Characterization of Nucleobaseâ Amino Acid Stacking Interactions

19652

J. Phys. Chem. B 2006, 110, 19652-19663

Characterization of Nucleobase-Amino Acid Stacking Interactions Utilized by a DNA Repair Enzyme Lesley R. Rutledge,† Lachlan S. Campbell-Verduyn,† Ken C. Hunter,† and Stacey D. Wetmore*,‡ Department of Chemistry, Mount Allison UniVersity, 63C York Street, SackVille, New Brunswick, Canada E4L 1G8, and Department of Chemistry and Biochemistry, UniVersity of Lethbridge, 4401 UniVersity DriVe, Lethbridge, Alberta, Canada T1K 3M4 ReceiVed: March 29, 2006; In Final Form: July 31, 2006

The present work characterizes the gas-phase stacking interactions between four aromatic amino acid residues (histidine, phenylalanine, tyrosine, and tryptophan) and adenine or 3-methyladenine due to the proposed utilization of these interactions by enzymes that repair DNA alkylation damage. The MP2 potential energy surfaces of the stacked dimers are considered as a function of four variables (vertical displacement, angle of rotation, horizontal displacement, and tilt angle) using a variety of basis sets. It is found that the maximum stacking interaction energy decreases with the amino acid according to TRP > TYR ≈ HIS > PHE for both nucleobases. However, the magnitude of the stacking interaction significantly increases upon alkylation (by 50-115%). Comparison of the stacking energies calculated using our surface scans to those estimated from experimental crystal structures indicates that the stacking interactions within the active site of 3-methyladenine DNA glycosylase can account for 65-75% of the maximum possible stacking interaction between the relevant molecules. The decrease in stacking in the crystal structure arises due to significant differences in the relative orientations of the nucleobase and amino acid. Nevertheless, alkylation is found to significantly increase the stacking energy when the crystal structure geometries are considered. Our calculations provide computational support for suggestions that alkylation enhances the stacking interactions within the active site of DNA repair enzymes, and they give a measure of the magnitude of this enhancement. Our results suggest that alkylation likely plays a more important role in substrate identification and removal than the nature of the aromatic amino acid that interacts with the substrate via stacking interactions.

Introduction Nature has a variety of natural repair mechanisms to combat the effects of damage caused by external forces (i.e., X-rays, UV light) and during normal processes (i.e., DNA replication). Perhaps the most important mechanism, base excision repair (BER), involves multiple enzymes.1 The first of these enzymes, the DNA glycosylases, remove damaged bases by cleaving the glycosidic bond of the nucleotides.2 Subsequently, other enzymes remove the base-free sugar moiety (AP endonucleases and AP lyases), add the correct nucleotide (DNA polymerases), and reseal the backbone (DNA ligases).3 Although oxidation and deamination are abundant forms of DNA damage,1,2 we are particularly interested in DNA alkylation, which occurs upon exposure to external alkylating agents or during side reactions in normal metabolic function.1,2,4 The nitrogen and oxygen positions of the DNA nucleobases are the primary targets for alkylation, and the effects of the damage depend on the mutation formed. For example, O6-alkylguanine and O4-alkylthymine are mutagenic since they form mismatched base pairs with thymine and guanine, respectively. 3-Methyladenine is arguably one of the most detrimental forms of damage since the N3-methyl group protrudes into the minor groove of the DNA double helix and thereby stops replication.5 Unlike other damaged nucleobases, cationic alkylated nucleobases are very reactive and undergo spontaneous hydrolysis * Corresponding author. E-mail: [email protected]. † Mount Allison University. ‡ University of Lethbridge.

more rapidly than their neutral counterparts.6 Therefore, the mechanisms-of-action of DNA glycosylases that remove alkylated nucleobases are expected to be very different from those of glycosylases that remove neutral pyrimidines (i.e., UDG) or purines (i.e., FPG, MutY).2 More specifically, although enzymes such as UDG and FPG rely on substrate-enzyme hydrogenbonding interactions, no groups capable of forming strong hydrogen bonds with the substrate are typically found in the active sites of enzymes that remove 3-methyladenine and various other alkylated purines in bacteria and humans, respectively.2c,7 Instead, the active sites of these enzymes are lined with aromatic residues (tryptophan, tyrosine, histidine, phenylalanine), and therefore aromatic stacking interactions have been proposed to be responsible for substrate recognition and stabilization. Indeed, recent crystal structures of DNA glycosylases responsible for repairing alkylation damage cocrystallized with modified nucleobases show the bases held in the active site by aromatic amino acid residues.8-19 It has been proposed that protonation of purines enhances π-orbital overlap between the base and aromatic amino acid residues and thereby creates a more favorable stacking interaction with the methylated base.11 However, the magnitude of these interactions have not been well characterized. Furthermore, since crystal structures with cationic nucleotides bound to the enzyme are difficult to obtain due to the high reactivity of the substrates, the nature and importance of active site stacking interactions are presently unknown. Computational studies can be used to characterize the interactions between natural or

10.1021/jp061939v CCC: $33.50 © 2006 American Chemical Society Published on Web 09/12/2006

Nucleobase-Amino Acid Stacking Interactions

J. Phys. Chem. B, Vol. 110, No. 39, 2006 19653 superposition error (BSSE) corrections, and therefore the stacking energy (∆E) is calculated as follows:

∆E ) Edimer - Enucleobase - Eamino acid + BSSE

Figure 1. Structure of amino acids (histidine (HIS), phenylalanine (PHE), tyrosine (TYR), and tryptophan (TRP)) and nucleobases (adenine (A) and 3-methyladenine (3MeA)) considered in the present study.

