Antimicrobial Activity and SAR Study of New GeminiImidazolium-Based Chlorides

Łukasz Pałkowski1,*, Jerzy Błaszczy�nski2,Andrzej Skrzypczak3, Jan Błaszczak3, KarolinaKozakowska1, Joanna Wr�oblewska4, SylwiaKo _zuszko4, Eugenia Gospodarek4, JerzyKrysi�nski1 and Roman Słowi�nski2,5

1Department of Pharmaceutical Technology, NicolausCopernicus University, Jurasza 2, 85-094 Bydgoszcz,Poland2Institute of Computing Science, Pozna�n University ofTechnology, Piotrowo 2, 60-965 Pozna�n, Poland3Institute of Chemical Technology, Pozna�n University ofTechnology, Skłodowskiej-Curie 2, 60-965 Pozna�n, Poland4Department of Microbiology, Nicolaus CopernicusUniversity, Skłodowskiej-Curie 9, 85-094 Bydgoszcz,Poland5Systems Research Institute, Polish Academy of Sciences,Newelska 6, 01-447 Warsaw, Poland*Corresponding author: Łukasz Pałkowski,lukaszpalkowski@cm.umk.pl

A series of 70 new 3,3´(a,x-dioxaalkyl)bis(1-alkylimi-dazolium) chlorides were synthesized. They werecharacterized with respect to surface active propertiesand antimicrobial activity against the following patho-gens: Staphylococcus aureus, Enterococcus faecalis,Acinetobacter baumannii, Escherichia coli, Klebsiellapneumoniae, Enterobacter cloacae, Pseudomonasaeruginosa, Candida krusei, and Candida albicans. Inthis article, besides description of the synthesis, wecharacterize a set of features of these compounds,concerning their structure (described by the length ofthe dioxaalkan spacer and the length of the alkyl sub-stituent in the aromatic ring) and surface active proper-ties (critical micelle concentration, value of surfacetension at critical micelle concentration, value of sur-face excess, molecular area of a single particle, andfree energy of adsorption of molecule). Then, we pres-ent a SAR study for Staphylococcus aureus, as one ofthe most widespread pathogenic strains, conductedwith the help of the Dominance-based Rough SetApproach (DRSA), that involves identification of rele-vant features and relevant combinations of featuresbeing in strong relationship with a high antimicrobialactivity of the compounds. The SAR study shows,moreover, that the antimicrobial activity is dependenton the type of substituents and their position at thechloride moiety, as well as on the surface activeproperties of the compounds.

Key words: cheminformatics, drug design, structure-baseddrug design

Received 11 March 2013, revised 6 September 2013 andaccepted for publication 9 September 2013

Cationic surfactants such as ammonium, phosphonium,pyridinium, and imidazolium salts have good biocidal activ-ity against broad spectrum of bacteria, fungi, and algae(1). Those compounds might also be used as anticorrosiveand anti-electrostatic agents in cosmetic, textile, and phar-maceutical industries, as a biocides in wood protectionand in the agriculture as antifungal agents (2,3). The char-acteristics of these compounds: the broad spectrum ofantimicrobial activity, low toxicity, good stability, and lackof odor of usable solutions are the reasons for the com-pounds’ wide usage as disinfectant, as cleaning agents infood and pharmaceutical industries and in hospitals (4).Bis-quaternary ammonium chlorides are a group of com-pounds with good antimicrobial activity (5–7). Bis-imidazoli-um derivatives are characterized by good surfaceproperties (8–10). Nevertheless, some microbial strainsmight become resistant to those compounds over thetime. Those various properties of imidazolium salts formthe base for seeking and synthesizing new, active prod-ucts. Numerous tests indicated that chemical and antimi-crobial properties of gemini imidazolium-based chloridesdepend on their structure (e.g. length of alkyl group) (11).The hydrophobic part of the molecule (alkyl chain) enablespenetration through the cell membrane, induce its damageand exchange of extracellular with intracellular fluids, whichlead to cell lysis and its death (12).

In the SAR analysis of the chemical compounds, differentchemometric statistical and nonstatistical methods (artificialneural networks, principal component analysis, parametricstatistic: regression, correlation) have been used. In ourstudy, we used a method based on rough set theory. Thismethod is called Dominance-based Rough Set Approach(DRSA) (13) and yields a description of structure-activityrelationships in terms of easily interpretable ‘if…, then…’decision rules.

In this work, we synthesized a new group of 3,3′(a,x-dioxaalkyl)bis(1-alkylimidazolium) chlorides, then determinedtheir surface properties and antimicrobial activity and finallywe performed SAR analysis using DRSA.

278 ª 2013 John Wiley & Sons A/S. doi: 10.1111/cbdd.12236

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Research Article

Methods and Materials

MaterialsAll reagents were obtained from Sigma-Aldrich or POCH(Gliwice, Poland).

