Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Chem Biol Drug Des 2010; 76: 425–432 ª 2010 John Wiley & Sons A/S doi: 10.1111/j.1747-0285.2010.01027.x Research Article Computational Studies on Effects of MDMA as an Anticancer Drug on DNA Siavash Riahi1,2,*, Solmaz Eynollahi2 and Mohammad R. Ganjali2,3 ties and high schools even though the side-effects of MDMA on the human body are those such as: neuronal damage and DNA damage (2,3). 1 Institute of Petroleum Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran 2 Center of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P. O. Box 14155-6455, Tehran, Iran 3 Endocrinology & Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran *Corresponding author: Siavash Riahi, [email protected] This research is designed to further understand the effects of the novel drug MDMA on biologic receptor of DNA. The ultimate goal is to design drugs that have higher affinity with DNA. Understanding the physicochemical properties of the drug as well as the mechanism by which it interacts with DNA should ultimately enable the rational design of novel anticancer or antiviral drugs. Molecular modeling on the complex formed between MDMA and DNA presented this complex to be fully capable of participating in the formation of a stable intercalation site. Furthermore, the molecular geometries of MDMA and DNA bases (Adenine, Guanine, Cytosine, and Thymine) were optimized with the aid of the B3LYP ⁄ 6-31G* method. The properties of the isolated intercalator and its stacking interactions with adenineÆÆÆthymine (AT) and guanineÆÆÆcytosine (GC) nucleic acid base pairs were studied with the DFTB method. DFTB method is an approximate version of the DFT method that was extended to cover the London dispersion energy. The B3LYP ⁄ 631G* stabilization energies of the intercalatorÆÆÆbase pair complexes were found to be )9.40 and )12.57 kcal ⁄ mol for ATÆÆÆMDMA and GCÆÆÆMDMA, respectively. Results from comparison of the DFTB method and HF method conclude close results and support each other. Key words: DFTB, DNA, drug design, intercalator, MDMA, stacking interaction Received 3 November 2009, revised 13 May 2010 and accepted for publication 22 August 2010 MDMA (3,4-methylenedioxy-N-methylamphetamine) is a ring-substituted amphetamine derivative that is structurally related to hallucinogenic drugs (1). Nowadays, MDMA used as ''ecstasy'' is becoming increasingly widespread among young adults in universi- In recent years, the DFT method was applied in different branches of chemistry (4–11)a. This paper presents the recently introduced approximate DFT method, DFTB technique (density functional tight-binding), empirical London dispersion energy term, which is accurate and reliable for computational studies (12), and calculations performed using the DFTB technique for H-bonded and stacked DNA base pairs (13). Furthermore, this computationally very efficient procedure can yet be used in quantum mechanical (QM) and QM ⁄ molecular mechanical (MM) MD simulations very conveniently and accurately (14,15). The quantum mechanical description of interactions between MDMA and DNA base pairs (Watson–Crick base pairing) employing the DFTB method are reported in this paper. To achieve this goal, MDMA and DNA base pairs were simulated; atomic charges, geometrical values (bond lengths, bond angles and dihedral angles), dipole moment, polarizability, and energies of the frontier molecular orbitals [high occupied molecular orbital (HOMO) and low unoccupied molecular orbital (LUMO)] were obtained. According to a literature survey, this is the first paper that studies MDMA and DNA base pair intercalations using the DFT method. In recent years, the DFT method was applied in different branches of chemistry (16–22). In this paper, we have used DFTB technique (density functional tight-binding), which is accurate and reliable for computational studies, especially for H-bonded and stacked DNA base pairs (23,24). The aim of this work was to study the geometries, electronic MDMA structures and its molecular complexes with nucleobases by DFTB methods. This study will shed more light on the nature of