damaged nucleobases and the aromatic amino acids, and thereby they may reveal the importance of these interactions for substrate identification and removal. Indeed, computational chemistry has provided useful information about the magnitude of stacking interactions between a variety of molecules (see, for example, refs 12-19). In the present study, the stacking interactions between four aromatic amino acid residues (histidine, phenylalanine, tyrosine, and tryptophan) and adenine or 3-methyladenine are investigated (Figure 1). This selection of molecules will allow us to separately consider the effects of the amino acid and nucleobase alkylation on the magnitude of stacking interactions. This information may help us understand how alkylated nucleobases are recognized and removed by DNA repair enzymes. Additionally, information about the magnitude of stacking interactions between DNA nucleobases and amino acid residues will be obtained, which has more general implications due to the use of these interactions in a variety of biological processes. Computational Details Stacking interactions have been shown to be very sensitive to the level of theory and basis set. Nevertheless, many computational studies on these interactions have appeared in the literature.12-17 Furthermore, Hobza and Sponer have carefully outlined suitable computational approaches to study stacking interactions between DNA nucleobases.12 We used a similar approach in the present study, which is outlined below. All calculations were performed with GAUSSIAN 03.20 The nucleobases were modeled by replacing the sugarphosphate backbone with a hydrogen atom. Similarly, the protein backbone of the amino acids was replaced by a hydrogen atom. Specifically, histidine (HIS) was modeled as imidazole, phenylalanine (PHE) as benzene, tyrosine (TYR) as phenol, and tryptophan (TRP) as indole. Optimizations on fixed planar (Cs symmetry) nucleobases and amino acids were performed at the MP2/6-31G(d) level of theory. Attempts to fully optimize stacked geometries generally leads to hydrogen-bonded arrangements, which is at least in part due to the absence of basis set superposition error (BSSE) corrections in the optimization routine.12,14d Furthermore, distortions in the monomer geometries are often seen upon attempts to fully optimize stacked dimers.21 Therefore, the conformational space of stacked systems was investigated by performing a series of single-point calculations using MP2 and the 6-31G*(0.25) basis set, which replaces the standard d-exponent for second-row atoms (0.8) with 0.25. The addition of diffuse-polarization functions has been shown to yield more accurate values of the correlation contribution to stacking at a reasonable computational cost.12-15 All reported stacking energies include basis set

To scan the gas-phase potential energy surface of stacked dimers, amino acids and nucleobases were stacked with respect to their centers of mass. Two relative orientations of the molecular planes were considered, where the second is denoted as flipped using a subscript f. The initial orientations between adenine and the amino acids are shown in Figure 2a, and the initial orientations for 3MeA dimers were defined similarly. Four variables were investigated in the surface scans (Figure 3). First, the optimum vertical separation (R1) was determined and fixed for remaining calculations. Subsequently, the angle of rotation (R) was considered by rotating one molecule by 30° in the righthand sense around an axis that passes through the centers of mass and perpendicular to the molecular planes. Using optimum values for R1 and R, the horizontal displacement (R2) was considered in eight directions (defined as 0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°) and four displacement distances (0.5, 1.0, 1.5, and 2.0 Å). Finally, the tilt angle (θ) was varied by (10° along two axes from the optimum stacked orientations determined from the previous scans. Although MP2/6-31G*(0.25) has been shown to produce the correct trends in stacking energies and recover approximately 80% of the correct stacking energy for natural nucleobase dimers,14 more accurate calculations can be performed. Indeed, previous work in the literature has suggested that basis set extrapolation is necessary to evaluate stacking interactions in the natural DNA nucleobases.15,16f In the present work, we consider the MP2 basis set limit using different extrapolation schemes and the aug-cc-pVDZ and aug-cc-pVTZ basis sets. Although computationally expensive, we used a triple-ζ basis set for the extrapolation since this was previously determined to be required to obtain counterpoise values within 1 kcal mol-1 of those obtained from the complete basis set limit.14d Further details of the extrapolation methods will be provided in the Results and Discussion. Although it has been suggested that it is imperative to go to the CCSD(T) level when considering the stacked benzene dimer,17d,f MP2 has been found to predict the correct trends in the stacking energy of substituted benzene dimers.17e Furthermore, although the use of CCSD(T) has been emphasized to be important when comparing the relative magnitude of hydrogenbonding and stacking interactions of the natural nucleobases, 15b MP2 has been found to recover most of the CCSD(T) stacking energy.14d,15 Since we are primarily interested in the trends in the data, we do not further consider the level of theory in the present work. We note that previous work has found that the RI-MP2 method accurately reproduces MP2 stacking energies between the natural nucleobases while saving up to 1 order of magnitude in computational time.14c,15b-c,16f Unfortunately, this promising method is not available in the computational package utilized for the present work, and therefore full MP2 calculations were performed. Results and Discussion (I) Stacking Interactions between Adenine and Aromatic Amino Acids. We begin our discussion of the stacking interactions utilized by DNA glycosylases that remove alkylated nucleobases by considering the potential energy surface of stacked dimers between the natural base adenine and the four aromatic amino acid residues (Figure 1), where Figure 2a shows

19654 J. Phys. Chem. B, Vol. 110, No. 39, 2006

Rutledge et al.

