological significance and confirmed as a bioisostere (a compound with identical biological activities but a different structure). The Xundrug MolOpt AI generative model of bioisosteric replacement tool was chosen as the optimisation technique in a cognitive exertion to improve the novel drug candidate salicin by its AI-assisted bioisosteric replacement. To retrieve the docking results, the top three ligands from Xundrug and the cell division protein of Candidatus Syngnamydia salmonis were uploaded to the HDOCK web server, which utilises a hybrid docking technique combining template-based modelling for docking. The target drug candidate was selected based on model 17's highest docking score of 135.6 kcal/mol. Furthermore, the Lipinski rule of five and the ADMET properties of the Bioisosteric Replaced Salicin model 17 (BRS-17) were carefully explored. The results showed that BRS-17 fulfilled the pharmacophore characteristics criteria, hence making it an ideal target candidate for Candidatus Syngnamydia salmonis' cell division protein. Additionally, the results are supported by -6.735Kcal/mol docking score predicted by DockThor. With the help of the supporting information from this study, the proposed drug design can close the gap in earlier studies for resistance to antibiotic treatments. It is suggested that in vitro tests be performed on this drug to show the effectiveness of the suggested design.