intercalations between a drug and DNA dominantly from the viewpoint of charge transfer, dispersion, and electrostatic forces. Hence, the study can help design new intercalators (drugs) that have higher affinity with DNA. Computational Methods Calculations on isolated molecules and molecular complexes were performed with GAUSSIAN 98 package (25). Both species were initially optimized with PM3 method. The optimized structures were again optimized with density functional 425 Riahi et al. theory using the 6-31G* basis set. Full geometry optimizations and frequency calculations were performed, and each species was found to be at minima, by having no negative values in the frequency calculation. The calculations gave internal energies at 0 K. To obtain gas-phase free energies at 298.15 K, it is necessary to calculate the zero-point energies and thermal corrections together with entropies to convert the internal energies to Gibbs energies at 298.15 K (26,27). Frequency calculations on these structures verify that they were at true minima and provided necessary thermal corrections to calculate H (Enthalpy) and G (Gibbs free energy). Finally, full optimizations and frequency calculations for each species were performed with the HF ⁄ 6-31G* and DFT ⁄ 6-31G* (28,29). The MDMA structure and geometry were optimized at the B3LYP level using the 6-31G* basis set. To find the most stable equilibrium structure for MDMAÆÆÆBase pairs complexes, the initial guess structures are considered based on PM3 semiempirical calculations. Full geometry search based on Newton–Rapson procedure as implemented in GAMESS quantum chemistry code were followed (30). The most stable geometries were achieved when the intercalator (MDMA) and base pairs adenineÆÆÆthymine and guanineÆÆÆcytosine (AT and GC) were situated in coplanar planes in such a way that the major system axes were parallel. There is special definition for the molecular geometries of DNA base pairs. In all cases, the QM-optimized geometries of the base pairs and intercalators were used for QM calculations. Thus, when the idealized geometries were utilized, the interacting molecules were overlaid by their HF ⁄ 6-31G* and B3LYP ⁄ 6-31G* optimized geometries, based on the least-squares fitting method. In the case of empirical potential calculations, either the subsystem geometries were relaxed by the empirical potential or the QM-optimized geometries were saved. This difference had an insignificant effect on the calculated energies. The other one-electron properties (dipole moment, polarizability, energies of the frontier molecular orbital) were also determined at the HF ⁄ 6-31G* and B3LYP ⁄ 6-31G* level. For charged species, the dipole moment was derived with respect to their mass center, because for the non-neutral molecules, the calculated dipole moment depends on the origin of the co-ordinate system. Dipole moment refers to the quality of a system to behave like a dipole. Dipole moment is the measured polarity of a polar covalent bond and is defined as the product magnitude of charge on the atoms and the distance between the two bonded atoms. Polarizability is the relative tendency of a charge distribution, like the electron cloud of an atom or molecule, to be distorted from its normal shape by an external electric field. The stabilization energies of selected complexes were determined by DFT calculations and calculated with a recently introduced method based on the combination of the approximate tight-binding DFTB with the empirical dispersion energy. The DFT methods are known to be inherently very deficient for stacking interactions as they basically ignore the dispersion attraction (31–33). As a consequence, their enlargement by an empirical dispersion term currently appears to be a very reasonable way to improve 426 the major deficiency of the DFT method for the evaluation of the molecular complexes. It should also be mentioned that interaction energies were obtained as the difference between the complex energy and the combined energies of the molecules in isolation (34). Processes in DNA environment depend on a delicate balance between stacking interactions, hydrogen