Figure 2. The angle of rotation (R) between amino acids and (a) adenine with R ) 0, (b) adenine that yields the maximum stacking interaction, or (c) 3MeA that yields the maximum stacking interaction (see Table 1).

the initial relative orientations of the monomers. Figure 4 displays the change in the interaction energy as a function of the vertical separation (R1, Figure 3). The shape of the graphs is in agreement with previous studies.12,13,17 Specifically, the interaction energy sharply decreases in magnitude at short interdimer distances due to increased short-range repulsion, and it decreases in magnitude more slowly at longer distances due to decreased dispersion-attraction forces. Furthermore, the interaction energies are not largely dependent upon vertical separation. Specifically, the maximum interaction energy typi-

cally varies by less than 3 kJ mol-1 over a vertical separation range of 0.4 Å centered on the energy minimum. The optimum vertical separation between the amino acids and adenine are summarized in Table 1. In general, the variation in R1 is related to the size of the amino acid residue, where the smallest distance is found for HIS (3.3 Å) and the largest for TRP (3.5-3.6 Å). The trend in the vertical separation with respect to the amino acid agrees with that expected based on the relative surface areas and polarizabilities.22 Consideration of the flipped orientations of the amino acid residues relative


J. Phys. Chem. B, Vol. 110, No. 39, 2006 19655

Figure 3. The definition of four variables (vertical separation (R1), angle of rotation (R), horizontal displacement (R2), tilt angle (θ)) considered in potential energy surface scans of stacked nucleobaseamino acid dimers.

Figure 5. Interaction energy between HIS (square), PHE (diamond), TYR (triangle), or TRP (circle) and adenine, as well as the flipped orientations (open symbols), as a function of the angle of rotation (R) with the best R1 (see Table 1) and R2 ) θ ) 0.

the dipole moment vectors are displayed in Figure 6a.23 In almost all instances, the orientation that yields the strongest stacking interaction energy (Figure 2b) best aligns the dipole moment vectors of the amino acid and adenine in opposite directions (Figure 6b). An exception is the A:HISf complex, where dipole alignment leads to unfavorable steric interactions between ring nitrogens, which results in a slight change in the preferred angle of rotation.24 The dependence of R on the dipole vectors implies that electrostatic interactions arising from dipole-dipole interactions between the electric fields of the molecules determine the preferred orientation with respect to R. This phenomenon has been previously noted in the literature for stacked DNA nucleobases.12 Using the optimum angle of rotation, the dependence of the stacking energy on the horizontal displacement was considered as a function of the displacement distance and direction as defined in Figure 7. It has been previously noted that the dependence of the stacking energy on horizontal displacement is due to quadrupole-quadrupole electrostatic interactions.12 We found that the (absolute) magnitude of the interaction energies generally increase by less than 2 kJ mol-1 as the amino acid is shifted horizontally relative to adenine from R2 ) 0 to the most favorable R2 value (see Figure 8 and Table 1). A larger change (4.3 kJ mol-1) is found for the (flipped) TRP:A pair. The R2 dependence on the displacement direction is very similar for all distances considered and thus, in all cases, stabilization of the dimers occurs for short displacement distances (0.5-1.5 Å, see Table 1). Larger displacements (1.5-2.0 Å) decrease the (absolute) magnitude of the stacking energy by up to 17 kJ mol-1. In summary, the optimum geometry with respect to R2

Figure 4. Interaction energy between HIS (square), PHE (diamond), TYR (triangle), or TRP (circle) and adenine, as well as the flipped orientations (open symbols), as a function of vertical separation (R1) with R, R2, and θ ) 0.

to the natural nucleobases does not significantly affect the preferred vertical separation (Figure 4), although there are slight changes in the binding strength. The optimum vertical separations were used for the remainder of the calculations. The dependence of the stacking interaction energy on the angle of rotation (R) is shown in Figure 5. The stacking interaction energy has a larger dependence on R compared with the vertical separation (R1). HIS consistently has the largest dependence on R, which varies by 10 kJ mol-1 throughout the scan for both orientations. Tryptophan has the next largest dependence (7.5-9.6 kJ mol-1), which is closely followed by tyrosine (6.7-9.5 kJ mol-1). Although R ) 0 and 30° yield different structures for the adenine-phenylalanine (modeled by benzene) dimer, the corresponding stacking energy does not show a strong twist dependence. The angles of rotation between the amino acids and adenine that yield the largest stacking energy are displayed in Figure 2b. We find that there is a direct correlation between the preferred R and the dipole moments of the monomers, where

TABLE 1: Summary of Maximum MP2 Stacking Interaction (kJ mol-1) between Amino Acids and Adenine or 3-Methyladenine as Determined from Potential Energy Surface Scans That Sequentially Vary R1 (Å), r (deg), R2 (Displacement (Å) and Direction (deg)), and θ (deg)a,b adenine HIS HISf PHE TYR TYRf TRP TRPf

