Dibasic derivatives of phenylcarbamic acid against mycobacterial strains: Old drugs and new tricks?

molecules

Article

Dibasic Derivatives of Phenylcarbamic Acid against

Mycobacterial Strains: Old Drugs and New Tricks?

Ivan Malík ^1,*, Jozef Csöllei ², Ivan Solovicˇ ^3,4, Šárka Pospíšilová ¹, Hana Michnová ¹,

5

1

Josef Jampílek ¹, Alois Cížek , Iva Kapustíková , Jana Curillová , Mária Pechácˇová ,

ˇ

Jirˇina Stolarˇíková ⁶, Daniel Pecher ^7,8and Michal Oravec ⁹

1

Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Comenius University in Bratislava,

Odbojárov 10, SK-832 32 Bratislava, Slovakia; sharka.pospisilova@gmail.com (Š.P.);

michnova.hana@gmail.com (H.M.); josef.jampilek@gmail.com (J.J.); kapustikova@fpharm.uniba.sk (I.K.);

ˇ

curilova2@uniba.sk (J.C.); mariapech901@gmail.com (M.P.)

Department of Chemical Drugs, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences

in Brno, Palackého 1946/1, CZ-612 42 Brno, Czech Republic; csolleij@vfu.cz

2

3

4

5

6

7

8

9

Clinic for Tuberculosis and Lung Diseases, National Institute for Tuberculosis, Lung Diseases and Thoracic

Surgery, Vyšné Hágy, SK-059 84 Vysoké Tatry, Slovakia; solovic@hagy.sk or ivan.solovic@ku.sk

Department of Public Health, Faculty of Health, Catholic University in Ružomberok, Hrabovská cesta 1A,

SK-034 01 Ružomberok, Slovakia

Clinic for Department of Infectious Diseases and Microbiology, Faculty of Veterinary Medicine, University of

Veterinary and Pharmaceutical Sciences, Palackého 1946/1, CZ-612 42 Brno, Czech Republic; cizeka@vfu.cz

Laboratory for Mycobacterial Diagnostics and Tuberculosis, Regional Institute of Public Health,

Partyzánské námeˇstí 7, CZ-702 00 Ostrava, Czech Republic; Jirina.Stolarikova@zu.cz

Department of Pharmaceutical Analysis and Nuclear Pharmacy, Faculty of Pharmacy,

Comenius University in Bratislava, Odbojárov 10, SK-832 32 Bratislava, Slovakia; pecher1@uniba.sk

Toxicological and Antidoping Center, Faculty of Pharmacy, Comenius University in Bratislava,

Odbojárov 10, SK-832 32 Bratislava, Slovakia

Global Change Research Institute CAS, Belidla 986/4a, CZ-603 00 Brno, Czech Republic;

oravec.m@czechglobe.cz

*

Correspondence: malikivan001@gmail.com; Tel.: +421-2-501-117-227

ꢀꢁꢂꢀꢃꢄꢅꢆꢇ

ꢀꢁꢂꢃꢄꢅꢆ

Received: 5 September 2018; Accepted: 24 September 2018; Published: 28 September 2018

Abstract: In order to provide a more detailed view on the structure–antimycobacterial activity

relationship (SAR) of phenylcarbamic acid derivatives containing two centers of protonation, 1-[2-

[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]pyrrolidinium oxalates

(

1a

propylammonio)propyl]azepanium oxalates (1i

were physicochemically characterized by estimation of their surface tension (

stalagmometric method), electronic features (log ; UV/Vis spectrophotometry) and lipophilic

–

d

)/dichlorides (1e

–

h

) as well as 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(di-

)/dichlorides (1m ; alkoxy = butoxy to heptyloxy)

; Traube’s

–

l

–p

γ

ε

properties (log k_w; isocratic RP-HPLC) as well. The experimental log k_wdataset was studied

together with computational logarithms of partition coefﬁcients (log P) generated by various

methods based mainly on atomic or combined atomic and fragmental principles. Similarities and

differences between the experimental and in silico lipophilicity descriptors were analyzed by unscaled

principal component analysis (PCA). The in vitro activity of compounds 1a–p was inspected against

Mycobacterium tuberculosis CNCTC My 331/88 (identical with H₃₇R_vand ATCC 2794, respectively),

M. tuberculosis H₃₇R_aATCC 25177, M. kansasii CNCTC My 235/80 (identical with ATCC 12478),

the M. kansasii 6509/96 clinical isolate, M. kansasii DSM 44162, M. avium CNCTC My 330/80 (identical

with ATCC 25291), M. smegmatis ATCC 700084 and M. marinum CAMP 5644, respectively. In vitro

susceptibility of the mycobacteria to reference drugs isoniazid, ethambutol, oﬂoxacin or ciproﬂoxacin

was tested as well. A very unique aspect of the research was that many compounds from the set

1a

–p were highly efﬁcient almost against all tested mycobacteria. The most promising derivatives

showed MIC values varied from 1.9

µM to 8

µM, which were lower compared to those of used

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Molecules 2018, 23, 2493

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standards, especially if concerning ability to ﬁght M. tuberculosis H₃₇R_aATCC 25177, M. kansasii DSM

44162 or M. avium CNCTC My 330/80. Current in vitro biological assays and systematic SAR studies

based on PCA approach as well as ﬁtting procedures, which were supported by relevant statistical

descriptors, proved that the compounds 1a–p represented a very promising molecular framework for

development of ‘non-traditional’ but effective antimycobacterial agents.

Keywords: dibasic phenylcarbamates; surface tension; electronic properties; lipophilicity;

Mycobacterium spp.

1. Introduction

The treatment of commonly encountered species of tuberculous and non-tuberculous

mycobacteria responsible for a multiplicity of different types of infections, including pulmonary,

respiratory, cutaneous, and systemic infections, by (i) brand new classes of promising compounds

preferably acting on novel targets; or (ii) ‘non-typical’ antimycobacterial drug candidates is still in very

dynamic and progressive debate [

of some -lactam antibiotics (ceftaroline or ceftazidime) in a combination with an

avibactam against Mycobacterium avium complex [ ]. Another encouraged example was in vitro and

1–

6]. The strategy was successfully used in a case of in vitro screening

β

β-lactamase inhibitor

3,4

ex vivo testing of tricyclic thioridazine (Figure 1a), an old neuroleptic phenothiazine. The molecule was

used alone or in a combinatorial therapy with anti-tuberculosis drugs (isoniazid, rifampin, linezolid or

moxiﬂoxacin) against M. tuberculosis regardless of its antibiotic resistance phenotype and was highly

active due to its multi mechanisms of action [5,6].

Figure 1. Chemical structure of thioridazine (

); as well as effective local anesthetics ( ) lidocaine (xylocaine); and (

All these compounds showed notable in vitro efﬁciency against some mycobacterial strains [

a

), a neuroleptic drug containing a phenothiazine scaffold

) dibucaine (cinchocaine).

12].

(

a

b

c

5–

Structural fragments of dibucaine were color-coded as follows: a lipophilic moiety (a dark green

framework), polar group (orange), connecting hydrocarbon chain (gray) and salt-forming (basic) group

(dark red), respectively.

Antimycobacterial properties of compounds originally designed and tested as local anesthetics

(LAs) have been investigated sporadically. Moreover, their application to management of the infections

caused by a broad spectrum of species of the Mycobacterium genus has not been systematically reviewed.

Nevertheless, Schmidt and Rosenkranz [7] as well as Fujii et al. [8] found that lidocaine (xylocaine;

Figure 1b), a highly efﬁcient LA drug [ 10], notably inhibited in vitro growth of some strains of human

9,

Molecules 2018, 23, 2493

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M. tuberculosis, M. bovis or M. kansasii. Similarly, a quinoline core-containing dibucaine (cinchocaine;

Figure 1c) [11], was able to effectively in vitro ﬁght rapidly growing M. phlei [12].

A common structural feature of given efﬁcient LAs (and promising antimycobacterials) was

presence of a lipophilic moiety, polar anilido or amido group, connecting hydrocarbon chain and

salt-forming fragment. All considered moieties were color-differentiated for a molecule of dibucaine

(cinchocaine; Figure 1c).

Sequencing of Mycobacterium spp. genomes proved that these microorganisms produced a

variety of enzymes [13–15] able to hydrolyze ester, anilide or amide bonds in a chemical structure

of antimycobacterial drug candidates. Isosteric replacement of these polar groups with a carbamate

moiety would provide very good proteolytic stability, especially if the modiﬁed structural arrangement

of novel derivatives would be as follows: Aryl–NH–C(O)O–Alkyl [16]. The carbamate functionality

imposes a degree of conformational restriction due to delocalization of non-bonded electrons on

nitrogen into a carboxyl moiety. Participation of the carbamate group in hydrogen bonding through

carboxyl and backbone N–H [17] should be also taken into account. Considering the importance of the

carbamate functionality, its incorporation into a structure of novel antimycobacterial agents was one of

key tasks in a process of their design and synthesis [18–20].

Currently evaluated 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)-

propyl]pyrrolidinium/azepanium oxalates/dichlorides (1a

Scheme 1 ) were synthesized with intention to ﬁnd effective LAs with favorable toxicity proﬁles [21].

The compounds contained two types of an anionic counterpart (1a and 1i versus 1e and 1m

Table 1) in order to achieve convenient aqueous solubility in biological assays [21].

–p; alkoxy = butoxy to heptyloxy; Table 1,

–d

–

l

–h

–p;

It was found that all tested derivatives showed higher indices deﬁning their relative surface (U_s) as

well as inﬁltration (U_i) local anesthetic efﬁciency than reference LA drugs cocaine (U_s= 1.0, U_i= 3.6) or

procaine (U_s= 0.1, U_i= 1.0) [21]. The most effective dibasic molecule in given types of local anesthesia

was 1-[2-[({[3-(pentyloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]-pyrrolidinium

dichloride (1f) with U_s= 130 and U_i= 250 (Table S1 in Supplementary Materials), respectively.

It might be expected that the carbamate moiety was sterically protected due to branching of both

connecting hydrocarbon chain and salt-forming group. Rotatable bonds of the 2-/3-alkoxy side chain

R could also contribute to the steric hindrance (Table 1). It was proved by ab initio procedures that an

intramolecular hydrogen bond between N–H of the carbamate functionality and oxygen atom of the

2-alkoxy chain was formed [22]. Such structural arrangements of compounds would provide stability

against effects of various mycobacterial enzymes and would consider them promising candidates for

antimycobacterial agents.

It was observed that surface tension (relative surface activity), electronic and lipophilic

properties of carbamate group-containing molecules notably inﬂuenced the in vitro antimycobacterial

efﬁciency [23–25]. However, the set 1a–p has not been satisfactorily characterized by values of relevant

physicochemical descriptors [26] (Table S1).

In a ﬁrst part of this study, attention was turned on more precise physicochemical characterization

of the derivatives 1a

tension of water ( ), estimation of electronic properties described by logarithms of molar absorption

coefﬁcients (log ) of their methanolic solutions, which were investigated in the UV/Vis region

–p. The research aimed determination of compounds’ ability to decrease surface

γ

ε

of an electromagnetic spectrum, as well as evaluation of lipophilic features deﬁned by calculated

log k_wparameters. These log k_wwere based on extrapolation procedures of estimated logarithms

of retention factors (log k) to elution with 100% water by reversed-phase high-performance liquid

chromatography (RP-HPLC). In addition, relationships between the log k_wdataset and calculated

logarithms of partition coefﬁcients (log P) related to the octan-1-ol/water partitioning system were

explored in order to provide a critical view on possibilities to predict lipophilic properties of the

compounds based on two-dimensional (2D) visualization of their chemical structures.

Next, a very essential objective of the research was in vitro screening of the derivatives 1a

–p

against various strains of tuberculous and non-tuberculous mycobacteria, i.e., M. tuberculosis CNCTC

Molecules 2018, 23, 2493

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My 331/88, M. tuberculosis H₃₇R_aATCC 25177, M. kansasii CNCTC My 235/80, a M. kansasii 6509/96

clinical isolate, M. kansasii DSM 44162, M. avium CNCTC My 330/80, M. smegmatis ATCC 700084 and

M. marinum CAMP 5644, respectively.

A key aim of the study was to ﬁnd some structural and physicochemical features of the compounds

1a–p, which might appear to be notable for their in vitro antimycobacterial efﬁciency.

2. Results and Discussion

2.1. Synthesis of the Compounds 1a–p

The investigated compounds 1a–p were prepared by multi step pathways using 2-aminophenol

(

1⁰a) and 3-aminophenol (1⁰b), respectively, as starting molecules (Scheme 1). Very brieﬂy,

a reaction of 1⁰a or 1⁰b with acetanhydride led to N-(2-/3-hydroxyphenyl)ethanamide (2⁰a or

2⁰b). A solution of 2⁰a or 2⁰b in anhydrous ethanol (EtOH) was added to sodium ethanoate.

After mixing, 1-bromoalkane (alkane = butane to heptane) was added in order to prepare a series of

N-(2-/3-alk-oxyphenyl)ethanamides (3⁰a ; alkoxy = butoxy to heptyloxy). The molecules 3⁰a

–h –h

were suspended in 18% hydrochloric acid and heated up to reﬂux. The solutions were cooled,

neutralized and crude intermediates were extracted into diethyl ether (DEE). The organic layer was

dried, ﬁltered and solutions were removed in vacuo giving 2-/3-alkoxyanilines (4⁰a

–

h

; alkoxy = butoxy

to heptyloxy) [27]. Reulting intermediates 4⁰a

–h were dissolved in anhydrous toluene and added

continuously into a saturated solution of phosgene [27]. The mixed solutions were reﬂuxed, toluene

was removed in vacuo providing desired 1-alkoxy-2-/3-isocyanatobenzenes (5⁰a–h).

Into an aqueous solution of N-propylpropanamine (6⁰), a (

)-2-(chloromethyl)oxirane reagent

±

was added and solution was allowed to stand at room temperature (r.t.; 48h). The mixture was heated

up to 75 ^◦C and treated with 38% sodium hydroxide. The cooled solution was ﬁltered and a crude

intermediate was formed. Extraction of the ﬁltrate with DEE, drying and removal of the organic layer

provided additional amount of the intermediate [28], which isolation and crystallization from absolute

EtOH led to (±)-N-(oxiran-2-ylmethyl)-N-propylpropanamine (7⁰).

The addition of pyrrolidine or azepane to 7⁰in anhydrous propan-2-ol (2-PrOH) provided

1-(dipropylamino)-3-pyrrolidin-1-ylpropan-2-ol (8⁰a) or 1-azepan-1-yl-3-(dipropylamino)-propan-2-ol

(8⁰b) [29].

Oily 1-(1-azacycloalkyl)-3-(dipropylamino)propan-2-yl (2-/3-alkoxyphenyl)carbamates (9⁰a

–p;

azacycloalkyl = pyrrolidinyl or azepanyl) were prepared by a reaction of 1-alkoxy-2-/3-isocyanato-

benzenes 5⁰a–h with a dibasic alcohol 8⁰a or 8⁰b in anhydrous toluene.

