New acridine derivatives as promising agents against methicillin-resistant staphylococci – From tests to in silico analysis. (October 2020)

• Record Type: Journal Article
• Authors: Czarnecka, Kamila; Lisiecki, Pawel; Szewczyk, Eligia; Chufarova, Nina; Wójtowicz, Przemysław; Kręcisz, Paweł; Szymański, Paweł
• Is Part Of: Computational biology and chemistry. Volume 88(2020)
• Publication Date: 2020-10
• Subjects: Acridine derivatives -- Methicillin-resistant staphylococci -- Antibacterial activity -- MIC -- MBC; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107321
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Antibacterial activity of several new derivatives of tacrine. Tested methicillin-resistant staphylococci. Quantitative structure-activity relationship analysis. Relationships between biological activity and the structural parameters. Select descriptors as independent variables for multiple linear regression models. Abstract: The present study describes the antibacterial activity of several new derivatives of tacrine or cyclopentaquinoline bound to either 6-hydrazinenicotinic acid or 4-fluorobenzoic acid through an aliphatic chain against methicillin-resistant staphylococcal strains. All derivatives showed antibacterial activity against all tested methicillin-resistant staphylococci. Of these, compounds 6, 18, 23 and 24 exhibited the highest activity, ranging from 4.87 to 19.5 μg/mL MBC (Minimum Bactericidal Concentration) depending on the bacterial strain. These values were not much greater than that for vancomycin, the reference standard for the treatment of methicillin-resistant Staphylococci infections in humans. In addition, all synthesized compounds underwent a quantitative structure-activity relationship analysis. Correlation and multicollinearity tests were used to select descriptors as independent variables for multiple linear regression models to quantify the relationships between biological activity and the structural parameters.