Cationic Biocides Tend to Embed into the Inner Layer of the Model Outer Membrane Vesicles of Gram-negative Bacteria: Computational Insights

Kholina, E.G.; Kovalenko, I.B.; Strakhovskaya, M.G.

Авторы: Kholina E.G., Kovalenko I.B., Strakhovskaya M.G.
Журнал: Математическая биология и биоинформатика
Том: 19
Номер: 2
Год издания: 2024
Первая страница: 261
Последняя страница: 275
DOI: 10.17537/2024.19.261
Аннотация: The outer membrane vesicles (OMVs), produced by many pathogenicbacteria, play a significant role in bacterial pathogenesis. They promote bacterialresistance to antibiotics and act as natural protective barriers. The study of OMVsis essential both for understanding the general mechanisms of bacterialpathogenicity and for the development of the antibacterial drugs. In this paper, wecreated model vesicle that imitate the OMVs of Gram-negative bacteria usingmolecular modeling techniques. To investigate the interaction of the cationicantimicrobial compounds with the outer lipopolysaccharide (LPS) monolayer andthe inner phospholipid monolayer of the OMV membrane, we performed moleculardynamics simulations by placing molecules of the cationic antiseptic octenidine onthe outside or inside of model vesicles. The interaction of octenidine with the outerand inner monolayer was significantly different: octenidine interacted weakly withthe outer LPS surface of the model OMV, but exhibited high affinity for thephospholipids of the inner monolayer. To study the translocation of cationicantimicrobial molecules within model OMV, we performed steered moleculardynamics simulations. For all three cationic biocide molecules, antisepticoctenidine, photosensitizer octakis(cholinyl)zinc phthalocyanine, and dyemethylene blue, it turned out that, along with the LPS of the outer membrane of theOMV, the phosphates of lipid A molecules represent the final barrier to theirpenetration into the model OMV.
Добавил в систему: Холина Екатерина Георгиевна

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Cationic Biocides Tend to Embed into the Inner Layer of the Model Outer Membrane Vesicles of Gram-negative Bacteria: Computational Insightsстатья

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