bonding and hydration effects (35). Hydration free energies could be calculated by implicit models like solvent reaction field (36) and Langevin dipole (37) methods, or by explicit models in conjunction with free energy calculations and molecular dynamics simulations (38). Because of complexity of these calculations, hydration effects will be evaluated in future studies. Results and Discussion MDMA characteristics The optimized structure, atom numbering, and atom charges of MDMA are shown in Figure 1. The equilibrium geometries of the MDMA subsystem were determined and confirmed by subsequent calculations of the vibrational frequencies. Geometrical optimizations were performed using the DFTB method, and the significant computed geometrical parameters are available in Table 1. This table contains significant geometrical values including: bond length, bond angles, and dihedral angles for MDMA, before and after the complex formation (MDMAÆÆÆAT and MDMAÆÆÆGC). MDMA does not have a planar structure – in fact, it illustrates one equal branch that is entirely out of plane (it demonstrate 73 out of planarity of the whole geometry). It should also be mentioned that the atom charge distribution in the MDMA is delocalized. Carbons 7 and 11 exhibit the highest positive charges, which are the cause of them bonding to the oxygen atoms with high electronegativity. The most negative charge is N2 because it is in close vicinity to hydrogen and carbon, which are electropositive atoms. O8 and O10 are electronegative atoms but they connect to a benzene ring that is electron withdrawing, so they are not the most negatively charged. The presence of electronegative elements in MDMA facilitated its interaction with the DNA molecule through hydrogen bonding with GC and AT hydrogen. Actually, there are two kinds of interactions between MDMA and DNA; electrostatic interactions and dispersion interactions, being discussed in the next paragraphs. Table 2 depicts the one-electron properties (dipole moment and polarizability) and the energies of the frontier molecular orbital (HOMO and LUMO) of MDMA using the DFTB and HF computational method. For validation of the results, HF and DFTB methods were applied. The results are close, and each method confirms other method. Because of the DFTB method covers the London dispersion energy, this method is more accurate. Dipole moment is the first derivative of energy with respect to an applied electric field as a measure of asymmetry in the molecular charge distribution. High values of dipole moment and polarizability show that electrostatic and dispersion contribution play a key role in the interaction with nucleobases. Chem Biol Drug Des 2010; 76: 425–432 Effects of MDMA as an Anticancer Drug on DNA 0.109 A 0.139 0.272 –0.255 0.102 0.151 –0.570 –0.335 0.144 0.128 –0.131 0.094 0.138 -0.557 0.294 0.146 –0.395 0.176 0.094 0.140 0.141 0.196 0.177 0.128 0.255 –0.556 –0.107 0.147 B 0.158(0.151) 0.264(0.270) 0.113 (0.130) 0.106(0.104) –0.257(–0.256) –0.141(–0.130) –0.330(–0.341) –0.570(–0.570) 0.057(0.058) –0.400(–0.396) 0.137(0.136) 0.131(0.141) 0.134(0.135) –0.638(–0.651) 0.256(0.250) 0.168(0.180) 0.222(0.193) 0.170(0.165) 0.089(0.096) –0.180(–0.184) 0.127(0.124) 0.265(0.259) –0.662(–0.660) –0.108(–0.102) 0.152(0.159) Figure 1: (A) The optimized structure and the atom charges of MDMA. (B) The optimized structure and the atom charges of MDMA after the complex formation with GC and AT (Parentheses include the changes after the complex formation with AT). Table 1: Significant computed geometrical parameters for MDMA before and after complex formation Bond lengths MDMA MDMA- GC MDMA- AT R(2,3) R(7,8) R(8,9) R(9,10) R(9,24) 1.473 1.407 1.473 1.472 1.091 1.476 1.402 1.481 1.478 1.088 1.474 1.406 1.471 1.475 1.094 Bond angles MDMA MDMA - GC MDMA - AT A(1,2,18) A(3,2,18) A(4,5,6) A(7,8,9) A(9,10,11) A(10,11,12) 111.9 111.6 119.7 106.2 106.2 128.1 111.4 111.0 119.3 105.5 105.8 127.7 111.6 111.3 119.5 105.9 105.8 128.4 Base pairs characteristics Optimized structures of adenineÆÆÆthymine (AT) and guanineÆÆÆcytosine (GC) base pairs in the Watson–Crick structures are visualized in