Prediction of the antimicrobial activity of quaternary ammonium salts against Staphylococcus aureus using artificial neural networks

Badura, Anna; Krysiński, Jerzy; Nowaczyk, Alicja; Buciński, Adam

doi:10.1016/j.arabjc.2021.103233

Cited by 17 publications

(8 citation statements)

References 30 publications

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“…It is important to note that hit-QAC 6a remains the most active compound against P. aeruginosa, the pathogen with the highest level of resistance …”

Section: Evaluation Of Microbiological Activitysupporting

confidence: 91%

“…It is important to note that hit-QAC 6a remains the most active compound against P. aeruginosa, the pathogen with the highest level of resistance. 63 The antimicrobial activity of the compounds increases in the series Gram-negative bacteria → Gram-positive bacteria → fungi, which is consistent with the literature data. 53 The fungicidal mechanism of QACs action is still the subject of discussion, and according to some data, it is not consistent with the antibacterial mechanism.…”

supporting

confidence: 91%

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Multicationic Quaternary Ammonium Compounds: A Framework for Combating Bacterial Resistance

et al. 2023

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During previous stages of research, high biocidal activity toward microorganism archival strains has been used as the main indicator in the development of new antiseptic formulations. Although this factor remains one of the most important characteristics of biocide efficiency, the scale of antimicrobial resistance spread causes serious concern. Therefore, focus shifts toward the development of formulations with a stable effect even in the case of prolonged contact with pathogens. Here, we introduce an original isocyanuric acid alkylation method with the use of available alkyl dichlorides, which opened access to a wide panel of multi-QACs with alkyl chains of various lengths between the nitrogen atoms of triazine and pyridine cycles. We used a complex approach for the resulting series of 17 compounds, including their antibiofilm properties, bacterial tolerance development, and antimicrobial activity toward multiresistant pathogenic strains. As a result of these efforts, available compounds have shown higher levels of antibacterial activity against ESKAPE pathogens than widely used commercial QACs. Hit compounds possessed high activity toward clinical bacterial strains and have also demonstrated a long-term biocidal effect without significant development of microorganism tolerance. The overall results indicated a high level of antibacterial activity and the broad application prospects of multi-QACs based on isocyanuric acid against multiresistant bacterial strains.

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“…It is important to note that hit-QAC 6a remains the most active compound against P. aeruginosa, the pathogen with the highest level of resistance …”

Section: Evaluation Of Microbiological Activitysupporting

confidence: 91%

supporting

confidence: 91%

Multicationic Quaternary Ammonium Compounds: A Framework for Combating Bacterial Resistance

et al. 2023

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“…The principal advantages of artificial neural network (ANN) techniques include their capacity for data learning and generalization, fault tolerance, and an innate ability to process contextual information, alongside their rapid computational capabilities [36]. According to Badura et al ( 2021), ANNs serve as excellent tools to support researchers in laboratory work, enabling the estimation of whether a tested compound possesses the desired antimicrobial activity [37]. It is also noteworthy that the primary advantage of ANNs is their ability to streamline the work of researchers who aim to uncover the intricate relationships among the physicochemical properties of compounds.…”

Section: Backpropagation Network (Bpn)mentioning

confidence: 99%

“…It is also noteworthy that the primary advantage of ANNs is their ability to streamline the work of researchers who aim to uncover the intricate relationships among the physicochemical properties of compounds. This approach enables researchers to target the chemical synthesis of compounds with the desired activity by leveraging theoretical models obtained through computational chemistry [37]. According to the studies conducted by Cabrera et al (2010), artificial neural networks serve as reliable, fast, and cost-effective tools, paving the way for predicting the antioxidant activity of essential oils [38].…”

Section: Backpropagation Network (Bpn)mentioning

confidence: 99%

Enhancing Bioactive Compound Classification through the Synergy of Fourier-Transform Infrared Spectroscopy and Advanced Machine Learning Methods

Sampaio,

Calado

2024

Antibiotics

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Bacterial infections and resistance to antibiotic drugs represent the highest challenges to public health. The search for new and promising compounds with anti-bacterial activity is a very urgent matter. To promote the development of platforms enabling the discovery of compounds with anti-bacterial activity, Fourier-Transform Mid-Infrared (FT-MIR) spectroscopy coupled with machine learning algorithms was used to predict the impact of compounds extracted from Cynara cardunculus against Escherichia coli. According to the plant tissues (seeds, dry and fresh leaves, and flowers) and the solvents used (ethanol, methanol, acetone, ethyl acetate, and water), compounds with different compositions concerning the phenol content and antioxidant and antimicrobial activities were obtained. A principal component analysis of the spectra allowed us to discriminate compounds that inhibited E. coli growth according to the conventional assay. The supervised classification models enabled the prediction of the compounds’ impact on E. coli growth, showing the following values for accuracy: 94% for partial least squares-discriminant analysis; 89% for support vector machine; 72% for k-nearest neighbors; and 100% for a backpropagation network. According to the results, the integration of FT-MIR spectroscopy with machine learning presents a high potential to promote the discovery of new compounds with antibacterial activity, thereby streamlining the drug exploratory process.

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“…In particular, Dolezal et al reported that optimal antimicrobial activity was observed with alkyl chains of QACs composed of 12 to 16 carbons. 19 QACs exhibit broad-spectrum antimicrobial activity against Gram-negative and Gram-positive bacteria 20,21 and also against enveloped viruses such as SARS-Cov-2. [22][23][24] The antiviral activity of textile products is evaluated by tests according to the ISO18184 standard that measures the viral log reduction (or percent reduction) of the viral suspension as a function of contact time with the bioactive textile.…”

Section: Introductionmentioning

confidence: 99%

Antiviral functionalization of a polypropylene nonwoven textile structure as a self-decontaminating layer for respiratory masks

et al. 2023

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Prediction of the antimicrobial activity of quaternary ammonium salts against Staphylococcus aureus using artificial neural networks

Cited by 17 publications

References 30 publications

Multicationic Quaternary Ammonium Compounds: A Framework for Combating Bacterial Resistance

Multicationic Quaternary Ammonium Compounds: A Framework for Combating Bacterial Resistance

Enhancing Bioactive Compound Classification through the Synergy of Fourier-Transform Infrared Spectroscopy and Advanced Machine Learning Methods

Antiviral functionalization of a polypropylene nonwoven textile structure as a self-decontaminating layer for respiratory masks

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