Studies on log Po/w of quinoxaline di-N-oxides: A comparison of RP-HPLC experimental and predictive approaches

Article abstract of DOI:10.3390/molecules16097893

As reported in our previous papers, a series of quinoxaline-2-carboxamide 1,4-di-N-oxide derivatives were synthesized and studied as anti-tuberculosis agents. Here, the capability of the shake-flask method was studied and the retention time (expressed as log K) of 20 compounds were determined by RP-HPLC analysis. We found that the prediction of log P by the RP-HPLC analysis can result in a high accuracy and can replace the shake-flask method avoiding the experimental problems presented by quinoxaline di-N-oxides. The studied compounds were subjected to the ALOGPS module with the aim of comparing experimental log Po/w values and predicted data. Moreover, a preliminary in silico screening of the QSAR relationship was made confirming the influence of reduction peak potential, lipophilicity, H-bond donor capacity and molecular dimension descriptors on anti-tuberculosis activity.

Full text of DOI:10.3390/molecules16097893

Molecules 2011, 16, 7893-7908; doi:10.3390/molecules16097893
OPEN ACCESS
molecules
ISSN 1420-3049
www.mdpi.com/journal/molecules
Article
Studies on Log Po/w of Quinoxaline di-N-Oxides: A Comparison
of RP-HPLC Experimental and Predictive Approaches
Elsa Moreno 1,2,*, Elisabetta Gabano 2, Enrique Torres 1, James A. Platts 3, Mauro Ravera 2,
Ignacio Aldana 1, Antonio Monge 1 and Silvia Pérez-Silanes 1
1
Neglected Diseases Section, Drug R&D Unit, Center for Applied Pharmacobiology Research,
University of Navarra, C/ Irunlarrea s/n, 31008 Pamplona, Spain
2
Dipartimento di Scienze dell’Ambiente e della Vita, Università del Piemonte Orientale “A. Avogadro”,
Viale Michel 11, 15121 Alessandria, Italy
3
School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK
* Author to whom correspondence should be addressed; E-Mail: emoreno4@alumni.unav.es;
Tel.: +34-948-425653; Fax: +34-948-425652.
Received: 30 August 2011; in revised form: 6 September 2011 / Accepted: 7 September 2011 /
Published: 13 September 2011
Abstract: As reported in our previous papers, a series of quinoxaline-2-carboxamide
1,4-di-N-oxide derivatives were synthesized and studied as anti-tuberculosis agents. Here,
the capability of the shake-flask method was studied and the retention time (expressed as
log K) of 20 compounds were determined by RP-HPLC analysis. We found that the
prediction of log P by the RP-HPLC analysis can result in a high accuracy and can replace
the shake-flask method avoiding the experimental problems presented by quinoxaline
di-N-oxides. The studied compounds were subjected to the ALOGPS module with the aim
of comparing experimental log Po/w values and predicted data. Moreover, a preliminary
in silico screening of the QSAR relationship was made confirming the influence of
reduction peak potential, lipophilicity, H-bond donor capacity and molecular dimension
descriptors on anti-tuberculosis activity.
Keywords: HPLC; lipophilicity; log P; quinoxalines