Figures 2 and 3, respectively. Tables 3 and 4 show the significant computed geometrical parameters, using the DFTB method before and after complex formation. In addition, Table 2 presents the oneelectron properties (dipole moment and polarizability) and energies of the frontier molecular orbital (HOMO and LUMO) of bases and base pairs. From Table 2, it is clear that all bases and base pairs Chem Biol Drug Des 2010; 76: 425–432 Bond dihedrals MDMA MDMA - GC MDMA - AT D(6,7,8,9) D(11,7,8,9) D(7,8,9,10) D(7,8,9,23) D(7,8,9,24) D(8,9,10,11) D(23,9,10,11) D(24,9,10,11) D(9,10,11,7) D(9,10,11,12) 179.8 0.1 )0.1 )118.4 118.2 0.1 118.4 )118.2 0.0 )179.7 170.4 )10.3 14.6 )102.9 131.9 )13.6 103.9 )130.8 7.6 )165.7 )174.5 8.0 )11.9 )129.8 106.0 11.4 128.8 )106.7 )6.8 175.2 are very poor electron acceptors (all LUMO energies are positive in contrast to LUMO energy of MDMA, which is negative). In this scenario, bases and base pairs are good electron donors, and among the isolated bases, the best one is guanine. This is in accordance with experimental and theoretical studies showing that ultimate carcinogens primarily react with DNA at the N7 atom of guanine (39,40). Base pairing can also further magnify electron donor ability. For example, the HOMO energy of guanine ()8.45 eV) increases by 1.1 eV upon pairing with cytosine. Furthermore, the high polariz427 Riahi et al. Table 2: Dipole moment [D], polarizability [B3], HOMO, and LUMO energies (in eV) of the drug, the bases and the base pairs with HF and DFTB methods HOMO LUMO Dipole moment Polarizability Compound DFTB HF DFTB HF DFTB HF DFTB HF AT GC MDMA A T G C )8.64 )7.35 )5.54 )8.83 )9.53 )8.45 )9.93 )8.21 )7.56 )5.30 )8.43 )9.57 )8.11 )9.22 3.01 2.74 )0.08 3.12 2.94 3.52 3.01 3.27 2.92 )0.13 3.74 3.26 4.13 3.30 1.28 2.51 0.90 2.49 3.88 2.76 6.12 1.18 2.22 0.89 2.52 3.32 2.56 7.97 213.2 223.4 174.3 101.2 89.1 109.2 80.4 201.6 215.6 154.3 96.1 85.1 100.7 83.6 0.246(0.346) –0.364(–0.450) –0.418(–0.690) 0.128(0.188) 0.118(0.173) 0.491(0.694) 0.162(0.161) –0.457(–0.740) –0.337(–0.358) 0.237(0.340) 0.358(0.426) – 0.512(–0.585) 0.304(0.438) 0.220(0.119) –0.337(0.053) 0.097(0.134) 0.472(0.524) – 0.390(– 0.709) 0.170(0.256) –0.476(–0.779) 0.115(0.177) –0.225(–0.457) 0.492(0.532) –0.104(0.075) 0.129(0.171) –0.410(–0.500) 0.129(0.165) 0.260(0.388) –0.335(–0.414) 0.237(0.341) Figure 2: Optimized structure and charge of AT base pair & MDMAÆÆÆAT before and after the complex formation (Parentheses include the changes after the complex formation). ability and dipole moment values of AT and GC (but more than those of MDMA) reveal that the electrostatic and dispersion contribution considerably influence the interaction with the intercalator. From previous papers, we can understand that the DFT method is more accurate. Moreover, the results conclude from the comparison of the DFTB method and HF method that these both show similar results and support each other. Complex characteristics The MDMAÆÆÆAT and MDMAÆÆÆGC optimized geometries are summarized in Figures 4A, B, respectively. The atom charge differences of MDMA, AT, and GC are presented in Figures 1A,B, 2 and 3, respectively. From Figure 1B, it is obvious that the charge difference after the complex formation is greater. For instance, in GCÆÆÆMDMA, C7 and C11, the atom charge differences are 0.256 and 0.265, respectively. In contrast, the oxygen charge moves to more negative values (i.e., for O8 and O10, the atom charge shifts from )0.557 and )0.556 to )0.638 and )0.662, respectively). These changes indicate that oxygen receives a part of its charge from the hydrogen atoms 428 in GC. Hence, weak hydrogen bonding was formed between MDMA and GC. The study of atom charges in GC and MDMAÆÆÆGC exhibits that the part shown with dash marks (the only part that is going to be discussed afterward) displays the highest changes because of MDMA and GC interactions. Similar changes have also been obtained in AT. Because the MDMA heteroatoms interact with GC hydrogen in the zone, the charge changes are not important for the other heteroatom of GC or AT bases pairs. This observation was proven by the increase in GC hydrogen charges (i.e., H26 atom charge shifted from 0.304 to 0.438), revealing a stronger hydrogen bond had been formed between these atoms and the heteroatoms in the drug and the decrease in their bond length (i.e., R bond length (2, 26) shifted from 1.910 to 1.851). After interaction with the MDMA, molecule bond angles of base pairs changed in the mentioned area, i.e., in GC, A (1, 10, 29) shifted from 117.2 to 125.6. The changes in dihedral angles denote that the base pair structures have shifted from planar, i.e., D (1,2,10,29) in GC displays the highest difference. As it is evident from Tables 1 and 3, bond lengths, bond angles, and dihedral Chem Biol Drug Des 2010; 76: 425–432 Effects of MDMA as an Anticancer Drug on DNA 0.229(0.327) –0.428(–0.508) 0.244(0.349) –0.501(–0.788) 0.262(0.393) 0.502(0.638) 0.564(0.666) –0.416(–0.415) 0.228(0.330) 0.354(0.446) –0.406(–0.669) 0.194(0.156) –0.522(–0.553) –0.491(–0.772) 0.472(0.557) –0.393(–0.722) –0.278(–0.141) 0.282(0.419) 0.439(0.495) –0.449(–0.763) –0.153(0.046) 0.129(0.182) 0.109(0.151) 0.151(0.250) 0.286(0.408) –0.443(–0.554) 0.228(0.321) –0.301(–0.389) 0.106(0.166) Figure 3: Optimized structure and charge of GC base pair & MDMAÆÆÆGC, before and after the complex formation (Parentheses include the changes after the complex formation). Table 3: Significant computed geometrical parameters for GC and MDMA before and after the complex formation Bond lengths GC GC-MDMA Bond angles GC GC-MDMA Bond dihedrals GC GC-MDMA R(1,2) R(1,10) R(2,3) R(2,12) R(2,26) R(3,11) R(10,29) R(11,15) R(11,16) R(12,22) R(17,22) R(17,23) R(21,22) R(21,24) R(23,28) R(23,29) 1.409 1.233 1.4373 1.032 1.910 1.348 1.8764 1.020 1.004 1.909 1.335 1.334 1.4357 1.228 1.005 1.035 1.466 1.312 1.475 1.051 1.851 1.431 1.789 1.031 1.037 1.867 1.408 1.343 1.442 1.311 1.023 1.020 A(2,1,10) A(1,2,3) A(1,2,12) A(3,2,12) A(2,3,11) A(1,10,29) A(3,11,15) A(3,11,16) A(15,11,16) A(22,17,23) A(22,21,24) A(17,22,21) A(17,23,28) A(17,23,29) A(28,23,29) 119.9 125.9 115.2 118.9 116.8 117.2 123.1 116.7 120.3 117.9 124.6 121.4 120.1 120.6 119.3 118.9 124.9 115.3 119.5 117.4 125.6 122.9 116.8 120.2 117.8 124.2 121.4 120.4 119.9 118.4 D(10,1,2,3) D(10,1,2,12) D(2,1,10,29) D(1,2,3,11) D(12,2,3,11) D(2,3,11,15) D(2,3,11,16) D(1,10,23,17) D(1,10,23,28) D(23,17,22,21) D(22,17,23,28) D(22,17,23,29) D(24,21,22,17) )180.0 0.0 0.0 )180.0 0.0 )0.1 )180.0 0.1 )180.0 )180.0 )180.0 0.0 )180.0 177.3 )8.1 22.4 178.6 4.2 )2.4 )179.7 )24.0 174.1 )178.7 178.4 11.4 177.6 angles alter significantly in a way that the hydrogen bonding becomes weak, causing changes in the DNA molecular structure. Therefore, drugs should be designed that bring about the least changes in DNA and its molecular structure. To avoid repetition, the results attained for AT are only listed in Table 4 and Figure 2, which are in agreement with those of GC. In general, a way for data collection regarding the electron distribution is by computing the polarizability. This property depends on the second derivative of the energy relating to an electric field. Table 2 delineates the high MDMA, GC, and AT polarizability values, supporting the fact that the dispersion energy is always important. Chem Biol Drug Des 2010; 76: 425–432 Another way is dipole moment of base pairs and the studied intercalator, which is presented in Table 2. The significant polarizability and dipole moment values prove the existence of dispersion and electrostatic interactions between DNA and MDMA. The polarizability and dipole moment of intercalator have the same effects on the interaction with DNA. Hence, a drug should be designed with high polarizability and dipole moment to increase the interactions between DNA and the drug. To evaluate the dependence of the Intercalator–Base Pair Stacking interaction energy on their vertical separation, investigations were carried out with the vertical distance between the interacting sys429 Riahi et al. Table 4: Significant computed geometrical parameters for AT and MDMA before and after the complex formation Bond lengths AT AT-MDMA Bond angles AT AT-MDMA Bond dihedrals AT AT-MDMA R(1,2) R(1,10) R(2,3) R(2,26) R(3,12) R(10,13) R(10,14) R(16,18) R(16,24) R(18,19) R(18,26) R(19,23) 