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JAC Advance Access published online on June 5, 2007
Journal of Antimicrobial Chemotherapy, doi:10.1093/jac/dkm172
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© The Author 2007. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Identification of individual structural fragments of N,N'-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives for cytotoxicity and antiherpetic activity allows the prediction of new highly active compounds

A. G. Artemenko1, E. N. Muratov1, V. E. Kuz'min1, N. A. Kovdienko1, A. I. Hromov1, V. A. Makarov2, O. B. Riabova2, P. Wutzler3 and M. Schmidtke3,*

1 A.V. Bogatsky Physical-Chemical Institute, Lustdorfskaya doroga 86, Odessa, Ukraine 2 Research Center for Antibiotics, Nagatinskaya Str. 3a, Moscow, Russia 3 Institute of Virology and Antiviral Therapy, Friedrich Schiller University, Hans-Knoell-Str. 2, Jena, Germany

* Corresponding author. Tel: +49-3641-657222; Fax: +49-3641-657301; E-mail: michaela.schmidtke{at}med.uni-jena.de

Received 30 January 2007; returned 6 April 2007; revised 20 April 2007; accepted 23 April 2007


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Objectives: The objectives of this study were (i) to apply computer-based technologies to evaluate the structure of 48 N,N'-(bis-5-nitropyrimidyl)dispirotripiperazines which belong to a new class of highly active antiviral compounds binding to cell surface heparan sulphates, (ii) to understand the chemical–biological interactions governing their activities, and (iii) to design new compounds with strong antiviral activity.

Methods: The logarithm of 50% cytotoxic concentration (CC50) in GMK cells, of 50% inhibitory concentration (IC50) against herpes simplex virus type 1, and of selectivity index (SI = CC50/IC50) was used to develop quantitative structure–activity relationships (QSARs) based on simplex representation of molecular structure. The QSAR model was applied to design new compounds. Two of these compounds were synthesized, physico-chemically characterized and tested for cytotoxicity and antiviral activity.

Results: Statistic characteristics for partial least squares models allow the prediction of CC50, IC50 and SI values. The QSAR results demonstrate a high impact of individual structural fragments for antiviral activity. Molecular fragments that promote and interfere with antiviral activity were defined on the basis of the obtained models. Electrostatic factors (38%) and hydrophobicity (34%) were the most important determinants of antiherpetic activity. Using the established method, new potential dispirotripiperazine derivatives were computationally designed. Two of these computationally designed compounds were synthesized. The biological test results confirm the computationally predicted values of these compounds.

Conclusions: The established QSAR model is suitable for the design of new antiherpetic compounds and prediction of their activity.

Key Words: QSAR , SiRMS , herpes virus , heparan sulfate , antiviral , drug design


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Herpes simplex virus types 1 and 2 (HSV-1 and HSV-2) belong to the family Herpesviridae which includes more than 100 human and animal viruses. Both virus types infect and replicate in the mucocutaneous surface. HSV-1 and HSV-2 establish lifelong latent infections in ganglions which can be reactivated spontaneously or due to a variety of stimuli. Recurrent viruses replicate at the primary site of infection and induce painful lesions there. Whereas recurrent HSV-1 infections occur mostly at the lip mucosa, recurrent HSV-2 produces genital infection. However, HSV-1 can also induce genital infection and HSV-2 has been detected in labial lesions. HSV-2 has been shown to be associated with a 2–4-fold increased risk of HIV-1 acquisition.1,2 Because of their high medical impact, prophylaxis and treatment of herpes simplex virus infections are important healthcare tasks. During the past three decades, great successes have been achieved in the therapy of herpes virus infections.3,4 However, new antiviral compounds are needed to overcome drug resistance in immuno-compromised patients5 and toxic side effects of existing drugs.6 Moreover, compounds preventing virus transmission are not available so far.2,7