Synthesis1-Alkylimidazoles, besides 1-methyl- and 1-butylimidazole,were synthesized according to the procedure describedearlier (14,15). Sodium (2.3 g/mol) was added to 75 mL ofanhydrous methanol and the imidazole (0.1 mol) was dis-solved. The appropriate amount (0.11 mol) of one of thebromoalkane: bromoethane, 1-bromopropane, 1-bromo-pentane, 1-bromohexane, 1-bromoheptane, 1-bromooc-tane, 1-bromononane, 1-bromodecane, 1-bromoundecane,1-bromododecane, 1-bromotetradecane, or 1-bromohex-adecane was added and the mixture was stirred for 6 h at65 °C. Precipitated sodium bromide was filtered and themethanol was removed. The final product, 1-ethyl-, 1-propyl-,1-pentyl-, 1-hexyl-, 1-heptyl-, 1-octyl-, 1-nonyl-, 1-decyl-,1-undecyl-, 1-dodecyl-, 1-tetradecyl-, 1-hexadecylimidazole,was twice distilled under reduced pressure (1 Torr). The yieldswere between 63% and 92% (Figure 1).

The degree of purity was determined using a HewlettPackard gas chromatograph 5890 Series II equipped witha capillary column HP-5 and a flame ionization detector tocheck the purity of samples under study. All samples werewith the purity of 99.9%.

a,x-Di(chloromethoxy)alkanes were obtained by passingHCl-gas through a mixture of formaldehyde and appropri-ate a,x-diol according to the procedure described earlier(16). Of 0.2 mol of appropriate a,x-diol was dissolved intoluene and 0.21 mol of formaldehyde was added. Then,through the stirred mixture 5 mol of HCl-gas was passedfor 2 h at 17 °C (Figure 2).

When the reaction was finished, the water phase andexcess of formaldehyde was removed and the finalproduct,1,2-di(chloromethoxy)ethane,1,3-di(chloromethoxy)propane,1,4-di(chloromethoxy)butane,1,5-di(chloromethoxy)pentane, 1,6-di(chloromethoxy)hexane, was twice distilledunder reduced pressure (1 Torr). The yields were between87% and 98%. The purity was controlled using a HewlettPackard gas chromatograph 5890 Series II equipped with

a capillary column HP-5 and a flame ionization detector tocheck the purity of samples under study. All samples werewith the purity of 99.6–99.8%.

All a,x-di(chloromethoxy)alkanes readily hydrolyzed in thepresence of small amount of water to form HCl, which inturn gives the 1-alkylimidazolium hydrochlorides. The sep-aration of the quaternization product and hydrochloride ispractically impossible. For this reason, quaternization reac-tions with a,x-di(chloromethoxy)alkanes were conductedunder strictly anhydrous conditions. The nucleophilicsubstitution is a specific type of Menschutkin reaction thatinvolves a SN1 mechanism. The initial rate-determiningstep involves the formation of the dimeric cation+CH2O(CH2)nOCH2

+. The obtained cation rapidly reactswith 1-alkylimidazole giving a very high yield (92.7–98.5%)of 70 gemini imidazolium based chlorides, which haveappropriate CH2O(CH2)nOCH2 spacer in the structure(Figure 3).

The synthesized compounds were determined on thebasis of NMR spectra (Bruker NMR spectrometer with tet-ramethylsilane as an internal standard), and their puritywas confirmed by thin-layer chromatography (TLC Mercksilica gel 60 F254 plates) and elemental analysis (Element-er Analyzensystem Vario EL III; see Table S1).

Surface active properties evaluationThe surface tension was measured using Kruss K12 tensi-ometer equipped with du Nouy Pt-Ir ring. All compoundswere diluted with triply distilled water. Measurements ofthe surface tension were made under atmospheric pres-sure, at the temperature of 20 � 0.01 °C, after the solu-tion tested reached the temperature equilibrium using atemperature-controlled bath. All measurements of surfacetension were repeated three times and each datum is anaverage of three individual points, with an accuracy of�0.2 mN/m.

Surface active properties of synthesized chlorides weredescribed by the following parameters: critical micelle con-centration (CMC; mol/L), value of surface tension at criticalmicelle concentration (cCMC; mN/m with an accuracy of�0.2 mN/m), value of surface excess (Γ 9 106; mol/m2

with an accuracy of 106 � 0.02 mol/m2;), molecular areaof a single particle (A 9 1020; m2 with an accuracy of

Figure 1: Synthesis of 1-alkylimidazoles.

Figure 2: Synthesis of α,x-di(chloromethoxy)alkanes.

Chem Biol Drug Des 2014; 83: 278–288 279

Antimicrobial Activity of New Gemini Chlorides

1020 � 0.08 m2), and free energy of adsorption of mole-cule (ΔGads; kJ/mol with an accuracy of � 0.2kJ/mol).

Strains and growth conditionThe antimicrobial activity of synthesized chlorides wastested against: Staphylococcus aureus ATCC 25213,Staphylococcus aureus MR-3 (methicillin resistant), Entero-coccus faecalis ATCC 29212, Escherichia coli ATCC25922, Klebsiella pneumoniae ATCC 700603, Pseudomo-

nas aeruginosa ATCC 27853, Acinetobacter baumanii

(multidrug resistant), Enterobacter cloacae, Candida albi-

cans ATCC 90028, and Candida krusei ATCC 6258. Allmicrobial strains were stored at �80 °C in Cryovial vials(Simport, Canada) and subcultured in M€uller Hinton brothbefore testing.