3-methyladenine

R1

∆Ec

R

∆Ed

R2

∆Ee

θ

∆E f

R1

∆Ec

R

∆Ed

R2

∆Ee

θ

∆E f

3.3 3.3 3.4 3.4 3.4 3.6 3.5

-19.7 -23.1 -24.3 -25.6 -26.1 -20.1 -25.5

90 330 0 180 330 90 240

-28.0 -26.8 -24.3 -28.4 -27.7 -29.7 -30.5

1.5, 225 0.5, 315 0, 0 0.5, 180 0.5, 0 1.0, 180 1.5, 135

-28.8 -27.4 -24.3 -30.4 -27.8 -31.7 -34.8

0 0 0 0 0 10 10

-28.8 -27.4 -24.3 -31.6 -27.8 -32.7 -37.1

3.3 3.2 3.3 3.3 3.3 3.5 3.4

-29.0 -52.8 -46.7 -52.9 -51.4 -51.4 -62.1

150 0 30 240 330 270 270

-51.3 -52.8 -47.2 -53.5 -52.2 -67.5 -68.6

0, 0 0, 0 0.5, 315 0.5, 0 0.5, 315 0.5, 180 0.5, 315

-51.3 -52.8 -48.4 -54.9 -52.8 -68.3 -69.6

10 10 0 0 0 0 0

-57.1 -58.0 -48.4 -54.9 -52.8 -68.3 -69.6

a Calculated using the 6-31G*(0.25) basis set. See the Computational Details section for full details of the potential energy surface scans. b See Figure 3 for definitions of the variables. c ∆E determined by varying R1 while maintaining R, R2, and θ ) 0. d ∆E determined by varying R while maintaining R2 and θ ) 0, and the best value of R1. e ∆E determined by varying R2 while maintaining θ ) 0, and the best values for R1 and R. f ∆E determined by varying θ while maintaining the best values for R , R, and R . 1 2


Rutledge et al.

Figure 6. (a) Dipole moment vectors in adenine and amino acids monomers. (b) Overlaid monomer geometries with dipole moment vectors aligned in opposing directions.23

is very closely approximated by center-of-mass stacking geometries, which is in agreement with the results for stacked DNA nucleobases.12 This finding validates our choice for the initial orientation. The last variable considered in the present study is the tilt angle. As discussed in the Computational Details, starting from the dimer geometry with the best R, R1, and R2, the amino acids were tilted by 10° with respect to the base in two directions along two axes as outlined in Figure 9. Tilting the amino acid with respect to the base by 10° generally decreases the stacking energy. However, for A:TRP complexes, a 10° tilt angle yields very slight (less than 2.3 kJ mol-1) stabilization of the dimers (Table 1). The largest stacking interaction energies calculated between adenine and the amino acids as each variable is sequentially considered are summarized in Table 1. The small changes in the interaction energy due to changes in the horizontal displacement or tilt angle, as well as the much larger changes due to the rotational angle for each amino acid can be clearly seen. This trend is in agreement with that previously reported for stacked dimers of the DNA nucleobases.12 We find that the maximum stacking energy between adenine and aromatic amino acid residues ranges between 24 and 37 kJ mol-1 and increases as PHE < HIS ≈ TYR < TRP. This trend arises due to a balance of the importance of the surface area and magnitude of the dipole moment of the amino acids. (II) Stacking Interactions between 3-Methyladenine and Aromatic Amino Acids. To evaluate the effects of methylation on stacking interactions with amino acids, we have characterized the stacking interactions involving (cationic) 3-methyladenine, and the results are summarized in Table 1. As discussed for

adenine, the optimum vertical displacement between the amino acids and 3-methyladenine increases with the size of the amino acid. However, R1 is typically 0.1 Å smaller for 3-methyladenine complexes compared with the corresponding adenine dimers. This suggests that the attraction of the amino acids to 3-methyladenine is stronger than to adenine, which is also reflected in a significant increase in the interaction energy upon methylation. The preferred angle of rotation between the amino acids and nucleobases is very similar for 3MeA and adenine dimers (Figures 2 and 10). Slight changes in the preferred twist angle upon methylation reduce unfavorable steric interactions with the N3 methyl substituent.25 The most notable difference in the orientations that lead to the maximum stacking energy is for the TRP complexes. However, Figures 5 and 10 indicate that there are two minima in the rotational scan for these dimers (∆E ≈ 1 and 5 kJ mol-1 for A and 3MeA, respectively), where each minimum involves a nearly perpendicular arrangement of the rings. Another notable difference is the greater variation in the stacking energy with respect to the angle of rotation for 3-methyladenine (Figure 10) compared with adenine (Figure 5). For example, the range in the interaction energies for HIS with 3-methyladenine is 23 kJ mol-1, but only 10 kJ mol-1 for adenine. The horizontal displacement (R2) affects the stacking energy of 3MeA dimers even less than discussed for adenine, where the optimum displacement distance is 0.5 Å and the corresponding stabilization provided is less than 1.5 kJ mol-1 (Table 1). However, a larger dependence of the stacking energy on the (10°) tilt angle is observed for 3MeA compared with A for HIS dimers, where the stacking energy increases by approximately 6 kJ mol-1. This increased tilt aligns the histidine



Figure 7. Definition of the horizontal displacement (R2) directions with respect to the amino acid in stacked adenine-amino acid dimers.

nitrogen with the cationic nucleobases, which may lead to further stabilization due to electron donation from histidine to the base cation. Due to this observed increase in stacking, the tilt dependence was further examined by considering tilt angles of 5, 15, and 20° for adenine and 3MeA histidine complexes. However, for both nucleobases, the strongest stacking interaction occurs with θ equal to 0 or 10°, and therefore no further angles were considered. The stacking interaction energy for 3-methyladenine increases as PHE < TYR < HIS < TRP. If the tilt angle is not considered, since this affects HIS more significantly than any other amino acid, the trend (PHE < HIS ≈ TYR < TRP) is the same as noted for adenine. Therefore, the major difference between the adenine and 3-methyladenine stacking energies is the magnitude of the interaction. Specifically, the stacking interaction in 3MeA is approximately 22-25 kJ mol-1 larger for HIS, PHE, and TYR dimers, and 34-37 kJ mol-1 larger for TRP. These energy differences represent a 78 (HIS)-115 (TRP) percent increase in the stacking energy of adenine upon N3 methylation. Previous work suggests that including a methyl group as a deoxyribose model rather than a hydrogen atom leads to only slight increases in the stacking energy.15b Methyl substitutent effects on benzene dimers have also been found to be small.17d Therefore, the large increase observed in the present study upon methylation is likely almost solely due to the introduction of charge. An interesting study has considered histidine stacked with phenylalanine, tyrosine, tryptophan, and adenine, and it also found significant stabilization of the stacked dimers upon protonation of histidine.18d To better understand the reason for the increase in the stacking energy upon methylation, Table 2 summarizes the HartreeFock (∆EHF) and correlation contribution (∆Ecorr) to the total