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1. Introduction
Quinoxaline derivatives are a class of compounds that show very interesting biological properties
and, therefore, they are receiving increasing attention from many medicinal chemistry researchers. The
quinoxaline ring has been described as a bioisoster of quinolein, naphthalene and some other
heterocycles which are the base of many antimalarial, antibacterial or antitumor agents (such as
quinine, mefloquine, isoniazid, pyrazinamide or tirapazamine) [1].
The oxidation of both nitrogens of this heterocyclic system, carried out in order to obtain
quinoxaline 1,4-di-N-oxide (QdO) derivatives, increases the number of biological properties [2]. It has
been reported that QdO derivatives actually improve the biological results shown by their reduced
analogues and are endowed with antiviral, anticancer [3,4], anticandidal [5,6], antibacterial [7-11], and
antiprotozoal activities [12,13]. In fact, since the 1940s, QdOs were known as potent antibacterial agents
and subtherapeutic levels have been used as animal growth promoters in feed additives [11,14,15].
Taking into account the fact that QdOs are receiving growing attention in the field of medicinal
chemistry, it would be interesting to study the physicochemical properties of this family of
compounds. The study of absorption, distribution, metabolism and excretion should be considered in
the first stages of compounds development as this information could be of great help when identifying
new candidates or optimizing structures [16-19]. The main properties for studying ADME in biological
systems are solubility, lipophilicity, stability, and acid-base character. Lipid solubility is one of the
most important determinants of the pharmacokinetic characteristics of a drug and many properties,
such as absorption, penetration or elimination are related to lipophilicity.
The logarithm of n-octanol/water partition coefficient (log Po/w) is the most frequently used
parameter for measuring as it has been shown that this partition system is a good model for many
biological processes [16,17,20-22]. In fact, log Po/w is also used as one of the standard properties
identified by Lipinski in the “rule of 5” for drug-like molecules [23,24].
Measurement of this parameter is always recommended and many methods have been developed
for this purpose. The classical shake-flask method is time-consuming. Its use is limited in the log Po/w
range between -2 and 4, and it is impossible to use with surface-active materials [25]. For these
reasons, many chromatographic methods have successfully been used to assess lipophilicity of organic
compounds. HPLC provides an easy, reliable and accurate way to determine the partition properties of
compounds based on their chromatographic retention times [16,17,26,27]. On the other hand, since the
1970s, several methods have been proposed for log P computation. These methods could be divided
into two groups: property-based methods and additive methods. The former group computes log P as a
function of molecular properties such as molecular surfaces, volumes, partial charges or
HOMO/LUMO energies, including topological indices as descriptors [28,29]. Additive methods firstly
introduced by Hansch and co-workers [30-32], use basic structural building blocks as descriptors. They
calculate the value of a molecule by summing up the contributions from all the blocks of the structure
and considering some correction factors [26,33-35].
In this paper the viability of the RP-HPLC and the shake-flask methods to measure the partition
coefficients of QdO is studied. Moreover, the capability of different predictive methods to properly
parametrize the N-oxide function is evaluated.

Molecules 2011, 16
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2. Results and Discussion
2.1. Experimental log Po/w: Shake-Flask vs. RP-HPLC Method
The lipophilicity of a drug is related to its ability to cross cell membranes by means of passive
diffusion. This property is usually expressed by the logarithm of the n-octanol/water partition
coefficient, log Po/w. The log Po/w reflects the relative solubility of the drug in n-octanol (a model of the
lipid bilayer of a cell membrane) and water (the fluid inside and outside cells). Traditionally, log Po/w
values are measured using the “shake-flask” with the n-octanol and water partition system.
The photochemical instability of QdO is well-known and many studies have been reported [36-38].
It has been observed that the absorption spectrum of neutral QdO solutions change quickly due to
exposure to sunlight. For these reasons, solutions of QdO must be kept protected from light and used
as soon as prepared. With the aim of studying the suitability of the shake-flask method, four
compounds (10, 14, 22 and 26) were selected and many attempts to measure the log Po/w were
performed using the classical shake-flask method. Thus, it was verified that the classical “shake-flask”
method is not suitable for the measurement of log Po/w values of QdO derivatives. In fact, these
compounds have very low solubility in water and, above all, some of them degrade in solution (see
supporting information for details) and create emulsions during the partition procedure.
For these reasons, a RP-HPLC method was used for the determination of log Po/w values of QdO
derivatives. The RP-HPLC method used (see Experimental section) is applicable to the QdO
derivatives because it is performed at pH = 7.4 and quinoxalines di-N-oxide derivatives are more stable
in neutral solutions than working at extreme pH values. Moreover, the period of time in which the
compounds are in contact with the mobile phase is not long enough for the quinoxalines to degrade as
was observed when studying the corresponding chromatograms (see supporting information for details).
2.1.1. Correlation between log Po/w and log k’0
In this study nine compounds (1–9) have been selected as reference compounds from the
Recommended Reference Compounds list published by the OECD [39]. The chosen compounds allow
building a model covering a fairly wide range of log Po/w values (i.e., from ca. 0 to 4.5). The retention
times of these reference compounds have been measured and expressed as log k’0. The log k’ values
have been extrapolated to 0% methanol in order to determine the capacity factors represented as log
k’0. To predict the log Po/w values using the log k’0 values, the least square regression was employed to
generate Equation (1):
log P = 0.2759 + 0.9962 log k
(1)
R2 = 0.999; RMSE = 0.111; n: 9.
The cross-validation statistical parameters determined with the Leave One Out procedure were the
following:
R2LOO = 0.987; RMSELOO = 0.140
The detailed results of the LOO test are presented in Table 1.

