DOI:
10.1039/C4RA11856A
(Paper)
RSC Adv., 2015,
5, 6536-6542
An α1-adrenergic receptor ligand repurposed as a potent antiproliferative agent for head and neck squamous cell carcinoma†
Received
6th October 2014
, Accepted 17th December 2014
First published on 17th December 2014
Abstract
In this study we report the anticancer properties of RN5-Me, an α1-adrenergic receptor ligand. Biological screening and circular dichroism data indicate that it acts as a DNA intercalator. Docking studies, confirming this behaviour, suggest that RN5-Me possesses great selectivity for alternating AT nucleobases upon GC ones. In the cytotoxicity assay, it shows IC50 values in the range of 4.2–25.0 nM towards the cancer cell lines HN6, HN13, HeLa, SK-Me1-103, PC3, and MCF7. It is noteworthy that RN5-Me shows a higher selectivity than Cisplatin for HN6 and HN13 over NOK-SI non-cancerous cells.
1. Introduction
Despite the tremendous resources being invested in cancer prevention and treatment, this disease remains one of the leading causes of mortality worldwide.1–3 Unfortunately, biopharmaceutical industry efforts in searching for new anticancer drugs suffer from a productivity problem: output has not kept pace with the enormous increases in pharma R&D spending.4 To overcome this productivity gap, recently, a new research strategy commonly known as drug repositioning, or even drug reprofiling or repurposing, has taken hold.5–8 This strategy has been usefully applied to a variety of diseases9,10 and in particular to cancer.11–19 Nowadays, with approximately 600
000 new cases annually, squamous cell carcinomas of the head and neck (HNSCCs), represent one of the six leading cause of cancer death.20 This disease, which includes malignant lesions arising in the oral cavity, larynx and pharynx, results in nearly 11
000 deaths each year in the United States alone. The limited five-year survival rate after diagnosis for HNSCC (approximately 50%) is likely due to a high proportion of patients presenting with advanced disease stages, lack of suitable markers for early detection, and failure to respond to available chemotherapy.21 Cisplatin and Cetuximab are currently the molecular targeted HNSCC therapy; however, both drugs provide poor 5 year overall survival benefit.20,22,23
In light of that, we have screened the most interesting molecules synthesized by us in the last twenty years trying to reposition some of them. Among these molecules, our attention was caught by a series of compounds possessing the 1H-pyrimido[5,4-b]indole-2,4(3H,5H)-dione skeleton, very similar to those present in alloxazine, pterin and riboflavin, i.e. vitamin B2, (Fig. 1). These molecules have been reported to interact with DNA, upon opportune decorations, by binding to a nucleobase opposite an abasic site in DNA duplexes24 and/or by intercalation.25,26
 |
| Fig. 1 Structures of two α1-AR inhibitors and three molecules with a similar core. | |
The prototype of this series, the 3-(2-(4-(2-methoxyphenyl)piperazin-1-yl)ethyl)-1H-pyrimido[5,4-b]indole-2,4(3H,5H)-dione (RN5) (Fig. 1), was developed as pharmacological tool for the study of α1-Adrenergic Receptors (α1-ARs).27
In the original study, RN5 was reported to show very high affinity (in the subnanomolar range; Ki = 0.21 nM) as well as selectivity for the rat α1-ARs over other aminergic receptors such as α2-and β2-adrenergic and 5-HT1A serotonergic receptors. At the time of its discovery, it was considered one of the most potent α1-AR ligand. Owing to its outstanding binding properties, RN5 became commercially available and it is still sold under the name of 3-MPPI (Tocris Bioscience).
Although RN5 served in a series of successive studies as template molecule for the discovery of novel α1-AR ligands endowed with high affinity and selectivity,28–35 a deeper study of its pharmacological properties in in vivo models did not follow the early papers reporting affinity and activity data from in vitro assays. One of the reasons of this lies in the very low aqueous solubility of RN5. It is practically insoluble in water and the sole solvents able to dissolve it in a reasonable way are DMSO and DMF.
On these premises, considering the renewed interest in the field of DNA intercalators36–39 as promising anticancer agents, and our continuous attention to this thematics,40–44 we have taken into consideration the possibility that a more soluble analogue of RN5, namely RN5-Me (Fig. 1), could recognize a double stranded DNA by intercalation into its base pairs, thus behaving as anticancer agent. RN5-Me is the 1,5-dimethyl analogue of RN5 and, as its parent compound, had been reported as a high-affinity ligand for the α1-ARs.3
In light of this, we have synthesized RN5-Me, as previously described,27 characterized (see ESI†), and evaluated its cytotoxic properties upon six cancerous and one non-cancerous cell lines.
Furthermore, exhaustive docking and circular dichroism (CD) studies have been performed to confirm and highlight the intercalation modalities of RN5-Me.