Figure 8. Interaction energy between (a) HIS, (b) PHE, (c) TYR, or (d) TRP and adenine as a function of horizontal displacement (R2) by 0.5 (square), 1.0 (diamond), 1.5 (triangle), and 2.0 (circle) Å from structures with the best R1 and R (see Table 1) and θ ) 0, where the flipped orientations are indicated by dotted lines and the unshifted stacking energies by the horizontal lines.


Rutledge et al.

Figure 9. Definition of the tilt (θ) axes with respect to the amino acid in stacked adenine-amino acid dimers.

Figure 10. Interaction energy between HIS (square), PHE (diamond), TYR (triangle), or TRP (circle) and 3-methyladenine, as well as the flipped orientations (open symbols), as a function of the angle of rotation (R) with best R1 (see Table 1) and R2 ) θ ) 0.

MP2 interaction energies for adenine and 3-methyladenine dimers with the optimum R1, R, and R2.26 There is a significant difference in the ∆EHF contributions, which destabilize adenine dimers (by up to 24 kJ mol-1) but stabilize 3-methyladenine dimers (by up to 15 kJ mol-1). This is not surprising since the HF contribution arises mainly due to electrostatic interactions, which are expected to be much larger in the charged dimers. Furthermore, the most stabilizing ∆EHF contribution for 3MeA dimers arises for the amino acids with the largest dipole moments (TRP and HIS). However, the differences in ∆EHF cannot account for the entire difference between the total stacking energies of adenine and 3MeA complexes. In particular, there are also significant differences (4-18 kJ mol-1) in the correlation contribution to the stacking energy of the neutral and charged dimers, which represent 10-35% increases in stacking upon methylation of adenine. These differences may arise at least in part due to differences in the (R) angle dependence of adenine and 3-methyladenine interaction energies (Figure 2), which arise in ∆Ecorr due to dispersion interactions. Interestingly, previous work has shown that the correlation contribution is roughly the same when histidine is neutral or protonated in complexes with other amino acids or adenine.18d In summary, we find that the dependence of the stacking energy of 3MeA-amino acid dimers on the vertical separation,

angle of rotation, horizontal displacement, and tilt angle is similar to that of the corresponding adenine dimers. However, MP2/6-31G*(0.25) predicts that the stacking interaction energies between adenine and the amino acids doubles upon N3 methylation of the nucleobase. Indeed, the increase in stacking upon alkylation (22-37 kJ mol-1) is significantly larger than the variation in the stacking energies between adenine and the four amino acids (13 kJ mol-1). This suggests that the role of alkylation in substrate identification and removal may be more important than the nature of the aromatic amino acid residue that stacks with the substrate in the active site. This hypothesis is supported by the variety of aromatic amino acids found stacked with substrates in the active sites of 3-methyladenine DNA glycosylases.8-10 (III) Comparison of the Stacking Interactions of Adenine and 3MeA: The Complete Basis Set Limit. Previous work has shown that although the Hartree-Fock contribution to the stacking energy converges for small (double-ζ) basis sets, the convergence of the correlation contribution with respect to the basis set is relatively slow.14,15 Indeed, although MP2 in combination with small (double-ζ) basis sets generally yields the correct relative stacking energies due to favorable cancellation of errors, expansion of the basis set leads to much larger stacking energies.17 In attempts to understand the differences in these trends for neutral and charged dimers, we consider the extrapolation of our MP2 stacking energies to the complete basis set (CBS) limit using Dunning’s aug-cc-pVDZ and aug-ccpVTZ basis sets and several extrapolation schemes. Before discussing the results from our extrapolations, we consider the stacking energies calculated using Dunning’s expanded basis sets (Table 2), where it should be noted that our current resources prohibit aug-cc-pVTZ calculations on TRP complexes. A 5-8 kJ mol-1 increase in the stacking energy of adenine dimers is found upon implementation of the aug-ccpVDZ basis set compared with 6-31G*(0.25). This is a more significant difference than previously reported for stacked natural DNA nucleobases.14 A smaller increase (1-2.5 kJ mol-1) is noted upon further basis set expansion to aug-cc-pVTZ. In comparison, the stacking energy of 3MeA dimers increases by 3-4.5 (5-7.5) kJ mol-1 upon consideration of aug-cc-pVDZ (aug-cc-pVTZ). The reason for the smaller basis set dependence of the 3MeA dimer stacking energies becomes apparent upon consideration of the Hartree-Fock and correlation contributions (Table 2). Specifically, for adenine complexes, the ∆EHF contributions are similar for all basis sets, while the ∆Ecorr contributions calculated with Dunning’s basis sets are more stabilizing (by 5-9 kJ mol-1). However, for 3MeA dimers, the ∆EHF contribution calculated with Dunning’s basis sets are less stabilizing compared with 6-31G*(0.25) values. This counteracts the increase

TABLE 2: Hartree-Fock (∆EHF) and Electron Correlation (∆Ecorr) Contributions to the Total MP2 Stacking Energy (kJ mol-1) for Adenine and 3-Methyladenine Dimers Using a Variety of Basis Setsa adenine 6-31G*(0.25)