Molecules 2011, 16
Table 1. log Po/w, log k’0 and related RP-HPLC log Po/w values for the reference compounds.
7896
LOO-predicted
RP-HPLC
log Po/w
0.15
RP-HPLC
a
Name
Code
log Po/w
log k’0
log k’
2-Butanone
Aniline
Acetanilide
Acetophenone
Benzene
Chlorobenzene
Bromobenzene
Naphthalene
Benzyl benzoate
1
2
3
4
5
6
7
8
9
0.3
0.9
1.0
1.7
2.1
2.8
3.0
3.6
4.0
−0.06
0.67
0.88
1.27
1.87
2.62
2.84
3.15
3.74
0.21
0.94
1.15
1.54
2.14
2.89
3.10
3.42
4.01
0.96
1.19
1.52
2.14
2.90
3.12
3.36
4.01
a Reference log Po/w values taken from OECD Guidelines.
Taking into account these values, it can be said that Equation (1) can be used to predict the log Po/w
of QdO derivatives using the log k’0 values.
2.1.2. log Po/w of Quinoxalines di-N-Oxide
Retention times of QdO 10–29 were measured and the capacity factors (log k’) were calculated in
varying proportions of methanol from 70% to 40%. The capacity factors were extrapolated to 0%
methanol as in the case of the reference compounds (Table 2). The related log Po/w values were
determined using Equation 6 and are also reported in Table 2.
Table 2. Capacity factors and related RP-HPLC log Po/w for QdO.
O-
N+
O
R7
R6
R
N
H
Capacity factors
RP-HPLC
N+
O-
log Po/w
R
R7/R6 Comp. log k’70 log k’60 log k’50 log k’40 log k’0
H/H
CH3/H
Cl/H
Cl/Cl
H/H
CH3/H
Cl/H
Cl/Cl
H/H
10
11
12
13
14
15
16
17
18
19
20
21
−0.64
−0.56
−0.36
−0.11
−0.58
−0.45
−0.37
−0.06
−0.24
−0.16
0.02
−0.34
−0.24
−0.05
0.27
−0.26
−0.13
0.00
0.34
0.11
0.21
0.42
−0.05
0.07
0.30
0.66
0.05
0.21
0.36
0.74
0.48
0.60
0.84
1.15
0.28
0.35
0.65
0.98
0.36
0.47
0.69
1.07
0.85
0.94
1.22
1.60
1.49
1.58
1.98
2.46
1.61
1.73
2.11
2.60
2.30
2.43
2.83
3.51
1.76
1.85
2.25
2.72
1.88
2.00
2.38
2.87
2.57
2.69
3.09
3.78
C6H5-CH2
2-
phenylethyl
CH3/H
Cl/H
Cl/Cl
p-BrC6H4-
CH2
0.19
0.65

