CC  Vol.8 No.2 , April 2020
Activity Trends in Desoxy Anthrapyrazoles: The Influence of Molar Volume, Polarizability and Lipophilicity of N2 C5 Side Chains on Their Anticancer Response
Abstract
QSAR methodology was used to assess the effects of lipophilicity (logP), molar volume (MV) and polarizability (pl) of the side chains at N2 and C5 of 20 known desoxy anthrapyrazoles on their in vitro anticancer activity expressed as the negative logarithm of the inhibitory concentration of 50% of L1210 murine leukemia cell line (1/logIC50). The main data set shows poor correlations between biological response and the descriptors with exception of MV of the C5 side chain, where a moderate correlation was discerned ( =0.60, n = 18, two outliers). To extract more information regarding mechanism, the main data set was visually classified to three clusters depending on N2 side chain. Cluster 1 containing six 5-substituted 2-[(2-hydroxyethyl) amino] ethyl anthrapyrazoles; cluster 2 contains ten 5-subsitutes 2-(diethyl amino) ethyl anthrapyrazoles and cluster 3 contains four anthrapyrazoles with miscellaneous substituents at both N2 and C5. For cluster 1, MV and pl of C5 show high correlation with biological response (R2s = 0.75 and 0.72 respectively) while logP gives a weak correlation (R2 = 0.44). For cluster 2, the correlations of logP and pl of C2side chain are higher (=0.66 and 0.62 respectively) compared with MV (=0.16). Cluster 3 shows very poor correlation with all descriptors (~0.3). This indicates mechanistic distinction between the three clusters. Derived descriptors which represent the difference between the descriptors of N2 and C5 side chains where used to explore the presence of interplay between these descriptors in affecting variability of the biological response.

1. Introduction

Anthrapyrazoles (Figure 1) are totally synthetic anti cancer agents that exhibit a good efficacy in the treatment of breast cancer [1] [2].

They relate to the anthracene-9, 10-dione based family of anticancer agents which include anthracyclines, e.g., Daunorubicin and doxorubicin [3]. Duanorubicin and doxorubicin, in addition to alkylaminoalkyl anthracene-9, 10-diones such as ametantrne and mitoxantrone [4].

Different mechanisms had been suggested to account for anticancer activity of anthracenediones-based anticancer chemotherapeutic agent like DNA intercalation [5], Topoisomerase II inhibition [6], generation of reactive oxygen species (ROS) among others. ROS generation is associated with all quinone containing anticancer agent and is an outcome of flavoenzyme-assisted redox cycling inside biological systems [7]. This redox cycling plays an important role in cytotoxicity of these compounds [8]. Regardless of the mechanism by which a given class of quinonoid drugs exerts its activity, substituents do indeed modify this activity either by enhancing, retarding or even banning it altogether. This is evident from the fact that from the multitude known anthrapyrazoles, only piroxantrone and losoxantrone has surfaced as potent clinical agents [9].

Similar argument could be assumed for anthracyclines and indeed for all other drugs. We reason that some kind of interplay may exist between substituents restricted in N2 and C5 positions of the basic nucleus which lead eventually to the observed alteration of activity profile of individual compound relative the parent anthrapyrazole. Shwalter et al. [1] found that basic side chains with two to three carbon spacers between the nitrogens, at positions N2 and C5 of the anthrapyrazole ring structure, enhanced in vivo antitumor activity against P388 murine leukemia. DNA binding and intercalation were also influenced by the side chains at N2 and C5.

Quantitative structure activity relationships is a field of science inaugurated in 1964 by seminal two papers by Hansch and Fujita [10], on one hand, and Free and Wilson [11] in the other. Since then tremendous strides were made in

Figure 1. General structure of desoxy anthrapyrazoles.