2. Biological evaluations
2.1. Cytotoxicity assay
The cytotoxicity of RN5-Me was evaluated in vitro against HNSCCs (HN6 and HN13), human cervical carcinoma (HeLa), human melanoma (SK-Me1-103), prostate and breast cancer (PC3 and MCF7), as well as non-cancerous oral keratinocytes (NOK-SI). As a screening assay, the cytotoxicity was assessed using a MTT tetrazolium reduction assay and expressed as IC50 (the concentration of compound where 50% of cells are viable) values. The IC50 values of RN5-Me are listed in Table 1 along with those of Cisplatin, one of the most widely used anticancer drug. RN5-Me shows IC50 values in the nanomolar range in all the cell lines tested. Concentration dependent effect of RN5-Me is showed in Fig. 2 for the most sensitive HN6, HN13 and HeLa cell lines. Comparison of IC50 values shows that RN5-Me is from 700- to 8000-fold more efficient than Cisplatin as cytotoxic agent.
Table 1 In vitro efficacy assay of compound RN5-Me expressed as IC50 at 24 h (nM)a
|
RN5-Me |
Cisplatin |
Mean of three independent triplicate experiments ± standard error. Ref. 46. Ref. 47. Ref. 48. Ref. 49. Ref. 50. |
HN6 |
4.2 ± 0.29 |
16 660 @ 24 hb |
HN13 |
4.8 ± 0.33 |
41 650 @ 24 hb |
Hela |
4.9 ± 0.32 |
9400 @ 24 hc |
SK-Me1-103 |
10.0 ± 0.23 |
7500 @ 48 hd |
PC3 |
11.1 ± 1.34 |
12 000 @ 48 he |
MCF7 |
25.0 ± 0.16 |
18 000 @ 96 hf |
NOK-SI |
24.7 ± 0.18 |
16 660 @ 24 hb |
 |
| Fig. 2 Concentration-dependent effect of RN5-Me in HN13, HN6 and HeLa cells. Cells were incubated with different concentrations (1–25 nM) of RN5-Me for 24 h. Cell viability, determined using a CellTiter-Glo luminescent cell viability assay kit, is shown as a percentage of surviving cells. | |
Interestingly, RN5-Me shows, for HN6, HN13 and HeLa cell lines, a 5- to 6-fold selectivity upon non-cancerous NOK-SI cells, whereas Cisplatin is much less selective (0.4- to 2-fold).
2.2. Topoisomerase I relaxation assay
Topoisomerase I (Topo I) is an essential DNA-targeting enzymes that regulates the topology of DNA.45 Topo I alters the supercoiling of DNA causing initial cleavage of one DNA strand, followed by the reorganization and the reconnection of the damaged DNA strand.
In order to investigate the ability of RN5-Me to inhibit Topo I or effectively intercalate into DNA base pairs, we performed an agarose-gel electrophoresis experiment ad hoc designed, based on the different electrophoretic mobility of supercoiled and relaxed conformations of DNA.
In this experiment, relaxed plasmid DNA is treated with Topo I in the presence of the investigated compound. Topo I inhibitors will prevent the enzyme from changing the state of the relaxed DNA; whereas, in the presence of an intercalator, Topo I will convert the relaxed DNA into a supercoiled state.51
As seen in the right side of Fig. 3, relaxed pGEM-T Easy plasmid substrate was converted to negatively supercoiled molecules by treatment with Topo I in the presence of RN5-Me at concentration of 10 nM, indicating that it acts as DNA intercalator.
 |
| Fig. 3 RN5-Me intercalation into DNA. Intercalation was monitored by conversion of relaxed (R) pGEM-T Easy plasmid to negatively supercoiled molecules (SC). An agarose gel stained with ethidium bromide is shown. Control reactions were carried out in the absence of enzyme [SC (left), R (center), RN5-Me + plasmid + Topo I (right)]. | |
3. Circular dichroism
To gain a deeper insight into the changes of polynucleotide properties induced by RN5-Me binding, with the aim to further prove the DNA intercalation emphasized by Topo I assay, we studied, by circular dichroism technique, the behaviour of this compound on the interaction with calf-tymus DNA (ct-DNA).