Minimum inhibitory concentration determinationBacterial, fungal suspensions with a turbidity equivalent tothat of a 0.5 McFarland standard were prepared by sus-pending growth from blood Trypticase Soy Agar (TSA,BBL) plates in 2 mL of sterile saline. The antibacterialeffects of gemini imidazolium-based chlorides were evalu-ated by determination of Minimal Inhibitory Concentration(MIC, % w/V) values using the disk-diffusion method rang-ing from 1.0 to 0.000125 and the control plate withoutdisinfectant. The test medium was Mueller–Hinton Agar(bio-M�erieux). The MIC was determined as the lowest con-centration of the tested agent at which no visible bacterialgrowth could be detected. A barely visible haze of growthwas disregarded. MIC was read at 37 °C, after 24 or 48 h

culture for the other bacteria and for Candida spp. Detailsof the agar dilution procedure for testing microorganismshave been published by Clinical and Laboratory StandardsInstitute (17).

Rough set-based SAR studyIn the course of the analysis, jRS and jMAF softwarebased on DRSA methodology were useda DRSA (13) waschosen as the most suitable method to discover syntheticrules that exhibit monotonic relationships between struc-ture and surface active properties of the compounds on

Figure 3: Synthesis of gemini imidazolium based chlorides.

Table 1: Numerical coding of the structure condition attributes

Code

Condition attributes

n R

1 CH3

2 C2H4 C2H5

3 C3H6 C3H7

4 C4H8 C4H9

5 C5H10 C5H11

6 C6H12 C6H13

7 C7H15

8 C8H17

9 C9H19

10 C10H21

11 C11H23

12 C12H25

14 C14H29

16 C16H33

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Table 2: Minimum inhibitory concentration for analyzed compounds

Compound

MIC (mM/L)

Sau MR-3 Efae Aba Eco Kpn Ecl Pae Ckr Cal

1 33.875 33.875 33.875 33.875 33.875 33.875 33.875 33.875 16.9372 28.468 28.468 28.468 28.468 28.468 28.468 28.468 14.234 3.5583 13.181 13.181 13.181 13.181 13.181 13.181 13.181 13.181 3.2954 6.590 6.590 6.590 6.590 6.590 13.180 13.180 1.634 1.6345 5.741 11.483 5.741 5.741 5.741 11.483 11.483 0.712 0.7126 2.697 10.788 10.788 1.338 5.394 5.394 10.788 0.669 0.0867 0.326 2.543 2.543 0.631 2.543 1.261 5.086 0.020 0.0208 0.077 0.308 0.597 0.308 0.597 0.308 1.193 0.010 0.0059 0.037 0.037 0.146 0.073 0.566 0.146 1.132 0.002 0.002