Figure 2. Plotting of 1/logIC50 against MVR2 of 5-substituted 2-{2-[(2-hydroxyethyl) amino]ethyl}anthra [1,9-cd]pyrazol-6(2H)-ones.

this field and indeed, in all in silico methods. Now QSAR methodology is a fully mature area of science which endeavor to correlate molecular descriptor or physicochemical parameters with biological response. The correlation is formulated in the form of a mathematical equation with statistical validation metrics. The formulated equation could be linear or non linear. Various algorithms had been devised to follow up relations between molecular and biological parameters. These include linear regression, partial least squire regression, neural networks among others [12]. The algorithm used in present study is non linear regression. The physicochemical descriptors used in the present study are two geometrical parameters polarizability (pol) and molar volume (MV), in addition to lipophilicity parameter (logP).

Polarizabilty is a measure of the ease with which the electrons of a molecule are distorted. It is the basis for evaluating the nonspecific attraction forces (London dispersion forces) that arise when two molecules approach each other. Each molecule distorts the electron cloud of the other and thereby induces an instantaneous dipole. The induced dipoles then attract each other [13]. Polarizability has been shown to play an important role in chemical-biological interactions. The first attempt to apply molecular refractivity in terms of the Polarizability was made by Pauling and Pressman [14]. Many empirical quantum mechanical methods of differing accuracy have been proposed for calculating molecular polarizabilities [15] - [20] and [21]. Molecular polarizability influences several other physical properties, including electronegativity [22] [23] [24] and [25], dipole moment [26] and ionization potential [27].

Molar volume (MV) is the geometrical-polarizability descriptor obtained from chemical structure according to the following formula:

MV = Mw / ρ

where Mw is the molecular weight and ρ is density. This parameter is closely related to the other two polarizability descriptors: molar refractivity and parachor but while the latters are additive, molar volume is strictly not. It is typically the volume enclosed within molecular surface area which is the area of outer surface of the volume from which water molecules are excluded [28].

logP is the calculated logarithm of octanol/water partition coefficient. It is the mostly used physicochemical parameters in QSAR studies [29]. It mimics the partitioning happening for xenobiotic between aqueous and lipid environments inside the body. The pharmokinetic stage in drug journey through various barriers inside the organism is monitored by this descriptor.

This paper is a continuation of our customary interest in mechanistic aspect of quionoid anticancer drugs [30] [31].

2. Material and Methods

The biological data were taken from literature [1]. Molar volumes (MV), polarizabilities (pl) and lipophilicities (logP) were calculated using ACD lab chemsketch 15 freeware, Advanced Chemistry Development Toronto Canada (http://www.acdlabs.com/). ΔMVN2C5, ΔplN2C5, and ΔlogPN2C5 parameters were obtained by subtracting the value of molar volume of substituent at C5 from that of N2 on the anthrapyrazole ring system. Parent compound from which the side chain at N2 and C5 were derived, were used for calculating the molar volume. General chemical structure of anthrapyrazoles used in this analysis is illustrated in Figure 1 and their individual chemical structures are illustrated in Table 1. The calculated parameters (MV, pl and logP) and the derived parameters (ΔMVN2C5, Δpl N2C5, and ΔlogPN2C5) are reported in Table 2.

Initially the R2 statistic were calculated for all the sets obtained by pairing each of the calculated and the derived parameters with anticancer activity (1/logIC50) to specify if any correlation exists between them. Then regression analysis was carried out.

3. Results and Discussion

The dependence of biological activity of the 6 desoxy anthrapyrazoles in which R2 = −CH2CH2NHCH2CH2OH on molar volume (MVR2) of the C2 side chain was found to be parabolic as shown by the Equation (1) below

1 / log I C 50 = 0.0689 M V R 2 0.0003 ( M V R 2 ) 2 + 3.4201 (1)

n = 6, R2 = 0.7535, s (1/logIC50) = 0.595, s (residual) = 0.295; F = 4.585.

The data set used to derive the above equation comprize compounds 4 - 9 (Table 1). Equation (2) correlates polarizability of C5 side (plR2) chain to biological activity for the same compounds

1 / log I C 50 = 0.0177 ( p l R 2 ) 2 + 0.448 p l R 2 + 4.483 (2)

n = 5, R2 = 0.7229, s (logIC50) = 0.595, s (residual) = 0.313068; F = 3.913.