The CD spectrum of ct-DNA, in B form, displays two conserved peaks at 246 and 272 nm; the first one, negative, is due to right-handed helicity whereas the second one, positive, is due to base stacking.52
The CD titration spectra of ct-DNA, monitored in the presence of increasing amounts of RN5-Me, are shown in Fig. 4. An increasing concentration of RN5-Me leads to a corresponding intensity gain of both 246 nm and 272 nm signals, without any shift in their positions, and to a concomitant appearance of an increasing, positive, induced CD (ICD) signal at 378 nm. These results are consistent with an intercalative binding of the tricyclic pyrimido[5,4-b]indoledione moiety of RN5-Me. In particular, the changes in the intrinsic CD spectrum of the ct-DNA reflect the diminished helicity (helix unwinding) and the extent of base stacking accompanied by stabilization of the right-handed B conformation of ct-DNA, as frequently observed for intercalators.53–57
 |
| Fig. 4 CD spectra of RN5-Me/ct-DNA system titration at 25 °C (up) and UV-Vis spectrum of RN5-Me (down). [ct-DNA] = 12.6 μM in base pair and [RN5-Me] = 0–35 μM. | |
An isodichroic point at 257 nm, well defined for all the titration course, suggests that in solution there is only one mode of binding, i.e. only two DNA absorbing species are present, the free one and that bound to RN5-Me.58
Moreover, the small positive ICD signal at 378 nm further proves the intercalation phenomenon;59,60 the ICD sign is in agreement with the pyrimido[5,4-b]indoledione moiety perpendicular to the DNA axis with its longer direction of elongation almost parallel to the base-pair long axis.54,55,61
Finally, the bathochromic shift of 27 nm (Fig. 4, up), observed for the signal at 351 nm, inherent to the free RN5-Me (Fig. 4, down), is a further proof of intercalation;62,63 this red shift is in fact associated to the strong π–π stacking interaction between the DNA base pairs and the aromatic part of the compound due to the decrease in the energy gap between the HOMO and LUMO molecular orbitals after binding.64
These CD experimental data are qualitatively well in agreement with the in silico ones.
4. Molecular modeling
In order to confirm and rationalize the observed biological results and gain more insight into the intercalation modality of RN5-Me, the supramolecular complexes of synthesized compound with DNA have been investigated by molecular modeling methodology. The adopted molecular modeling template consists of the following five steps: (i) poly-(dA-dT)2 and poly-(dG-dC)2 were simulated as a dodecamer fragment of (dA-dT)2 and (dG-dC)2, respectively. They were constructed in the B-DNA conformation with the nucleic acids macro implemented in the YASARA software,65 and minimized with the Amber03 force field,66 which is one of the most accurate force fields used for DNA minimization and molecular dynamics (MD) simulations, ensuring DNA stability until 25 ns;67 (ii) the simulations for the intercalation between paired nucleobases of RN5-Me bound to poly-(dA-dT)2 and poly-(dG-dC)2 were carried out using docking methodology.68 Firstly, the compound was manually inserted into the middle base-step (between 6th and 7th base pairs) of each fragment from the minor or major groove. While the compound atom positions were fixed, the remaining molecules were minimized to make the free fragment adjusted to suitably accommodate the ligand; (iii) to obtain the best and most reliable docking results, for each complex, a coarse docking simulation was first performed by applying the Lamarckian genetic algorithm (LGA) implemented in AutoDock 4.2.5.1,69 which has been recently demonstrated to be able to accurately reproduce the complex crystallographic structures of a collection of DNA-binding small ligands;70 (iv) the best obtained ligand pose was further subjected to a MD simulation of 5 ns in a physiological environment (pH 7.2, H2O, NaCl 0.9%) to allow the ligand to be better accommodated in the pocket as well as to model the grooves interactions; (v) finally, RN5-Me ligand was well docked, by LGA, on the best MD obtained system. At physiological conditions the N1 nitrogen atom belonging to the piperazine moiety present in RN5-Me is completely protonated; therefore only the ammonium form was considered for all molecular modeling studies.
We also considered the possibility that the RN5-Me complexation mode with DNA may occur by binding along the grooves. This last task was performed similarly to the above described procedure, but eliminating step (ii) and substituting step (iii) with a blind docking procedure.71
The calculated binding energies of the above docking study, summarized in Table 2, show that RN5-Me interacts with DNA exclusively by intercalation and with a clear preference towards the (dA-dT)2 dodecamer. The intercalation can occur either by insertion from the minor or major groove, with a slight preference for the former. It resulted in a calculated binding energy of 13.77 kcal mol−1 that is in good agreement with the obtained cytotoxicity IC50 values in the nanomolar range.
Table 2 Calculated binding energies (kcal mol−1) for RN5-Me, intercalated or groove bound to (dA-dT)2 and (dG-dC)2 dodecamers
RN5-Me |
Major groove |
Minor groove |
Poly-AT |
Intercalated |
−13.30 |
−13.77 |
Groove bound |
−8.77 |
−9.55 |
|
Poly-GC |
Intercalated |
−9.73 |
−9.81 |
Groove bound |
−7.80 |
−10.40 |
The established interactions of RN5-Me with (dA-dT)2 dodecamer, depicted in Fig. 5 for the intercalation from the minor groove, are principally of van der Waals type, with an additional stabilizing hydrogen bond between the piperazine ammonium and the O2 of thymine T6. Moreover, the orientation of the long axis of pyrimido[5,4-b]indoledione scaffold is almost parallel to the base-pair dyad (Fig. 5, down) well according to the ICD signal at 257 nm (Fig. 4).