3-methyladenine

aug-cc-pVDZ

aug-cc-pVTZ

base

∆EHF ∆Ecorr ∆Etotal ∆EHF ∆Ecorr ∆Etotal ∆EHF ∆Ecorr ∆Etotal

HIS HISf PHE TYR TYRf TRP TRPf

8.4 13.9 23.8 18.3 21.4 18.0 9.8

a

-37.2 -41.4 -48.2 -48.6 -49.2 -49.7 -44.5

-28.8 -27.4 -24.4 -30.4 -27.8 -31.7 -34.8

7.4 13.1 23.1 17.6 20.7 16.8 8.5

-42.1 -46.9 -54.7 -55.3 -55.8 -56.3 -50.7

-34.6 -33.8 -31.6 -37.7 -35.1 -39.5 -42.1

7.3 12.9 22.9 17.3 20.4

-43.8 -48.9 -56.6 -57.1 -57.8

-36.5 -35.9 -33.7 -39.8 -37.4

6-31G*(0.25) ∆EHF

∆Ecorr ∆Etotal

-7.5 -4.6 8.0 4.1 6.5 -14.9 -8.5

-43.7 -48.2 -56.4 -59.0 -59.3 -53.5 -61.0

augcc-pVDZ ∆EHF

augcc-pVTZ

∆Ecorr ∆Etotal ∆EHF ∆Ecorr ∆Etotal

-51.3 -4.7 -49.2 -52.8 -1.6 -54.1 -48.4 11.0 -63.6 -54.9 7.0 -66.3 -52.8 9.1 -65.9 -68.3 -11.7 -60.4 -69.6 -4.7 -68.8

-53.9 -55.8 -52.7 -59.3 -56.8 -72.1 -73.5

-4.8 -1.8 10.7 6.9 8.9

-51.3 -56.8 -66.7 -69.4 -69.2

-56.1 -58.5 -56.0 -62.5 -60.3

The stacking energies were calculated for dimer geometries with R1, R, and R2 that yield the maximum stacking interaction (see Table 1).



TABLE 3: MP2 Stacking Interaction (kJ mol-1) between Adenine or 3-Methyladenine and the Four Amino Acids Calculated with a Variety of Basis Sets and Extrapolation Methodsa adenine

3-methyladenine

6-31G*(0.25) aug-cc-pVDZ aug-cc-pVTZ HIS HISf PHE TYR TYRf TRP TRPf a

-28.8 -27.4 -24.3 -30.4 -27.8 -31.7 -34.8

-34.6 -33.8 -31.6 -37.7 -35.1 -39.5 -42.1

-36.5 -35.9 -33.7 -39.7 -37.4

1/N -36.6 -36.3 -29.2 -38.7 -36.5

Truhlar Helgaker 6-31G*(0.25) aug-cc-pVDZ aug-cc-pVTZ -37.7 -37.3 -35.1 -41.2 -38.9

-37.3 -36.8 -34.6 -40.6 -38.3

-51.3 -52.8 -48.4 -54.9 -52.8 -68.3 -69.6

-53.9 -55.8 -52.7 -59.3 -56.8 -72.1 -73.5

-56.1 -58.5 -56.0 -62.5 -60.3

1/N -58.0 -60.9 -56.6 -64.9 -63.0

Truhlar Helgaker -57.6 -60.4 -58.2 -64.7 -62.7

-57.0 -59.7 -57.4 -63.8 -61.8

The stacking energies were calculated for dimer geometries with R1, R, and R2 that yield the maximum stacking interaction (see Table 1).

in stabilization provided by ∆Ecorr, and thus leads to smaller differences in the total stacking interaction among basis sets. As mentioned, a number of extrapolation schemes were considered in the present work, and the results are summarized in Table 3. First, the extrapolation of the energy as 1/N, where N is the number of basis functions, was investigated. Second, two more sophisticated extrapolation schemes were implemented. The extrapolation scheme by Helgaker and co-workers27 uses the following equations

EXHF ) ECBSHF + A e-R X and

EXcorr ) ECBScorr + BX-3 while the Truhlar28 extrapolation scheme uses

EXHF ) ECBSHF + AX-R and

EXcorr ) ECBScorr + BX-β In both sets of equations, EX is the energy calculated using the double- (X ) 2) or triple- (X ) 3) ζ basis set, and ECBS is the energy in the complete basis set limit. R and β are parameters defined in the original papers. It should be noted that Truhlar’s exponents were optimized for the nonaugmented forms of Dunning’s basis sets. Extrapolations were applied to the monomer and dimer energies, as well as the basis set superposition error corrections. These extrapolation methods and basis sets have been previously used successfully to study stacked and hydrogen-bonded dimers of the natural nucleobases.15 Extrapolation to the CBS limit using the 1/N extrapolation scheme generally changes the aug-cc-pVTZ stacking energy of adenine dimers by less than 1 kJ mol-1. The exception is the PHE dimer, where a 5 kJ mol-1 decrease is found. The Helgaker and Truhlar extrapolation schemes yield nearly identical results for the CBS limit, and they increase the aug-cc-pVTZ results by only 1-1.5 kJ mol-1. In comparison to 6-31G*(0.25), the 1/N extrapolation scheme leads to a 19-32% increase in the stacking energy, while a slightly larger increase (29-44%) is seen for both Helgaker and Truhlar. However, the increases in the stacking energy upon basis set expansion are smaller for 3-methyladenine dimers, where extrapolation to the complete basis set limit increases the stacking energy by on 10-17%. Due to the differences in the dependence of the MP2 stacking energy on the basis set for 3-methyladenine dimers compared with adenine dimers, the enhancement in the stacking interactions upon methylation of adenine previously discussed for 6-31G*(0.25) (22-25 kJ mol-1 or 78-115%) decreases upon consideration of the CBS limit (19-24 kJ mol-1 or 50-65%).