10 0.017 0.017 0.278 0.017 0.538 0.139 0.538 0.002 0.01711 0.017 0.017 0.265 0.017 0.513 0.265 0.513 0.002 0.01712 0.032 0.032 1.978 0.063 0.981 0.491 0.491 0.002 0.01613 0.116 0.029 1.817 0.451 1.817 0.901 1.817 0.002 0.11614 0.108 0.108 13.441 1.680 1.680 1.680 1.680 0.027 0.10815 14.826 29.652 29.652 29.652 29.652 29.652 29.652 0.237 29.65216 27.375 27.375 27.375 27.375 27.375 27.375 27.375 13.687 27.37517 25.423 25.423 6.356 12.711 25.423 25.423 25.423 1.576 6.35618 5.933 5.933 11.865 5.933 5.933 5.933 5.933 2.966 5.93319 1.112 22.249 5.562 5.562 11.125 11.125 22.249 1.379 1.37920 2.618 5.235 0.649 2.618 5.235 2.618 10.471 0.649 0.08221 0.158 0.158 0.613 1.226 0.613 0.613 4.945 0.077 0.15822 0.009 0.036 0.150 0.300 0.581 0.581 1.162 0.150 0.00923 0.069 0.069 0.069 0.142 0.552 0.069 4.451 0.009 0.03424 0.008 0.008 0.526 0.008 0.271 0.136 0.526 0.032 0.00825 0.008 0.008 0.502 0.259 0.502 0.502 0.502 0.008 0.08126 0.008 0.124 0.960 0.124 0.480 0.480 15.484 0.008 0.00827 0.056 0.056 7.123 0.883 7.123 7.123 7.123 0.007 0.01428 0.211 0.106 13.192 1.649 6.596 1.649 13.192 0.013 0.10629 28.468 28.468 28.468 28.468 28.468 28.468 28.468 0.114 7.11730 26.363 26.363 26.363 26.363 26.363 26.363 26.363 6.591 3.29531 26.360 26.360 3.295 26.360 26.360 26.360 26.360 3.295 3.29532 2.871 22.966 11.483 0.712 22.966 22.966 11.483 2.871 0.71233 0.345 2.697 2.697 10.788 5.394 10.788 10.788 1.338 0.17334 0.079 0.079 1.261 2.543 1.261 1.261 5.086 0.326 0.01035 0.010 0.308 0.308 1.193 0.308 0.597 1.193 0.010 0.01036 0.009 0.018 0.146 0.292 0.146 0.566 2.283 0.009 0.00937 0.009 0.009 0.278 0.139 0.069 0.278 0.278 0.009 0.00938 0.008 0.008 0.066 0.265 0.133 0.265 0.066 0.008 0.00839 0.008 0.008 0.981 0.032 0.063 0.063 3.957 0.008 0.00840 0.061 0.061 0.470 0.470 0.940 0.940 0.940 0.008 0.03041 0.056 0.056 0.056 0.112 0.433 0.433 0.223 0.028 0.00742 0.052 0.207 12.952 0.052 0.052 0.052 12.952 0.006 0.10443 27.375 27.375 27.375 27.375 27.375 27.375 27.375 0.109 6.84444 25.423 25.423 25.423 25.423 25.423 25.423 25.423 6.356 3.17845 5.933 23.730 11.865 23.730 23.730 23.730 23.730 2.966 0.73646 2.781 22.249 22.249 22.249 2.781 2.781 11.125 0.779 0.69047 0.168 5.235 10.471 5.235 20.942 20.942 20.942 0.008 0.16848 0.158 4.945 19.780 4.945 4.945 4.945 2.472 9.890 0.15849 0.019 0.300 1.162 0.581 18.740 18.740 18.740 0.075 0.09450 0.142 2.226 4.451 4.451 0.285 0.285 2.226 0.142 0.07151 0.008 0.034 0.068 0.034 2.120 2.120 0.136 0.085 0.00852 0.008 0.008 0.129 0.016 0.259 0.129 0.065 0.065 0.00453 0.015 0.031 0.062 0.062 0.062 0.062 0.248 0.004 0.00454 0.030 0.030 0.119 0.059 0.119 0.059 0.460 0.004 0.03055 0.055 0.110 0.110 0.110 0.425 0.110 0.849 0.003 0.02756 0.102 0.102 1.590 0.204 1.590 0.789 12.721 0.006 0.10257 13.181 6.591 6.591 6.591 3.295 3.295 26.363 0.026 1.63458 0.817 13.180 26.360 13.180 26.360 26.360 26.360 0.105 1.63459 0.712 22.966 22.966 2.871 22.966 22.966 22.966 11.483 0.712

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Antimicrobial Activity of New Gemini Chlorides

the one hand, and their antimicrobial properties on theother hand. It is well suited for this application because ithandles qualitative and quantitative attributes, without theneed of discretization of quantitative attributes or transfor-mation of qualitative attributes into quantitative ones.DRSA is also able to deal with possible inconsistencies inthe information table prior to induction of rules. Moreover,it handles global or local monotonic relationships betweenvalues of condition attributes and quality of the decisionclass. These characteristics of DRSA perfectly fit the typeof data to be analyzed. Using this method, we obtain deci-sion rules with ranges of values of condition attributes inparticular classes of activity. The rules are useful for syn-thesis of new chemical entities with good antimicrobialcharacteristics.

Information table is the basis of SAR analysis of thechemical compounds. It includes a set of objects (inrows) described by a set of attributes (in columns). Theset of attributes is composed of condition and decisionattributes. In our case, condition attributes describe sur-face active properties and structure of analyzed chlo-rides. The decision attribute concerns antimicrobialproperties of bis-quaternary imidazolium chlorides repre-sented by 3 classes of values of MIC for Staphylococcusaureus ATCC 25213 in the following way: class of goodantimicrobial properties: MIC ≤ 0.02 mM/L, class of med-ium antimicrobial properties: 0.02 < MIC < 1 mM/L, classof weak antimicrobial properties: MIC ≥ 1 mM/L. Numeri-cal coding of the structure condition attributes is pre-sented in Table 1. The synthesized chlorides are listed inTable 3.

Results and Discussion

The antimicrobial activity of synthesized gemini imidazolium-based chlorides is presented in Table 2.

The bacteriostatic activity of imidazolium chloridesdepends on the species of the strains and the structure ofcompounds. The highest values of MIC were obtained forPseudomonas aeruginosa ATCC 27853, Enterobacter

cloacae, and Klebsiella pneumaniae ATCC 700603. Thelowest values of MIC were obtained for staphylococci,including the methicillin-resistant one. Low values of MICwere also obtained for Candida yeasts. Chlorides withshort R-alkyl substituent (methyl to pentyl, compounds:1–5, 15–19, 29–33, 43–47, 57–61) possess the weakestantibacterial action. The most active are those with R-alkylchain from octyl to dodecyl one (compounds: 8–12,22–26, 36–40, 50–54, 64–68). The activity of chlorideswith tetradecyl and hexadecyl substituents is decreasing.

In Table 3 surface active properties, structure of analyzedcompounds (according to Table 1 and Figure 2) and theirantimicrobial activity against Staphylcoccus aureus ATCC

25213 are presented. This table forms an information tablein SAR analysis.