 |
| Fig. 5 Plot representing RN5-Me intercalated into poly-(dA-dT)2 from minor groove. Side view (up) and upper view (down). | |
5. Experimental procedure
5.1. Biology
5.1.1. Cell viability assay. HN6, HN13, HeLa, SK-Me1-103, PC3, MCF7, and NOK-SI cell viability was measured using a commercial MTT assay (CellTiter 96 Aqueous One Solution Assay, Promega Co., USA), according to the Manufacturer's instructions. The assay is based on the ability of viable cells to metabolize yellow 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to violet formazan that can be detected spectrophotometrically. Briefly, 10
000 cells per well were seeded into 96-well culture plates at 37 °C with 5% CO2 and allowed to attach for 24 h. Cells were exposed to increased concentrations of the test compound for additional 24 h and then incubated with MTT assay solution (5 mg mL−1 in phosphate buffered saline) for 4 h at 37 °C. Formation of MTT to formazan crystals by viable cells was assessed using 200 μL per well DMSO at room temperature for 15 min. Absorbance was measured at 490 nm using a microplate reader (Bio-Tek EL-311, Bio-Tek Instruments). The assays were performed in triplicate and a non-linear regression analysis was used to get dose-response curves.
5.1.2. DNA unwinding assay. The assay was carried out using negatively supercoiled or relaxed pGEM-T Easy plasmid. Relaxed plasmid was generated by treating negatively supercoiled pGEM-T Easy with Topo I. Reaction mixtures (10 μL final volume) containing 0.3 μg of supercoiled or relaxed pGEM-T Easy, Topo I and the studied compound RN5-Me at concentration of 10 nM were incubated in reaction buffer (50 mM Tris–HCl pH 7.5, 20 mM KCl, 1 mM EDTA, 1 mM dithiothreitol, and BSA at 0.3 mg mL−1) for 30 min at 37 °C. The reactions were terminated by the addition of 0.5% SDS and 0.5 mg mL−1 proteinase K. Samples were incubated for 30 min at 50 °C. Next, 1.2 μL of 10× loading buffer (20% Ficol 400; 0.1 M Na2EDTA, pH 8.0, 1.0% SDS, and 0.25% bromphenol blue) were added and reactions mixtures were loaded onto a 1% agarose gel made in 1× TBE buffer. Gels were run in 1× TBE containing 0.1% SDS. After electrophoresis, DNA bands were stained in ethidium bromide (10 μg mL−1) and visualized by transillumination with ultraviolet light (300 nm).
5.2. Circular dichroism
5.2.1. General. The circular dichroism spectra were recorded by means of a JASCO J-815 spectropolarimeter equipped with a 150 W xenon lamp. The ellipticity was obtained calibrating the instruments with a 0.06% (w/v) aqueous solution of ammonium D-10-camphorsulfonate and with a 0.08% (w/v) aqueous solution of tris(ethylenediamine)cobalt(III) chloride complex 2{(−)-Δ-[Co(en)3]Cl3}·NaCl·6H2O. The measurements, corrected for the contribution from cell and solvent, were performed at constant temperature of 25 °C in quartz cells. The temperature of J-815 was controlled by means of a Jasco PTC-423S/15 Peltier-type temperature control system, cooled with an external water circulator. The spectra have been corrected to take into account the dilution effect after each addition.The concentrations of ct-DNA, in base pair, were determined by absorption spectroscopy, using the following molar extinction coefficient: 13
200 M−1 cm−1 at 260 nm.
5.2.2. Titration. CD spectra were performed in a standard quartz cell of 1 cm path length in the 235–450 nm range. For each spectrum 5 runs were averaged with a 5 min equilibration interval before each scan. All the spectra were recorded using fixed concentration of ct-DNA (12.6 μM in base pair) in the absence or in presence of different concentrations of RN5-Me (4.26 mM solution in DMSO) ranging from 0 to about 35 μM.
5.3. Molecular modeling
5.3.1. Preparation of RN5-Me ligand. 3D structure of RN5-Me ligand was built using Winmostar (4.101) software72 and the geometry was fully optimized, in the same software, with the semiempirical AM1 (ref. 73) Hamiltonian implemented in MOPAC2012 (14.04 W).74 RN5-Me was optimized as ammonium ion (charge +1).
5.3.2. Molecular dynamics simulations. The molecular dynamics simulations of the DNA/ligand complexes were performed with the YASARA Structure package (13.9.8).65 A periodic simulation cell with boundaries extending 10 Å from the surface of the complex was employed. The box was filled with water, with a maximum sum of all bumps per water of 1.0 Å, and a density of 0.997 g mL−1 with explicit solvent. YASARA's pKa utility was used to assign pKa values at pH 7.2,75 and the cell was neutralized with NaCl (0.9% by mass); in these conditions RN5-Me results protonated at the N1 piperazine atom. Water molecules were deleted to readjust the solvent density to 0.997 g mL−1. The Amber03 force field was used with long-range electrostatic potentials calculated with the Particle Mesh Ewald (PME) method, with a cutoff of 7.86 Å.66,76,77 The ligand force field parameters were generated with the AutoSMILES utility,78 which employs semiempirical AM1 geometry optimization and assignment of charges, followed by assignment of the AM1BCC atom and bond types with a refinement using the RESP charges, and finally the assignments of general AMBER force field atom types. A short MD was run on the solvent only. The entire system was then energy-minimized using first a steepest descent minimization to remove conformational stress, followed by a simulated annealing minimization until convergence (<0.01 kcal mol−1 Å−1). The MD simulation was then initiated, using the NVT ensemble at 298 K, and integration time steps for intramolecular and intermolecular forces every 1.25 fs and 2.5 fs, respectively. The MD simulation was stopped after 5 ns and, on the pose with the best binding energy of ligand relative to the last one ns of MD trajectory, a second cycle of energy minimization, identical to the first, was applied.