Figure 11. Structure of modified nucleobases (hypoxanthine (HYP), 1-N6-ethenoadenine (A), and 3,9-dimethyladenine (3,9MeA)) considered in the present work.

A larger enhancement in stacking is seen for the adeninetryptophan complexes upon methylation when expansion to the aug-cc-pVDZ basis set is considered (75-80% (30-35 kJ mol-1) increase). This larger enhancement upon methylation for the TRP:A dimers could arise due to the increased polarizability of tryptophan, as well as better electron donating abilities due to increased surface area and less negative HOMO energy. In summary, we find that although MP2/6-31G*(0.25) predicts that the stacking doubles upon methylation, the CBS limit indicates that adenine stacking increases by approximately 50-75%. Nevertheless, both 6-31G*(0.25) and the CBS limit predict the same trends. It is cautioned, however, that prediction of the same trends for our systems might be fortuitous. Finally, it should be noted that the significant increases observed in the gas phase upon methylation of adenine may be smaller within the active site of DNA repair enzymes. Indeed, previous studies have noted a decrease in the effect of protonation of histidine in stacked complexes with benzene upon consideration of solvent effects.18d Future work will address this issue for amino acids stacked with natural and damaged nucleobases. (IV) Stacking Interactions between Other Nucleobases and Aromatic Amino Acids. Enzymes that repair DNA alkylation damage have been shown to remove many different damaged nucleobases.29 As discussed in the Introduction, crystal structures for DNA glycosylases that remove alkylated nucleobases have been obtained with several damaged bases (hypoxanthine (HYP), 1-N6-ethenoadenine (A), and 3,9-dimethyladenine (3,9MeA)) bound at the active site,8-10 where hypoxanthine is formed upon deamination of adenine30 and A is formed during reactions with 1-halooxiranes.31 These experimentally determined structures will allow us to consider the differences between stacking interactions that occur within the active sites of DNA repair enzymes and those calculated through our potential energy surface scans. The use of crystal structures has enhanced the understanding of stacking interactions within crystals of DNA nucleobases and the DNA double helix.16 We performed scans similar to those discussed for A and 3MeA that consider R1, R, and R2 (0.5 and 1.0 Å shifts) for neutral HYP and A, as well as charged 3,9MeA (Figure 11),32 and the results are summarized in Table 4. The optimum vertical separation and small change in stacking energy upon consid-


Rutledge et al.

Figure 12. Interactions between amino acids and modified nucleobases (HYP, A, 3,9MeA) in the active sites of (a) AlkA,8 (b) MagIII,9 and (c) AAG.10

TABLE 4: Summary of Maximum MP2 Stacking Interactions (kJ mol-1) between the Amino Acids and Hypoxanthine, 1-N6-Ethenoadenine, or 3,9-Dimethyladenine as a Function of R1 (Å), r (deg), and R2 (Displacement (Å) and Direction (deg))a,b hypoxanthine HIS HISf PHE TYR TYRf TRP TRPf a

1-N6-ethenoadenine

3,9-dimethyladenine

R1

∆E

R

∆E

R2

∆E

R1

∆E

R

∆E

R2

∆E

R1

∆E

R

∆E

R2

∆E

3.3 3.3 3.4 3.4 3.4 3.5 3.5

-12.5 -32.2 -26.2 -26.8 -25.0 -24.7 -34.9

240 330 0 60 30 240 0

-32.9 -33.7 -26.2 -32.9 -30.7 -37.5 -34.9

0, 0 0, 0 0, 0 0.5, 225 0.5, 180 1.0, 180 1.0, 45

-32.9 -33.7 -26.2 -33.9 -32.6 -39.3 -40.7

3.3 3.3 3.3 3.4 3.4 3.4 3.3

-17.2 -33.8 -31.3 -33.1 -27.6 -34.6 -46.2

210 60 30 300 120 210 0

-37.4 -37.3 -31.3 -35.6 -37.6 -43.7 -46.2

0.5, 90 0.5, 135 0.5, 315 0.5, 0 0.5, 90 0.5, 0 0.5, 90

-37.6 -38.3 -31.3 -36.5 -37.8 -46.9 -49.1

3.3 3.2 3.3 3.3 3.3 3.4 3.4

-31.1 -56.1 -49.7 -54.3 -55.0 -54.6 -65.7

180 330 0 30 0 270 270

-54.1 -57.0 -49.7 -57.2 -55.0 -73.2 -71.0

0, 0 0, 0 0.5, 315 0, 0 0.5, 0 0.5, 270 0.5, 0

-54.1 -57.0 -50.7 -57.2 -55.9 -73.8 -72.2

Calculations were performed with the 6-31G*(0.25) basis set. b See Figure 11.