1.351 1.341 1.346 1.823 1.086 1.020 1.006 1.380 1.214 1.389 1.046 1.229 1.367 1.345 1.359 1.713 1.083 1.024 1.008 1.381 1.248 1.390 1.060 1.263 A(2,1,10) A(1,2,3) A(1,2,26) A(3,2,26) A(2,3,12) A(1,10,13) A(1,10,14) A(13,10,14) A(18,16,24) A(16,18,19) A(16,18,26) A(19,18,26) A(18,19,23) 119.7 119.7 123.2 117.1 114.8 120.7 118.6 120.6 124.4 127.1 115.9 117.0 120.8 119.3 120.6 122.8 116.3 115.4 120.5 119.3 120.2 124.1 126.5 116.0 117.4 120.6 D(10,1,2,3) D(10,1,2,26) D(2,1,10,13) D(2,1,10,14) D(1,2,3,12) D(26,2,3,12) D(1,2,18,16) D(1,2,18,19) D(3,2,18,16) D(3,2,18,19) D(24,16,18,19) D(24,16,18,26) D(16,18,19,23) D(26,18,19,23) 180.0 0.0 0.0 180.0 180.0 0.0 )180.0 0.0 0.0 179.9 )180.0 0.0 )180.0 0.0 )179.0 7.6 1.2 )177.2 )178.5 )4.7 162.9 )12.3 )9.4 175.4 179.4 2.7 179.8 )3.5 A 2 A 0 –2 –4 –6 B E (kcal/mol) –8 –10 B 25 20 15 10 5 0 –5 –10 Figure 4: (A, B) Optimized structures of MDMA ÆÆÆAT and MDMA ÆÆÆGC, respectively. tems. The interaction energies were corrected for the basis set superposition error using the counterpoise method (41,42). Figures 5A, B illustrate the investigated structures for AT and GC with MDMA, respectively. As it is apparent from Figures 5A, B, the minimum values of the respective potential energy curve for ATÆÆÆMDMA and GCÆÆÆMDMA were found at 4.35 and 4.02 , respectively. The stabilization energies (energy necessary to separate MDMA and AT pair to infinity) of ATÆÆÆMDMA and GCÆÆÆMDMA were equal to )9.40, )7.95 and )12.57, )10.88 kcal ⁄ mol, by DFTB and HF methods, respectively. Consequently, as the interaction 430 –15 2 4 r (Å) 6 Figure 5: Stabilization energies (DE) of MDMA ÆÆÆAT (A) and MDMA ÆÆÆGC (B), r is the distance between base pairs and drug molecule. energy increases, the distance between the DNA molecule and drug reduces. In addition, computational chemistry methods as a kind of extension of the experimental approach have a great interest in chemotherapy studies of DNA-drug binding. These theoretical studies are used to predict convenient structures of DNA-drugs binding to control the DNA changes. Chem Biol Drug Des 2010; 76: 425–432 Effects of MDMA as an Anticancer Drug on DNA It is evident that only the theoretical procedures properly cover the dispersion and polarization effects; therefore these procedures were used for the study of intercalation processes and designing a drug that has higher affinity with DNA molecules. Acknowledgments We gratefully acknowledge the support of this work by the Institute of Petroleum Engineering, Tehran University Research Councils. References Figure 6: Optimized structures of MDMA with different DNA double base pairs. The evaluation of the BSSE was carried out that for MDMA-GC and MDMA-AT were equal to 3.347 and 3.590 kcal ⁄ mol, respectively. Interaction between MDMA and DNA did not happen with only single base pair. Actually, intercalators bind with whole molecule of DNA and total SNA structure is important. In computational methods, at least interaction with a double base pair is recommended (43). So, the intercalation reaction between MDMA and different double base pairs of DNA (A–T ⁄ A–T, A–T ⁄ T–A, A–T ⁄ G–C, A–T ⁄ C–G, C– G ⁄ G–C, C–G ⁄ C–G) were also studied by the PM3 method. Figure 6 is a sample related to this study. The double base pairs of DNA were built by the nucleic acid database of Hyperchem, and their 3D geometry was optimized with PM3 method. Because of the 3D geometries of MDMA and double base pairs of DNA were similar, one of them was shown in Figure 6. Conclusion and Future Directions MDMA is a good electron acceptor with high polarizability. In contrast, AT and GC base pairs are good electron donors. These outcomes are very favorable for aromatic stacking interactions between these two systems. In designing a drug, changes in the structure and addition of specific groups should be to increase values of the main parameters such as polarizability, dipole moment, and interaction energy. With high values of these factors, it can be concluded that the drug design is suitable. Chem Biol Drug Des 2010; 76: 425–432 1. Li N., Ma Y., Yang C., Guo L., Yang X. (2005) Interaction of anticancer drug mitoxantrone with DNA analyzed by electrochemical and spectroscopic methods. Biophys Chem;116:199–205. 