5.3.3. Docking protocol. DNA–ligand complexes, as obtained after coarse minimization or MD simulation and energy minimization, were prepared with Vega ZZ79 (3.0.3.18), assigning Gasteiger charges to protein and AM1BCC ones to ligand. The graphical user interface AutoDockTools (1.5.7 rc1)80 was used to establish the Autogrid points as well as to visualize docked ligand–nucleic acid structures. Docking was performed with AutoDock (4.2.5.1) software.69 To define all binding sites and to have structural inputs, a grid based procedure was used.81 Here the output was saved as a PDBQT. The grid box was set, and the output was saved as a .gpf file. The ligand-centered maps were generated by the program AutoGrid (4.2.5.1) with a spacing of 0.375 Å and dimensions that encompass all atoms extending 10 Å from the surface of the ligand (for blind docking DNA-centered maps were generated with a spacing of 0.375 Å and dimensions that encompass all atoms extending 10 Å from the surface of DNA). All of the parameters were inserted at their default settings. In the docking tab, the macromolecule and ligand are selected, and GA parameters are set as ga_runs = 100, ga_pop_size = 150, ga_num_evals = 2
500
000 for coarse docking and 20
000
000 for fine docking, ga_num_generations = 27
000, ga_elitism = 1, ga_mutation_rate = 0.02, ga_crossover_rate = 0.8, ga_rossover_mode = two points, ga_cauchy_alpha = 0.0, ga_cauchy_beta = 1.0, number of generations for picking worst individual = 10, output is selected as LGA, and the file is saved as .dpf.
6. Conclusions
In this study we report the identification of RN5-Me as a potent antiproliferative agent acting by DNA intercalation. RN5-Me had been synthesized as α1-adrenergic receptor ligand and, on the base of its similitude with other well-known intercalator molecules, it has been now exhaustively evaluated as DNA binder. It shows a very potent cytotoxic activity (with IC50 values in the nanomolar range) towards high resistant cancer cell lines, with a higher selectivity than Cisplatin upon non-cancerous cells. Topo I assay and CD experiments have confirmed that RN5-Me binds to DNA in intercalative mode and docking studies, confirming this, indicate a great selectivity for alternating AT nucleobases upon GC ones.
Obtained results point out the potent antiproliferative properties of RN5-Me and suggest that its structure, upon discrete modifications, can be useful as a template for future development of new potent anticancer agents lacking the methoxyphenyl portion, essential for its α1-adrenergic activity.
Acknowledgements
The authors thanks the University of Catania (Ricerca Scientifica di Ateneo 2012), the Ministero Istruzione Università e Ricerca (MIUR, Roma) for the partial financial support by the project PON01_00074 – DIATEME and PRIN 2012, N. 20109Z2XRJ_003 (Progettazione e sintesi stereoselettiva di composti attivi verso bersagli proteici coinvolti in patologie virali e tumorali).
Notes and references
- Worldwide cancer statistics, http://www.cancerresearchuk.org/cancer-info/cancerstats/world/cancer-worldwide-the-global-picture.
- F. Bray, J. S. Ren, E. Masuyer and J. Ferlay, Int. J. Cancer, 2013, 132, 1133–1145 CrossRef CAS PubMed.
- J. Ferlay, H. R. Shin, F. Bray, D. Forman, C. Mathers and D. M. Parkin, Int. J. Cancer, 2010, 127, 2893–2917 CrossRef CAS PubMed.
- P. Landers, Wall St. J., 2004, A1–A8 Search PubMed.
- M. J. Barratt and D. Frail, Drug repositioning : bringing new life to shelved assets and existing drugs, John Wiley & Sons, Hoboken, 2011 Search PubMed.
- Z. C. Liu, H. Fang, K. Reagan, X. W. Xu, D. L. Mendrick, W. Slikker and W. D. Tong, Drug Discovery Today, 2013, 18, 110–115 CrossRef CAS PubMed.
- D. L. Ma, D. S. H. Chan and C. H. Leung, Chem. Soc. Rev., 2013, 42, 2130–2141 RSC.
- T. I. Oprea and J. Mestres, AAPS J., 2012, 14, 759–763 CrossRef CAS PubMed.