Addition of a saturated solution of oxalic acid in anhydrous EtOH or ethereal hydrogen

chloride to the bases 9⁰a

–

p

dissolved in chloroform led to solid colorless 1-[2-[({[2-/3-(alkoxy)phenyl]-

amino}carbonyl)oxy]-3-(dipropylammonio)propyl]pyrrolidinium oxalates (1a )/dichlorides (1e

and 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium

oxalates (1i )/dichlorides (1m ; Scheme 1, Table 1) as well. More detailed procedures describing

syntheses of particular intermediates and ﬁnal molecules were provided in Supplementary Materials.

Chemical structure of the compounds 9⁰a

and 1a was previously veriﬁed by their infrared

(IR) spectra, which conﬁrmed presence of all key groups. In addition, elemental analyses results

–d

–h)

–l

–p

(% C, H, N) were within

±

0.40% of theoretical values for both bases 9⁰a

–

p

and salts 1a

–

p

were

[

21].

Melting points (m.p.⁰s), R_fvalues (TLC) and acid-base pK_a1and pK_a2parameters of 1a

–p

already published [21,26] and can be found in Table S1.

Current liquid chromatography high resolution mass spectroscopy (HPLC-HR-MS) analyses,

which were performed on the LC Agilent Inﬁnity System coupled with the Quadrupole Time-Of-Flight

Mass Spectrometer (6520 Accurate Mass Q-TOF LC/MS), conﬁrmed structural identity of the

intermediates 9⁰a–p (Supplementary Materials).

After re-crystallization from a mixture of acetone/ethanol (subgroups 1a

–d, 1e–h and 1m–p) or

acetone (1i ), high-resolution mass spectra (HR-MS) of these salts were measured by the Dionex

–

l

Molecules 2018, 23, 2493

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UltiMate 3000 High-Performance Liquid Chromatograph coupled with the LTQ Orbitrap XL Hybrid

Ion Trap-Orbitrap Fourier Transform Mass Spectrometer equipped with a HESI II (heated electrospray

ionization) source in a positive (1a

–d, 1i–l) or negative (1e–h, 1m–p) mode. The analyses conﬁrmed

structural identity of given molecules.

Scheme 1. Synthesis of 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)-

propyl]pyrrolidinium/azepanium oxalates/dichlorides (1a ; alkoxy = butoxy to heptyloxy). Reagents

–

p

and conditions: (i) (CH₃CO)₂O, reﬂux (1h); (ii) Na, anhydrous EtOH, 1-bromoalkane (alkane = butane to

heptane), r.t. (12h), reﬂux (3h); (iii) 18% HCl, reﬂux (2h); (iv) phosgene, anhydrous toluene, reﬂux (3h);

◦

(v) (

±

)-2-(chloromethyl)oxirane, 35 C (2h), r.t. (48h), 38% NaOH; (vi) pyrrolidine/azepane, anhydrous

2-PrOH, reﬂux (6h); (vii) anhydrous toluene, reﬂux (8h); (viii) saturated solution of (a) oxalic acid in

anhydrous EtOH or (b) ethereal hydrogen chloride.

2.2. Determination and Prediction of Some Physicochemical Properties of the Compounds 1a–p

2.2.1. Surface Tension

Surface tension (relative surface activity;

γ

) of aqueous solutions of the compounds 1a

–p

(

c = 2.0 × 10⁻³

M) was determined by a drop count technique [30,31] using a Traube stalagmometer.

All evaluated substances were able to decrease surface tension of water (γ = 0.07259 N/m) at 21 ^◦C.

Elongation of the 2-/3-alkoxy side chain R led to more surface-active derivatives within

homological sets 1a

a research paper [32]. The 2-alkoxy substituted molecules 1a

surface tension of water than their 3-alkoxy substituted isomers 1e–h or 1m–p (Table 1, Figure 2).

–d

,

1e

–

h,

1i

–l

and 1m–p. This behavior was also in agreement with conclusions of

–d

and 1i showed lower ability to reduce

–l

Relationships between the number of carbon atoms forming the chain R (n_c) and

γ values

(in N/m units) was inspected using a linear function, polynomial function of 2^ndorder and sigmoidal

ﬁtting, respectively.

Molecules 2018, 23, 2493

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Equations related to the most relevant functions and values of common statistical descriptors,

namely, number of points (number of cases; n), degrees of freedom (DF), reduced chi-square (χ ²

_red),

,

residual sum of squares (RSS), correlation coefﬁcient (R), adjusted coefﬁcient of determination (Adj. R²),

root mean squared error (standard deviation; RMSE), norm of residuals (NR), Fisher’s signiﬁcance ratio

(Fisher’s F-test; F) and probability of obtaining the F Ratio (signiﬁcance of a whole model; Prob > F),

respectively, can be found in Table S2.

Indication of a signiﬁcance level of the F Ratio was as follows: one star symbol (*) for statistically

signiﬁcant, two stars symbol (**) for statistically very signiﬁcant or three stars symbol (***) for

statistically extremely signiﬁcant level was used. The regression equations and their statistical

characteristics were calculated and visualized by the Origin Pro ver. 9.0.0 SR2 software (OriginLab

Corporation, Northampton, MA, USA).

The relationships between n_cand

1i and 1m ) or very signiﬁcant (1e

(Figure 2, Equations (S1–S4) in Table S2).

γ

were described most precisely by statistically signiﬁcant

(1a

–

d,

–

l

–p

–h) models built on polynomial functions of 2nd order

Table 1. Chemical structure of evaluated compounds 1a

–

p, their surface tension

γ

(relative surface

activity; in N/m units), wavelengths of observed absorption maxima (λ₁

,

λ_{2 (Ch-T)}

, λ₃) and logarithms

of molar absorption coefﬁcients (log ε₁, log ε_{2 (Ch-T)}, log ε₃) of compounds’ methanolic solutions

−5

(c = 8.0 × 10 M), which were investigated in the UV/Vis region of an electromagnetic spectrum.

1

Comp.

R

X

Y

γ (N/m)

λ₁

log ε₁

λ_{2 (Ch-T)}

log ε_{2 (Ch-T)}

λ₃

log ε₃

1a

1b

1c

1d

1e

1f

1g

1h

1i

2-OC₄H₉

2-OC₅H₁₁

2-OC₆H₁₃

2-OC₇H₁₅

3-OC₄H₉

3-OC₅H₁₁

3-OC₆H₁₃

3-OC₇H₁₅

2-OC₄H₉

2-OC₅H₁₁

2-OC₆H₁₃

2-OC₇H₁₅

3-OC₄H₉

3-OC₅H₁₁

3-OC₆H₁₃

3-OC₇H₁₅

A

B

C

D

C

D

0.06464

0.06366

0.06222

0.05985

0.06316

0.06285

0.06105

0.05786

0.06302

0.06206

0.06065

0.05853

0.06298

0.06154

0.05925

0.05692

208

210

208

210

4.51

4.39

4.58

4.43

4.65

4.55

4.54

4.66

4.44

4.54

4.42

4.44

4.52

4.56

4.52

4.65

236

238

236

238

237

236

238

4.19

4.05

4.52

4.08

4.24

4.27

4.13

4.27

4.08

4.22

4.10

4.14

4.09

4.18

4.01

4.20

280

278

280

279

280

279

3.63

3.51

3.49

3.55

3.59

3.62

3.48

3.63

3.57

3.71

3.57

3.59

3.44

3.52

3.37

3.56

1j

1k

1l

1m

1n

1o

1p

1

B

log ε_{2 (Ch-T)}, Logarithms of molar absorption coefﬁcients observed at the charge-transfer absorption maximum

λ_{2 (Ch-T)}= 236–238 nm.

The derivatives containing an azepanium moiety (1i

decrease surface tension of water than their positional isomers with a pyrrolidinium salt-forming

group (1a 1e ). The most surface active were 1-[2-[({[3-(heptyloxy)phenyl]amino}carbonyl)-oxy]-3-

(dipropylammonio)propyl]azepanium dichloride (1p) with = 0.05692 N/m and 1-[2-[({[3-

–l, 1m–p) showed slightly higher ability to

–

d,

–h

γ

(heptyloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]pyrrolidinium dichloride (1h),

which showed γ = 0.05786 N/m (Table 1, Figure 2).

ˇ

Very similar behaviors to present ﬁndings were observed when Cižmárik with co-workers [33

,34]

analyzed structurally similar compounds JC-01a , effective LAs [33], which contained only one

–

l

Molecules 2018, 23, 2493

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centrum of basicity (Figure 3). All given molecules showed ability to decrease surface tension of water

and 3-alkoxy substituted derivatives JC-01g (alkoxy = propoxy to octyloxy) were more efﬁcient

surfactants than their 2-alkoxy positional isomers JC-01a . Relationships between n_c(n_c= 3–8) and

–

l

–

f

γ

(in N/m units) of these alkoxy positional isomers were described very satisfactorily by polynomial

functions of 2nd order [34].

Concerning presently analyzed dichlorides 1m

–

p, branching of their connecting chain and

presence of a dipropylammonium moiety resulted in the

γ

values (Table 1 ), which were slightly

lower in comparison to those of JC-01h–k [34].

Figure 2. Relationships between number of carbon atoms forming the 2-/3-alkoxy side chain R (n_c;

alkoxy = butoxy to heptyloxy) and γ values (in N/m units) of the compounds 1a–p.

Figure 3. Chemical structure of the compounds JC-01a–l, effective local anesthetics [33], which were

able to decrease surface tension of water [34].

2.2.2. Electronic Properties

Electronic properties of the molecules 1a

absorption coefﬁcients (log ) of their methanolic solutions (c = 8.0

UV/Vis region of an electromagnetic spectrum.

–

p

(Table 1) were characterized by logarithms of molar

ε

×

10⁻⁵M) investigated in the

The solutions showed three absorption maxima in a near ultraviolet (quarz) region of this

spectrum between 200 nm and 400 nm [35], namely, λ₁= 208–210 nm, λ_{2 (Ch-T)}= 236–238 nm and

λ₃= 278–280 nm (Table 1), respectively. Positions of these absorption bands in the spectrum were

typical for derivatives of (substituted) phenylcarbamic acid and the bands were assigned as ﬁrst

local excitation (λ₃), charge-transfer (λ_{2 (Ch-T)}) and second local excitation (λ₁) absorption maxima,

respectively [36]. The λ₁and λ_{2 (Ch-T)}maxima of 2-alkoxy substituted compounds 1a

–

d

and 1i–l were

slightly lower compared to those of their 3-alkoxy substituted positional isomers 1e

–

h

and 1m–p

Molecules 2018, 23, 2493

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(Table 1), respectively. Chemical structures of analyzed derivatives 1a

–d

and 1i

–l

indicated that steric

inability of both carbamoyloxy and alkoxy groups to achieve coplanarity inhibited ‘proper’ resonance.

The log ε_{2 (Ch-T)}parameters of compounds 1a , which were observed at λ_{2 (Ch-T)}, varied from

4.01 (1o) to 4.52 (1c). The methanolic solutions of 1a were characterized by higher log ε_{2 (Ch-T)}

values than those of 1i and ranged from 4.05 (1b) to 4.52 (1c; Table 1), excluding the molecules

–

p

–

h

–

p

1j (4.22) and 1l (4.14). In addition, there was found nor linear neither quasi-parabolic relationship

between number of carbon atoms forming the side chain R (n_c) and log ε_{2 (Ch-T)}values (Figure S1 in

Supplementary Materials).

In next sections of the paper, which are aimed at relationships between structure and in vitro

activity, special consideration is devoted to the log ε_{2 (Ch-T)}values because they could be the most

sensitive to differences in electronic environment of a phenylcarbamoyloxy moiety due to different

position and length of a substituent R [36].

2.2.3. Lipohydrophilic Properties

Lipophilicity has been the physicochemical parameter of notable importance in QSAR and SAR

studies as a predominant descriptor encoding information on a network of inter- and intramolecular

forces affecting drug transport via lipophilic compartments as well as drug’s interactions with target

effector sites [37,38].

A classical shake-ﬂask method for a partitioning measurement of a compound in the

octan-1-ol/buffer (or water) system, thus estimation of its log P_expvalue, is quite time-consuming,

it requires the solute to be pure and with adequate solubility in an aqueous phase. Insolubility often

means that highly lipophilic compounds may not be determined accurately [39]. Concerning these

issues very seriously, RP-HPLC was rather applied to estimate lipophilic properties of the molecules

1a–p than the shake-ﬂask alternative.

Octadecyl-functionalized silica gel was currently used as a stationary phase (SPh) and a

gradient of two solvents at different volume ratios modiﬁed retention properties of the SPh [39,40].

Liquid binary mixtures of methanol (MeOH) with water were employed as mobile phases (MPhs)

in the isocratic RP-HPLC. The MeOH modiﬁer was preferred because of similarity of both observed

and extrapolated lipophilicity parameters with the ones determined in the octan-1-ol/water partition

system, considering also sensitivity to H-bond donor properties of investigated compounds [41].

The modiﬁer was applied in different volume concentrations, which varied from 85% to 100%

(v/v) with 5% increments. This interval was chosen due to very high lipophilicity of investigated

salts. Practically, lower volume concentration of MeOH, i.e., less than 85% (v/v) in used MPhs, caused

uncertainty of retention times (t_r) due to notable peaks broadening, especially within subsets 1i

–l and

1m . In addition, their t_rvalues were considerably prolonged with increase in water content (v/v)

–

p

of the MPhs so it was no longer possible to determine t_rvalues in such MPhs. Taking the 85–100%

volume concentrations range, the isocratic separation was feasible and reasonable retention of the

compounds 1a–p was observed in all MPhs. The highest t_rparameters were found for the molecules

1k (t_r= 47.108 min) and 1l (t_r= 70.012 min) in the MPh containing 85% proportion (v/v) of MeOH

(Table 2).

In addition, purity (in percentages) of the compounds 1a–p was veriﬁed by RP-HPLC. Areas of

their peaks were measured using the MPh, which contained 90% proportion (v/v) of MeOH. The purity

of given salts varied from 96.82% (1j) to 99.65% (1m; Table S3).

Estimated retention factor (capacity factor; k) values were found in an area from 0.5063 (1e

)

to 2.5096 (1l) if pure MeOH was used as the MPh, and from 3.6174 (1e) to 30.4159 (1l) if the 80:20

MeOH/water (v/v) MPh was applied (Table S3).

Regarding a group of oxalates (Scheme 1), a pyrrolidium moiety-containing derivatives 1a

showed lower log k values in all used MPhs than those with an azepanium fragment 1i . Same trends

showed lower log k outputs compared to

–d

–

l

were observed for dichlorides, i.e., the compounds 1e

those of a series 1m–p.

–h

Molecules 2018, 23, 2493

9 of 37

Elongation of the R substituent (Table 1) led to increase in t_ras well as log k values within all

evaluated subgroups 1a 1e 1i and 1m (Table 2 ). Increase in a volume concentration (v/v) of

MeOH caused shortening of both t_rand log k for all analyzed compounds 1a–p (Table 2).