Recently, we discovered a new class of antiherpetic compounds, N,N'-bis-5-pyrimidyl derivatives of 3,12-diaza-6,9-diazonia(5,2,5,2)dispirohexadecane dichloride (dispirotripiperazine; DSTP).8 Using DSTP 27 as an example, it was shown that dispirotripiperazines specifically block heparan sulphate (HS)-containing receptors on the cell membrane and prevent in this manner virus adsorption to host cells.9,10 DSTP derivatives also inhibit replication of HSV-2, cytomegalovirus, respiratory syncytial virus and human immunodeficiency viruses but not of varicella zoster virus and Epstein–Barr virus. All susceptible viruses are known to use N- and O-sulphated proteoglycans (HSPG) as receptor or co-receptor. Interactions between viruses and cell surface HS can be also competitively inhibited by polyanions like HS or the soluble HS analogue heparin. However, these polyanions carry inherent disadvantages like high and variable molecular weight, high structural variability and biological origin that can be overcome by DSTP derivatives. An advantage of DSTP derivatives over polyanions is also their long-lasting protective effect following a single treatment of host cells before virus addition.9 Because of their good compatibility, broad spectrum of antiviral activity, their new mode of antiviral activity and their long-lasting protective effect following a single treatment, DSTP derivatives seem to be appropriate candidate compounds to prevent virus transmission. In particular, DSTP derivatives could contribute to the development of new microbicides. The development of topical microbicides for prevention of sexually transmitted viruses is an important area of antiviral research.2,7

In the present study, a computational approach that can distinguish highly active inhibitors from less useful compounds and predict new potent compounds was established and applied. For many years, quantitative structure–activity relationships (QSARs) have been used for the analysis of toxicity and antiviral activity.11–16 This technique quantitatively relates variations in biological activity to changes in molecular properties. Electronic, hydrophobic, and steric indices are routinely used as standard molecule descriptors in QSAR analysis. They were also applied in the present study. The established QSAR model was applied (i) to determine structural elements of 48 N,N'-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives having an influence on cytotoxicity and antiherpetic activity by using the QSAR approach on the base of simplex representation of molecular structure (SiRMS), (ii) to predict structural elements enhancing the antiviral activity, and to use this knowledge for (iii) the molecular design of novel highly active compounds.


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Work set compounds

The 48 DSTP derivatives used in the work set of this study (Figure 1) to establish (training set; 38 compounds) and prove (test set; 10 compounds) the QSAR model were synthesized as described previously.17–20 Their chemical structure, cytotoxicity and antiherpetic activity were determined and published by Schmidtke et al.8


Figure 1
Figure 1
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  		Figure 1.. Structures of work set compounds.

 
Quantitative structure–activity relationship

Good tolerability and strong antiviral activity are both important for the development of antiviral drugs. Therefore, thorough investigation of the relationship between structure and (i) cytotoxicity in GMK cells, (ii) antiherpetic activity, as well as (iii) the selectivity index (SI) of 48 N,N'-bis-5-nitropyrimidyl derivatives of dispirotripiperazine has been carried out in the present study. The cytotoxicity is expressed in terms of 50% cytotoxic concentration (CC50, µM) in GMK cells and the antiherpetic activity in terms of 50% inhibitory concentration (IC50, µM) determined against HSV-1 strain Kupka in GMK cells. The SI represents the ratio of CC50 to IC50. All original data have been converted into log10 response variables (log10 CC50, log10 IC50 and log10 SI). The corresponding values (observed) are presented in Table 1.


