Analysis of Relationships Between Structure, Surface Properties, and Antimicrobial Activity of Quaternary Ammonium Chlorides

Krysiński, Jerzy; Płaczek, Jakub; Skrzypczak, Andrzej; Błaszczak, Jan; Prędki, Bartłomiej

doi:10.1002/qsar.200860135

Cited by 6 publications

(4 citation statements)

References 26 publications

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“…This study was followed by another on the relationship between structure, surface properties, and antimicrobial activity of quaternary ammonium chlorides in two microbial strains, which gave less conclusive results but was still able to give some guidelines for desirable structural properties for antimicrobial activity against one of the strains. 98 The Krysinski group still work in this area. Their most recent publication analyzing the SAR of antimicrobial activity of imidazolium chloride compounds was published in 2014.…”

Section: Applicationsmentioning

confidence: 99%

“…The remaining rules could be used to aid decisions about the synthesis of further active compounds. This study was followed by another on the relationship between structure, surface properties, and antimicrobial activity of quaternary ammonium chlorides in two microbial strains, which gave less conclusive results but was still able to give some guidelines for desirable structural properties for antimicrobial activity against one of the strains . The Krysinski group still work in this area.…”

Section: Applicationsmentioning

confidence: 99%

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Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis

Gardiner

Gillet

2015

J. Chem. Inf. Model.

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Knowledge Discovery in Databases (KDD) refers to the use of methodologies from machine learning, pattern recognition, statistics, and other fields to extract knowledge from large collections of data, where the knowledge is not explicitly available as part of the database structure. In this paper, we describe four modern data mining techniques, Rough Set Theory (RST), Association Rule Mining (ARM), Emerging Pattern Mining (EP), and Formal Concept Analysis (FCA), and we have attempted to give an exhaustive list of their chemoinformatics applications. One of the main strengths of these methods is their descriptive ability. When used to derive rules, for example, in structure-activity relationships, the rules have clear physical meaning. This review has shown that there are close relationships between the methods. Often apparent differences lie in the way in which the problem under investigation has been formulated which can lead to the natural adoption of one or other method. For example, the idea of a structural alert, as a structure which is present in toxic and absent in nontoxic compounds, leads to the natural formulation of an Emerging Pattern search. Despite the similarities between the methods, each has its strengths. RST is useful for dealing with uncertain and noisy data. Its main chemoinformatics applications so far have been in feature extraction and feature reduction, the latter often as input to another data mining method, such as an Support Vector Machine (SVM). ARM has mostly been used for frequent subgraph mining. EP and FCA have both been used to mine both structural and nonstructural patterns for classification of both active and inactive molecules. Since their introduction in the 1980s and 1990s, RST, ARM, EP, and FCA have found wide-ranging applications, with many thousands of citations in Web of Science, but their adoption by the chemoinformatics community has been relatively slow. Advances, both in computer power and in algorithm development, mean that there is the potential to apply these techniques to larger data sets and thus to different problems in the future.

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Section: Applicationsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis

Gardiner

Gillet

2015

J. Chem. Inf. Model.

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“…Moreover they may be used in cosmetics industries [10,11], nanomaterials synthesis or pharmaceuticals [12,13]. Besides they have biological active properties, which is the reason why they are very often used as bactericidals, fungicidals [13] and also as herbicides [6,[14][15][16][17][18][19]. Pyridine oximes and their quaternary salts are also used as selective and efficient extractants in metals recovery from aqueous solution [20,21].…”

Section: Introductionmentioning

confidence: 99%

Synthesis and Spectral Analysis of Pyridine Derivates

Wojciechowska¹,

Wieszczycka²,

Framski³

2017

MOCR

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The present study described a detailed investigation of the synthesis of novel quaternary pyridinium salts: derivates of 1-(3-pyridine)undecane-1-one (1-propyl-3-undecanoylpyridinium bromide and 1-propyl-3-undecanoylpyridinium chloride) and N-decyloxypyridine-3-carboximidamide (3-[1-(N-decyloxyimine)ethyl]-1-propylpyridinium chloride and 3-[1-(N-decyloxyimine)ethyl]-1propylpyridinium bromide). The structures of the products were confirmed by spectral( 1 H-NMR, 13 C-NMR, FT-IR) analysis, mass spectrometry methods. Estimation of the pharmacotherapeutic potential has been accomplished for synthesized compounds on the basis of Prediction of Activity Spectra for Substances (PASS programe).

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“…These tests were based on statistical methods (regression) and non-statistical methods (artificial neural networks) [22,23]. Classical rough set approach was also applied in SAR analysis [14].…”

Section: Introductionmentioning

confidence: 99%

Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-Quaternary Imidazolium Chlorides

Pałkowski

Krysiński

Błaszczyński

et al. 2014

Fundamenta Informaticae

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The paper investigates relationships between chemical structure, surface active properties and antibacterial activity of 70 bis-quaternary imidazolium chlorides. Chemical structure and properties of imidazolium chlorides were described by 7 condition attributes and antimicrobial properties were mapped by a decision attribute. Dominance-based Rough Set Approach (DRSA) was applied to discover a priori unknown rules exhibiting monotonicity relationships in the data, which hold in some parts of the evaluation space. Strong decision rules discovered in this way may enable creating prognostic models of new compounds with favorable antimicrobial properties. Moreover, relevance of the attributes estimated from the discovered rules allows to distinguish which of the structure and surface active properties describe compounds that have the most preferable and the least preferable antimicrobial properties.

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Analysis of Relationships Between Structure, Surface Properties, and Antimicrobial Activity of Quaternary Ammonium Chlorides

Cited by 6 publications

References 26 publications

Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis

Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis

Synthesis and Spectral Analysis of Pyridine Derivates

Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-Quaternary Imidazolium Chlorides

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