El Tayar et al. [42 43] investigated lipophilic properties of protonated basic compounds, which

–

d,

–

h,

–

l

–p

,

were therapeutically used as psychoactive agents, and inspected relationships between their log k

values and volume concentrations (v/v) of MeOH. They found that these relationships were notably

inﬂuenced by nature of solutes. The models were preferably built on linear functions and MeOH

exerted its own solvophobic effect in the MPhs, which contained more than 80% (v/v) of given organic

modiﬁer if focusing on analyses of neutral and non-ionic compounds.

For partially and completely ionized polar compounds, the relationships appeared to be nearly

parabolic but the parts of parabolic curves, which corresponded to MeOH-rich eluents (80% or higher

volume concentration (v/v) of MeOH) were regarded as linear [42,43].

Paschke et al. [44] analyzed a series of highly lipophilic tetrachlorobenzyltoluene isomers by

isocratic RP-HPLC and found linear relationships (R > 0.9995) between their log k values and volume

concentrations of MeOH, which varied from 80% to 100% (v/v).

Table 2. Retention times t_r(RP-HPLC) and lipophilicity indices log k (RP-HPLC) of the compounds

1a–p estimated in the mobile phases with a various volume ratio (v/v) of a methanol (MeOH) organic

modiﬁer and water.

Mobile Phase MeOH/Water (v/v)

80:20

85:15

t_r(min)

90:10

95:5

t_r(min)

Pure MeOH

Comp.

t_r(min)

log k

t_r(min)

log k

t_r(min)

log k

1a

1b

1c

1d

1e

1f

1g

1h

1i

1j

1k

1l

1m

1n

1o

1p

13.883

17.200

25.694

31.000

10.330

12.400

17.200

22.003

24.020

29.525

47.108

70.012

15.731

22.183

29.174

33.719

0.7165

0.8254

1.0206

1.1092

0.5584

0.6574

0.8254

0.9521

0.9881

1.0863

1.3023

1.4831

0.7805

0.9502

1.0807

1.1484

10.694

12.647

16.950

19.600

6.917

0.5756

0.6656

0.8162

0.8882

0.3183

0.4911

0.6104

0.7159

0.8153

0.8981

1.0424

1.2152

0.4922

0.6542

0.7059

0.8215

7.830

9.449

11.292

13.553

5.400

6.280

7.483

8.532

11.691

13.060

16.533

22.636

6.420

8.156

9.634

11.332

0.3958

0.5064

0.6053

0.7022

0.1478

0.2546

0.3679

0.4565

0.6240

0.6828

0.8038

0.9619

0.2695

0.4205

0.5174

0.6072

5.766

6.514

7.431

7.892

3.822

4.022

5.153

5.788

7.765

8.520

9.641

11.670

4.685

4.995

5.095

5.801

0.2008

0.2841

0.3683

0.4052

4.224

4.526

5.246

5.385

3.329

3.340

3.583

3.556

5.127

5.295

6.938

7.756

3.519

3.947

4.127

3.925

−0.0403

0.0203

0.1287

0.1573

−

0.1454

0.0941

−0.2956

−0.2913

−0.2067

−0.2153

0.1205

0.1449

0.3303

0.3996

−0.2275

−0.1047

−0.0618

−0.1102

9.200

−

11.402

13.701

16.917

20.021

27.001

38.800

9.218

12.370

13.651

17.129

0.1182

0.2092

0.3954

0.4509

0.5221

0.6271

0.0424

0.0941

0.1095

0.2051

On the other hand, observed log k data could not be used in terms of a universal scale to express

lipophilicity of compounds because the log k values were dependent on chromatographic conditions,

i.e., they depended on both MPhs and SPhs. Extrapolation of estimated solute retention (log k) to

elution with 100% water (calculation of log k_w) would deﬁnitely be much more precise approach than

using of log k, because the k_wparameters were independent of any effect of the organic modiﬁer and

relied on the SPh alone [45]. It has been recognized that the log k_wdescriptor was very efﬁcient for

anticipation of in vitro antimycobacterial properties of compounds [46–49].

According to the authors’ opinions based on systematic scientiﬁc literature survey, a current

research paper was the ﬁrst, which aimed the log k_wparameters of 2-/3-alkoxyphenylcarbamic

acid derivatives containing two centers of protonation. The log k_wvalues were extrapolated from

intercepts of a relationship between log k and volume fraction of the MPh modiﬁer (ϕ_M) using the

Snyder–Soczewin´ski linear solvent strength model [50

–52]. The relationship was justiﬁed by R > 0.9900,

Adj. R²> 0.9750 as well as F > 180.00 for calculation of particular log k_wparameters (Table 3).

Molecules 2018, 23, 2493

10 of 37

Table 3. Extrapolated log k_wparameters (RP-HPLC) of analyzed molecules 1a–p and values of statistical

descriptors (χ²_red, RSS, R, Adj. R², RMSE, NR, F and Prob > F), which characterized a linear relationship

between the log k and ϕ_Mvalues for a particular compound. The ϕ_Mparameter was a volume fraction

of MeOH in the isocratic elution RP-HPLC.

1

2

3

4

5

6

7

8

9

Comp.

log k_w

S

χ²

RSS

R

Adj. R²

RMSE

NR

F

Prob > F

red

1a

1b

1c

1d

1e

1f

1g

1h

1i

1j

1k

1l

1m

1n

1o

1p

3.7688

4.0454

4.6049

4.9487

4.0258

4.6722

4.9446

5.5384

4.4679

4.8466

5.2359

5.8966

4.7099

5.2087

5.6569

6.1749

3.7768

3.9834

4.4634

4.7736

4.3434

4.9652

5.1128

5.6830

4.3102

4.6600

4.9286

5.5102

4.9316

5.3398

5.7628

6.2672

0.0011

0.0018

0.0002

0.0011

0.0013

0.0028

0.0013

0.0042

0.0014

0.0016

0.0005

0.0007

0.0004

0.0011

0.0045

0.0022

0.0034

0.0055

0.0007

0.0033

0.0038

0.0084

0.0040

0.0126

0.0042

0.0048

0.0017

0.0020

0.0013

0.0032

0.0134

0.0067

0.9953

0.9931

0.9993

0.9971

0.9960

0.9932

0.9969

0.9923

0.9955

0.9956

0.9987

0.9988

0.9990

0.9978

0.9920

0.9966

0.9875

0.9817

0.9982

0.9923

0.9894

0.9821

0.9919

0.9795

0.9879

0.9882

0.9964

0.9965

0.9972

0.9941

0.9789

0.9909

0.0335

0.0429

0.0152

0.0332

0.0354

0.0530

0.0366

0.0648

0.0376

0.0401

0.0234

0.0259

0.0205

0.0325

0.0668

0.0474

0.0580

0.0744

0.0263

0.0574

0.0614

0.0917

0.0634

0.1122

0.0652

0.0695

0.0406

0.0449

0.0356

0.0564

0.1157

0.0820

317.64

215.17

2155.37

518.15

375.47

219.79

487.75

192.51

328.27

337.19

1106.57

1127.92

1442.73

673.05

186.23

438.042

0.0001 ***

0.0007 ***

0.0001 ***

0.0002 ***

0.0003 ***

0.0007 ***

0.0002 ***

0.0008 ***

0.0004 ***

0.0001 ***

0.0009 ***

0.0001 ***

1

S, Slope; ²χ²_red, reduced chi-square; ³RSS, residual sum of squares; ⁴R, correlation coefﬁcient; ⁵Adj. R², adjusted

coefﬁcient of determination; ⁶RMSE, root mean squared error (standard deviation); ⁷NR, norm of residuals; ⁸F,

Fisher’s signiﬁcance ratio (Fisher’s F-test); ⁹Prob > F, probability of obtaining the F Ratio (signiﬁcance of a whole

model). Indication of a signiﬁcance level of the F Ratio was as follows: *** (three stars), extremely signiﬁcant.

Goodness of ﬁt for all proposed models generating log k_w, in other words, quantity used to test

whether any given data were well described by a suggested function, was adjusted by χ²_redvalues,

which varied from 0.0002 (1c) to 0.0045 (1o). As can be seen, the linear relationships minimized RSS

values, as variabilities about regression lines, which ranged from 0.0007 (1c) to 0.0134 (1o). The linearity

was also proved by calculated RMSE parameters, as standard deviations of the data about regression

lines, which were found in an interval from 0.0152 (1c) to 0.0668 (1o; Table 3).

The extrapolated log k_wvalues of compounds 1a

their elution order and hydrophobicity and varied from 3.7688 (1a) to 6.1749 (1p). Assuming

presence of an identical azacycloalkyl moiety, oxalates (1a 1i ) were less lipophilic than

corresponding positional isomers synthesized as dichlorides (1e 1m ; Table 3). As expected,

1-[2-[({[3-(hept-yloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium oxalate

1l) and 1-[2-[({[3-(heptyloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium

–p (Table 3 ) were in accordance with

–

d,

–l

–

h,

–p

(

dichloride (1p; Table 1) were found to be the most lipophilic showing log k_wof 5.8966 (1l) and 6.1749

(1p; Table 3), respectively.

Increase in n_c(Table 1) led to higher log k_wvalues in all inspected subgroups 1a

–d, 1e–h, 1i–l

and 1m . These relationships were deﬁned by statistically signiﬁcant (1e 1i ), very signiﬁcant

–

p

–

h,

–l

(1a–d) and extremely signiﬁcant (1m–p) linear functions and values of relevant statistical descriptors

(Equations (S5)–(S8) in Table S4).

The S index (Table 3) in RP-HPLC has been a function of molecular structure parameters. For sets

of non-polar homologues, linear relationships between their S and number of carbon atoms in a

hydrocarbon side chain was found. Increase in size and van der Waals volume of a solute led to

increased S parameter as well [53].

Results of present analyses agreed with given conclusions. Increase in length of the side chain R led

to higher S within all inspected homological subgroups. The compounds containing an azepanium moiety

showed higher S parameters, which varied from 4.3102 (1i) to 6.2672 (1p), than those with a pyrrolidium

group, i.e., from 3.7768 (1a) to 5.6830 (1h; Table 3 ), if same position and length of R was presumed.

The slope S values of linear regression functions used to obtain log k_wwere connected with

speciﬁc hydrophobic surface areas of compounds and could serve as indicative measure of uniformity

of retention mechanisms. If the uniformity was observed, a convenient model between the slope(s)

and intercept(s), i.e., log k_wvalues, was anticipated [40]. Statistically extremely signiﬁcant relationship

between the log k_wand S values of 1a–p was found and described by Equation (1):

Molecules 2018, 23, 2493

11 of 37

S = 0.9449 (±0.0823) × log k_w+ 0.2755 (±0.4087)

(1)

n = 16, DF = 14, χ,²_red= 0.0470, RSS = 0.6586, R = 0.9508, Adj. R²= 0.8971,

RMSE = 0.2169, NR = 0.8115, F = 131.75, Prob > F = 0.0001 ***

Based on values of statistical descriptors provided above, the uniformity of a retention mechanism

was proven and suitability of chosen MPhs was conﬁrmed for lipophilicity evaluation of the

derivatives 1a–p.

Statistical analyses indicated that both position and length of the side chain R (Equations

(S9) and (S10) in Table S5) were more important factors, which contributed to the uniformity of

retention behavior, compared to nature (and physicochemical properties) of a salt-forming fragment

(Equations (S11) and (S12) in Table S5) of inspected compounds, despite the fact that all partial models

built on linear regression analyses were statistically extremely signiﬁcant.

To provide better understanding and give a critical review of relationships between the

experimental lipophilicity measures and in silico prediction of lipophilic properties, the log k_wdataset

was studied together with computational logarithms of partition coefﬁcients (log P).

Practical estimation of log P_expfor some molecules from the set 1a–p by a shake-ﬂask method was

not possible due to their insolubility in phosphate buffer systems (pH = 7.30). Thus, the lack of enough

reliable log P_expvalues would be a very limiting factor for eventual investigation of the relationships

between log P_expand in silico log P. On the other hand, linear models between log k_wand log P_exp

were already observed [39], so interchangeability of these descriptors was fully justiﬁed.

The log P parameters of non-protonated forms of analyzed compounds, i.e., 9⁰a

–p (Scheme 1,

Table 4), were calculated for the octan-1-ol/water partitioning system. These values were generated by

the ChemBioDraw Ultra 12.0 software package (CambridgeSoft, Cambridge, MA, USA), various Java

and non-Java interactive applets as well.

The Ghose and Crippen⁰s log P_Cr55], Viswanadhan⁰s log P_V[56 ], Broto’s log P_B[57 ] and Leo’s

[54 ,

CLOGP 4.0 [58 ] atomic and atomic/fragmental-based approaches were chosen to calculate the log p

values (Table 4 ) by the ChemBioDraw Ultra 12.0 software, respectively. The Virtual Computer Chemistry

Laboratory [59 ], a freely available web-based tool working in Java environment, was used to calculate

log P by the Wang’s XLOGP 2.0 [60 ], Cheng’s XLOGP 3.0 [61 ], Moriguchi’s MLOGP [62 ], Sander’s

(Actelion’s) ACLOGP [63 ], Molinspiration’s miLogP 2.2 [64 ], ALOGP [65 ] and Tetko’s ALOGPs 2.1 [66

]

method (Tables 4 and 5 ), respectively. All these methods integrated algorithms combining atomic and

fragmental principles, except for ALOGPs 2.1, which considered a molecule in the whole [66 ].

Finally, the SILICOS-IT hybrid method, which used proprietary fragment- and property-based

principles, was also employed to generate log P parameters (log P_S-IT; Table 5). The method was

implemented in the SwissADME applet, a free web tool designed to evaluate pharmacokinetics and

drug-likeness of small molecules [67].

A common issue connected with given in silico approaches [26] was that they did not allow

to correctly predict log p values of particular salts 1a

targeted on the calculations related to non-protonated bases 9⁰a–p.

The compounds 9⁰i showed higher log P than their positional isomers 9⁰a

a different salt-forming moiety. Almost all used predictor tools indicated the molecules 9⁰a

–p. This was the reason why current research

–p

–

h, which contained

–p

highly

lipophilic with log p > 4.27 (Tables 4 and 5), excluding the MLOGP method. The calculations based on

MLOGP indicated moderate or high lipophilicity of these substances, which log P were found in a

range from 2.75 (9⁰a and 9⁰e) to 3.76 (9⁰l and 9⁰p; Table 5).

The CLOGP 4.0 predicted the highest lipophilic nature of the bases 9⁰a

–p and their log P varied

from 6.23 (9⁰a and 9⁰e) to 8.94 (9⁰l and 9⁰p; Table 4). As might be assumed, all employed atomic and

atomic/fragmental methods did not consider a position of the side chain R when generating log P

(Tables 4 and 5 ). Only the whole-molecule ALOGPs 2.1 approach took into account this aspect, so the

2-alkoxy substituted compounds 9⁰a

–d –l were less lipophilic than their 3-alkoxy substituted

and 9⁰i

positional isomers 9⁰e–h and 9⁰m–p (Table 5), respectively.