- A. Corbett, J. Pickett, A. Burns, J. Corcoran, S. B. Dunnett, P. Edison, J. J. Hagan, C. Holmes, E. Jones, C. Katona, I. Kearns, P. Kehoe, A. Mudher, A. Passmore, N. Shepherd, F. Walsh and C. Ballard, Nat. Rev. Drug Discovery, 2012, 11, 833–846 CrossRef CAS PubMed.
- A. Khanapure, P. Chuki and A. De Sousa, Indian J. Appl. Res., 2014, 4, 462–466 CrossRef PubMed.
- S. C. Gupta, B. Y. Sung, S. Prasad, L. J. Webb and B. B. Aggarwal, Trends Pharmacol. Sci., 2013, 34, 508–517 CrossRef CAS PubMed.
- E. B. Haura and U. Rix, J. Natl. Cancer Inst., 2014, 106 DOI:10.1093/jnci/dju250.
- N. S. Jahchan, J. T. Dudley, P. K. Mazur, N. Flores, D. Yang, A. Palmerton, A. F. Zmoos, D. Vaka, K. Q. T. Tran, M. Zhou, K. Krasinska, J. W. Riess, J. W. Neal, P. Khatri, K. S. Park, A. J. Butte and J. Sage, Cancer Discovery, 2013, 3, 1364–1377 CrossRef CAS PubMed.
- J. Stenvang, I. Kumler, S. B. Nygard, D. H. Smith, D. Nielsen, N. Brunner and J. M. Moreira, Front. Oncol., 2013, 3, 313 Search PubMed.
- U. Bharadwaj, T. K. Eckols, M. Kolosov, M. M. Kasembeli, A. Adam, D. Torres, X. Zhang, L. E. Dobrolecki, W. Wei, M. T. Lewis, B. Dave, J. C. Chang, M. D. Landis, C. J. Creighton, M. A. Mancini and D. J. Tweardy, Oncogene, 2014 DOI:10.1038/onc.2014.72.
- P. Pantziarka, G. Bouche, L. Meheus, V. Sukhatme and V. P. Sukhatme, ecancermedicalscience, 2014, 8, 443 CrossRef PubMed.
- P. Pantziarka, G. Bouche, L. Meheus, V. Sukhatme, V. P. Sukhatme and P. Vikas, ecancermedicalscience, 2014, 8, 442 CrossRef PubMed.
- J. J. Roix, S. D. Harrison, E. A. Rainbolt, K. R. Meshaw, A. S. McMurry, P. Cheung and S. Saha, PLoS One, 2014, 9, e101708 Search PubMed.
- M. Wang, J. S. Shim, R. J. Li, Y. Dang, Q. He, M. Das and J. O. Liu, Br. J. Pharmacol., 2014, 171, 4478–4489 CrossRef CAS PubMed.
- C. Fung and J. R. Grandis, Expert Opin. Emerging Drugs, 2010, 15, 355–373 CrossRef CAS PubMed.
- A. A. Molinolo, P. Amornphimoltham, C. H. Squarize, R. M. Castilho, V. Patel and J. S. Gutkind, Oral Oncol., 2009, 45, 324–334 CrossRef CAS PubMed.
- K. P. Pendleton and J. R. Grandis, Clin. Med. Insights: Ther., 2013, 5, 103–116 CAS.
- Y. Suh, I. Amelio, T. Guerrero Urbano and M. Tavassoli, Cell Death Dis., 2014, 5, e1018 CrossRef CAS PubMed.
- B. Rajendar, A. Rajendran, Z. Q. Ye, E. Kanai, Y. Sato, S. Nishizawa, M. Sikorski and N. Teramae, Org. Biomol. Chem., 2010, 8, 4949–4959 CAS.
- I. Naseem, M. Ahmad and S. M. Hadi, Biosci. Rep., 1988, 8, 485–492 CrossRef CAS.
- S. R. Dalton, S. Glazier, B. Leung, S. Win, C. Megatulski and S. J. N. Burgmayer, J. Biol. Inorg. Chem., 2008, 13, 1133–1148 CrossRef CAS PubMed.
- F. Russo, G. Romeo, S. Guccione and A. De Blasi, J. Med. Chem., 1991, 34, 1850–1854 CrossRef CAS.
- E. Patanè, V. Pittalà, F. Guerrera, L. Salerno, G. Romeo, M. A. Siracusa, F. Russo, F. Manetti, M. Botta, I. Mereghetti, A. Cagnotto and T. Mennini, J. Med. Chem., 2005, 48, 2420–2431 CrossRef PubMed.
- V. Pittalà, G. Romeo, L. Salerno, M. A. Siracusa, M. Modica, L. Materia, I. Mereghetti, A. Cagnotto, T. Mennini, G. Marucci, P. Angeli and F. Russo, Bioorg. Med. Chem. Lett., 2006, 16, 150–153 CrossRef PubMed.
- G. Romeo, L. Materia, G. Marucci, M. Modica, V. Pittalà, L. Salerno, M. A. Siracusa, M. Buccioni, P. Angeli and K. P. Minneman, Bioorg. Med. Chem. Lett., 2006, 16, 6200–6203 CrossRef CAS PubMed.
