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2000
Volume 15, Issue 12
  • ISSN: 1570-1808
  • E-ISSN: 1875-628X

Abstract

Background: Due to the increase of multidrug-resistant microorganisms, the search for biologically active molecules does not stop. In the present study, we developed the effective QSAR model which allows a quick search of new potential Staphylococcus aureus inhibitors in the series of quaternary phosphonium salts. A number of the most promising 1,3-oxazol-4-yltriphenylphosphonium derivatives with predicted activities were synthesized and examined to confirm their antibacterial properties and the accuracy of the forecast. Furthermore, the toxicity of the investigated compounds was evaluated. Methods: The predictive QSAR model was developed using Artificial Neural Network approach. Antibacterial properties of the investigated compounds were performed using standard disk diffusion method. The toxicity of the compounds was determined in vivo using zebrafish (Danio rerio) and in vitro on acetylcholinesterase (AChE) enzyme as the test models. Results: The predictive ability of the regression model was tested by cross-validation, giving the cross-validated coefficient q2=0.82. Derivatives of 1,3-oxazol-4-yltriphenylphosphonium salts predicted as active were synthesized and screened for their antibacterial activities. All compounds demonstrated antibacterial activity according to the prediction. The toxicity tests indicated that all investigated samples were less toxic than well-known cationic surfactants. Conclusion: The most promising compound 2b exhibited strong antibacterial activity together with low toxicity and can be considered as a new efficient biocidal agent for future investigation. In addition, the proposed QSAR model can be used for predicting and designing novel potential S. aureus inhibitors among ionic liquids/salts.

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/content/journals/lddd/10.2174/1570180815666180219164334
2018-12-01
2025-07-15
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/content/journals/lddd/10.2174/1570180815666180219164334
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