Molecules 2018, 23, 2493

12 of 37

It was found that linear relationships between the extrapolated log k_wvalues of compounds

(Table 3) and particular in silico log P parameters of non-protonated derivatives 9⁰a

, namely,

1a

–

p

–p

log P_Cr, log P_V, log P_B, CLOGP 4.0, XLOGP 2.0, XLOGP 3.0, MLOGP, ACLOGP, miLogP 2.2, ALOGP,

log P_S-ITand ALOGPs 2.1 (Tables 4 and 5), respectively, were statistically extremely signiﬁcant (Prob >

F = 0.0001) and were deﬁned by R > 0.9300, Adj. R²> 0.8650, F > 99.00 and other common statistical

descriptors (Equations (S13)–(S24) in Table S6).

0

Table 4. Values of logarithms of partition coefﬁcients of basic (non-protonated) compounds 9 a

–

p

predicted for the o₀ctan-1-ol/water partitioni₀ng system by the Ghose and Crippen⁰s approach (log

P

_Cr), Viswanadhan s principle (log P_V), Broto s algorithm (log P_B) and CLOGP method (CLOGP 4.0),

respectively, as well as by both XLOGP approaches (XLOGP 2.0 and XLOGP 3.0).

CLOGP

4.0

XLOGP

2.0

XLOGP

3.0

Comp.

R

X

log P_Cr

log P_V

log P_B

0

9 a

2-OC₄H₉

2-OC₅H₁₁

2-OC₆H₁₃

2-OC₇H₁₅

3-OC₄H₉

3-OC₅H₁₁

3-OC₆H₁₃

3-OC₇H₁₅

2-OC₄H₉

2-OC₅H₁₁

2-OC₆H₁₃

2-OC₇H₁₅

3-OC₄H₉

3-OC₅H₁₁

3-OC₆H₁₃

3-OC₇H₁₅

A

B

4.59

5.00

5.42

5.84

4.59

5.00

5.42

5.84

5.42

5.84

6.26

6.67

5.42

5.84

6.26

6.67

4.45

4.85

5.24

5.64

4.45

4.85

5.24

5.64

5.24

5.64

6.04

6.43

5.24

5.64

6.04

6.43

4.51

4.97

5.42

5.88

4.51

4.97

5.42

5.88

5.42

5.88

6.33

6.79

5.42

5.88

6.33

6.79

6.23

6.76

7.29

7.82

6.23

6.76

7.29

7.82

7.35

7.88

8.41

8.94

7.35

7.88

8.41

8.94

4.52

5.09

5.66

6.23

4.52

5.09

5.66

6.23

5.24

5.81

6.38

6.95

5.24

5.81

6.38

6.95

5.14

5.68

6.22

6.77

5.14

5.68

6.22

6.77

5.86

6.40

6.84

7.48

5.86

6.40

6.84

7.48

0

9 b

0

9 c

0

9 d

0

9 e

0

9 f

0

9 g

0

9 h

0

9 i

0

9 j

0

9 k

0

9 l

0

9 m

0

9 n

B

0

9 o

0

9 p

0

Table 5. Values of logarithms of partition coefﬁcients of basic (non-protonated) compounds 9 a

–

p

predicted for the octan-1-ol/water partitioning system by the MLOGP, ACLOGP, miLogP 2.2, ALOGP,

SILICOS-IT (log P_S-IT) and ALOGPs 2.1 method, respectively.

miLogP

2.2

ALOGPs

2.1

Comp.

MLOGP

ACLOGP

ALOGP

log P_S-IT

0

9 a

2.75

2.96

3.16

3.36

2.75

2.96

3.16

3.36

3.16

3.36

3.56

3.76

3.16

3.36

3.56

3.76

5.05

5.52

5.98

6.45

5.05

5.52

5.98

6.45

5.69

6.16

6.62

7.08

5.69

6.16

6.62

7.08

5.30

5.80

6.32

6.81

5.32

5.83

6.33

6.84

6.31

6.81

7.32

7.82

6.33

6.84

7.34

7.85

5.42

5.87

6.33

6.79

5.42

5.87

6.33

6.79

6.33

6.79

7.24

7.70

6.33

6.79

7.24

7.70

4.27

4.68

5.10

5.53

4.27

4.68

5.10

5.53

4.78

5.20

5.62

6.04

4.78

5.20

5.62

6.04

5.18

5.57

5.93

6.25

5.21

5.61

5.95

6.32

5.93

6.23

6.54

6.77

5.97

6.27

6.59

6.83

0

9 b

0

9 c

0

9 d

0

9 e

0

9 f

0

9 g

0

9 h

0

9 i

0

9 j

0

9 k

0

9 l

0

9 m

0

9 n

0

9 o

0

9 p

Molecules 2018, 23, 2493

13 of 37

In an effort to characterize these relationships more precisely, similarities and differences between

given descriptors were analyzed by using unscaled principal component analysis (PCA), a powerful

multivariate statistical technique, that analyzed a set of values, in which observations were described

by several inter-correlated quantitative dependent variables. A set of new orthogonal variables, called

principal components (PCs), and pattern of similarity of observations was a result the analysis [68].

Current PCAs were performed by the Origin Pro ver. 9.0.0 SR2 software. Number of concerned PCs

was determined by visual evaluation of a scree plot, as a relationship between calculated eigenvalues

(

λ_e) and number of PCs. The λ_edescriptor measured amount of variation retained by each PC [68].

The ﬁrst two PCs, i.e., Principal Component 1 (PC 1) and Principal Component 2 (PC 2), of the analysis

accounted for 99.26% of the total variance in the data. It meant that other PCs might be ignored

without losing any substantial information. The PCs did not prove existence of ‘real’ parameters,

they only indicated that existence of these descriptors was mathematically possible within the set of

analyzed values.

A relationship between PC 1 and PC 2 resulted in division of examined compounds into

characteristic groups. Differences in lipophilic properties of the bases 9⁰a

–

p

were reﬂected in their PC 1

values. One group, deﬁned by negative PC 1 values, included derivatives containing a pyrrolidin-1-yl

moiety (9⁰a 9⁰e ) as well as molecules with both azepan-1-yl fragment and butoxy side chain (9⁰i

9⁰m). Conversely, second group, which was characterized by positive PC 1 values, encompassed

compounds containing an azepan-1-yl moiety (9⁰j 9⁰n

) as well as derivatives with both sterically

smaller azacycloalkyl ring and heptyloxy substituent (9⁰d 9⁰h). The most negative PC 1 value

–

c,

–

g

,

–l

,

–p

,

was generated for the least lipophilic derivative 9⁰a, which salt 1a showed the lowest experimental

lipophilicity (log k_w= 3.7688). The most positive PC 1 output was registered for the most lipophilic

compound 9⁰p, a base of the most lipophilic salt 1p (log k_w= 6.1749; Figure 4).

It was found that PC 2 took into consideration a type of an azacycloalkyl moiety as well as position

–h –p. Higher PC 2

and length of R. The derivatives 9⁰a showed higher PC 2 than the compounds 9⁰i

were assigned to the 3-alkoxy substituted molecules compared to their 2-alkoxy positional isomers,

when assuming their identical salt-forming moiety.

Increase in n_cof the side chain R led to higher PC 1 as well as PC 2. There were found no

compounds (points), which could be regarded as outliers to the remaining ones along PC 1 or PC 2

(Figure 4).

The PCA-based 2D biplot showed both PC scores (PC 1, PC 2) of evaluated compounds (green

dots) and loadings of variables indicated as orange straight lines [68]. The lines characterizing log

k_w, log P_I-IT, XLOGP 2.0, XLOGP 3.0 and ACLOGP variables were located on upper right side of this

biplot. The line related to log k_wformed the smallest angles with those of log P_I-IT, XLOGP 2.0 or

XLOGP 3.0, which meant that these descriptors correlated each other most positively. Conversely,

the largest angle was observed between the lines connected with log k_wand CLOGP 4.0, so these

variables were unlikely to correlate each other (Figure 4).

The PC 1 was inﬂuenced almost equally by loadings of all inspected variables, as indicated

particular scores on top axis. The scores varied from 0.27 (log k_w) to 0.28 (log P_Cr, log P_V, log P_B,

miLogP 2.2 and ALOGP, respectively). The most positive impact on PC 2 showed a loading of the

log k_wand log P_I-ITvariable, which scored approximately 0.45 and 0.37, respectively, on right axis.

Conversely, the strongest inverse relationship was found between PC 2 and loading of the CLOGP

4.0 variable (−0.28; Figure 4).

Following visualization, the in silico log P_I-IT, XLOGP 2.0 and XLOGP 3.0 descriptors might be

used to characterize lipophilic properties of analyzed salts and bases, especially if they contained

highly lipophilic side chain R. Those molecules were deﬁned by positive values of both PC 1 and PC 2.

In addition, very close grouping was observed for 9⁰l with 9⁰p (Figure 4).

Molecules 2018, 23, 2493

14 of 37

Figure 4. Two-dimensional biplot (mapping) showing both Principal Component 1 and 2 scores

0

of the compounds 9 a–p and loadings of extrapolated chromatographic (log k_w; 1a–p) and in silico

lipophilicity variables, i.e., log P_S-IT, XLOGP 2.0, XLOGP 3.0, ACLOGP, ALOGPs 2.1, miLogP 2.2,

CLOGP 4.0, log P_Cr, log P_V, log P_B, MLOGP and ALOGP, respectively.

Considering observed physicochemical characteristics of the compounds 1a

–p, there was found

statistically extremely signiﬁcant linear relationship between the and log k_wvalues. This dependence

γ

was expressed by Equation (2) and values of relevant statistical descriptors as follows:

γ = −0.0031 (±0.0003) × log k_w+ 0.0765 (±0.0015)

(2)

n = 16, DF = 14, χ,²_red= 6.436 × 10⁻⁷, RSS = 9.010 × 10⁻⁶, R = 0.9383, Adj. R²= 0.8718,

RMSE = 8.022 × 10⁻⁴, NR = 0.0030, F = 103.02, Prob > F = 0.0001 ***

Linearity of this model was adjusted by relatively very low χ²_red, RSS and RMSE values. The

and log k_wparameters of 1i showed the most positive impact to ﬁnal statistical analysis data

γ

–

p

(Equation (S28) in Table S7) connected with Equation (2) compared to those of a subset 1a–h (Equation

(S27) in Table S7).

One of the major tasks to consider in drug design is the ability of a compound to cross biological

membranes. The blood–brain barrier (BBB) is a critical biological structure for maintaining homeostasis

of central nervous system and preventing damage to the brain. Compounds primarily designed as

neuroactive agents are required to cross the BBB to provide their therapeutic effect. Conversely,

molecules that target other compartments of a body ideally should not cross this barrier to avoid

possible psychotropic side effects. Thus, the task of predicting the BBB permeability of new compounds

is of great importance [69].

Norinder and Haeberlein [70] suggested some simple rules to preliminary answer a question

whether a drug candidate would be able to cross the BBB. Very brieﬂy, if a sum of nitrogen and oxygen

atoms (n_N+ n_O) in a molecule was

≤

5 or if [CLOGP

−

(n_N+ n_O)] > 0 then the compound would

have a good chance to enter the brain by passive diffusion. The originally employed CLOGP was a

lipophilicity descriptor generated in silico. In addition, molecular weight (MW) of such compound

should be ≤ 450 to facilitate brain permeation [71].

Molecules 2018, 23, 2493

15 of 37

Each of the oxalates 1a–d and 1i–l contained (n_N+ n_O) = 10, each of the chlorides 1e–h and 1m–p

contained (n_N+ n_O) = 6 (Table 1 ), respectively. If presently calculated CLOGP 4.0 parameter would be

replaced with log P_S-IT(Table 5), which was closer to a ‘real’ log k_wlipophilicity descriptor (Figure 4),

only basic forms of the most lipophilic compounds 1l and 1p, i.e., the substances 9⁰l and 9⁰p, might

be considered to possess very limited brain permeation. On the other hand, calculated MW > 450 for

these derivatives [21] indicated that they might not be able to passively cross the BBB.

2.3. In Vitro Antimycobacterial Assays

The in vitro activity of compounds 1a–p was inspected against Mycobacterium tuberculosis CNCTC

My 331/88 (identical with H₃₇R_vand ATCC 2794, respectively; abbreviation used: MT_vH₃₇R_v),

M. tuberculosis H₃₇R_aATCC 25177 (MT_aH₃₇R_a), M. kansasii CNCTC My 235/80 (identical with

ATCC 12478; MK 235/80), a M. kansasii 6509/96 clinical isolate (MK 6509/96), M. kansasii DSM 44162

(MK DSM), M. avium CNCTC My 330/80 (identical with ATCC 25291; MA 330/80), M. smegmatis

ATCC 700084 (MS) and M. marinum CAMP 5644 (MM), respectively, by the methods described

earlier [20,72–75]. In vitro susceptibitity of given mycobacteria to reference drugs isoniazid (INH),

ethambutol (EMB), oﬂoxacin (OFLX) or ciproﬂoxacin (CPX) was tested as well (Tables 6 and 7).

A value of a minimum inhibitory concentration (MIC) was the lowest concentration of a tested

compound, (i) which inhibited growth of MT_vH₃₇R_v, MK 235/80, MK 6509/96 and MA 330/80,

respectively; (ii) at which no visible growth of MT_aH₃₇R_a, MS, MK DSM as well as MM was

observed [20,72–75].

The in vitro screening procedures related to particular mycobacterial strains were repeated

three times and the MIC values, reported in Tables 6 and 7 (in

µM units), were average values

of these determinations.

A very unique aspect of a present research was that many compounds from the set 1a–p

were

in vitro efﬁcient against almost all tested mycobacteria. The most promising molecules with observed

MIC ≤ 8 µM were indicated in gray (Tables 6 and 7).

The 3-alkoxy substituted derivatives 1e–h and 1m–p were slightly more effective against all

screened strains than their 2-alkoxy substituted isomers 1a

(Heptyloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium dichloride (1p

was the most active against almost complete spectrum of tested microorganisms (MIC M),

–d and 1i–l, respectively. 1-[2-[({[3-

)

≤

8 µ

excluding MA 330/80 only. Comparable efﬁciency to 1p was observed for 1-[2-[({[3-(heptyl-

oxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]pyrrolidinium dichloride (1h), which

also showed MIC

MS. In addition, antimycobacterial activity of 1-[2-[({[3-(pentyloxy)phenyl]amino}carbonyl)oxy]-3-(di-

propylammonio)propyl]azepanium dichloride 1n and 1-[2-[({[3-(hexyloxy)phenyl]amino}-

≤

8 µM against almost all tested mycobacteria, excluding MA 330/80 as well as

(

)

carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium dichloride (1o), respectively, was only slightly

lower compared to activity of the substances 1p and 1h (Tables 6 and 7).

It was found that MT_vH₃₇R_vwas not so sensitive to the compounds 1a

0.5 µM and 1 M). The most promising substances 1d 1h 1l 1n or 1p showed MIC = 4

(Table 6), respectively.

