Development and application of in silico models to design new antibacterial 5-amino-4-cyano-1,3-oxazoles against colistin-resistant E. coli strains

Development and application of in silico models to design new antibacterial 5-amino-4-cyano-1,3-oxazoles against colistin-resistant E. coli strains

Here we describe the results of QSAR analysis based on artificial neural networks, synthesis, activity evaluation and molecular docking of a number of 1,3-oxazole derivatives as anti-E. coli antibacterials. All developed QSAR models showed excellent statistics on training (with determination coeffic...

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Bibliographic Details
Main Authors: Ivan Semenyuta, Diana Hodyna, Vasyl Kovalishyn, Bohdan Demydchuk, Maryna Kachaeva, Stepan Pilyo, Volodymyr Brovarets, Larysa Metelytsia
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Artificial Intelligence Chemistry
Subjects:
Machine learning modeling
QSAR
Molecular docking
5-amino-4-cyano-1,3-oxazoles
E. coli
Colistin resistance
Online Access:http://www.sciencedirect.com/science/article/pii/S2949747723000246

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http://www.sciencedirect.com/science/article/pii/S2949747723000246

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