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In silico and in vitro studies of a number PILs as new antibacterials against MDR clinical isolate Acinetobacter baumannii.
Trush, Maria M; Kovalishyn, Vasyl; Hodyna, Diana; Golovchenko, Olexandr V; Chumachenko, Svitlana; Tetko, Igor V; Brovarets, Volodymyr S; Metelytsia, Larysa.
Afiliação
  • Trush MM; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
  • Kovalishyn V; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
  • Hodyna D; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
  • Golovchenko OV; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
  • Chumachenko S; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
  • Tetko IV; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
  • Brovarets VS; BIGCHEM GmbH, Unterschleißheim, Germany.
  • Metelytsia L; V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Science of Ukraine, Kyiv, Ukraine.
Chem Biol Drug Des ; 95(6): 624-630, 2020 06.
Article em En | MEDLINE | ID: mdl-32168424
ABSTRACT
QSAR analysis of a set of previously synthesized phosphonium ionic liquids (PILs) tested against Gram-negative multidrug-resistant clinical isolate Acinetobacter baumannii was done using the Online Chemical Modeling Environment (OCHEM). To overcome the problem of overfitting due to descriptor selection, fivefold cross-validation with variable selection in each step of the model development was applied. The predictive ability of the classification models was tested by cross-validation, giving balanced accuracies (BA) of 76%-82%. The validation of the models using an external test set proved that the models can be used to predict the activity of newly designed compounds with a reasonable accuracy within the applicability domain (BA = 83%-89%). The models were applied to screen a virtual chemical library with expected activity of compounds against MDR Acinetobacter baumannii. The eighteen most promising compounds were identified, synthesized, and tested. Biological testing of compounds was performed using the disk diffusion method in Mueller-Hinton agar. All tested molecules demonstrated high anti-A. baumannii activity and different toxicity levels. The developed classification SAR models are freely available online at http//ochem.eu/article/113921 and could be used by scientists for design of new more effective antibiotics.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Compostos Organofosforados / Acinetobacter baumannii / Líquidos Iônicos / Antibacterianos Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Compostos Organofosforados / Acinetobacter baumannii / Líquidos Iônicos / Antibacterianos Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article