PuSH - Publication Server of Helmholtz Zentrum München: In silico and in vitro studies of a number PILs as new antibacterials against MDR clinical isolate <em>Acinetobacter baumannii.</em>

Information

Clues to quality of journals

Open Access Policy of Helmholtz Association 2016

CC Licencences

Publication Metrics

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... HMGU-Authors/Consortia

... Organizational Structure

... Journal

... Publication Type

... Research Data

... Arbeitsgruppen

... Publication Year

Publication overview

Statistics

Statistics (last 5 years)

OA Publications

Publish

Submit Publication

Import publication from...

...EVA

Report missing publication

Highlights

Support & Contact

Contact persons

Help

Data protection

Helmholtz Open Science

JANE Journal Estimator

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

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)

Postprint

Research data

DOI

PMC

	Open Access Green

Abstract
Metrics
Extra information

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

2.548

0.652