Decision rulesDecision rules represent the most important cause–effectrelationships between values of condition attributes andthe class assignment. A decision rule induced from aninformation table is denoted as E ? H, which reads as ‘ifE, then H ‘. A rule consists of a condition part (called alsopremise or evidence) E, and a conclusion (called also deci-sion part or prediction, or hypothesis) H. Considering afinite set of condition attributes C = {q1, q2,… qn}, the con-dition part of the rule is a conjunction of elementary condi-tions on a particular subset of attributes:

E = ei1 ^ ei2 ^…^eip, where {i1, i2,… ip} � {1, 2,…, n},p ≤ n, and eih is an elementary condition defined on thevalue set of attribute qih, h 2 {i1, i2,… ip} (e.g.,eih ≡ qih > 0.5 or eih ≡ qih = 1 or eih ≡ qih 2 [0.5, 1]).

Table 2: continued

Compound

MIC (mM/L)

Sau MR-3 Efae Aba Eco Kpn Ecl Pae Ckr Cal

60 0.669 5.394 21.576 2.697 21.576 21.576 2.697 0.669 0.34561 0.041 0.163 5.086 0.326 10.172 20.344 5.086 0.631 0.01062 0.077 0.154 2.406 0.308 0.597 0.308 1.193 2.406 0.03863 0.018 0.037 0.566 0.073 0.292 0.292 0.566 0.009 0.00564 0.009 0.009 0.139 0.009 0.278 0.139 1.077 0.035 0.00265 0.017 0.033 0.066 0.017 0.133 0.133 0.033 0.004 0.00866 0.004 0.004 0.063 0.004 0.253 0.127 0.016 0.002 0.00267 0.015 0.015 0.015 0.030 0.030 0.030 0.470 0.002 0.00868 0.029 0.029 0.233 0.116 0.233 0.058 3.634 0.002 0.01569 0.108 0.108 3.360 1.680 0.417 0.108 0.417 0.002 0.05470 0.100 0.050 1.562 0.387 3.125 6.249 1.562 0.006 0.100

Sau MR-3, Staphylococcus aureus MR-3; Efae, Enterococcus feacalis ATCC19212; Aba, Acinetobacter baumani; Eco, Escherichia coli

ATCC 25922; Kpn, Klebsiella pneumaniae ATCC 700603; Ecl, Enterobacter cloacae; Pae, Pseudomonas aeruginosa ATCC 27853;Ckr, Candida krusei ATCC 6258; Cal, Candida albicans ATCC 90028.

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Table 3: SAR table (Information table)

No

Condition attributes

MIC (mM/L) Classn R �lgCMC cCMC Γ�106 A�1020 ΔGads

1 C2H5 CH3 2.15 61.9 2.75 52 20.2 33.875 weak2 C2H5 C2H5 2.23 60.1 2.71 54 20.8 28.468 weak3 C2H5 C3H7 2.38 59.8 2.69 56 21.3 13.181 weak4 C2H5 C4H9 2.41 57.4 2.65 58 21.7 6.590 weak5 C2H5 C5H11 2.49 55.5 2.61 60 22.3 5.741 weak6 C2H5 C6H13 2.58 53.4 2.57 62 22.7 1.338 weak7 C2H5 C7H15 2.65 51.2 2.53 64 23.5 0.163 medium8 C2H5 C8H17 2.72 48.9 2.49 66 23.9 0.038 medium9 C2H5 C9H19 2.81 47.5 2.45 68 24.3 0.018 good

