Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-quaternary Ammonium Chlorides

Pałkowski, Łukasz; Błaszczyński, Jerzy; Krysiński, Jerzy; Słowiński, Roman; Skrzypczak, Andrzej; Błaszczak, Jan; Gospodarek, Eugenia; Wróblewska, Joanna

doi:10.1007/978-3-642-31900-6_14

Cited by 5 publications

(4 citation statements)

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“…We consider attribute relevance measures that satisfy the property of Bayesian confirmation. These measures take into account interactions between attributes present in the decision rules . In this case, the property of confirmation is related to quantification of the degree to which the presence of an attribute in the premise of a rule provides evidence for or against the conclusion of the rule.…”

Section: Resultsmentioning

confidence: 99%

Antimicrobial Activity and SAR Study of New Gemini Imidazolium‐Based Chlorides

et al. 2013

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A series of 70 new 3,3'(α,ω-dioxaalkyl)bis(1-alkylimidazolium) chlorides were synthesized. They were characterized with respect to surface active properties and antimicrobial activity against the following pathogens: Staphylococcus aureus, Enterococcus faecalis, Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae, Pseudomonas aeruginosa, Candida krusei, and Candida albicans. In this article, besides description of the synthesis, we characterize a set of features of these compounds, concerning their structure (described by the length of the dioxaalkan spacer and the length of the alkyl substituent in the aromatic ring) and surface active properties (critical micelle concentration, value of surface tension at critical micelle concentration, value of surface excess, molecular area of a single particle, and free energy of adsorption of molecule). Then, we present a SAR study for Staphylococcus aureus, as one of the most widespread pathogenic strains, conducted with the help of the Dominance-based Rough Set Approach (DRSA), that involves identification of relevant features and relevant combinations of features being in strong relationship with a high antimicrobial activity of the compounds. The SAR study shows, moreover, that the antimicrobial activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds.

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Section: Resultsmentioning

confidence: 99%

Antimicrobial Activity and SAR Study of New Gemini Imidazolium‐Based Chlorides

et al. 2013

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“…The decision attribute (dependent variable) is distinguishing the following classes of MIC: good, medium, and weak. To explain the class assignment in terms of condition attributes, we used the rough set concept, and its particular extension, called the dominance-based rough set approach (DRSA) [ 27 , 28 ].…”

Section: Methodsmentioning

confidence: 99%

Structure-Activity Relationships of the Imidazolium Compounds as Antibacterials of Staphylococcus aureus and Pseudomonas aeruginosa

Pałkowski

Karolak

Błaszczyński

et al. 2021

IJMS

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This paper presents the results of structure–activity relationship (SAR) studies of 140 3,3’-(α,ω-dioxaalkan)bis(1-alkylimidazolium) chlorides. In the SAR analysis, the dominance-based rough set approach (DRSA) was used. For analyzed compounds, minimum inhibitory concentration (MIC) against strains of Staphylococcus aureus and Pseudomonas aeruginosa was determined. In order to perform the SAR analysis, a tabular information system was formed, in which tested compounds were described by means of condition attributes, characterizing the structure (substructure parameters and molecular descriptors) and their surface properties, and a decision attribute, classifying compounds with respect to values of MIC. DRSA allows to induce decision rules from data describing the compounds in terms of condition and decision attributes, and to rank condition attributes with respect to relevance using a Bayesian confirmation measure. Decision rules present the most important relationships between structure and surface properties of the compounds on one hand, and their antibacterial activity on the other hand. They also indicate directions of synthesizing more efficient antibacterial compounds. Moreover, the analysis showed differences in the application of various parameters for Gram-positive and Gram-negative strains, respectively.

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“… 28 In general, in the RS approach, the information is represented in the form of condition attributes C and decision attributes D . 30 The relation between the condition and the decision attributes in RS is defined by the indiscernibility degree of the data points handled using the concept of sets’ approximation. There are two main types of the approximation in RS, upper and lower, which are denoted as

and

, respectively; they are defined as follows in Equations 1 and 2 :

According to the determined upper and lower approximation of the sets, the accuracy of the classification results can be quantified as follows:

These approximations are the base of finding the reduction for data set.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The syntax of the decision rules usually has the form of logic expression or if … then rule. 30 , 31…”

Section: Problem Formulationmentioning

confidence: 99%

Computational tool for optimizing the essential oils utilization in inhibiting the bacterial growth

El-Attar¹,

Awad²

2017

AABC

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Day after day, the importance of relying on nature in many fields such as food, medical, pharmaceutical industries, and others is increasing. Essential oils (EOs) are considered as one of the most significant natural products for use as antimicrobials, antioxidants, antitumorals, and anti-inflammatories. Optimizing the usage of EOs is a big challenge faced by the scientific researchers because of the complexity of chemical composition of every EO, in addition to the difficulties to determine the best in inhibiting the bacterial activity. The goal of this article is to present a new computational tool based on two methodologies: reduction by using rough sets and optimization with particle swarm optimization. The developed tool dubbed as Essential Oil Reduction and Optimization Tool is applied on 24 types of EOs that have been tested toward 17 different species of bacteria.

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Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-quaternary Ammonium Chlorides

Cited by 5 publications

References 10 publications

Antimicrobial Activity and SAR Study of New Gemini Imidazolium‐Based Chlorides

Antimicrobial Activity and SAR Study of New Gemini Imidazolium‐Based Chlorides

Structure-Activity Relationships of the Imidazolium Compounds as Antibacterials of Staphylococcus aureus and Pseudomonas aeruginosa

Computational tool for optimizing the essential oils utilization in inhibiting the bacterial growth

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