- V. Pittalà, M. A. Siracusa, M. N. Modica, L. Salerno, A. Pedretti, G. Vistoli, A. Cagnotto, T. Mennini and G. Romeo, Bioorg. Med. Chem., 2011, 19, 5260–5276 CrossRef PubMed.
- G. Romeo, L. Materia, M. N. Modica, V. Pittalà, L. Salerno, M. A. Siracusa, F. Manetti, M. Botta and K. P. Minneman, Eur. J. Med. Chem., 2011, 46, 2676–2690 CrossRef CAS PubMed.
- G. Romeo, L. Salerno, V. Pittalà, M. N. Modica, M. A. Siracusa, L. Materia, M. Buccioni, G. Marucci and K. P. Minneman, Eur. J. Med. Chem., 2014, 83, 419–432 CrossRef CAS PubMed.
- M. Matarrese, R. M. Moresco, G. Romeo, E. A. Turolla, P. Simonelli, S. Todde, S. Belloli, A. Carpinelli, F. Magni, F. Russo, M. G. Kienle and F. Fazio, Eur. J. Pharmacol., 2002, 453, 231–238 CrossRef CAS.
- G. Romeo, L. Materia, F. Manetti, A. Cagnotto, T. Mennini, F. Nicoletti, M. Botta, F. Russo and K. P. Minneman, J. Med. Chem., 2003, 46, 2877–2894 CrossRef CAS PubMed.
- M. C. C. Luca, V. V. Tura and I. I. Mangalagiu, Med. Hypotheses, 2010, 75, 627–629 CrossRef CAS PubMed.
- H. K. Liu and P. J. Sadler, Acc. Chem. Res., 2011, 44, 349–359 CrossRef CAS PubMed.
- M. Stiborova, T. Eckschlager, J. Poljakova, J. Hrabeta, V. Adam, R. Kizek and E. Frei, Curr. Med. Chem., 2012, 19, 4218–4238 CrossRef CAS.
- A. Rescifina, C. Zagni, M. G. Varrica, V. Pistarà and A. Corsaro, Eur. J. Med. Chem., 2014, 74, 95–115 CrossRef CAS PubMed.
- A. Rescifina, M. A. Chiacchio, A. Corsaro, E. De Clercq, D. Iannazzo, A. Mastino, A. Piperno, G. Romeo, R. Romeo and V. Valveri, J. Med. Chem., 2006, 49, 709–715 CrossRef CAS PubMed.
- A. Rescifina, U. Chiacchio, A. Piperno and S. Sortino, New J. Chem., 2006, 30, 554–561 RSC.
- A. Rescifina, U. Chiacchio, A. Corsaro, A. Piperno and R. Romeo, Eur. J. Med. Chem., 2011, 46, 129–136 CrossRef CAS PubMed.
- A. Rescifina, M. G. Varrica, C. Carnovale, G. Romeo and U. Chiacchio, Eur. J. Med. Chem., 2012, 51, 163–173 CrossRef CAS PubMed.
- A. Rescifina, C. Zagni, G. Romeo and S. Sortino, Bioorg. Med. Chem., 2012, 20, 4978–4984 CrossRef CAS PubMed.
- Y. Pommier, Nat. Rev. Cancer, 2006, 6, 789–802 CrossRef CAS PubMed.
- L. O. Almeida, A. C. Abrahao, L. K. Rosselli-Murai, F. S. Giudice, C. Zagni, A. M. Leopoldino, C. H. Squarize and R. M. Castilho, FEBS Open Bio, 2014, 4, 96–104 CrossRef CAS PubMed.
- L. N. Putral, M. J. Bywater, W. Y. Gu, N. A. Saunders, B. G. Gabrielli, G. R. Leggatt and N. A. J. McMillan, Mol. Pharmacol., 2005, 68, 1311–1319 CrossRef CAS PubMed.
- V. Z. Mota, G. S. G. de Carvalho, A. D. da Silva, L. A. S. Costa, P. D. Machado, E. S. Coimbra, C. V. Ferreira, S. M. Shishido and A. Cuin, BioMetals, 2014, 27, 183–194 CrossRef CAS PubMed.
- S. Tardito, C. Isella, E. Medico, L. Marchio, E. Bevilacqua, M. Hatzoglou, O. Bussolati and R. Franchi-Gazzola, J. Biol. Chem., 2009, 284, 24306–24319 CrossRef CAS PubMed.
- K. I. Ansari, J. D. Grant, S. Kasiri, G. Woldemariam, B. Shrestha and S. S. Mandal, J. Inorg. Biochem., 2009, 103, 818–826 CrossRef CAS PubMed.
- M. R. Webb and S. E. Ebeler, Anal. Biochem., 2003, 321, 22–30 CrossRef CAS.
- V. I. Ivanov, L. E. Minchenkova, A. K. Schyolkina and A. I. Poletayev, Biopolymers, 1973, 12, 89–110 CrossRef CAS PubMed.