Equation (3) correlates the logarithm of octanol/water partition coefficient (logPR2) of C5 side chain to biological activity for same series

1 / log I C 50 = 0.8945 ( log P R 2 ) 2 + 1.5659 log P R 2 + 6.825 (3)

n = 5, R2 = 0.823, s (logIC50) = 0.572, s (residual) = 0.240768, F = 4.65.

Compound 8 is considered to be an outlier.

All the above 3 equations show reasonable statistics. For instant in Equation (1), F-test indicate that the probability that there is no relationship between

Table 1. Individual structure of used Anthrapyrazole compounds.

Table 2. Parameters and biological activity for compounds 1 - 20.

biological activity and MVR2 is less than 5%. The standard deviation of the residuals calculated from the model (0.295) is smaller than the standard deviation of the original data (0.595). The correlation is depicted graphically in Figure 2.

It is apparent from Equation (3) that anticancer activity of this particular series of anthrapyrazoles show excellent dependence on logPR2. This is to be expected since logP is the parameter that encodes partitioning behaviors of xenobiotics via cell membrane.

MVR2 gives with 1/logIC50 a good parabolic correlation (R2 = 0.76) while plR2 gives a weaker correlation (R2 = 0.72). This suggests slightly higher contribution MVR2 to the observed activity compared to plR2. It well known that biological activity of anthrapyrazole is due to their capability to bind and to intercalate to DNA. The former is due largely to the effect of substituents at N2 and C5 and the latter is enhanced by certain features of the rigid chromophore, e.g., presence of hydroxyl group at Ring A. it may be suggested that MVR2 contributes to the capability of anthrapyrazoles to intercalate into DNA possibly by adding to the overall molar volume and modifying the orientation of the intercalator in-betweens DNA double helical structure. On the other hand, plR2 contributes to DNA binding ability of anthrapyrazole since it is the basis for evaluating the nonspecific attraction forces (London dispersion forces) that may arise between the molecule and DNA.

The second subset where side chain at N2 is fixed as 2-(diethylamino) ethyl (R1 = −H2CH2NEt2) contain compounds 11 - 20. Upon similar treatment as above, the following correlations were found:

1 / log I C 50 = 0.0001 ( M V R 2 ) 2 0.0377 M V R 2 + 9.8842 (4)

n = 10, R2 = 0.7982, s (logIC50) = 0.568, s (residual) = 0.266, F = 13.827

1 / log I C 50 = 0.0066 ( p l R 2 ) 2 0.302 p l R 2 + 9.5374 (5)

n = 10, R2 = 0.7973, s (logIC50) = 0.568, s (residual) = 0.256, F = 13.767

1 / log I C 50 = 0.12 ( log P R 2 ) 2 0.302 log P R 2 + 6.383 (6)

n = 10, R2 = 0.646, s (logIC50) = 0.568, s (residual) = 0.337, F = 14.64.

For this subgroup, MVR2 and plR2 give a better parabolic correlation (R2’s ~ 0.80) compared with those of the first subgroup (R2’s ~ 0.75 and 0.73 for MVR2 and plR2 respectively), in contrast to logPR2 which gives a poorer correlation (R2 = 0.65) compared to that of the first subgroup(R2 = 0.82). This indicates a modified mechanistic profile in which steric and polarizability effects have a greater influence on the activity while lipophilicity has a lesser influence as compared to first subgroup. The correlation between MVR2 and 1/logIC50 for compounds 11 - 20 is shown graphically in Figure 3.

Third group of compounds contains compounds 1, 2 and 3 in addition to compounds 8 and 10 which were removed as outliers from the first and the second subgroups. The following equations were obtained for the substituents at N2

1 / log I C 50 = 0.001 ( M V R 1 ) 2 + 0.238 M V R 1 3.597 (7)

n = 5, R2 = 0.855, s (1/logIC50) = 0.824, s (residuals) = 1.68

1 / log I C 50 = 0.116 ( p l R 1 ) 2 + 2.087 p l R 1 1.560 (8)

Figure 3. Plotting of 1/logIC50 against MVR2 of 5-substituted 2-{2-[(2-(diethylamino)ethyl}anthra [1,9-cd]pyrazol-6(2H)-ones.

n = 5, R2 = 0.895, s (1/logIC50) = 0.824, s (residuals) = 0.265.