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  		Table 1.. Observed and predicted values of biological parameters of N,N'-bis-5-nitropyrimidyl derivatives of dispirotripiperazine

 
The SiRMS method has been used as the main tool for QSAR investigations. This method showed good results in previous studies for solving different ‘structure–activity’ problems.21–24 Simplex descriptors (number of four-atom fixed structural fragments with fixed constitution, topology, chirality and symmetry) were used to describe the molecular structure. This approach considers not only the atom type, but also other atom characteristics important for possessing biological activity of compounds e.g. charge, lipophilicity, refraction and atom ability for being a donor/acceptor in hydrogen-bond formation (H-bond). For atom characteristics that have real values (charge, lipophilicity and refraction) division of value ranges into definite discrete groups was carried out. The number of groups (G) is a variable tuning parameter (as a rule G = 3–7). For atom H-bond characteristic the atoms were subdivided into three groups: A (acceptor of hydrogen in H-bond), D (donor of hydrogen in H-bond) and I (indifferent atom). The use of diverse variants of differentiation of simplex vertexes (atoms) represents the principal feature of the offered approach. The main advantages of SiRMS are the opportunity of analysis of molecules with noticeable structural differences within a training set of compounds as well as the possibility to reveal individual molecular fragments (simplex combinations) promoting or interfering with the strength of biological activities. A hierarchic methodology23 was used for QSAR task solution (2D -> 4D -> 3D). Because the 2D modelling shows good results, 3D and 4D QSAR models have not been generated although SiRMS allows also generation of 3D and 4D ones.23 2D models consider constitution and topology of molecules and are based on structural formulae. The number of simplex descriptors generated on the base of SiRMS method for this task was ~8000. The partial least squares method (PLS) has been shown to be efficient for working with a large number of variables.25 The genetic algorithm,26 trend-vector method27 and automatic variables selection strategy based on interactive28 and evolutionary29 variables selection have been used for selection of descriptors in PLS.

Structure analysis

The chemical structures of compounds 51 and 52 were determined by Mass-FAB, NMR and IR spectra, element analysis and by UV-spectra if necessary. NMR spectra were recorded on an Oxford Unity spectrometer at 400 MHz (Varian) with tetramethylsilane as the reference. Mass spectra were obtained on a Finnigan SSQ-700 spectrometer. All IR spectra were recorded on a Perkin-Elmer 2000 FT-IR unit. Elemental analyses were performed on a Carlo-Erba model 5500 elemental analyser. Melting points were obtained on an electro thermal 9100 (UK) melting point apparatus and are uncorrected.

Cytotoxicity and antiviral assay

Two-day-old confluent GMK cell monolayers grown in 96-well plates were incubated with serial 2-fold compound dilutions for 72 h (37°C; 5% CO2).30 Then, the cells were fixed and stained with a crystal violet formalin solution. Cytotoxicity was quantified spectrophotometrically with a plate reader.

The cytopathic effect (CPE) inhibitory assay was also described previously.30 Briefly, 50 µL of drug solution and 50 µL of a constant amount of HSV-1 (moi 0.1) were added to confluent GMK cell monolayer grown in 96-well plates. The inhibition of virus-induced CPE was scored spectrophotometrically 48 h after infection when untreated infected control cells showed maximum cytopathic effect.

For determination of cytotoxicity as well as antiviral activity, two independent tests were performed. Each compound concentration was tested in triplicate in the tests. The mean dose–response curve of the two tests was used to calculate the 50% cytotoxic and 50% inhibitory activity (CC50 and IC50). The SI was calculated by dividing the CC50 by the IC50.


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QSAR model

The work set (48 compounds, Figure 1) was subdivided into training and test sets. Ten compounds (~20%) differing in activity were selected for the test set. The remaining 38 compounds were assigned to the training set. The experimentally determined (observed) values of activities of investigated structures are presented in Table 1. For the majority of compounds, the observed values are in excellent correlation with predicted values of cytotoxicity, antiviral activity and selectivity (Table 1 and Figure 2). Approximately 8000 simplex descriptors were calculated during the initial stage of work. Differentiation of atoms in simplexes was done on the base of the following characteristics: (i) atom type (used as mark in the simplex vertexes), (ii) partial charge, (iii) lipophilicity, (iv) refraction and (v) a mark, which characterizes atom as possible donor or acceptor of H-bond.


Figure 2
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  		Figure 2.. Plots of observed versus predicted values of cytotoxicity, antiherpetic activity and selectivity index for obtained QSAR models, linear correlation.