Molecules 2011, 16
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Table 2. Cont.
O-
O
R7
R6
N+
R
N
H
Capacity factors
RP-HPLC
log Po/w
N+
O-
R
R7/R6 Comp. log k’70 log k’60 log k’50 log k’40 log k’0
H/H
CH3/H
Cl/H
Cl/Cl
H/H
CH3/H
Cl/H
Cl/Cl
22
23
24
25
26
27
28
29
−0.44
−0.36
−0.25
0.14
−0.33
−0.12
−0.13
0.25
−0.10
−0.01
0.15
0.54
0.14
0.33
0.38
0.76
0.25
0.34
0.54
0.93
0.62
0.80
0.91
1.31
0.62
0.66
0.93
1.33
1.06
1.21
1.38
1.78
2.02
2.02
2.51
2.91
2.92
3.02
3.42
3.86
2.29
2.29
2.77
3.18
3.18
3.28
3.69
4.12
p-CH3C6H4-
CH2
2,2-
diphenylethyl
Examination of the data indicates the influence of the quinoxaline structure on the log Po/w values.
As expected, the log Po/w values of all the QdO derivatives are positive in a range between 1.5 and 4.5.
The 20 compounds can be divided into five different series based on structure. Within each series of
analogues, the insertion of a methyl group resulted in a soft increase of the log Po/w value, and
replacing the hydrogen atom with one or two chloro groups supposed an increase of 0.5 or 1.0 unit,
respectively. Increasing the aliphatic chain between the amide group and the aromatic system resulted
in an increase of the log Po/w values as can be observed comparing derivatives 10, 11, 12, 13 versus 14,
15, 16, 17. The p-bromo substituent (compounds 18–21) increases the lipophilicity of the molecules.
Finally, looking at the values of compounds 26, 27, 28 and 29, it can be observed that these
compounds, which contain a diphenyl substituent on the amide chain, presented the highest log Po/w
values of all the QdO derivatives.
Therefore, the results suggest that the HPLC analysis is a suitable method for determining the log
Po/w for quinoxaline derivatives instead of classical methods which are too slow, labor intensive and
expensive. In particular, the RP-HPLC method for the QdO derivatives allows avoiding the problems
associated with the classical shake-flask method, impossible to use with this kind of compounds.
2.2. Calculated log Po/w
All of the QdO were subjected to the ALOGPS online module. Seven values were obtained for each
compound using different computational methods included in this module. The predicted log Po/w data
are reported in Table 3. RMSE was calculated for each computational method in order to judge which
method best suits experimental RP-HPLC.
The RMSE calculated from experimental and estimated log Po/w values ranged between 0.36 and
3.52 for XLOGP3 and MLOGP, respectively. From these data, XLOGP3 can be considered as the best
approach to estimate log Po/w for the QdO.

Molecules 2011, 16
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Table 3. Calculated log Po/w for quinoxaline derivatives and related RMSE.
Calculated log Po/w
RP-HPLC
log Po/w
1.76
Comp.
ALOGPs miLOGP ALOGP MLOGP LogKOW XLOGP2 XLOGP3
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
0.43
0.50
1.03
1.72
0.63
0.80
1.25
2.03
1.14
1.29
1.82
2.74
0.56
0.75
1.22
2.31
1.78
1.98
2.36
3.19
1.28
−0.48
−0.05
0.18
0.78
−0.07
0.35
0.58
1.19
0.33
0.76
0.99
1.59
−0.03
0.40
0.63
1.07
1.31
1.74
1.97
2.57
1.96
1.11
1.60
1.77
2.44
1.43
1.92
2.09
2.76
1.86
2.34
2.52
3.19
1.60
2.08
2.26
2.71
2.78
3.27
3.45
4.11
0.43
−1.71
−1.47
−1.20
−0.70
−1.47
−1.24
−0.97
−0.47
−1.08
−0.85
−0.59
−0.09
−1.47
−1.24
−0.97
−0.36
−0.35
−0.14
0.12
0.55
1.10
1.20
1.84
1.04
1.59
1.69
2.33
1.44
1.99
2.09
2.73
1.10
1.65
1.74
2.16
2.16
2.71
2.81
3.45
0.89
5.03
5.46
5.65
6.27
5.18
5.62
5.80
6.43
5.82
6.26
6.44
7.07
5.46
5.90
6.08
6.71
6.67
7.11
7.29
7.92
3.47
1.28
1.64
1.90
2.53
1.74
2.10
2.37
2.99
1.97
2.33
2.60
3.22
1.64
2.01
2.27
2.90
3.19
3.56
3.82
4.45
0.36
1.85
2.25
2.72
1.88
2.00
2.38
2.87
2.57
2.69
3.09
3.78
2.29
2.29
2.77
3.18
3.18
27
28
29
3.28
3.69
4.12
0.60
3.52
RMSE