Similar trends were observed when evaluating susceptibility of MK 235/80. The molecules 1h

and 1p showed MIC = 8 M, however, the OFLX reference drug was more active (MIC = 0.5 M and

M; Table 6). Comparable ability to ﬁght MK 6509/96 was found for the derivative 1h, series 1n

(MIC = 4 µM and 8 µM) and INH (MIC = 2–8 µM; Table 6), respectively.

All 3-alkoxy substituted molecules 1e–h and 1m–p were more active against MT_aH₃₇R_a(MIC =

3.7–8.1 M) than INH (MIC = 36.5 M) or CPX (MIC = 48.3 M). The dibasic compounds were also

able to ﬁght MK DSM more effectively, their MIC values ranged from 1.9 M (1h) to 16.2 M (1e),

than INH (MIC = 29.2 M; Table 6). Moreover, the derivatives 1g 1h and 1n were almost equally

efﬁcient against MA 330/80 as EMB (MIC = 16 µM; Table 7).

–

p

as to INH (MIC =

µ

,

µM and 8

µM

,

1n

µ

1

µ

–p

µ

,

–p

Molecules 2018, 23, 2493

16 of 37

If attention was paid to the 2-alkoxy substituted compounds 1a

–

d

and 1i

–

l, 1-[2-[({[2-(heptyl-

oxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]pyrrolidinium dichloride (1d) was

more active against both MT_aH₃₇R_a(MIC = 12.5 µM) and MK DSM (MIC = 6.2 µM) than INH

(Table 6).

Waisser et al. [76] in vitro tested two series of structurally similar molecules JC-01a–l (Figure 3)

and JC-02a (Figure 5) against MT_vH₃₇R_v, MK 235/80, MK 6509/96 and MA 330/80, respectively.

–

l

The authors found that the compounds with an azepanium group were antimycobacterially more

promising agents than the ones containing a pyrrolidinium heterocycle.

Current in vitro assays revealed that both branching of a connecting hydrocarbon chain and

presence of ‘an additional’ dipropylammonium group within a salt-forming part of tested compounds

1a–p were favorable for their antimycobacterial activity and they were more effective than the sets

JC-01a–l and JC-02a–l.

The INH standard was less effective against MS (MIC = 117

than almost all screened phenylcarbamic acid-based substances, exluding the derivatives 1a

µ

M) as well as MM (MIC = 467

1i 1k or 1l

(Table 7). 1-[2-[({[2-(Pentyloxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]-azepanium

oxalate (1j) was the most active against MS (MIC = 6.2 M), the molecule 1h ﬁght MM most efﬁciently

(MIC < 3.7 M). On the other hand, these strains were sensitive to lower MICs of CPX (MIC = 0.4 µM

and 0.8 M; Table 7). It should be also mentioned that both sets JC-01a (Figure 3) and JC-02a

(Figure 5) have not been in vitro tested against MT_aH₃₇R_a, MK DSM, MS or MM.

µM)

,

µ

–

l

–l

Table 6. The in vitro activity (MIC values in µM units) of investigated compounds 1a–p and reference

drugs isoniazid (INH), ethambutol (EMB), oﬂoxacin (OFLX) and ciproﬂoxacin (CPX) against M.

tuberculosis CNCTC My 331/88 (M. tuberculosis H₃₇R_v; MT_vH₃₇R_v), M. tuberculosis H₃₇R_aATCC

25177 (MT_aH₃₇R_a), M. kansasii CNCTC My 235/80 (MK 235/80), M. kansasii 6509/96 (MK 6509/96)

and M. kansasii DSM 44162 (MK DSM), respectively.

MIC [µM]

MT_v

H₃₇R_v

MT_a

H₃₇R_a

MK

DSM

MK 235/80

MK 6509/96

Comp.

1

2

3

14-d

21-d

7-d

14-d

21-d

7-d

14-d

21-d

7-d

1a

1b

1c

1d

1e

1f

1g

1h

1i

1j

1k

1l

1m

1n

1o

1p

INH

EMB

OFLX

CPX

32

16

8

16

8

32

16

8

32

16

8

32

16

8

16

8

213

52

25

12.5

8.1

<3.9

<3.8

<3.7

203

199

195

96

15.4

7.5

7.3

62.5

32

16

32

16

8

32

16

8

62.5

32

16

32

16

8

62.5

32

16

8

16

8

>250

–

1

–

62.5

32

16

8

62.5

32

8

16

8

>250

–

1

32

16

8

16

8

62.5

32

16

8

62.5

16

32

16

8

32

16

8

2

1

–

53

26.1

12.7

6.2

16.2

7.9

3.8

1.9

51

8

4

16

8

4

8

4

8

4

0.5

1

16

8

4

2

32

16

8

4

2

50

98

382

7.7

7.5

3.6

29.2

–

16

8

1

2

8

7.1

36.5

–

48.3

>250

–

0.5

–

1

0.5

–

1

–

0.5

–

3.0

–

1

2

3

14-d, 14-Day cultivation; 21-d, 21-day cultivation; 7-d, 7-day cultivation. The most promising values of

compounds´ in vitro antimycobacterial activity (MIC ≤ 8 µM) were indicated in gray cells of Table 6.

The chemometric PCA tool was applied to study activity–activity relationships of the compounds

1a–p to explore similarities or differences in their impact on particular mycobacterial strains.

The analysis was carried out by the XLSTAT ver. 2016.02.28451 software (Addinsoft, New York,

Molecules 2018, 23, 2493

17 of 37

NY, USA), a statistical application for Microsoft Excel ver. 2013 (Microsoft Corp., Redmont, WA, USA).

Number of PCs was determined using visual evaluation of a scree plot, as a relationship between

calculated λ_eand number of PCs. A present selection of PCs was based on a Kaiser–Guttman rule, as

the most common stopping rule in PCA [77], which aimed an average value of λ_e> 1.0. The ﬁrst two

interpreted PCs of the analysis (with λ_e> 1.0) accounted for 89.59% of the total variance in the data as

follows: 77.22% (PC 1) and 12.37% (PC 2), respectively.

Table 7. The in vitro activity (MIC values in µM units) of investigated compounds 1a–p and reference

drugs isoniazid (INH), ethambutol (EMB), oﬂoxacin (OFLX) and ciproﬂoxacin (CPX) against M. avium

CNCTC My 330/80 (MA 330/80), M. smegmatis ATCC 700084 (MS) and M. marinum CAMP 5644

(MM), respectively.

MIC [µM]

Comp.

MA 330/80

MS

MM

1

2

3

14-d

21-d

3-d

21-d

1a

1b

1c

1d

1e

1f

1g

1h

1i

1j

1k

1l

1m

1n

125

62.5

32

62.5

32

16

8

62.5

32

125

62.5

32

62.5

32

213

104

51

24.9

16.2

15.8

15.4

15.0

203

6.2

390

382

30.7

15.0

7.3

106

52

25.5

12.5

32.5

<3.9

<3.8

<3.7

51

50

98

191

15.4

15.0

7.3

16

125

62.5

32

16

1o

1p

16

> 250

16

32

–

16

> 250

16

62.5

–

7.1

117

–

0.4

7.1

467

–

0.8

INH

EMB

OFLX

CPX

2

1

3

14-d, 14-Day cultivation; 21-d, 21-day cultivation; 3-d, 3-day cultivation. The most promising values of

compounds in vitro antimycobacterial activity (MIC ≤ 8 µM) were indicated in gray cells of Table 7.

Figure 5. Chemical structure of the derivatives of 2-/3-alkoxyphenylcarbamic acids JC-02a–l (alkoxy =

propoxy to octyloxy), which were in vitro screened against MT_vH₃₇R_v, MK 235/80, MK 6509/96 and

MA 330/80 [76], respectively.

The quality of 2D representation of a variable was visualized by a distance between the projected

variable onto a plane and circle of correlation. The loadings of variables were indicated as variously

colored vectors, connected with particular mycobacterial strains, and numbered according to their

position in the circle of radius 1 in an absolute value (Figure 6). In more detail, the digit 1 was assigned

to the vector built on the log (1/MIC [M]) values, which were connected with 14-d in vitro testing of

the compounds 1a–p against MT_vH₃₇R_v(MT_vH₃₇R_v, 14-d). Analogously, numbering of other vectors

Molecules 2018, 23, 2493

18 of 37

was as follows: 2 (MT_vH₃₇R_v, 21-d), 3 (MK 235/80, 7-d), 4 (MA 330/80, 14-d), 5 (MK 235/80, 21-d),

6 (MK 235/80, 14-d), 7 (MK 6509/96, 14-d), 8 (MK 6509/96, 7-d), 9 (MA 330/80, 21-d), 10 (MK 6509/96,

21-d), 11 (MT_aH₃₇R_a, 7-d), 12 (MM, 21-d), 13 (MK DSM, 7-d) and 14 (MS, 3-d), respectively.

A position of the variable in mapping could be deﬁned by values of square cosines (cos2), which

estimated quality of representation. The sum of cos2 for variables on PCs is equal to one. The higher

cos2, the more perfect representation of a variable by chosen PCs [68]. The highest sum of cos2 on PC 1

and PC 2 was found for the vector 1 (MT_vH₃₇R_v, 14-d). This vector was characterized by cos2 = 0.961

(Table S8) indicating its almost exclusive representation by both PC 1 and PC 2. In addition, its position

was the closest to a circle of correlation (Figure 6) compared to positions of the vectors 2–14. The cos2

values on particular PCs related to concerned vectors are listed in Table S8.

The vectors 1–3 were deﬁned by PC 1 > 0.75 and PC 2 > 0.25, the vectors 4–10 were described

by PC 1 > 0.75 and PC 2, which could be found in an interval from 0.25 to -0.25. Furthermore, PC 1 >

0.75 together with PC 2 between

−

0.35 and

−

0.53 were used to characterize the vectors 11–13. Finally,

the vector 14 was described by PC 1 < 0.75 and PC 2 < −0.50 (Figure 6), respectively.

Visual assessment indicated the smallest angles between the vectors 5–10. A relatively sharp angle

was also observed between 1 and 2 as well as 12 and 13, respectively. Conversely, there was found ‘almost

orthogonal’ arrangement of the vectors 1 and 14. Regarding this visualization, it could be assumed that

the compounds 1a–p showed (i) similar mechanisms of action against MK 235/80, MK 6509/96 and MA

330/80, respectively; (ii) different mechanisms of action against MT_vH₃₇R_vand MS.

Figure 6. Two-dimensional mapping of the loadings of variables (variously colored vectors) indicating

their (i) positions towards a circle of correlation; and (ii) relationships to both Principal Component 1

and 2. Numbering of the vectors was as follows: 1 (the vector built on the log (1/MIC [M]) values, which

were observed after 14-d in vitro cultivation against MT_vH₃₇R_v), 2 (MT_vH₃₇R_v, 21-d), 3 (MK 235/80,

7-d), 4 (MA 330/80, 14-d), 5 (MK 235/80, 21-d), 6 (MK 235/80, 14-d), 7 (MK 6509/96, 14-d), 8 (MK

6509/96, 7-d), 9 (MA 330/80, 21-d), 10 (MK 6509/96, 21-d), 11 (MT_aH₃₇R_a, 7-d), 12 (MM, 21-d),

13 (MK DSM, 7-d) and 14 (MS, 3-d), respectively.

Molecules 2018, 23, 2493

19 of 37

2.4. Structure–Activity Relationships

As suggested in previous sections of the paper, surface tension (relative surface activity γ;

in N/m units), electronic (log ε_{2 (Ch-T)}) and lipophilic (log k_w) properties of the compounds 1a–p

might notably affect their in vitro efﬁciency (in log (1/MIC [M]) units) against tested mycobacterial

strains. The PCA approach was applied for preliminary SAR studies of these derivatives by the

XLSTAT ver. 2016.02.28451 software. Number of PCs was determined using visual evaluation of a scree

plot, as a relationship between calculated λ_eand number of PCs. The ﬁrst three PCs of the analysis

with λ_e> 1.0 [77] accounted for 90.01% of the total variance in the data as follows: 69.59% (PC 1),

14.35% (PC 2) and 6.07% (PC 3), respectively.

The 2D visualization of relationships between the vectors describing physicochemical parameters

and in vitro antimycobacterial activities of the compounds 1a–p on axes (i) PC 1 and PC 2 (Figure S2),

as well as (ii) PC 1 and PC 3 (Figure S3) revealed the closest connection between lipophilicity (log k_w;

vector A) and efﬁciency against MT_vH₃₇R_v(14-d; 1). In addition, there were found notably negatively

correlated variables (vectors), which were positioned on opposed quadrants of the loading plots

(Figures S2 and S3). These correlations aimed

γ (C) versus log k_w(A) or C versus the vectors built

on in vitro activity against MT_vH₃₇R_v(14-d; 1), MT_vH₃₇R_v(21-d; 2), MA 330/80 (14-d; 3) as well as

MK 235/80 (7-d; 4). It seemed that ‘almost orthogonal’ arrangement of the vector characterizing log

ε_{2 (Ch-T)}(B) to those of antimycobacterial activities (5–14; Figure S3) indicated no correlation.

A linear, quasi-parabolic (polynomial function of 2^ndorder) and sigmoidal function, respectively,

was also employed in order to investigate SAR in more detailed manner. The research focused on

relationships between the independent variables (

γ

, log ε_{2 (Ch-T)}, log k_w) and dependent variable(s),

i.e., biological values (in log (1/MIC [M]) units).

Resulting equations and values of common statistical descriptors, namely, n, DF, χ ²

,

_red, RSS,

R, Adj. R², RMSE, NR, F and Prob > F, respectively, were calculated by using the Origin Pro ver.

9.0.0 SR2 software. In addition, only statistically signiﬁcant (Prob > F values varied from 0.0100 to

<0.0500; one-star indication), very signiﬁcant (Prob > F from 0.0010 to <0.0100; two stars indication) or

extremely signiﬁcant (Prob > F from 0.0000 to <0.0010; three stars indication) relationships between the

independent and dependent variables were presented in next paragraphs. These models were also

characterized by R ≥ 0.9000, Adj. R²≥ 0.7750 and F ≥ 25.00, respectively.

Respecting given criteria, the following discussion considered relationships connected with MT_v

H₃₇R_v, MK 235/80, MK 6509/96, MK DSM, MA 330/80 and MS as well. Conversely, there were found

no statistically signiﬁcant, very signiﬁcant neither extremely signiﬁcant models related to MT_aH₃₇R_a

or MM. It should be also noted that suggested models meeting those requirements were connected

mostly with the subgroups containing a limited number of compounds (n = 8). However, it was not

possible to perform the speciﬁc PCA for such subsets due to this restriction, i.e., number of effective

observations was lower (n = 8) than number of examined variables (n = 17). This was a reason why

next sections were focused mainly on linear, quasi-parabolic or sigmoidal ﬁtting procedures and their

statistical descriptions.

2.4.1. Models Related to Mycobacterium tuberculosis CNCTC My 331/88

Notable linear relationships between the

on both 14-d and 21-d in vitro screenings against MT_vH₃₇R_vwere observed for the series 1a

models were deﬁned by Equations (3)–(6) and found to be statistically very signiﬁcant or extremely

γ

or log k_wparameters and log (1/MIC [M]) values based

–

h. These

signiﬁcant. Decrease in

antitubercular proﬁle.