 
The atoms have been divided into seven groups corresponding to their (i) partial charge A ≤ –0.1 < B ≤ –0.05 < C≤ –0.01 < D ≤ 0.01 < E ≤ 0.05 < F ≤ 0.1 < G, (ii) lipophilicity A ≤ –1 < B ≤ –0.5 < C ≤ –0.1 < D ≤ 0.1 < E ≤ 0.5 < F ≤ 1 < G and (iii) refraction A ≤ 2 < B ≤ 3 < C ≤ 4 < D ≤ 6 < E ≤ 9 < F ≤ 12 < G.

The R2 values shown in Table 2 (R2 = 0.844 – 0.910) demonstrate a strong correlation between calculated values and those obtained from measurements. The quality of the cross-validation correlation coefficient Q2 = 0.614 – 0.678 is quite satisfactory. Furthermore, obtained models show good prediction results for the test set compounds (R2test = 0.676 – 0.705). This indicates that the variables employed provide a model with good predictive potential for cytotoxic and antiviral activities of the investigated compounds.


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  		Table 2.. Statistical characteristics of the QSAR models

 
It is well known25 that the PLS equation can be represented as


Formula

where Y is appropriate activity, bi is PLS regression coefficients, xi is the ith descriptor value (the number of simplexes of ith type in the SiRMS), and N is the total number of descriptors. Using this equation, it is possible to perform the reverse analysis (interpretation of QSAR models) by using the SiRMS approach. The contribution of each atom in the molecule can be defined as ratio of the sum of PLS regression coefficients (bi) of all simplexes that this atom contains, to the number of atoms in the simplex. Atoms having a positive or negative influence on the studied biological activity of compounds can be coloured. This helps to present the results and to determine visually the groups of atoms responsible for activity. For example, the structure of compound 22 (Table 1) is shown in Figure 3. Atoms and structural fragments necessary for antiviral activity are coloured visually in dark grey. Light grey was used to visualize atoms and structural fragments reducing antiviral activity.


Figure 3
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  		Figure 3.. Example of colour-coded structure of DSTP 22. Atoms and structural fragments enhancing antiviral activity are coloured in dark grey and those reducing antiviral activity are coloured in light grey and white.

 
Influence of individual structural fragments on biological activity and selected physical–chemical properties

Results from previous structure–activity relationship studies demonstrate that dispirotripiperazine fragments A or B are essential for antiviral activity.8 Derivatives either without a dispirotripiperazine moiety or with that moiety disrupted did not inhibit the replication of HSV-1. Moreover, when the cationic fragment A was substituted by a non-cationic linker instead of dispirotripiperazine e.g. N-(2-aminoethyl)ethane-1,2-diamine, ethylenediamine or piperazine, antiviral activity was lost (data not shown). Taken together, these results prove that the cationic character of DSTP is required for antiviral activity. Therefore, DSTP derivatives were used as the basis of the present QSAR studies. They determine the applicability domain of the established model.

The strongest influence on antiviral activity of DSTP derivatives was exhibited by the fragments S5, R9–R14, R19, R25 and R27 (Table 3). All of them increased the antiherpetic activity. Whereas R9 and R27 do not have an influence on the SI of investigated compounds, all other fragments enhance the SI. Moreover, the introduction of R10, R13, R19, R25 and R27 leads to decreased cytotoxicity. Compounds containing these fragments were shown to be the most active compounds under experimental conditions as well as in computational studies.


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  		Table 3.. Examples of molecular fragments and their relative influence on the investigated properties

 
The structural fragments S6, R16, R18 and R28 facilitate antiherpetic activity as well as cytotoxicity of investigated compounds. The consequences are lower selectivity indexes.

The existence of fragments R20–R24, R36, R37 and R48 antagonizes the antiherpetic activity and/or decreases the selectivity of investigated compounds. A markedly distinctive increase of cytotoxicity is found in compounds containing S7, R4 and R35.