Molecules 2011, 16
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Nevertheless, and in an attempt to improve the predictive capacity of the ALOGPS, the LIBRARY
mode was used, and experimental log Po/w data of compounds 10–13 were used to generate the library
that was taken into consideration for recalculating the log Po/w of the rest of QdO (Table 4).
Table 4. Calculated log Po/w for quinoxaline derivatives using ALOGPS with and without
LIBRARY mode.
RP-HPLC
log Po/w
1.88
ALOGPs
LIBRARY
1.93
Comp.
ALOGPs
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
0.63
1.25
0.80
2.03
1.14
1.82
1.29
2.74
0.56
1.22
0.75
2.31
1.78
2.36
1.98
3.19
1.29
2.38
2.00
2.87
2.57
3.09
2.69
3.78
2.29
2.77
2.29
3.18
3.18
3.69
3.28
4.12
2.43
2.08
3.04
2.40
2.92
2.54
3.54
1.90
2.41
2.06
3.19
3.18
3.67
3.33
4.32
0.19
RMSE
The examination of the data reveals that ALOGPS LIBRARY mode presents a RMSE of 0.19,
making it the best approach for predicting the partition coefficients of QdOs.
In Silico Screening of the QSAR Relationship
The anti-tuberculosis activity of the studied compounds has been previously reported [40,41].
In vitro evaluation of the anti-tuberculosis activity has been carried out within the Tuberculosis
Antimicrobial Acquisition & Coordinating Facility (TAACF) screening program for the discovery of
novel drugs for the treatment of tuberculosis. The compounds were tested against Mycobacterium
tuberculosis H37Rv (ATCC 27294) in BACTEC 12B medium using the Microplate Alamar Blue
Assay (MABA). Compounds showing an IC90 value of ≤10 µg/mL were considered “Active” for
antitubercular activity and considered for the VERO cell cytotoxicity assay. Cytotoxicity is determined
as the CC50 using a curve fitting program. Ultimately, the CC50 is divided by the IC90 to calculate a SI
(Selectivity Index) value. SI values of ≥10 are considered “Active”.
Since log Po/w is an important ADME parameter, a correlation with the anti-tuberculosis activity of
compounds was looked for. However, it was verified that there is not a strong relationship (R2 < 0.2)
between log Po/w and activity, expressed as log(1/IC50) or log(1/IC90). In spite of this, it seems that a
low value of log Po/w could be related with better values of anti-tuberculosis activity.