2. Durr F.E. (1987) Biologic and Biochemical Effects of Mitoxantrone. Semin Oncol;11:3–19. 3. Rosenberg L.S., Carblin M.J., Krugh T.R. (1986) The antitumor agent mitoxantrone binds cooperatively to DNA: evidence for heterogeneity n DNA conformation. Biochem;25:1002–1008. 4. Birchall L.A., Bailey N.P., Blackledge G.R. (1991) An Overview of Mitozantrone. Br J Clin Pract;45:208–211. 5. Nathanson L. (1984) Mitoxantrone. Cancer Treat Rev;11:289– 293. 6. Faulds D., Balfour J.A., Chrisp P., Langtry H.D. (1991) Mitoxantrone. A Review of Its Pharmacodynamic and Pharmacokinetic Properties, and Therapeutic Potential in the Chemotherapy of Cancer. Drugs;41:400–449. 7. Goodin D.S., Arnason B.G., Coyle P.K., Frohman E.M., Paty D.W., (2003) The use of mitoxantrone (Novantrone) for the treatment of multiple sclerosis: Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology. Neurology;61:1332–1338. 8. Lerman L.S. (1961) Considerations in the interaction of DNA and acridines. J Mol Biol;3:18–30. 9. Wang S., Peng T., Yang C.F., Frohman E.M., Paty D.W. (2003) Electrochemical determination of interaction parameters for DNA and mitoxantrone in an irreversible redox process. J Biophys Chem;104:239–248. 10. Reszka K., Kolodziejczyk P., Hartley J.A., Wilson W.D., Lown J.W. (1998) In Anthracycline and Anthracenedione based Anticancer Agents. Amsterdam: Elsevier Press, pp. 401–405. 11. Bren U., Hodoscek M., Koller J. (2005) Development and validation of empirical force field parameters for netropsin. J Chem Inf Model;45:1546–1552. 12. Dolenc J., Borstnik U., Hodoscek M., Koller J., Janezic D. (2005) An ab initio QM ⁄ MM study of the conformational stability of complexes formed by netropsin and DNA. The importance of van der Waals interactions and hydrogen bonding. J Mol Struct (TEOCHEM);718:77–85. 13. EL-Gogary T.M. (1998) The role of charge transfer complex formation on the overall structure activity relationships of DNA radioprotectants and radiosensitizers. Ph.D. Thesis, Leicester, UK: Mansoura University, Egypt ⁄ De Montfort University. 431 Riahi et al. 14. Chaires J.B. (1998) Drug-DNA interactions. Curr Opin Struct;8:314–320. 15. Riahi S., Moghaddam A.B., Ganjali M.R., Norouzi P. (2007) Determination of the oxidation potentials of pyrogallol and some of its derivatives: theory and experiment. J Theor Comput Chem (JTCC);6:331–340. 16. Riahi S., Moghaddam A.B., Ganjali M.R., Norouzi P. (2007) Theoretical and experimental study of electrical and electrochemical properties of (E)-3-(4, 5-dihydroxy-2-(phenylsulphonyl) phenyl) acrylic acid as a new caffeic acid derivative. J Theor Comput Chem (JTCC);6:255–268. 17. Riahi S., Ganjali M.R., Moghaddam A.B., Norouzi P., Davarani S.S.H. (2008) Structural study of 2-(1-oxo-1 H-inden-3-yl)-2H-indene-1,3-dione by ab initio and DFT calculations, NMR and IR spectroscopy. Spectrochim Acta, Part A;70:94–98. 18. Riahi S., Norouzi P., Moghaddam A.B., Ganjali M.R., Karimipour G.R., Sharghi H. (2007) Theoretical and experimental report on the determination of electrode potentials of dihydroxyanthracene and thioxanthens derivatives. Chem Phys;337:33–38. 19. Riahi S., Moghaddam A.B., Norouzi P., Ganjali M.R. (2007) Density-functional theory studies on electrode potentials and electronic structure of (E)-3-(4,5-dihydroxy-2-tosylphenyl) acrylic acid as a new caffeic acid derivative: experimental and theoretical. J Mol Struct (THEOCHEM);814:131–139. 20. Ganjali M.R., Norouzi P., Faridbod F., Riahi S., Ravanshad J., Tashkhourian J., Salavati-Niasari M., Javaheri M. (2007) Determination of vanadyl ions by a new PVC membrane sensor based on N,N'-bis-(salicylidene)-2,2-dimethylpropane-1,3-diamine. IEEE Sens J;7:544–550. 21. Ganjali M.R., Norouzi P., Mirnaghi F.S., Riahi S., Faridbod F. (2007) Lanthanide recognition: monitoring of praseodymium(III) by a novel praseodymium(III) microsensor based on N'-(Pyridin-2Ylmethylene)Benzohydrazide. IEEE Sens J;7:1138–1144. 