Trush, M.M.* ; Kovalishyn, V.* ; Hodyna, D.* ; Golovchenko, O.V.* ; Chumachenko, S.* ; Tetko, I.V. ; Brovarets, V.S.* ; Metelytsia, L.*
In silico and in vitro studies of a number PILs as new antibacterials against MDR clinical isolate Acinetobacter baumannii.
Chem. Biol. Drug Des. 95, 624-630 (2020)
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 and could be used by scientists for design of new more effective antibiotics.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Acinetobacter Baumanii ; Antibacterial Activity ; Machine Learning ; Ochem ; Phosphonium Ionic Liquids; Antimicrobial Resistance; Phosphonium; Susceptibility; Derivatives; Inhibitors
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2020
Prepublished im Jahr
HGF-Berichtsjahr
2020
ISSN (print) / ISBN
1747-0277
e-ISSN
1747-0285
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 95,
Heft: 6,
Seiten: 624-630
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Blackwell
Verlagsort
Los Angeles, Calif.
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30203 - Molecular Targets and Therapies
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-503000-001
Förderungen
Copyright
Erfassungsdatum
2020-04-16