Molecules 2011, 16
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This fact could be explained as a consequence of the structure of the M. tuberculosis envelope
structure. Porin presented in the membrane control the diffusion of small hydrophilic molecules; and,
therefore, M. tuberculosis is more permeable to hydrophilic drugs such as INH, PZA, EMB or
gatifloxacin that present a log P of −0.71, −0.71, −0.12 and −0.23, respectively (ALOGPS, [42]) In this
sense, lipophilic molecules should be able to easily cross the lipid bilayer; however, the bilayer’s
uncommon thickness and the presence of the mycolic acids seem to dicrease the permeability to
lipophilic drugs. Nevertheless, it has been observed that the more lipophilic the agents are, the more
active they usually are against M. tuberculosis, as for instance, PAS, RIF or rifapentine presenting log
P values of 0.62, 3.85 and 4.83, respectively (ALOGPS). This fact suggests that there must be an
specific pathway for lipophilic drug transport [43].
Recent studies have focused on the influence of physicochemical properties of antibacterial drugs
and they have concluded that it is not possible to establish a strong relationship between these
properties and the anti-tuberculosis activity. In this sense, it seems that much work is needed in order
to understand M. tuberculosis and its metabolism. At this moment, recent reviews affirm that
antibacterial drugs constitute an special physicochemical space completely different from the space
covered by drugs in many other therapeutic areas [44].
On the other hand, in the previous paper a good relationship was found between redox peak
potential Epc,1 and activity [45]. In that case, however, the correlation was found within an almost
homogeneous series of molecules. Here a more heterogeneous set of compounds has been studied. For
molecules 11–24, 26–29 there is not a strong relationship (R2 < 0.2) between peak potential and
activity. However, it is evident that the compounds roughly align (according to the R substituent) or
group themselves (according to the R6 and R7 substituents) in homologous series. This behaviour
justifies the previously found relationship for a small and almost uniform set of molecules.
The above said results point out that log Po/w and Epc,1, although important parameters, cannot
explain alone the observed activity. When considering simultaneously the effect of both factors, a
two-variable model was built to predict activity, resulting in a better fitting ability (R2 ≅ 0.53). Some
other variable is probably needed to improve the model.
In order to enlarge the set of possible variables, the structures of compounds 10–29 were optimised
with the MOE (Molecular Operating Environment) software using a MMFF force field [46]. From the
optimised structures 333 molecular descriptors were calculated. This set of parameters was reduced to
269 excluding variables with constant values. A multiple linear regression (MLR) procedure with a
stepwise forward selection of the variables was applied to the whole set of variables (269 from MOE
plus the experimental log Po/w and redox peak potential). This resulted in a two-variable model
(R2 ≅ 0.8) both for log(1/IC50) and log(1/IC90).
One selected descriptor (vsurf_HB6) belongs to the “Surface Area, Volume and Shape Descriptors”
family and is related to the H-bond donor capacity. The other descriptor (SlogP_VSA4) belongs to the
“Subdivided Surface Areas” group and is related to an approximate accessible van der Waals surface
area calculation for each atom, along with the contribution to log Po/w (as calculated in MOE) for each
atom (see Supporting Information).
The addition of both experimental log Po/w and Epc,1 to the previously selected two descriptors
allowed us to build a four-variable model with R2 = 0.85 for log(1/IC50) and R2 = 0.84 for log(1/IC90).

Molecules 2011, 16
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In conclusion, the reported statistical analysis confirms the importance of the reduction peak
potential Epc,1 in the definition of the cytotoxic activity. This reduction process has been demonstrated
to be consistent with reduction of the N-oxide functionality to form a reactive radical anion, which
could lead further to superoxide ion or other toxic oxy radical species responsible for the biological
activity [45]. However, in order to obtain a more general QSAR relationship, three other descriptor
should be considered. Although the relatively small number of compounds considered, with respect to
the large set of descriptors, limited the fitting ability of the model (R2 ≥ 0.84), the lipophilicity, the
H-bond donor capacity and a descriptor related to the molecular dimensions were found to be involved
in the modulation of the final biological activity. In particular, on the basis of the regression
coefficient, the redox properties (Epc,1) correlate positively with both log(1/IC50) and log(1/IC90); this
means that an easy reduction increases the activity. On the contrary, the lipophilicity and shape
descriptors affect the activity negatively.
3. Experimental Section
3.1. Chemical Synthesis
The synthesis of the quinoxaline 1,4-di-N-oxide derivatives was carried out by a variation of the
Beirut reaction [36,47-51], where the appropriate benzofuroxan (BFX) reacts with the corresponding
β-ketoamide in the presence of calcium chloride and ethanolamine as catalysts (Scheme 1). The
methods for the synthesis of quinoxaline-2-carboxamide 1,4-di-N-oxide derivatives and the structure
characterization were reported elsewhere [40,41].
Scheme 1. General synthetic scheme.
Reagents and conditions: (I) N,N-DMF, NaClO, rt.; (II) methanol, 0 °C, N2 atm.;
(III) methanol, CaCl2, ethanolamine.