Using the established QSAR model, the influence of selected physical–chemical properties of investigated compounds on cytotoxicity, antiherpetic activity and selectivity was studied (Figure 4). Cytotoxicity depends on electrostatic (50%), hydrophobic (34%) and mixed factors determined by atom nature (16%). Electrostatic factors (38%) and hydrophobicity (25%) are also very important for antiherpetic activity. Furthermore, mixed factors (19%), dispersion (10%) and H-bonding (8%) have an influence on the antiviral effect. The selectivity index depends 64% on atom nature and 36% on hydrophobicity.


Figure 4
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  		Figure 4.. Relative influence of some physico-chemical factors on variation of cytotoxicity, anti-HSV-1 activity and selectivity index estimated on the basis of QSAR models.

 
Prediction of new antiherpetic compounds and synthesis, chemical properties and biological activity of two selected compounds

Using the results from the established QSAR on strength and direction of the influence of distinct structural fragments, new compounds were computationally designed. The values of investigated properties for these compounds were predicted by obtained PLS models. For example, compounds 49–53 with the best potential antiherpetic activity are shown in Table 4. The predicted 50% inhibitory concentration of the majority of these compounds is lower than 10 µM.


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  		Table 4.. Molecular design results

 
The two compounds (51 and 52) with the lowest predicted inhibitory concentration were synthesized and tested for cytotoxicity and antiviral activity. The compound 4,6-di([3-oxyran-2-ylmethyl]3,12-diaza-6,9-diazonia(5,2,5,2)dispirohexadecane)-5-nitropyrimidine tetrachloride tetrahydrate (51), C34H59Cl4N11O2 x 4H2O (m.w. 899.8) was synthesized as described as follows. The solution of 0.96 mL (7.0 mmol) of triethylamine and 0.136 mL (3.5 mmol) of (±)-epichlorohydrin in 10 mL of ethanol was added to the solution of 1.5 g (1.74 mmol) of 4,6-di(3,12-diaza-6,9-diazonia(5,2,5,2)dispirohexadecane)-5-nitropyrimidine tetrachloride dihydrochloride tetrahydrate in 10 mL of water.8 Reaction mixture was refluxed for 24 h, cooled and a mixture of 25 mL of acetone and 25 mL of methanol was added. The very light yellow precipitate was filtered and recrystallized (water/methanol). Yield 1.05 g (67%), Mp. 274–278°C with decomposition. MS FAB (3NBA) [M+H]+: m/z = gef. 685.9; IR (oil): 1547, 1236, 996 cm–1; 1H NMR (DMSO-d6): {delta} (ppm): 8.18 (2H, s, 2 CH-pyrimidine), 4.24 (6H, s, 2 CH3), 4.08 (br) and 3.94–4.27 (24H, m, CH2–CH2 piperazine), 2.63–2.77 (6H, m, CH–CH2 oxirane). Anal. Calcd. for C34H67Cl4N11O8 (899.77): C, 45.39; H, 7.51; N, 17.12%. Found: C, 45.32; H, 7.64; N, 16.96.

Compound 2-methyl-4,6-di([3-oxyran-2-ylmethyl]3,12-diaza-6,9-diazonia(5,2,5,2)dispirohexadecane)-5-nitropyrimidine tetrachloride tetrahydrate (52), C35H61Cl4N11O4 x 4H2O (m.w. 913.8) was prepared analogously. Yield 72%, Mp. 268–272°C with decomposition. MS FAB (3NBA) [M+H]+: m/z = gef. 699.9; IR (oil): 1573, 1284, 1012 cm–1; 1H NMR (DMSO-d6): {delta} (ppm): 4.24 (6H, s, 2 CH3), 4.08 (br) and 3.94–4.27 (24H, m, CH2–CH2 piperazine), 2.63–2.77 (6H, m, CH–CH2 oxirane), 1.74 (3H, s, CH3). Anal. Calcd. for C35H69Cl4N11O8 (913.80): C, 46.00; H, 7.61; N, 15.52%. Found: C, 46.11; H, 7.52; N, 15.61.