22. Riahi S., Ganjali M.R., Norouzi P., Jafari F. (2008) Application of GA-MLR, GA-PLS and the DFT quantum chemical (QM) calculations for the prediction of the selectivity coefficients of a histamine-selective electrode. Sens. Actuators B;132:13–19. 23. Elstner M., Hobza P., Frauenheim T., Suhai S., Kaxiras E. (2001) Hydrogen bonding and stacking interactions of nucleic acid base pairs: a density-functional-theory based treatment. J Chem Phys;114:5149–5155. 24. El-Gogary T.M., Koehler G. (2007) Interaction of psoralens with DNA-bases (I). An ab initio quantum chemical, density functional theory and second-order Miller-Plesset perturbational study. J Mol Struct (THEOCHEM);808:97–109. 25. Frisch M.J., Trucks G.W., Schlegel H.B., Scuseria G.E., Robb M.A., Cheeseman J.R., Zakrzewski V.G. et al. (1998) Gaussian 98, Revision A.7. Pittsburgh, PA: Gaussian Inc. 26. Stewart J.J.P. (1989) Optimization of parameters for semi-empirical methods I. method. J Comp Chem;10:210–222. 27. Stewart J.J.P. (1989) Optimization of parameters for semiempirical methods II. Applications, J Comp Chem;10:221–264. 28. Yang W., Wu Q. (2002) Direct Method for Optimized Effective Potentials in Density-Functional Theory. Phys Rev Lett;89: 143002 ⁄ 1–143002 ⁄ 4. 29. Parr R.G., Yang W. (1995) Density-Functional Theory of the Electronic Structure of Molecules. Annu Rev Phys Chem;46:701–728. 432 30. Schmidt M.W., Baldridge K.K., Boatz J.A., Elbert S.T., Gordon M.S., Jensen J.H., Koseki S., Matsunaga N., Nguyen K.A., Su S.J., Windus T.L., Dupuis M., Montgomery J.A. (1993) General atomic and molecular electronic structure system. J Comput Chem;14:1347–1363. 31. Duijneveldt F.B., Duijneveldt-van de Rijdt J.G.C.M., Lenthe J.H. (1994) State of the Art in Counterpoise Theory. Chem Rev;94:1873–1885. 32. Nieaus T.A., Elstner M., Frauenheim T., Suhai S. (2001) Application of an approximate density-functional method to sulfur containing compounds. J Mol Struct (THEOCHEM);541:185–194. 33. Zhou H.Y., Tajkhorshid E., Frauenheim T., Suhai S., Elstner M. (2002) Performance of the AM1, PM3, and SCC-DFTB methods in the study of conjugated Schiff base molecules. Chem Phys;277:91–103. 34. Hobza P., Zahradnik R. (1988) Intermolecular Complexes. Amsterdam: Elsevier. 35. Bren U., Martinek V., Florian J. (2006) Free energy simulations of uncatalyzed DNA replication fidelity: structure and stability of T center dot G and dTTP center dot G terminal DNA mismatches flanked by a single dangling nucleotide. J Phys Chem B;110:10557–10566. 36. Mierts S., Scrocco E., Tomasi J. (1981) Electrostatic interaction of a solute with a continuum. A direct utilization of AB initio molecular potentials for the prevision of solvent effects. Chem Phys;55:117–129. 37. Florian J., Warshel A. (1997) Langevin dipoles model for ab initio calculations of chemical processes in solution: parametrization and application to hydration free energies of neutral and ionic solutes and conformational analysis in aqueous solution. J Phys Chem B;101:5583–5595. 38. Bren U., Martinek V., Florian J. (2006) Decomposition of the solvation free energies of deoxyribonucleoside triphosphates using the free energy perturbation method. J Phys Chem B;110:12782–12788. 39. Bren U., Zupan M., Guengerich F.P., Mavri J. (2006) Chemical reactivity as a tool to study carcinogenicity: reaction between chloroethylene oxide and guanine. J Org Chem;71:4078–4084. 40. Bren U., Guengerich F.P., Mavri J. (2007) Guanine alkylation by the potent carcinogen aflatoxin B-1: quantum chemical calculations. Chem Res Toxicol;20:1134–1140. 41. Frisch M.J., Del Bene J.E., Binkley J.S., Schaefer H.F. (1986) Extensive Theoretical-Studies of the Hydrogen-Bonded Complexes (H2O)2, (H2O)2H+, (HF)2, (HF)2H+, F2H-, AND (NH3)2. J Chem Phys;84:2279–2289. 42. Schwenke D.W., Truhlar D.G. (1985) Systematic study of basis set superposition errors in the calculated interaction energy of 2 HF Molecules. J Chem Phys;82:2418–2426. 43. Miri R., Javidnia K., Hemmateenejad B., Azarpira A., Amirghofran Z. (2004) Synthesis, cytotoxicity, QSAR, and intercalation study of new diindenopyridine derivatives. Bioorg Med Chem;12:2529–2536. Note a [Online] available: http://www2.netdoctor.co.uk/medicines/100001882.html. Chem Biol Drug Des 2010; 76: 425–432