Molecules 2011, 16
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3.2. RP-HPLC Method
The RP-HPLC methods of Minick [52] and Lombardo [53] were considered for estimating the
n-octanol/water partition coefficients (log Po/w) of QdO. The inorganic salts and the reference
compounds were, at least, of analytical grade (Sigma Aldrich and Fluka) and used without further
purification. HPLC-grade methanol, n-octanol (Sigma-Aldrich) and bi-distilled water were used to
prepare the mobile phase. The retention times (tR) were measured using a Waters 2695 Separation
Module system and a Waters 2487 Dual λ Absorbance Detector with Empower Pro Software.
The Supelcosil LC-ABZ column (5 μm, 15 cm × 4.6 mm) [18,52-54] was selected to substitute the
organic phase of the shake-flask method because it has been reported that this column affords a
reasonable correlation model for a great variety of compounds [18,22,49,55]. The mobile phase
consisted of 20 mM 3-morpholinopropanesulfonic acid (MOPS) buffer (pH 7.4) and methanol in
varying proportions, from 70 to 40%. n-Octanol (0.25%) was added to methanol, and n-octanol-
saturated water was used to prepare the buffer [41]. The other chromatographic conditions were: flow
1.0 mL/min−1; isocratic elution, UV-visible detector set at the wavelength with maximum absorbance
(260 and 210 nm). The test solutions were 0.3 mM in the desired compound. All the experiments were
performed at 25 ± 2 °C at least twice.
The tR of each QdO derivative 10–29 was measured at different proportions of methanol (from 70 to
40%) and injections of pure methanol were used to determine the column dead-time (t0). The capacity
factors were calculated according to Equation (2):
log k’ = log[(tR − t0) / t0]
(2)
Starting from these results, the extrapolation to 0% methanol for each compound was calculated and
the capacity factors were used to predict the corresponding log Po/w.
The capacity factors of compounds 1–9, with known log Po/w [16,20,39] and accepted as reference
compounds by the OECD [39], were used to create a calibration curve [Equation (3)]:
log Po/w = a log k’0 + b
(3)
The common coefficient of determination R2 was used to evaluate the fitting ability of the model.
Another measurement for defining the accuracy of the proposed model is the RMSE (Root Mean
Squared Error), which summarizes the overall error of the model [Equation (4)]:
n
2
ˆ
(
yi − yi
)
∑
i=1
(4)
RMSE =
n
where ŷi is the log Po/w value calculated by Equation (2), yi is the reference value and n is the number
of reference compounds used to create the curve.
3.3. Cross-Validation of the RP-HPLC Method
In order to judge if the experimentally measured log k’0 can be used to predict the log Po/w value, a
calibration curve was created with the capacity factors of the reference compounds and a linear
regression equation between the log Po/w and log k’0 was determined.

Molecules 2011, 16
7903
The robustness of the model and its predictivity were evaluated by the leave-one-out (LOO)
cross-validation procedure [28,56]. According to this procedure, the log Po/w value of each compound
in the reference data set is predicted by the equations derived from all the other compounds except the
predicted one. At the end of this procedure two values are available for each reference compound, the
reference shake-flask log Po/w value (yi) and the predicted one (ŷi). With these data, two statistical
parameters (R2LOO, RMSELOO) were calculated to indicate the predictivity of the model. The regression
coefficient (R2LOO) is defined by Equation (5):
n
2
ˆ
(
(
yi − yi
)
∑
∑
RL2OO =1−
i=1
2
(5)
n
yi − yi
)
i=1
where yi is the mean of the reference shake-flask log Po/w value and n is the number of reference
compounds. A high value of R2
indicates a good predictive ability of the model. The root mean
LOO
squared error in prediction (RMSELOO) is calculated with Equation (6):
n
2
ˆ
(
yi − yi
)
∑
=
i=1
(6)
RMSELOO
n
3.4. log Po/w Predictive Approaches
All of the synthesized QdO were subjected to the ALOGPS module with the aim of comparing
experimental log Po/w values and predicted data. The ALOGPS method is part of the ALOGPS 2.1
program and provides interactive on-line predictions of log Po/w and aqueous solubility. log Po/w values
can be obtained from different computation methods: ALOGPS 2.1 includes, among other calculation
programs, ALOGPs, miLogP, ALOGP, MLOGP, KOWWIN, XLOGP2 and XLOGP3 [42].
The lipophilicity calculations within ALOGPS 2.1 are based on the associative neural network
approach and an efficient partition algorithm. ALOGPs was developed with 12,908 molecules from the
PHYSPROP database using 75 E-state indices. 64 neural networks were trained using 50% of
molecules selected by chance from the whole set. The log Po/w prediction accuracy is RMSE = 0.35
and standard mean error s = 0.26 [33].
This program also provides a possibility to include new data into the memory of neural nets without
retraining the neural networks themselves in the so-called LIBRARY mode. The LIBRARY
dramatically improves prediction of the ALOGPS program for the log Po/w prediction using in-house
data sets [21,33,35]. The LogKow (Kow-WIN) program estimates the log Po/w of organic compounds
and drugs using an atom/fragment contribution method developed at Syracuse Research Corporation [57].
The miLogP is calculated by the methodology developed by Molinspiration as a sum of fragment-
based contributions and correction factors. This method for log Po/w prediction is based on group
contributions which have been obtained by fitting calculated log Po/w with experimental log Po/w for a
training set of more than twelve thousand, mostly drug-like molecules. Molinspiration methodology [58]
for log Po/w calculation is very robust and capable of processing practically all organic and most
organometallic molecules XLOGP2 gives log Po/w values by summing the contributions of component
atoms and correction factors. Altogether 90 atom types are used to classify carbon, nitrogen, oxygen,
sulfur, phosphorus and halogen atoms, and 10 correction factors are used for some special