10 C2H5 C10H21 2.92 45.3 2.41 70 24.8 0.017 good11 C2H5 C11H23 3.04 42.5 2.37 72 25.6 0.017 good12 C2H5 C12H25 3.15 41.4 2.33 74 26.3 0.032 medium13 C2H5 C14H29 3.34 37.5 2.25 78 27.5 0.058 medium14 C2H5 C16H33 3.52 33.9 2.17 82 28.8 0.108 medium15 C3H7 CH3 2.18 60.8 2.74 54 20.5 29.652 weak16 C3H7 C2H5 2.26 58.9 2.70 56 21.1 27.375 weak17 C3H7 C3H7 2.32 57.8 2.66 58 21.6 25.423 weak18 C3H7 C4H9 2.44 56.3 2.62 60 22.0 5.933 weak19 C3H7 C5H11 2.52 54.4 2.58 62 22.6 5.562 weak20 C3H7 C6H13 2.61 52.3 2.54 64 23.0 1.298 weak21 C3H7 C7H15 2.68 50.1 2.59 66 23.8 0.158 medium22 C3H7 C8H17 2.75 47.9 2.46 68 24.2 0.009 good23 C3H7 C9H19 2.84 46.4 2.42 70 24.6 0.069 medium24 C3H7 C10H21 2.95 44.2 2.38 72 25.1 0.008 good25 C3H7 C11H23 3.07 42.4 2.34 74 25.9 0.016 good26 C3H7 C12H25 3.18 40.3 2.30 76 22.6 0.008 good27 C3H7 C14H29 3.37 36.4 2.22 80 27.7 0.056 medium28 C3H7 C16H33 3.55 32.8 2.14 84 29.1 0.106 medium29 C4H9 CH3 2.22 59.6 2.71 56 20.9 28.468 weak30 C4H9 C2H5 2.30 57.7 2.67 58 21.4 6.591 weak31 C4H9 C3H7 2.39 56.6 2.63 60 21.9 13.180 weak32 C4H9 C4H9 2.45 55.1 2.59 62 22.3 0.712 medium33 C4H9 C5H11 2.53 53.2 2.55 64 22.9 0.345 medium34 C4H9 C6H13 2.64 51.1 2.51 66 23.3 0.079 medium35 C4H9 C7H15 2.71 48.9 2.47 68 23.9 0.010 good36 C4H9 C8H17 2.79 46.7 2.43 70 24.5 0.009 good37 C4H9 C9H19 2.88 45.2 2.39 72 24.9 0.009 good38 C4H9 C10H21 3.00 43.0 2.35 74 25.4 0.008 good39 C4H9 C11H23 3.13 41.2 2.31 76 26.2 0.032 medium40 C4H9 C12H25 3.22 39.2 2.27 78 26.9 0.061 medium41 C4H9 C14H29 3.40 35.2 2.19 82 28.0 0.028 medium42 C4H9 C16H33 3.58 31.5 2.11 86 29.3 0.052 medium43 C5H11 CH3 2.25 58.5 2.68 58 21.2 27.375 weak44 C5H11 C2H5 2.33 56.6 2.64 60 21.7 25.423 weak45 C5H11 C3H7 2.41 55.7 2.60 62 22.2 5.933 weak46 C5H11 C4H9 2.49 53.9 2.56 64 22.7 0.178 medium47 C5H11 C5H11 2.58 52.1 2.52 66 23.2 2.618 weak48 C5H11 C6H13 2.67 50.1 2.48 68 23.7 0.158 medium49 C5H11 C7H15 2.75 47.8 2.44 70 24.2 0.019 good50 C5H11 C8H17 2.83 45.6 2.40 72 24.8 0.142 medium51 C5H11 C9H19 2.91 44.0 2.36 74 25.3 0.008 good52 C5H11 C10H21 3.07 41.9 2.32 76 25.9 0.004 good53 C5H11 C11H23 3.16 40.1 2.28 78 26.5 0.015 good

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The rules induced from the information table structuredusing DRSA represent all relevant patterns of cause–effectrelationships, which are free of inessential and redundantinformation. The rules that are considered in DRSA aremainly certain rules. This kind of rules covers consistentobjects only. To represent the most important cause–effectdependencies between values of condition attributes andvalue of decision attribute, decision rules are not onlyinvolving important condition attributes but they alsoinclude a minimal number of elementary conditions indis-pensable for representation of the dependencies. The setof decision rules may be understood as a representationof cause–effect relationships existing in the informationtable, from which all inessential and redundant informationwas removed.

Table 4 includes those from among all decision rules thatcover compounds from Table 3 belonging to ‘good’ or‘weak’ class, which are strong and relevant. We do notinduce rules for class ‘medium’ since these rules are notinteresting from the view point of SAR analysis (it is moreimportant to know what are the features of chlorides withdefinitely good or weak antimicrobial properties). Note, how-ever, that the presence of chlorides from the ‘medium’ classis important in the rule induction process. The rules withconclusion ‘good’ discriminate chlorides with ‘good’ antimi-crobial properties from those chlorides which have ‘med-ium’ or ‘weak’ properties (analogously for rules withconclusion ‘weak’). The decision rules from Table 4 can beviewed as the most interesting certain patterns among allpatterns that can be found to describe features of chlorides

from Table 3. In particular, these decision rules involve spe-cific values of condition attributes describing structure andsurface active properties. The rules are characterized byvarious parameters, such as examples (i.e., number ofobjects covering a given rule), strength (i.e. the proportion ofobjects covered by premise that are also covered by conclu-sion), or confirmation (i.e. measure that is quantifying thedegree to which premise provides evidence for conclusion;see Appendix S1). Strong decision rules are supported bymajority of objects from the class that they refer to, while rel-evant decision rules are characterized by high values ofBayesian confirmation measures. The rules presented inTable 4 cover 60% of chlorides that belong to class ‘good’and 95% of chlorides that belong to class ‘weak’. Thus, onecan conclude that chlorides with good antimicrobial proper-ties are more diverse and they are harder to describe bystrong (and relevant) rules. The decision rules provide guide-lines for synthesis of new compounds with better antimicro-bial properties. In decision rules covering chlorides with goodantimicrobial activity, the attribute n-spacer length is absent,while attributes describing the surface active properties ofanalyzed compounds are often present. Moreover, the valueof R-chain in these rules ranges from 6 to 11 (the alkyl chainlonger than hexyl and shorter than undecyl one), �logCMCvalues are in the range (2.71; 3.13), values of surface tensionat critical micelle concentration are below 46.4, values of sur-face excess are below 2.42, and values of free energy ofadsorption of molecule are >24.6. In decision rules coveringchlorides with weak antimicrobial activity, value of n-chain isbelow 6 (the spacer shorter than [1,10-(2,9-dioxadecane)]),value of �logCMC is below 2.68, value of surface tension at