γ and increase in log k_wof these derivatives led to their more promising

MT_vH₃₇R_v(14-d)/1a-h: log (1/MIC [M]) = -120.2060 (±12.9578) × γ + 12.3509 (±0.8027) (3)

n = 8, DF = 6, χ,²_red= 0.0058, RSS = 0.0347, R = 0.9669, Adj. R²= 0.9240,

RMSE = 0.0761, NR = 0.1863, F = 86.06, Prob > F = 0.0001 ***

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MT_vH₃₇R_v(14-d)/1a-h: log (1/MIC [M]) = 0.4301 (±0.0737) × log k_w+ 2.9438 (±0.3393) (4)

n = 8, DF = 6, χ,²= 0.0133, RSS = 0.0798, R = 0.9220, Adj. R²= 0.8251,

red

RMSE = 0.1153, NR = 0.2825, F = 34.03, Prob > F = 0.0011 **

MT_vH₃₇R_v(21-d)/1a-h: log (1/MIC [M]) = -103.4692 (±18.7975) × γ + 11.1642 (±1.1644) (5)

n = 8, DF = 6, χ,²= 0.0122, RSS = 0.0730, R = 0.9136, Adj. R²= 0.8072,

red

RMSE = 0.1103, NR = 0.2702, F = 30.30, Prob > F = 0.0015 **

MT_vH₃₇R_v(21-d)/1a-h: log (1/MIC [M]) = 0.3957 (±0.0633) × log k_w+ 2.9505 (±0.2911) (6)

n = 8, DF = 6, χ,²= 0.0098, RSS = 0.0587, R = 0.9312, Adj. R²= 0.8449,

red

RMSE = 0.0989, NR = 0.2424, F = 39.13, Prob > F = 0.0008 ***

It seemed that ability to decrease surface tension of water was slightly more important than

increase in lipophilicity of inspected compounds 1a–h with the intention to improve their antitubercular

properties, especially when concerning 14-d in vitro biological evaluation.

It would not be reasonable to suggest some biparametric linear models containing γ, log k_w

and log (1/MIC [M]) parameters with an attempt to provide more satisfactory values of statistical

descriptors related to the set 1a . The reason not to apply bilinear reggresion analyses would be

–

h

that statistically extremely signiﬁcant relationships between

Table S7) were already observed.

γ and log k_w(Equations (S25)–(S28) in

ˇ

Current ﬁndings were only in partial agreement with a research of Cižmárik et al. [38,78,79],

who studied derivatives of 2-/3-alkoxyphenylcarbamic acid (alkoxy = propoxy do decyloxy), which

basic part was formed by only one azacycloalkyl moiety (pyrrolidinium or piperidinium). The authors

employed a linear, quasi-parabolic and sigmoidal model, respectively, to provide comprehensive

QSAR investigation. They found that simultaneous increase in lipophilicity and in vitro antitubercular

activity of these molecules was quite limited [78,79]. In addition, this behavior was also observed

when inspecting relationships between the in silico log p values (CLOGP 4.0) and in vitro efﬁciency

of these monobasic compounds against non-tuberculous MK 235/80, MK 6509/96 and MA 330/80,

respectively [38].

The antitubercular activities of derivatives 1a–p might theoretically indicate that comparable

efﬁciency of homologues containing a pyrrolidinium group would be observed, if length of their side

chain R would be beyond a certain border, i.e., if R = 2-/3-OC₈H₁₇or 2-/3-OC₉H₁₉.

A cell envelope of MT_vH₃₇R_vis composed of three major segments, namely, a plasma membrane,

cell wall core and outermost layer. The cell wall core, which is essential for viability, consists of

peptidoglycan (PG) in covalent attachment via phosphoryl-N-acetylglucosaminosyl-rhamnosyl linkage

units with heteropolysaccharide arabinogalactan (AG). The AG is in turn esteriﬁed at its non-reducing

ends to long-chain (C₇₀–C₉₀) mycolic acids. The latter form the bulk of the inner leaﬂet of the outer

membrane, with the outer layer consisting of a variety of non-covalently attached (glyco)lipids,

polysaccharides, lipoglycans, and proteins [80].

Results of present statistical analyses indicated that not only lipophilic nature of the compounds

1a–p, possible interactions of their side chain R with some components of the cell wall or ability do

decrease surface tension of water in order to ‘non-speciﬁcally’ disrupt the cell envelope could be

decisive for their in vitro efﬁciency. In fact, suggested mechanisms of antitubercular action might

become more relevant for the subgroup 1a–h compared to 1i–p.

A closer look at the relationships between inspected physichochemical and biological descriptors

among particular positional isomers proved that there were calculated more convenient statistical

values for the 2-alkoxy substituted compounds 1a

–d and 1i–l (Equations (S29)–(S32) in Table S9)

compared to those of the 3-alkoxy substituted isomers 1e–h and 1m–p, respectively.

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2.4.2. Models Related to the Mycobacterium kansasii Species

Statistically signiﬁcant linear relationships between the log k_wparameters and log (1/MIC [M])

values connected with in vitro testing of the series 1a against MK 235/80 were found. The MIC

–

h

values observed after 7-d and 14-d cultivation were the same (Table 6), so both proposed models were

deﬁned by Equation (7). More prospective anti-MK 235/80 compounds showed higher log k_wvalues.

MK 235/80 (14-d)/1a-h: log (1/MIC [M]) = 0.4395 (±0.0650) × log k_w+ 2.6388 (±0.2990)

(7)

n = 8, DF = 6, χ,²= 0.0103, RSS = 0.0620, R = 0.9403, Adj. R²= 0.8648,

red

RMSE = 0.1016, NR = 0.2489, F = 45.76, Prob > F = 0.0001 ***

Statistically extremely signiﬁcant linear models between the log k_wand log (1/MIC [M]) values

resulting from 7-d and 21-d in vitro screening of the subgroup 1a against MK 6509/96 were also set.

–

h

The observed dependences were deﬁned by Equations (8) and (9). Higher log k_wvalues were related

to more promising anti-MK 6509/96 agents.

MK 6509/96 (7-d)/1a-h: log (1/MIC [M]) = 0.5072 (±0.0757) × log k_w+ 2.5914 (±0.3485)

(8)

n = 8, DF = 6, χ,²= 0.0140, RSS = 0.0842, R = 0.9392, Adj. R²= 0.8624,

red

RMSE = 0.1185, NR = 0.2901, F = 44.86, Prob > F = 0.0001 ***

MK 6509/96 (21-d)/1a-h: log (1/MIC [M]) = 0.5061 (±0.0737) × log k_w+ 2.3356 (±0.3393) (9)

n = 8, DF = 6, χ,²= 0.0133, RSS = 0.0798, R = 0.9418, Adj. R²= 0.8682,

red

RMSE = 0.1153, NR = 0.2825, F = 47.12, Prob > F = 0.0005 ***

Increase in lipophilicity of the derivatives 1a–h was more important factor to positively inﬂuence

their efﬁciency compared to surface properties. However, it could be assumed that constant increase

in lipophilicity due to elongation of the side chain R would not led to more promising derivatives,

as observed for a subgroup 1i–p (Table 6).

Statistically very signiﬁcant and extremely signiﬁcant linear relationships between the

γ or

log k_wand log (1/MIC [M]) descriptors were also found when concerning the molecules 1a

–

h

and their 7-d in vitro efﬁciency against MK DSM. The models were characterized by Equations (10)

and (11), respectively.

Highly lipophilic compounds with ability to decrease surface tension of water more markedly

showed higher potential to ﬁght given mycobacterium. Conversely, increase in lipophilicity due to

increase in number of carbons of the azacycloalkyl fragment (1i

improvement in anti-MK DSM activity (Table 6).

–p) would not be a guaranty of

MK DSM (7-d)/1a-h: log (1/MIC [M]) = -192.0357 (±33.5781) × γ + 16.8889 (±2.0800)

(10)

(11)

n = 8, DF = 6, χ,²_red= 0.0388, RSS = 0.2330, R = 0.9192, Adj. R²= 0.8192,

RMSE = 0.1971, NR = 0.4827, F = 32.71, Prob > F = 0.0012 **

MK DSM (7-d)/1a-h: log (1/MIC [M]) = 0.7579 (±0.0817) × log k_w+ 1.5371 (±0.3758)

n = 8, DF = 6, χ,²_red= 0.0163, RSS = 0.0979, R = 0.9670, Adj. R²= 0.9240,

RMSE = 0.1277, NR = 0.3129, F = 86.15, Prob > F = 0.0001 ***

2.4.3. Models Related to Mycobacterium avium CNCTC My 330/80

Different models were suggested when exploring relationships between

γ

and log (1/MIC [M])

values resulting from 14-d and 21-d in vitro screening of the compounds 1a–p against MA 330/80.

Concerning well-known differences in their salt-forming fragment, a statistically very signiﬁcant linear

model was found for a subgroup 1a–h (14-d) and deﬁned by Equation (12).

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MA 330/80 (14-d)/1a-h: log (1/MIC [M]) = -150.5250 (±29.7405) × γ + 13.7803 (±1.8423)

(12)

n = 8, DF = 6, χ,²_red= 0.0305, RSS = 0.1828, R = 0.9001, Adj. R²= 0.7790,

RMSE = 0.1745, NR = 0.4275, F = 25.61, Prob > F = 0.0032 **

If a main criterion to consider was a position of compounds’ side chain R, a bilinear model between

γ and log (1/MIC [M]) was regarded as the most convenient for two subsets 1e–h and 1m–p (Figure 7 ).

A bilinear model proposed by Kubinyi [81] was generally applicable and presented a smooth

synthesis of both linear and non-linear parts of SAR as an effort to simulate a complex process in a

rather simplistic way.

The compounds with

capability to act against MA 330/80 (21-d). Further increase in

γ

varying from 0.05692 N/m (1p) to 0.06154 N/m (1n) showed a comparable

, i.e., minor ability to decrease surface

γ

tension of water, resulted in sharp decrease in their antimycobacterial efﬁciency. The observed

behavior could indicate a non-speciﬁc mechanism of action of these derivatives, which might be

based on their ability to disrupt an outermost layer of a cell envelope of MA 330/80. The layer,

which consists of diverse amphiphilic glycolipids, namely, mycosides C, glycolipids, peptidolipids,

and phospholipids, respectively, hinders diffusion of chemotherapeutic agents via the wall thus causing

multiple drug-resistance by exclusion [82].

Statistically very signiﬁcant or extremely signiﬁcant linear relationships between log k_wand log

(1/MIC [M]) resulting from 14-d and 21-d in vitro screening of the compounds 1a–h were also observed.

The suggested models were deﬁned by Equations (13) and (14). As expected, higher log k_wvalues

were connected with more effective agents.

MA 330/80 (14-d)/1a-h: log (1/MIC [M]) = 1.6968 (±0.3122) × log k_w+ 0.6051 (±0.0678)

(13)

(14)

n = 8, DF = 6, χ,²= 0.0113, RSS = 0.0675, R = 0.9643, Adj. R²= 0.9182,

red

RMSE = 0.1061, NR = 0.2599, F = 79.57, Prob > F = 0.0001 ***

MA 330/80 (21-d)/1a-h: log (1/MIC [M]) = 1.8560 (±0.4695) × log k_w+ 0.5458 (±0.1020)

n = 8, DF = 6, χ,²= 0.0255, RSS = 0.1528, R = 0.9092, Adj. R²= 0.7978,

red

RMSE = 0.1596, NR = 0.3909, F = 28.62, Prob > F = 0.0081 **

Statistical characteristics given above might support a hypothesis, which was based on a

non-speciﬁc mechanism of action of the molecules 1a against MA 330/80. However, the model

–

h

related to 21-d in vitro biological evaluation (Equation (14)) provided clearly worse values of the

statistical descriptors than those connected with 14-d in vitro screening (Equation (13)).

If attention was turned to the 3-alkoxy substituted derivatives 1e–h and 1m–p, increase in their

log k_wup to approximately 5.1000 (Table 3) meant sharp increase in activity against MA 330/80 (21-d).

Further increase in lipophilicity beyond this border was not reﬂected in higher antimycobacterial

potential of the compounds 1n, 1h, 1o and 1p showing log k_wof 5.2087, 5.5384, 5.6569 and 6.1749

(Table 3, Figure 8), respectively.

2.4.4. Models Related to Mycobacterium smegmatis ATCC 700084

There was observed a very signiﬁcant quasi-parabolic relationship between the log ε_{2 (Ch-T)}

values and log (1/MIC [M]) parameters connected with 3-d in vitro evaluation of the pyrrolidium

moiety-containing compounds 1c–h against MS (Equation (S33) in Table S9). The possibility to exclude

the molecules 1a and 1b from a current analysis was based on the observation that they showed the

lowest efﬁciency against given mycobacterium (Table 7).

It was found that anti-MS activity increased with increasing log ε_{2 (Ch-T)}, reached a maximum

if this independent variable was between 4.24 and 4.27 (1e, 1f and 1h) and then decreased with

Molecules 2018, 23, 2493

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further increase in the log ε_{2 (Ch-T)}values (Figure S4, Table 1). This behavior, deﬁned as a cut-off effect,

was originally reviewed and rationalized in number of mechanistic ways by Hansch and Clayton a

few decades ago [83].

It was also found that lower

γ and higher log k_wdid not lead to increase in anti-MS activity of the

compounds 1i , as explored by some models, which were not provided because of their statistical

–

p

insigniﬁcance (Prob > F ≥ 0.0500).

Figure 7. Bilinear relationship between the

γ (in N/m units) and log (1/MIC [M]) parameters resulting

from 21-d in vitro screening of the 3-alkoxy substituted compounds 1e–h and 1m–p (alkoxy = butoxy

to heptyloxy) against MA 330/80.

Figure 8. Bilinear relationship between the log k_wand log (1/MIC [M]) parameters resulting from

21-d in vitro screening of the 3-alkoxy substituted compounds 1e

heptyloxy) against MA 330/80.

–h and 1m–p (alkoxy = butoxy to

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3. Materials and Methods

3.1. General Information

Liquid chromatography high resolution mass spectroscopy (HPLC-HR-MS) analyses of the

compounds 9⁰a

(Supplementary Materials) were performed on a chromatographic apparatus

–

p

consisting of the LC Agilent Inﬁnity System (Agilent Technologies, Santa Clara, CA, USA) equipped

with a gradient pump (1290 Bin Pump VL), automatic injector (1260 HiPals), and column thermostat

(1290 TCC). The LC system was coupled with the Quadrupole Time-Of-Flight mass spectrometer

(6520 Accurate Mass Q-TOF LC/MS). Q-TOF was equipped with an electrospray ionization source

operated in a positive and negative ionization mode as well.

For data acquisition and processing, a personal computer with the Mass Hunter software ver.

MassHunter Workstation B 04.00 (Agilent Technologies) was used.

Each of the compounds 9⁰a

1 mg/L. Particular solutions were ﬁltered via 0.22

–

p

was dissolved in 50% (v/v) MeOH to reach a concentration of

m nylon syringe ﬁlter and 1.0 L was used for the

50 mm, 1.7 µm

µ

HPLC-HR-MS analyses at 35 ^◦C using the RP-C₁₈column Zorbax Extend-C₁₈, 2.1

×

(Agilent Technologies).