1 / log I C 50 = 1.527 ( log P R 1 ) 2 2.632 log P R 1 + 5.863 (9)

n = 5, R2 = 0.5, s (1/logIC50) = 0.824, s (residuals) = 0.584.

As it is apparent from Equations (7)-(9), the third subgroup shows good correlations between MVR1 and plR1 with activity while logP gives a moderate correlation.

The side chain at C2 gives the following equations and metrics:

1 / log I C 50 = 0.001 ( M V R 2 ) 2 0.444 M V R 2 + 34.3 (10)

n = 5, R2 = 0.334, s (1/logIC50) = 0.824, s (residuals) = 3.00.

1 / log I C 50 = 0.323 ( p l R 2 ) 2 8.643 p l R 2 + 63.33 (11)

n = 5, R2 = 0.626, s (1/logIC50) = 0.824, s (residuals) = 0.503.

1 / log I C 50 = 0.323 ( p l R 2 ) 2 8.643 p l R 2 + 63.33 (12)

n = 5, R2 = 0.316, s (1/logIC50) = 0.824, s (residuals) = 0.68.

Equations (10)-(12), shows poor correlation between MVR2 and logPR2 with activity while plR2 gives a mild correlation. This indicates that N2 substituent influence the activity more than C2 substituents for this subgroup.

The present analysis shows that when N2 side chains are held constant, the activity depends on C2 side chains but when the N2 substituents are varied, the activity depends on them rather C2 side chains.

To explore the combined effect of both N2 and C5 substituents on biological activity, new parameters ΔMVN2C5, ΔplN2C5, and ΔlogPN2C5, which represent the difference between MV, pl and log P of N2 and C5 side chains respectively, were introduced. Visual clustering yields poor results with these derived descriptors, in contrast to regression clustering which separates the original data set into 2 clusters for each descriptor, with expelling of a few data points as outliers. This indicates a kind of interplay between the two side chains in affecting the variability of the biological response.

For ΔMVN2C5, Significant parabolic correlation were found to 1/logIC50 for 13 out of the 20 anthrapyrazoles (R2 = 0.816). Six of the remaining seven compounds which do not fit into above mentioned correlation give a parabolic correlation (R2 = 0.88) while one compound was considered to be as an outlier. For ΔplN2C5 a parabolic correlation were discerned for 12 of them (R2 = 0.778). Six of the remaining compound shows a different parabolic correlation (R2 = 0.84) and two were considered as outliers. ΔlogPN2C5 show linear correlation for 15 compounds (R2 = 0.717). The remaining 5 compounds correlate parabolically to 1/logIC50 (R2 = 0.846). This advocates the use of derived parameters such as ΔMVN2C5, ΔplN2C5 and ΔlogPN2C5 to explore the interplay of local molecular descriptors on the global activity of different molecular entity.

4. Conclusion

For the desoxy anthrapyrazoles studied in the present paper, the side chain at N2 determines the segregation of the compounds into three subgroups. One group contains six compounds with 2-hydroxyethylaminoethyl side chain at N2. The second group contains 2-(diethylamino)ethyl side chain at N2. The third group contains miscellaneous side chains at N2. The biological response of the first and the second subgroups depends parabolically on the molar volume, polarizability and logP of C5 side chain while the third group shows poor dependence. There is an interplay between the two side chain at N2 and C5 through derived descriptor obtained by subtracting the MV’s, pl’s and logP’s of the two side chains. The third subgroup shows strong dependence of descriptor/response correlation on the miscellaneous side chain at N2 while the C2 side chain has poor dependence. Such findings indicate mechanistic intricacies between the members of this group of desoxy anthrapyrazoles.