The 50% cytotoxic concentration of compounds 51 and 52 is 165.7 and 142.7 µM, respectively. The HSV-1-induced cytopathic effect was reduced by 50% by 1.1 µM compound 51 and 1.6 µM compound 52. Based on these data selectivity indices of 151 and 89 were calculated.


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Derivatives of N,N'-bis(1-oxido[1,2,5]oxadiazolo[3,4-d]pyrimidin-7-yl)-3,12-diaza-6,9-diazonia(5,2,5,2)dispirohexadecane dichloride are well tolerated, synthetic low molecular weight compounds that have been shown to bind to specific structural moieties of HS.9,10 Binding of DSTP to HS prevents adsorption and/or entry of viruses from different families that use HS to attach to and/or enter into host cells. In the present study, a 2D model of quantitative structure–activity interactions was established using the SiRMS-based QSAR approach for the description of molecular structures. The correlation coefficients calculated for predicted and observed values of cytotoxicity (0.858), antiherpetic activity (0.844) and SI (0.910) demonstrate that the QSAR model accurately reflects substantial factors concerning cytotoxic and antiherpetic activity of DSTP derivatives.

The QSAR results demonstrate that individual structural fragments and their steric arrangement rather than the steric form of the whole molecule are important for the studied biological activities. The main determinants of cytotoxicity of DSTP derivatives are electrostatic factors (50%) and hydrophobicity (34%). Electrostatic factors (38%) and hydrophobicity (25%) also have a strong influence on antiherpetic activity of DSTP derivatives. An electrostatic binding between negatively charged sulphate as well as carbonyl groups and the positively charged nitrogen atom of DSTP was predicted with the computer-based structure modelling program HyperChem 7.01, recently.10 The results of the present study completely support this prediction and suggest that the electrostatic interaction between HS and DSTP may result in a very strong binding. Possibly, this contributes to the long-lasting protective effect after a single DSTP treatment of host cells before virus addition.9 Enveloped as well as non-enveloped viruses from different families use HSPG to bind to and/or enter into host cells.31 HSPG can mediate binding and concentration of viruses to the target cells and assist their internalization by protein receptors32–35 or facilitate entry of viruses into target cells.36–38 Thereby, specifically sulphated HS interacts with viral proteins.37,39–41 Because DSTP derivatives prevent virus binding and/or entry to cell surface HS, this class of compounds offers the possibility of topical treatment to inhibit sexual transmission of viruses as microbicides. Additionally, DSTP derivatives may serve as an interesting tool for studies on other protein–HS interactions. A computational approach can help to distinguish potential inhibitors from less useful compounds.

The established QSAR model was used to design and estimate the activity of new compounds. Two of these compounds (51 and 52) were synthesized and chemically as well as biologically characterized. The experimental data obtained for compounds 51 and 52 are in good (cytotoxicity) and excellent (antiherpetic activity) accordance with predicted values. These compounds are special in the way that they bear ethylene oxide moieties. Hypothetically, after an initial binding to HS (based on their cationic character) they can finally bind in a covalent manner with their target via the epoxide that is attacked by a nucleophile present in the target. However, according to results of previous studies on properties and stability of prospidine and its ethylene oxide analogue (compound 7), the ethylene oxide moiety is stable under in vitro conditions up to 24 h.42 Moreover, results from NMR studies demonstrate that the ethylene oxide ring opens only at pH > 8.43 But antiviral assays in cell cultures are performed at nearly neutral pH. Therefore, the possibility of nucleophile reactions of epoxide was not taken into consideration in the present study even though it cannot be excluded completely. The results confirm the quality of the established QSAR model and demonstrate that it provides a potential tool for computational design of new highly active compounds.


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None to declare.


   Acknowledgements
 
This work was partially supported by a grant of the Ukraine (President of Ukraine grant for young investigators GP/F11/0115) and the Science and Technology Center in Ukraine (STCU project 3147).


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