The mobile phases consisted of 0.1% aqueous solution of formic acid in demineralized water

(mobile phase A) and acetonitrile (mobile phase B). Gradient elution was used with linear gradient

from 5% to 95% of acetonitrile per 8 min. The ﬂow rate of a mobile phase was set to 400 µL/min.

The MS spectrometer was operated in a positive and negative ionization mode, respectively,

◦

keeping particular speciﬁcations as follows: drying gas temperature 360 C, drying gas ﬂow 12 L/min,

nebulizing gas pressure 60 psi, ESI source voltage 4000 V, fragmentor voltage 125 V, skimmer voltage

65 V and collision gas N₂, respectively. The m/z ratios of both [M + H]⁺and [M

recorded in an interval from 50 m/z to 1500 m/z. Observed m/z values of the adducts were compared to

the theoretical ones. The difference (in ppm units; Supplementary Materials) was calculated according

to Equation (15):

−

H]⁻ions were

Difference = [(m/z _theoretical− m/z _obtained)/m/z _theoretical] × 10⁶

(15)

High-resolution mass spectra of the compounds 1a–p were measured using the Dionex UltiMate

3000 high-performance liquid chromatograph (Thermo Scientiﬁc, West Palm Beach, FL, USA) coupled

with the LTQ Orbitrap XL Hybrid Ion Trap-Orbitrap Fourier Transform Mass Spectrometer (Thermo

Scientiﬁc) equipped with a HESI II (heated electrospray ionization) source operating in a positive

(

1a

Chromatography Data System ver. 7.2 (Thermo Scientiﬁc). The separation was performed on a

C₁₈-Hypersil Gold (3 m, 50 mm 2.1 mm) column (Thermo Scientiﬁc). A mobile phase consisted of

–d, 1i–l) or negative (1e–h, 1m–p) mode. The HPLC system was controlled through the Chromeleon

µ

×

water Purelab Classic (ELGA LabWater, High Wycombe, Bucks, UK) and acetonitrile hypergrade for

LC-MS LiChrosolv (Merck KGaA, Darmstadt, Germany) in 80:20 volume ratio (v/v). Total ﬂow rate

was 0.3 mL/min, injection volume was 1 µL, and column temperature was set to 30 ^◦C, respectively.

The UV/Vis spectra of methanolic solutions of analyzed compounds 1a

–

p

(c = 8.0

×

10⁻⁵M)

were observed on_◦the 8452A Diode Array spectrophotometer HP-8452A (Hewlett-Packard, Palo Alto,

CA, USA) at 21 C. Methanol for UV-spectroscopy (Merck, Darmstadt, Germany) was used for

preparation of these solutions. Results of the UV/Vis analyses were collected and stored digitally using

the ChemStation controller software (Agilent Technologies, Waldbronn, Germany). The HP-8452A

apparatus measured a complete range of compounds’ spectrum from 190 nm to 820 nm.

The HPLC separation module Waters e2695 equipped with a Waters 2996 PDA Detector (Waters

Corp., Milford, MA, USA) and chromatographic column Symmetry C₁₈

W21751W016 (Waters Corp.) were used for estimation of lipophilic properties of the compounds 1a–p

at 21 ^◦C.

×

5

µ

m, 4.6

×

250 mm, Part No.

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The HPLC separation process was monitored by the Empower 3 Chromatography Data Software

(Waters Corp.) working on a personal computer HP Compaq (Hewlett-Packard, Palo Alto, CA, USA)

equipped with Intel^®Core^TMi5 processor (Intel Corp., Santa Clara, CA, USA), 2400 CPU, 3.10 GHz,

and 4.00 GB of RAM, respectively. The computer operated on the Windows 7 Professional system,

a 64-bit version (Microsoft Corp., Redmont, WA, USA).

Isocratic elution was carried out using mobile phases consisting of methanol p.a. (MeOH;

Honeywell, Paris, France) and puriﬁed water in various volume ratios (80:20, 85:15, 90:10, 95:5

(v/v) and pure MeOH, respectively). Distilled water (CentralChem, Bratislava, Slovak Republic) was

puriﬁed by the Aquinity2 P10 ultra-pure water system for production of ultra-pure water with an

integrated 10 L permeate tank (membraPure, Hennigsdorf, Germany).

Total ﬂow of the column was 1.0 mL/min, injection volume was 4 µL and column temperature

was set to 40 ^◦C. The detection wavelengths varying from 236 nm to 238 nm were chosen for current

experimental procedures.

3.2. Synthesis of Compounds

Presently analyzed 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)-

propyl]pyrrolidinium oxalates (1a

–

d

)/dichlorides (1e

–

h) as well as 1-[2-[({[2-/3-(alkoxy)phenyl]-

amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium oxalates (1i

–l

)/dichlorides (1m

–p;

alkoxy = butoxy to heptyloxy) were prepared by multi step pathways (Scheme 1) using 2-aminophenol

(1a) and 3-aminophenol (1b), respectively, as starting compounds [21,27–29].

Procedures for preparation of reaction intermediates 2⁰a

,

2⁰b

,

3⁰a

–

h,

4⁰a

–

h

,

5⁰a

27

–

h

–

,

7⁰

, , ,

8⁰a 8⁰b

9⁰a

–

p

and ﬁnal molecules 1a

–

p

were originally published in research papers [21

,

29] and are

provided in Supplementary Materials. In addition, HPLC-HR-MS spectral characterizations of the

compounds 9⁰a–p are included as well.

Spectral data (IR), elemental analyses results (% C, H, N), melting point (m.p.) values, R_f

parameters (TLC) and acid-base dissociation constants (pK_a1, pK_a2), respectively, of solid colorless

compounds 1a

Supplementary Materials.

The molecules 1a–p were re-crystallized from mixture of acetone/ethanol (1a–d, 1e–h, 1m–p) or

acetone (1i ) before being spectrally, physicochemically and biologically investigated. Present HR-MS

–p can be found in the papers [21,26] and some of given characteristics are also listed in

–

l

spectral description of these compounds was given below.

The compound 1a: HR-MS for C₂₄H₄₂N₃O₃[M + H]⁺calculated 420.32207 m/z, found 420.32343

m/z; 1b: HR-MS for C₂₅H₄₄N₃O₃[M + H]⁺calculated 434.33772 m/z, found 434.33920 m/z; 1c: HR-MS

for C₂₅H₄₆N₃O₃[M + H]⁺calculated 448.35337 m/z, found 448.35471 m/z. 1d: HR-MS for C₂₇H₄₇N₃O₃

[M + H]⁺calculated 462.36902 m/z, found 462.37048 m/z; 1e: HR-MS for C₂₄H₄₀N₃O₃[M

−

H]⁻

H]⁻calculated

H]⁻calculated 446.33881

H]⁻calculated 460.35446 m/z, found

calculated 418.30751 m/z, found 418.30746 m/z; 1f: HR-MS for C₂₅H₄₂N₃O₃[M

432.32316 m/z, found 432.32294 m/z; 1g: HR-MS for C₂₆H₄₄N₃O₃[M

m/z, found 446.33912 m/z; 1h: HR-MS for C₂₇H₄₆N₃O₃[M

−

460.35458 m/z; 1i: HR-MS for C₂₆H₄₆N₃O₃[M + H]⁺calculated 448.35337 m/z, found 448.35458 m/z;

1j: HR-MS for C₂₇H₄₈N₃O₃[M + H]⁺calculated 462.36902 m/z, found 462.37045 m/z; 1k: HR-MS for

C₂₈H₅₀N₃O₃[M + H]⁺calculated 476.38567 m/z, found 476.38608 m/z; 1l: HR-MS for C₂₉H₅₂N₃O₃

[M + H]⁺calculated 490.40192 m/z, found 490.40210 m/z; 1m: HR-MS for C₂₆H₄₄N₃O₃[M

−

H]⁻

H]⁻calculated

H]⁻calculated 474.37011

H]⁻calculated 488.38576 m/z, found

calculated 446.33881 m/z, found 446.33908 m/z; 1n: HR-MS for C₂₇H₄₆N₃O₃[M

460.35446 m/z, found 460.35474 m/z; 1o: HR-MS for C₂₈H₄₈N₃O₃[M

−

m/z, found 474.36996 m/z; 1p: HR-MS for C₂₉H₅₀N₃O₃[M

488.38596 m/z.

−

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3.3. Determination and Prediction of Physicochemical Properties

3.3.1. Estimation of Surface Tension

Surface tension (relative surface activity;

γ

) of the derivatives 1a

–

p

was determined by a drop

count method using a glassy Traube stalagmometer (Kavalier Glass, Prague, Czech Republic). Number

of drops of compounds’ and reference solutions were counted between upper and lower marks of

the stalagmometer [30

deionized water (c = 2.0

which showed = 0.07259 N/m. The drops were allowed to form at constant temperature 21 C.

,

31]. Aqueous solutions of the molecules 1a

×

–p were prepared with distilled,

10⁻³M). Distilled deionized water was also used as a reference solution,

◦

γ

The experimental procedure was described in a paper [31]. Current measurements were done in six

replicates and average γ values (in N/m units) were reported (Table 1).

3.3.2. Estimation of Electronic Properties

The log

ε

values characterizing methanolic solutions of the compounds 1a

–

p

(c = 8.0

×

10⁻⁵

M) were observed at λ₁= 208–210 nm, λ_{2 (Ch-T)}= 236–238 nm and λ₃= 278–280 nm (Table 1),

respectively, in a near ultraviolet (quarz) region of the electromagnetic spectrum between 200 nm and

400 nm [35]. The log ε values for presently observed absorption maxima were calculated following the

Lambert-Beer’s law, which was discussed in [35], for example, and expressed by Equation (16):

A = ε × c × l

(16)

where the A parameter represented absorbance of a compound’s solution, the

ε descriptor was a molar

absorption coefﬁcient (in L/mol/cm units) and l was path length (in cm units).

3.3.3. Estimation and In Silico Investigation of Lipohydrophilic Properties

Lipophilicity of the compounds 1a–p was determined by reversed-phase high-performance liquid

chromatography (RP-HPLC). Methanol (MeOH)/water mobile phases with varying volume ratio of the

organic modiﬁer and water (80:20, 85:15, 90:10, 95:5 (v/v) and pure MeOH, respectively) were chosen.

A methanolic solution of potassium iodine was used for dead time (t_d) determination. Retention

factors (capacity factors; k) were calculated according to Equation (17):

k = (t_r− t_d)/t_d

(17)

where t_rwas retention time of a solute (in min), the t_dparameter denoted dead time of potassium

iodine, an unretained analyte (in min).

The observed retention (t_r) and dead (t_d) times were means of three independent determinations.

Average t_dvalues of potassium iodine in used MPhs were as follows: 2.237 min (MeOH/water

ratio (v/v) was 80:20), 2.245 min (85:15), 2.245 min (90:10), 2.228 min (95:5) and 2.210 min (pure

MeOH), respectively.

The log k_wvalues, i.e., the logarithms of extrapolated retention (capacity) factors for 100% water

in the isocratic RP-HPLC, were determined from intercepts of linear plots between the log k and φ_M

(a volume fraction of an organic modiﬁer in the isocratic elution RP-HPLC) according to Equation (18):

log k = log k_w− S × φ_M

(18)

where the S parameter represented the slope of a regression curve, which was related to solvent

strength of a pure organic solvent [51,52].

Purity (in percentages) of the compounds 1a–p was also veriﬁed by RP-HPLC. Areas of their

peaks were measured using the MPh, which contained 90% proportion (v/v) of MeOH. The purity of

given salts is provided in Table S3.

Molecules 2018, 23, 2493

27 of 37

The log p values of non-protonated bases 9a⁰

–

p

(Scheme 1 , Table 4) for the octan-1-ol/water

partitioning system were calculated by the Ghose and Crippen⁰s log P_Cr

[ ,

55], Viswanadhan⁰s

54

[56], Broto’s log P_B[57] and Leo’s CLOGP 4.0 [58] atomic as well as combined atomic and

log P_V

fragmental methods using the ChemBioDraw Ultra 12.0 software package (CambridgeSoft, Cambridge,

MA, USA).

The Virtual Computer Chemistry Laboratory [59], a freely available web-based tool working

in Java environment, was taken to generate log P by the Wang’s XLOGP 2.0 [60], Cheng’s XLOGP

3.0 [61], Moriguchi’s MLOGP [62], Sander’s (Actelion’s) ACLOGP [63], Molinspiration’s miLogP

2.2 [64], ALOGP [65] and Tetko’s ALOGPs 2.1 [66] method (Tables 4 and 5), respectively. All these

approaches integrated algorithms based on atomic/fragmental principles, excluding ALOGPs 2.1,

which considered a molecule in the whole [66].

The SILICOS-IT hybrid method, which used a proprietary fragment- and property-based

principles, was also employed to generate log P parameters (log P_S-IT; Table 5). The method was

implemented in the SwissADME applet, a free web tool designed to evaluate pharmacokinetics and

drug-likeness of small molecules [67].

3.4. In Vitro Antimycobacterial Assays

The in vitro activity of compounds 1a–p was inspected against Mycobacterium tuberculosis CNCTC

My 331/88 (identical with H₃₇R_vand ATCC 2794, respectively; abbreviation used: MT_vH₃₇R_v),

M. kansasii CNCTC My 235/80 (identical with ATCC 12478; MK 235/80), the M. kansasii 6509/96 clinical

isolate (MK 6509/96) and M. avium CNCTC My 330/80 (identical with ATCC 25291; MA 330/80),

respectively, in the Laboratory for Mycobacterial Diagnosis and Tuberculosis (Institute of Public

Health in Ostrava, Czech Republic). These strains were purchased from the National Reference

Laboratory—Czech National Collection of Type Cultures (CNCTC; The National Institute of Public

Health, Prague, Czech Republic), excluding MK 6509/96, which was clinically isolated because the

INH-resistant M. kansasii strains have not been found in Czech Republic or Slovak Republic. In the

experiments, dilution of the strains was as follows: 10⁻³M (MT_vH₃₇R_v), 10⁻⁴M (MK 235/80,

MK 6509/96) and 10⁻⁵M (MA 330/80), respectively.

The molecules 1a–p were also in vitro screened against an avirulent M. tuberculosis H₃₇R_a

ATCC 25177 (MT_aH₃₇R_a), M. kansasii DSM 44162 (MK DSM), M. smegmatis ATCC 700084 (MS)

and M. marinum CAMP 5644 (MM), respectively, in the Department of Infectious Diseases and

Microbiology (Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences

in Brno, Czech Republic).

Standard drugs. Isoniazid (INH), ethambutol (EMB), oﬂoxacin (OFLX) and ciproﬂoxacin (CPX)

reference drugs were purchased from Sigma-Aldrich (Darmstadt, Germany), respectively, showing

purity of analytical grade.