Cite this paper
Hashim, H. , El-Fakii, M. and Saeed, A. (2020) Activity Trends in Desoxy Anthrapyrazoles: The Influence of Molar Volume, Polarizability and Lipophilicity of N2 C5 Side Chains on Their Anticancer Response. Computational Chemistry, 8, 17-26. doi: 10.4236/cc.2020.82003.
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https://doi.org/10.1124/pr.56.2.6

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[37]   Gutierrez, P.L. (2000) The Metabolism of Quinone-Containing Alkylating Agents: Free Radical Production. Frontiers in Bioscience, 5, d629-d638.
https://doi.org/10.2741/A538

[38]   Deavall, D.G., Martin, E.A., Horner, J.M. and Roberts, R. (2012) Drug-Induced Oxidative Stress and Toxicity. Journal of Toxicology, 2012, Artical ID: 645460.
https://doi.org/10.1155/2012/645460

[39]   Beylin, V.G., Colbry, N.L., Goel, L.P., Haky, J.E., Johnson, J.E., Johnson, D.R., Kanter, G.D., Leeds, R.L., Leja, B., Lewis, E.P., Ritner, C.D., People, W.T., Showalter, H.D.H., Serces, A.O., Turner, W.P. and Uhlendorf, S.E. (1989) Anticancer Anthrapyrazoles. Improved Syntheses of Clinical Agents CI-937, CI-941, and Piroxantrone Hydro-chloride. Journal of Heterocyclic Chemistry, 26, 85-96.
https://doi.org/10.1002/jhet.5570260117

[40]   Hansch, C. and Fujita, T. (1964) σ-ρ-π Analysis. A Method for the Correlation of Biological Activity and Chemical Structure. Journal of the American Chemical Society, 86, 1616-1626.
https://doi.org/10.1021/ja01062a035

[41]   Free Jr., S.M. and Wilson, J.W. (1964) A Mathematical Contribution to Structure Activity Studies. Journal of the American Chemical Society, 7, 395-399.
https://doi.org/10.1021/jm00334a001

[42]   Roy, K., Kar, S. and Das, R.N. (2015) Understanding the Basics of QSAR for Application in Pharmaceutical Science and Risk Assessment. Volume 6, Academic Press, London, 191-228.

[43]   Lowry, T.H. and Richardson, K.S. (1976) Mechanism and Theory in Organic Chem-istry. Harper & Row Publishers, New York, 87.

[44]   Pauling,W. and Pressman, G. (1973) Strategy of Drugs Design a Molecullar Guide Biological Activity. Wiley, New York.

[45]   Yatsenko, A.A. and Yatsekom, A.V. (2003) Calculation of Quadruple Polarizability of O2-Ions in Ionic Crystals of an LiNbO3 Ferroelectric. Glass Physics and Chemistry, 29, 406-409.
https://doi.org/10.1023/A:1025133212436

[46]   Tretiak, S., Saxena, A., Martin, R.L. and Bishop, A.R. (2001) Collective Electronic Oscillator/Semi-Empirical Calculations of Static Nonlinear Polarizabilities in Con-jugated Molecule. The Journal of Chemical Physics, 115, 699.
https://doi.org/10.1063/1.1377035

[47]   Buldakov, M.A. and Cherepanov, V.N. (2004) Polarizability Functions of Diatomic Homo-Nuclear Molecules: Semi-Empirical Approach. Journal of Computational Methods in Science and Engineering, 14, 237-250.
https://doi.org/10.3233/JCM-2004-4302

[48]   Salih Shihab, M. (2010) Semi-Empirical Calculation to Study the a Minature of Di- and Tri-Molecular Assembly of Atomic Interactions. The Arabian Journal for Science and Engneering, 35, 96.

[49]   Buldakov, M.A., Cherepanov, V.N. and Nagornova, N.S. (2006) Polarizability Fun-ctions of Diatomic Hetero-Nuclear Molecules: Semi-Empirical Approach. Journal of Computational Methods in Science and Engineering, 6, 15-163.
https://doi.org/10.3233/JCM-2006-61-412

[50]   Semwal, R.P. and Balodi, J.P. (2001) Semi-Emprical and Initio Studies on the Structure and Polarizability of C60, C70, and C84. Indian Journal of Chemistry, 40, 687-692.

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