Table 3: continued

No

Condition attributes

MIC (mM/L) Classn R �lgCMC cCMC Γ�106 A�1020 ΔGads

54 C5H11 C12H25 3.25 38.1 2.24 80 27.1 0.030 medium55 C5H11 C14H29 3.43 33.9 2.16 84 28.3 0.027 medium56 C5H11 C16H33 3.61 29.6 2.08 88 29.6 0.204 medium57 C6H13 CH3 2.29 47.1 2.73 56 29.3 6.591 weak58 C6H13 C2H5 2.37 44.8 2.66 59 30.2 0.817 medium59 C6H13 C3H7 2.45 42.6 2.59 62 30.9 0.712 medium60 C6H13 C4H9 2.54 39.4 2.53 65 31.5 0.669 medium61 C6H13 C5H11 2.62 37.6 2.47 68 32.1 0.041 medium62 C6H13 C6H13 2.71 36.3 2.41 71 32.6 0.077 medium63 C6H13 C7H15 2.79 35.1 2.34 74 33.1 0.018 good64 C6H13 C8H17 2.87 34.2 2.28 77 33.6 0.009 good65 C6H13 C9H19 2.95 33.3 2.22 80 34.0 0.017 good66 C6H13 C10H21 3.07 32.2 2.15 83 34.4 0.004 good67 C6H13 C11H23 3.20 31.2 2.09 86 34.8 0.015 good68 C6H13 C12H25 3.29 30.3 2.03 89 35.2 0.029 medium69 C6H13 C14H29 3.47 28.3 1.90 95 36.1 0.027 medium70 C6H13 C16H33 3.65 26.4 1.77 101 37.1 0.100 medium

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CMC is over 44.8, value of surface excess is over 2.53, valueof molecular area of single particle is below 66, and value offree energy of adsorption of molecule is below 30.2.

As we mentioned earlier, the decision rules presented sofar can be seen as a representation of the most importantrelationships existing in the data table. Another aspectof applying DRSA to SAR analysis is the predictive power ofthe induced rules. Since the SAR table, that is the basis of

this analysis, consists of only 70 chlorides, we used 3-foldstratified cross-validation procedure to assess the predic-tive accuracy of rules. The cross-validation was repeated100 times to obtain better reproducibility of results. Thepredictive accuracy of DRSA decision rules was over 90%for both classes, that is sufficient to consider these rulesas useful guidelines for synthesis of compounds with bet-ter antimicrobial properties. The rules are further analyzedto assess relevance of the condition attributes.

Table 4: Decision rules

No

Condition attributes

Examples Strength (%) Confirmation measure c1n R �log CMC cCMC Γ 9 106 A 9 1020 ΔGads

Decision class good

1 (2.71, 3.13) <45.6 12 60 0.75862 >6 <3.13 <45.6 12 60 0.75863 <3.13 <45.6 <2.41 11 55 0.73304 <3.13 <45.6 >71 11 55 0.73305 >6 <3.13 >24.8 11 55 0.73306 <3.13 <2.41 >24.8 11 55 0.73307 (2.84, 3.13) 11 55 0.73308 (2.83, 3.13) <46.4 11 55 0.73309 (2.83, 3.13) <2.42 11 55 0.7330

10 <3.13 <2.40 11 55 0.733011 (2.83, 3.13) >24.6 11 55 0.733012 (2.71, 3.13) >24.8 11 55 0.733013 >8 <3.13 <2.42 10 50 0.708314 >8 <3.13 >24.6 10 50 0.708315 (6, 11) <45.6 10 50 0.708316 <11 >2.71 <45.6 10 50 0.7083

Decision class weak

17 >44.8 >2.59 16 80 0.870318 >2.59 <30.2 16 80 0.870319 >55.1 15 75 0.840920 <6 >2.59 15 75 0.840921 <2.45 >44.8 15 75 0.840922 <2.45 <30.2 15 75 0.840923 >44.8 <62 15 75 0.840924 <62 <30.2 15 75 0.840925 <6 <62 14 70 0.812526 <6 <2.45 14 70 0.812527 <22.3 14 70 0.812528 <4 >44.8 13 65 0.785029 <4 <30.2 13 65 0.785030 <4 <7 12 60 0.758631 <4 <2.65 12 60 0.758632 <4 >51.2 12 60 0.758633 <4 >50.1 >2.53 12 60 0.758634 <4 <2.68 >2.53 12 60 0.758635 <4 >2.53 <66 12 60 0.758636 <4 >2.53 <23.8 12 60 0.758637 <4 <12 <23.5 12 60 0.758638 <4 <3.18 <23.5 12 60 0.758639 <4 >40.3 <23.5 12 60 0.758640 <4 >2.30 <23.5 12 60 0.758641 <4 <76 <23.5 12 60 0.758642 <6 <4 12 60 0.758643 <59 12 60 0.7330

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Antimicrobial Activity of New Gemini Chlorides

Attribute relevanceWe consider attribute relevance measures that satisfy theproperty of Bayesian confirmation. These measures takeinto account interactions between attributes present in thedecision rules (18,19). In this case, the property of confir-mation is related to quantification of the degree to whichthe presence of an attribute in the premise of a rule pro-vides evidence for or against the conclusion of the rule.The measure increases when more rules involving an attri-bute suggest a correct decision, or when more rules thatdo not involve the attribute suggest an incorrect decision,otherwise it decreases (20,21).