Determination of a minimum inhibitory concentration (MIC) against MT_vH₃₇R_v, MK 235/80,

MK 6509/96 and MA 330/80. Efﬁciency of the compounds 1a–p and standard drugs (INH, EMB and

OFLX, respectively) against given mycobacteria were determined in lyophilized Šula’s semisynthetic

medium (Sevac, Prague, Czech Republic) by a dilution-micromethod [20,72,84].

Each tested mycobacterial strain was simultaneously inoculated into Petri plates containing the

Šula’s medium for sterility control and growth of the inoculum [84]. All screened molecules were

added to this medium as solutions in dimethyl sulfoxide (DMSO; Sigma-Aldrich, Irvine, UK). In the

in vitro assays, following concentrations of the solutions were used: 1000, 500, 250, 125, 62.5, 32, 16, 8,

4, 2, 1, 0.5 and 0.25

µ

M, respectively. The inoculated plates kept in microtone bags were incubated at

◦

37 C. Particular reading was carried out macroscopically on a stand with a bottom magnifying mirror

using a magnifying glass.

Growth in the plates [20,72] was evaluated after 7, 14 and 21 days (MK 235/80, MK 6509/96) or

after 14 and 21 days (MT_vH₃₇R_v, MA 330/80).

Molecules 2018, 23, 2493

28 of 37

The value of a minimum inhibitory concentration (MIC) was the lowest concentration (on the

above concentration scale) of a tested compound, which inhibited growth of the mycobacteria [20 72].

M units), reported in Tables 6 and 7,

,

The screening was repeated three times and the MIC values (in

µ

were the same.

Determination of a minimum inhibitory concentration (MIC) against MT_aH₃₇R_a. The mycobacterium

was grown on Middlebrook broth (MB; MiddleBrook Pharmaceuticals, Inc., Westlake, TX, USA),

supplemented with Oleic-Albumin-Dextrose-Catalase (OADC) supplement (Difco, Lawrence, KS, USA)

and salicylate-derived mycobactin J (2

siderophore [85,86].

µg/mL; Allied Monitor Inc., Fayette, MO, USA), an iron-binding

At log phase growth, a culture sample (10 mL) was centrifuged at 15,000 rpm/20 min using

a bench top centrifuge MPW-65R (MPW Med Instruments, Warsaw, Poland). Following removal

of the supernatant, a pellet was washed in fresh liquid Middlebrook 7H9GC broth (MiddleBrook

Pharmaceuticals, Inc.) and re-suspended in a fresh OADC-supplemented MB (10 mL).

Turbidity was adjusted to match the McFarland standard No. 1 [87] containing approximately

3 × 10⁸Colony Forming Units (CFU) with MB broth. Further 1:20 dilution of the culture was performed

in MB broth.

Susceptibility of MT_aH₃₇R_awas investigated in a 96-well plate format. In the experiments, sterile

deionized water (300

of the medium in test wells during incubation. Each evaluated compound (100

MT_aH₃₇R_a(100 L). Dilutions of each compound were prepared in triplicate and ﬁnal concentrations

varied from 1000 g/mL to 8 g/mL. All tested molecules were dissolved in DMSO (Sigma-Aldrich,

µL) was added to all outer-perimeter wells of the plates to minimize evaporation

µL) was incubated with

µ

Irvine, UK), and subsequent dilutions were made in supplemented MB broth. The plates were sealed

with paraﬁlm and incubated at 37 ^◦C for 7 days.

Following incubation, 10% addition a water-soluble dye, the alamarBlue reagent (AbD

Serotec, Kidlington, UK) was mixed into each well. This resaurin-based reagent served as an

oxidation-reduction indicator of metabolic function and cellular health in cell viability bioassays [88].

Absorbance readings at 570 nm and 600 nm were taken, initially for background subtraction and

after 24h re-incubation. The subtraction is necessary for strongly colored compounds, where the color

may interfere with the interpretation of any color change. For non-interfering compounds, a blue color

in a well was interpreted as absence of growth and pink color was scored as growth [73,74].

The minimum inhibitory concentration (MIC) was deﬁned as the lowest concentration of a

compound, at which no visible bacterial growth was observed. In other words, the MIC was the lowest

concentration that prevented visual color change from blue to pink. The MIC value has been routinely

and widely used in bacterial assays and it has been a standard detection limit according to the Clinical

and Laboratory Standards Institute [73,74]. Clinically used antimycobacterials INH and CPX were

applied as reference drugs. The estimated MIC values (in µM units) were provided in Table 6.

Determination of a minimum inhibitory concentration (MIC) against MK DSM, MS and MM. A broth

dilution micromethod in Middlebrook 7H9 medium (Difco, Lawrence, MO, USA) supplemented with

BD BBL Middlebrook OADC Enrichment medium (Becton, Dickinson & Company, Franklin Lakes,

NJ, USA) containing 8.5 g NaCl, 50.0 g bovine albumin (fraction V), 20.0 g dextrose, 0.03 g catalase,

and 0.6 mL oleic acid [89], respectively, was used to determine the MIC values for given strains, as

described [75].

Tested phenylcarbamic acid-based molecules 1a–p as well as standard drugs INH and CPX were

dissolved in DMSO (Sigma-Aldrich, Irvine, UK) and ﬁnal concentration of DMSO did not exceed 2.5%

of the total solution composition. The ﬁnal concentrations, varying from 256 µg/mL to 0.125 µg/mL,

were obtained by a two-fold serial dilution of a stock solution in a microtiter plate with sterile medium.

Bacterial inocula were prepared by transferring colonies from culture into sterile water.

Cell density was adjusted to the 0.5 McFarland units [87] using the cell density meter Densi-La-Meter

(LIAP, Riga, Latvia). Final inoculum was made by 1:1000 dilution of the suspension with sterile

water. Drug-free controls, sterility controls and controls consisted of medium and DMSO alone were

Molecules 2018, 23, 2493

29 of 37

included. Results were determined visually after static incubation in darkness in aerobic atmosphere

◦

for: (i) 3 days at 37 C in a case of MS; (ii) 7 days at 37 C (MK DSM) and (iii) 21 days at 28 C

(MM), respectively.

The MIC parameter was deﬁned as the lowest concentration of a compound, at which no visible

bacterial growth was observed. The MIC value has been routinely and widely used in bacterial

assays considering it a standard detection limit according to the Clinical and Laboratory Standards

Institute [73,74]. Presently observed MIC values (in µM units) are provided in Tables 6 and 7.

3.5. Calculations and Statistical Analyses

Regression equations of relevant ﬁtting procedures and their statistical characteristics were

calculated and visualized by the Origin Pro ver. 9.0.0 SR2 software (OriginLab Corporation,

Northampton, MA, USA).

In a current research, those statistical parameters were calculated: number of points (number

of cases; n), degrees of freedom (DF), reduced chi-square (χ ²

, _red), residual sum of squares (RSS),

correlation coefﬁcient (R), adjusted coefﬁcient of determination (Adj. R²), root mean squared error

(standard deviation; RMSE), norm of residuals (NR), Fisher’s signiﬁcance ratio (Fisher’s F-test; F) and

probability of obtaining F Ratio (signiﬁcance of a whole model; Prob > F), respectively.

The analyses were also focused on indication of a signiﬁcance level of calculated F Ratio as

follows: * (one star)—statistically signiﬁcant; ** (two stars)—statistically very signiﬁcant; *** (three

stars)—statistically extremely signiﬁcant. Detailed information regarding given statistical descriptors

could be found in a research paper [47].

The chemometric principal component analysis (PCA) tool was used to explore relationships

between (i) experimental and in silico lipophilicity descriptors, (ii) in vitro efﬁciency against all tested

mycobacterial strains as well as (iii) physicochemical descriptors and in vitro biological activities of

the compounds 1a–p. The PCA is a mathematical algorithm that reduces the dimensionality of the

data while retaining most of variation in the data set. It accomplishes this reduction by identifying

directions, called principal components (PCs), along which the variation in the data is maximal.

By using a few components, each sample can be represented by relatively few numbers instead of by

values for thousands of variables. Samples can then be plotted, making it possible to visually assess

similarities and differences between samples and determine whether samples can be grouped [90].

The PCA was performed by the XLSTAT ver. 2016.02.28451 software (Addinsoft, New York, NY,

USA), a cloud-based statistical application for statistics and data analyses, which worked as an add-on

to the Microsoft Excel ver. 2013 software (Microsoft Corp., Redmont, WA, USA).

4. Conclusions

In summary, determination of physicochemical properties and in vitro antimymycobacterial

screening in connection with SAR analyses of 1-[2-[({[2-/3-(alkoxy)phenyl]amino}carbonyl)oxy]-3-

(dipropylammonio)propyl]pyrrolidinium oxalates (1a

oxy)phenyl]amino}carbonyl)oxy]-3-(dipropylammonio)propyl]azepanium oxalates (1i

(1m–p; alkoxy = butoxy to heptyloxy) were considered main objectives of the research.

All compounds 1a in aqueous solutions (c = 2.0

10⁻³M) were able to decrease surface tension

of water ( varied from 0.05692 N/m (1p) to 0.06464 N/m (1a).

= 0.07259 N/m) at 21 ^◦C and their

Relationships between number of carbon atoms forming their side chain R (n_c) and values (in N/m

–

d)/dichlorides (1e

–

h) and 1-[2-[({[2-/3-(alk-

–l

)/di- chlorides

–p

×

γ

units) were described most precisely by statistically signiﬁcant or very signiﬁcant models based on

polynomial functions of 2^ndorder within all homological subsets 1a–d, 1e–h, 1i–l and 1m–p.

Electronic properties of the molecules 1a

–

p

were characterized by logarithms of molar absorption

10⁻⁵M) investigated in the UV/Vis

coefﬁcients (log ) of their methanolic solutions (c = 8.0

ε

×

region of an electromagnetic spectrum. The solutions showed three absorption maxima in a near

ultraviolet (quarz) region of the spectrum between 200 nm and 400 nm. The maxima were found

at λ₁= 208–210 nm (second local excitation band), λ_{2 (Ch-T)}= 236–238 nm (charge-transfer band) and

Molecules 2018, 23, 2493

30 of 37

λ₃= 278–280 nm (ﬁrst local excitation band), respectively. There was observed nor linear neither

quasi-parabolic relationship between n_cand log ε_{2 (Ch-T)}, as the maximum being the most sensitive to

differences in electronic environment of a phenylcarbamoyloxy moiety due to different position and

length of a substituent R.

The log k_wvalues, as descriptors characterizing lipophilic properties of 1a–p, were extrapolated

from intercepts of statistically extremely signiﬁcant linear relationships between log k parameters and

volume fractions of MeOH modiﬁer (φ_M) using the Snyder–Soczewin´ski solvent strength model. These

log k_wvalues were in accordance with an elution order and hydrophobicity of the molecules 1a–p

and varied from 3.7688 (1a) to 6.1749 (1p). Increase in length of their side chain R led to higher S, as a

function of molecular structure parameters, within all homological sets. The compounds containing an

azepanium moiety showed higher S than those with a pyrrolidium group presuming same position

and length of R. The calculated S parameters varied from 3.7788 (1a) to 6.2672 (1p). A statistically

extremely signiﬁcant relationship between the log k_wand S values was found.

The experimental log k_wdataset was studied together with computational logarithms of partition

coefﬁcients (log P). The log P parameters of non-protonated bases 9⁰a

–p were calculated for the

octan-1-ol/water partitioning system using the Ghose and Crippen⁰s log P_Cr, Viswanadhan⁰s log

P_V, Broto’s log P_B, Leo’s CLOGP 4.0, Wang’s XLOGP 2.0, Cheng’s XLOGP 3.0, Moriguchi’s MLOGP,

Sander’s (Actelion’s) ACLOGP, Molinspiration’s miLogP 2.2, ALOGP, SILICOS-IT and Tetko´s ALOGPs

2.1 method as well. Similarities and differences between log k_wand in silico descriptors were analyzed

by unscaled principal component analysis (PCA). There was conﬁrmed high sensitivity of PCA for

detecting of small differerences between analyzed positional isomers, which given in silico methods

could not perform with satisfactory visibility. The log P_I-IT, XLOGP 2.0 and XLOGP 3.0 descriptors

might be used to characterize lipophilic properties of investigated salts and bases, especially if they

contained highly lipophilic side chain R.

The compounds 1a–p were in vitro screened against Mycobacterium tuberculosis CNCTC My

331/88 (identical with H₃₇R_v; abbreviation used: MT_vH₃₇R_v), M. tuberculosis H₃₇R_aATCC 25177

(MT_aH₃₇R_a), M. kansasii CNCTC My 235/80 (MK 235/80), the M. kansasii 6509/96 clinical isolate

(MK 6509/96), M. kansasii DSM 44162 (MK DSM), M. avium CNCTC My 330/80 (MA 330/80),

M. smegmatis ATCC 700084 (MS) and M. marinum CAMP 5644 (MM), respectively. In vitro susceptibility

of given mycobacteria to clinically used reference drugs isoniazid (INH), ethambutol (EMB), oﬂoxacin

(OFLX) or ciproﬂoxacin (CPX) was tested as well.

A very unique aspect of a present research was that many compounds from the set 1a

–p were

in vitro efﬁcient against almost all tested mycobacterial strains. The compounds 1h and 1p were the

most active practically against the whole spectrum of tested mycobacteria (MIC

MA 330/80.

≤

8 µM), excluding

All 3-alkoxy substituted molecules 1e

MIC = 3.7–8.1 µM) than INH or CPX. The dibasic compounds also inhibited growth of MK DSM

more effectively (MIC = 1.9–16.2 M) compared to INH. Moreover, the derivatives 1g 1h and 1n

showed approximately equal activity against MA 330/80 (MIC = 16 M) as EMB. Regarding MT_v

H₃₇R_v, however, none of the molecules 1a showed similar ability to ﬁght given mycobacterium as

INH. Comparable activity against MK 6509/96 was found for the substances 1h 1n (MIC = 4

and 8 M) and INH. If concerning the 2-alkoxy substituted compounds 1a and 1i , the derivative

1d was more promising against MT_aH₃₇R_a(MIC = 12.5 M) and MK DSM (MIC = 6.2 M) than INH.

The INH standard was also less effective against MS or MM than practically all tested phenylcarbamic

–h and 1m–p were more efﬁcient against MT_aH₃₇R_a

(

µ

,

–p

µ

–

p

,

–

p

µM

µ

–d

–l

µ

acid-based substances, from which were 1j (MIC = 6.2 µM; anti-MS) and 1h (MIC < 3.7 µM; anti-MM)

the most efﬁcient.

The chemometric PCA approach as well as ﬁtting procedures, supported by relevant equations

and adequate statistical analyses, were used to comprehensively investigate SAR of the derivatives

1a

–

p. It seemed that ability to decrease surface tension of water was slightly more important than

increase in lipophilicity of a pyrrolidinium moiety-containing compounds 1a

–h

in order to improve

Article Doi

Dibasic derivatives of phenylcarbamic acid against mycobacterial strains: Old drugs and new tricks?

DOI: 10.3390/molecules23102493

Source and publish data:

Authors:

Article abstract of DOI:10.3390/molecules23102493

Full text of DOI:10.3390/molecules23102493

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