- B. Norden and F. Tjerneld, Biopolymers, 1982, 21, 1713–1734 CrossRef CAS PubMed.
- E. Grueso and R. Prado-Gotor, Chem. Phys., 2010, 373, 186–192 CrossRef CAS PubMed.
- F. Secco, M. Venturini, T. Biver, F. Sanchez, R. Prado-Gotor and E. Grueso, J. Phys. Chem. B, 2010, 114, 4686–4691 CrossRef CAS PubMed.
- Y. M. Chang, C. K. M. Chen and M. H. Hou, Int. J. Mol. Sci., 2012, 13, 3394–3413 CrossRef CAS PubMed.
- S. Parodi, F. Kendall and C. Nicolini, Nucleic Acids Res., 1975, 2, 477–486 CrossRef CAS.
- J. P. Macquet and J. L. Butour, Eur. J. Biochem., 1978, 83, 375–385 CrossRef CAS PubMed.
- R. Lyng, A. Rodger and B. Norden, Biopolymers, 1991, 31, 1709–1720 CrossRef CAS PubMed.
- R. Lyng, A. Rodger and B. Norden, Biopolymers, 1992, 32, 1201–1214 CrossRef CAS PubMed.
- R. Lyng, T. Hard and B. Norden, Biopolymers, 1987, 26, 1327–1345 CrossRef CAS PubMed.
- N. Shahabadi, S. Mohammadi and R. Alizadeh, Bioinorg. Chem. Appl., 2011 DOI:10.1155/2014/716578.
- H. Zipper, H. Brunner, J. Bernhagen and F. Vitzthum, Nucleic Acids Res., 2004, 32, e103, DOI:10.1093/nar/gnh101.
- K. Nakamoto, M. Tsuboi and G. D. Strahan, Drug-DNA interactions: structures and spectra, John Wiley & Sons, Hoboken, N.J., 2008 Search PubMed.
- E. Krieger, YASARA, YASARA Biosciences GmbH, Vienna, Austria, 2013 Search PubMed.
- Y. Duan, C. Wu, S. Chowdhury, M. C. Lee, G. M. Xiong, W. Zhang, R. Yang, P. Cieplak, R. Luo, T. Lee, J. Caldwell, J. M. Wang and P. Kollman, J. Comput. Chem., 2003, 24, 1999–2012 CrossRef CAS PubMed.
- C. G. Ricci, A. S. C. de Andrade, M. Mottin and P. A. Netz, J. Phys. Chem. B, 2010, 114, 9882–9893 CrossRef CAS PubMed.
- O. A. Santos, J. D. FigueroaVillar and M. T. Araujo, Bioorg. Med. Chem. Lett., 1997, 7, 1797–1802 CrossRef.
- G. M. Morris, R. Huey, W. Lindstrom, M. F. Sanner, R. K. Belew, D. S. Goodsell and A. J. Olson, J. Comput. Chem., 2009, 30, 2785–2791 CrossRef CAS PubMed.
- P. A. Holt, J. B. Chaires and J. O. Trent, J. Chem. Inf. Model., 2008, 48, 1602–1615 CrossRef CAS PubMed.
- C. Hetenyi and D. van der Spoel, Protein Sci., 2002, 11, 1729–1737 CrossRef CAS PubMed.
- N. Senda, Idemitsu Gihou, 2006, 49, 106–111 Search PubMed.
- M. J. S. Dewar, E. G. Zoebisch, E. F. Healy and J. J. P. Stewart, J. Am. Chem. Soc., 1985, 107, 3902–3909 CrossRef CAS.
- J. J. P. Stewart, Stewart Computational Chemistry, Colorado Springs, CO, USA, 2012 Search PubMed.
- E. Krieger, J. E. Nielsen, C. A. E. M. Spronk and G. Vriend, J. Mol. Graphics Modell., 2006, 25, 481–486 CrossRef CAS PubMed.
- W. D. Cornell, P. Cieplak, C. I. Bayly, I. R. Gould, K. M. Merz, D. M. Ferguson, D. C. Spellmeyer, T. Fox, J. W. Caldwell and P. A. Kollman, J. Am. Chem. Soc., 1995, 117, 5179–5197 CrossRef CAS.
- U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee and L. G. Pedersen, J. Chem. Phys., 1995, 103, 8577–8593 CrossRef CAS PubMed.
- A. Jakalian, D. B. Jack and C. I. Bayly, J. Comput. Chem., 2002, 23, 1623–1641 CrossRef CAS PubMed.
- A. Pedretti, L. Villa and G. Vistoli, J. Comput.-Aided Mol. Des., 2004, 18, 167–173 CrossRef CAS.
- M. F. Sanner, J. Mol. Graphics Modell., 1999, 17, 57–61 CAS.
- P. J. Goodford, J. Med. Chem., 1985, 28, 849–857 CrossRef CAS.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c4ra11856a |
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