Molecules 2011, 16
7904
substructures. The contributions of each atom type and correction factor are derived by multivariate
regression analysis of 1853 organic compounds with known experimental log Po/w
values [34]. The additive model implemented in XLOGP3 uses a total of 87 atom/group types and two
correction factors as descriptors. It is calibrated on a training set of 8,199 organic compounds with
reliable log Po/w data through a multivariate linear regression analysis [26]. ALOGP, also known as
“Ghose-Crippen octanol-water partition coefficient”, is a log Po/w calculated with the Ghose-Crippen
contribution method based on hydrophobic atomic constants measuring the lipophilic contributions of
atoms in the molecule, each described by its neighbouring atoms [59]. MLOGP, also known
as “Moriguchi octanol-water partition coefficient”, expresses log Po/w in terms of 13 structural
parameters.
4. Conclusions
In this study the RP-HPLC retention times of 20 QdO derivatives were measured and it was found
that highly accurate log Po/w values can be predicted from the experimental log k’0 by using the linear
regression equation relating log Po/w and log k’0 (Equation 1). Consequently, the results suggest that the
determination of log Po/w for QdO can be successfully carried out by measuring the capacity factors
based on the simple RP-HPLC method. This method allows us to avoid the experimental problems
presented by the classical shake-flask method when trying to measure the partition coefficients of QdO
derivatives that present low stability in aqueous solution and create emulsions during partitioning.
After a comparison among different methods for the calculation of log Po/w, in cases where no
experimental data is available, XLOGP3 is proposed as the best program to calculate the log Po/w
values for the QdO presented in this work (RMSE = 0.36). On the other hand, the ALOGPS
LIBRARY method, implemented with the experimental data, predicts log Po/w values that match the
experimental ones with the lowest RMSE (0.19).
Finally, a preliminary statistical analysis confirms the importance of the reduction peak potential
Epc,1 in the definition of the cytotoxic activity of QdO. Moreover, the lipophilicity, the H-bond donor
capacity and a descriptor related to the molecular dimension were found to also be involved in the
modulation of the final biological activity.
Acknowledgments
Giuseppe Ermondi (CASSMedChem, University of Torino, Italy) is gratefully acknowledged for
the use of MOE software. This work has been carried out with the financial support of the PIUNA
project from University of Navarra and Fondo de Investigaciones Sanitarias (PI080817). E. M. is
indebted to the La Rioja Government for a grant.
Conflict of Interest
The authors declare no conflict of interest.

Molecules 2011, 16
7905
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© 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/3.0/).