The attributes with the highest values of confirmation mea-sure c1 are the most relevant from the view point of cor-rect class assignment of compounds to the MIC decisionclasses. We can observe, in Figure 4, that attributes: �logCMC (critical micelle concentration) and surface excesshave the highest impact on the correct assignment of theanalyzed compounds to the class good. On the otherhand, the assignment of the compounds to the class weakis influenced the most by attributes �log CMC and surfacetension at CMC.

Surface active properties and antimicrobial activity ofobtained bis-imidazolium compounds depend on thelength of spacer and on the type of alkyl substituent inimidazole ring. Clear dependence between bacteriostaticaction and structure was observed: in active compoundsthe longer the spacer (in certain range) the shorter R-alkyl

substituent with regard to two opposite homologousspacer type series of [1,6-(2,5-dioxahexane)] (n = 2) and[1,10-(2,9-dioxadecane)] one (n = 6). In the first one, theweakest bacteriostatic action was observed for com-pounds 1–6 (R substituent from methyl to hexyl) and 12–14(R substituent from dodecyl to hexadecyl). Compoundswith the strongest action are 9–11 (R substituent from no-nyl to undecyl). It is worth mentioning that the chloride 1with methyl substituent has the highest MIC value. In thehomologous series of [1,10-(2,9-dioxadecane)] (n = 6), thebest bacteriostatic action was observed for compounds63–67 (R from heptyl to undecyl). The activity of com-pounds with dodecyl to hexadecyl substituents was similarto the activity of compounds from [1,6-(2,5-dioxahexane)](n = 2) homologous series. According to literature data,compounds with high antimicrobial activity possess med-ium length alkyl substituents and a short spacer (22). Theoptimal activity was determined for the spacer with 4 car-bon atoms (23,24). When the spacer is longer than hexylone, the CMC values are relatively high and the antimicro-bial activity is decreasing (25).

Monotonic dependencies between chemical structure andsurface active properties of analyzed chlorides were alsoobserved (Table 3). In each homologous series, the longerwas R-alkyl substituent, the smaller were values of surfacetension at CMC and surface excess, and the greater werevalues of molecular area of single particle, and values offree energy of adsorption of molecule. Similarly, the longerwas the spacer, the greater were values of molecular area

Con

firm

atio

n m

easu

re c

1–0

.10

–0.0

6–0

.02

γ C

MC

γ C

MC n

ΔGad

s

ΔGad

s

A*1

020

A*1

020

R

–log

CM

C

Γ*10

6

Γ*10

6

Con

firm

atio

n m

easu

re c

1–0

.05

0.05

0.15

R n

–log

CM

C Figure 4: Predictive attributeconfirmation calculated for MICdecision classes: good (top) andweak (bottom).

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of single particle and free energy of adsorption. The valuesof surface tension at CMC and surface excess weredecreasing with elongation of the spacer.

It might be concluded that surface active propertiesinfluence strongly the antimicrobial activity. Structuralattributes are less significant. According to the literaturedata, physicochemical properties of quaternary com-pounds determine adsorption to the cell membrane andtheir penetration to the bacterial cell, and therefore its lysisas an effect of biocidal action (26–28). From the otherside, physicochemical properties of compounds aredependent on their structure. In this work, only two struc-tural and five surface active attributes were analyzed andthis could determine results of SAR analysis. From thispoint of view, it might be interesting to study the influenceof spacer longer than [1,10-(2,9-dioxadecane)] (n = 6) onsurface active properties and antimicrobial activity of 3,3′-[a,x-dioxaalkyl]bis(1-alkylimidazolium) derivatives.

Conclusions

Antimicrobial activity of gemini imidazolium-based chlorideswith dioxaalkyl spacer depends mainly on the length ofalkyl substituents in the aromatic ring. Moreover, elonga-tion of dioxaalkyl spacer might lead to active gemini imi-dazolium salts with shorter substituent in imidazole ring(heptyl, octyl). Obtained decision rules with their confirma-tion measures indicate directions of synthesis of newactive bis-imidazolium compounds. Dominance-basedrough set approach (DRSA) is a valuable tool in SARanalysis.

Acknowledgment

The second and the tenth author wish to acknowledgefinancial support from the Polish National Science Centre,grant no. DEC-2011/01/B/ST6/07318. The third authoracknowledge financial support from the Polish NationalScience Centre, grant no. NN 209437639.

Conflict of Interest

The authors have no conflict of interest to declare.

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Note

ahttp://www.cs.put.poznan.pl/jblaszczynski/Site/jRS.html

Supporting Information

Additional Supporting Information may be found in theonline version of this article:

Appendix S1. DRSA, confirmation measure, and chemis-try details.

Table S1. Bis-imidazolium quaternary chlorides – elementalanalysis.

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