eration of horizontal displacement for HYP and A dimers are very similar to those previously discussed for adenine complexes, while the dependence of stacking on the angle of rotation is different for each nucleobase due to differences in the orientation of the dipole vectors, as well as the location and nature of exocyclic functional groups. Although the trend in the stacking energies with respect to the amino acid for HYP and A dimers is the same as found for adenine (PHE < TYR ≈ HIS < TRP), the binding strengths increase slightly (to 2641 and 31-49 kJ mol-1 for HYP and A dimers, respectively). The increase in stacking for these dimers is likely due to the increased surface areas, polarizabilities, and dipole moments of the nucleobase. The stacking interaction energies of 3,9-dimethyladenine (Table 4) and 3-methyladenine (Table 1) dimers are very similar. This suggests that the importance of the positive charge outweighs the importance of the damage location and/or the presence of additional methyl groups when determining the magnitude of the stacking interaction. To compare the above results to the stacking energy estimated from crystal structures, we focus on 3-methyladenine DNA glycosylase since this enzyme has the ability to excise a wide variety of damaged bases29 and the reason for this reduced selectivity is unclear. We consider three crystal structures of 3-methyladenine DNA glycosylase from different sources and bound to different substrates: (1) 3-methyladenine-DNA glycosylase from E. coli (AlkA), which has been cocrystallized with free hypoxanthine;8 (2) 3-methyladenine-DNA glycosylase from Helicobacter pylori (MagIII) bound to 3,9-dimethyladenine and 1,N6-ethenoadenine;9 and (3) human 3-methyladenine DNA glycosylase (AAG) complexed to DNA containing 1,N6ethenoadenine.10 We note that 3-methyladenine DNA glycosylase I (TAG) has been identified to be a related enzyme, which has a high specificity for only 3-methyladenine and 3-meth-

ylguanine.33 However, since the solution structure of this enzyme suggests that hydrogen-bonding, as well as stacking, interactions may be important for catalysis,34 and we are solely interested in stacking interactions in the present work, we do not consider this related enzyme. Nevertheless, it should be noted that hydrogen bonding,10,29b as well as general acid-base catalysis,35 has also been implicated as a way for alkyl DNA glycosylases to discriminate against undamaged purines. Figure 12 shows the main nucleobase-amino acid interactions in the three crystal structures considered in the present work. From all three structures, it is clear that the relative orientation of the damaged nucleobase and amino acid residues is very different in the active site compared with the optimum orientation determined from our surface scans. Due to the significant dependence of the stacking energy on the angle of rotation, it is anticipated that the relative orientations within the crystal structure lead to different stacking energies compared with the maximum stacking interaction found in the present work. Furthermore, in all crystal structures, the molecular plane of one amino acid is nearly parallel to the molecular plane of the (modified) nucleobase, while the amino acid(s) on the remaining nucleobase face adopts a significant tilt angle. Since we find that tilting by 10° generally leads to a decrease in the stacking energy, the reason for the tilt is unclear, where the tilt may be responsible for substrate recognition or selectivity rather than catalysis. Nevertheless, it is important to characterize these interactions. To calculate the stacking energy in the crystal structure geometry, the MP2 optimized amino acids and hypoxanthine were overlaid (according to maximum atomic overlap of heavy atoms) onto the corresponding molecule in the crystal structure.36,37 The results are presented, and compared to the corresponding results from the potential energy surface scans, in Table 5. We also considered 3MeA and A within MagIII,



TABLE 5: Comparison of MP2 Stacking Interactions (kJ mol-1) Calculated Using Crystal Structures of 3-Methyladenine DNA Glycosylase and Potential Energy Surface Scans crystal structurea enzyme AlkAc MagIIId

AAGe

nucleobase

amino acids

∆E

HYP HYP HYP A A A 3,9MeA 3,9MeA 3,9MeA 3MeA 3MeA 3MeA A A A A A A A A A A

TRP TYR TRP+TYR TRP PHE TRP+PHE TRP PHE TRP+PHE TRP PHE TRP+PHE TRP PHE TRP+PHE TYR1 HIS TYR2 TYR1+HIS TYR1+TYR2 HIS+TYR2 TYR1+HIS+TYR2

-26.9 -16.5 -43.8 -15.3 -23.0 -39.2 -38.2 -38.8 -76.3 -37.0 -36.6 -72.7 -22.4 -18.8 -41.9 -28.9 -9.0 -5.7 -37.9 -34.9 -22.9 -52.2

additive

-43.4 -38.3 -77.0 -73.5 -41.2

-37.9 -34.6 -14.7 -43.6

surface scansb ∆E -40.7 -32.6 -73.1 -49.1 -31.3 -81.4 -72.2 -50.7 -119.5 -69.6 -48.4 -120.8 -34.8 -24.3 -60.0 -37.8 -37.6 -75.6

additive

-73.3 -80.4 -122.9 -118.0 -59.1

-75.4

a See Figure 12 for pictures of the active site interactions. b See Table 4. c Crystal structure taken from ref 8 (PDB ID code: 1PVS). d Crystal structure taken from ref 9 (PDB ID codes: 1PU7 and 1PU8). e Crystal structure taken from ref 10 (PDB ID code: 1EWN).

where the optimum overlay was performed using only the ring heavy atoms of 3,9MeA. The consideration of a wider variation of nucleobases will allow us to determine the effects of alkylation on the magnitude of the stacking interaction energy in the context of the active site. When considering the stacking between the nucleobase and the amino acid with a nearly planar relative orientation, we find that the interaction energy estimated from the crystal structure orientation is only 23-34% smaller than that calculated from the surface scans. The decrease is larger when the amino acids with nonplanar relative orientations are considered, and it varies with the crystal structure due to differences in nonplanarity. The changes in the stacking energy represent 49% reduction for AlkA, 35-69% for MagIII, and 76% for AAG. The larger reduction along the series AAG > MagIII > AlkA makes sense due to the increased tilt angle and horizontal shift of the relevant amino acid with respect to the nucleobase (Figure 12). As previously mentioned, consideration of different nucleobases within the active site of MagIII allows us to reconsider the effects of protonation on the stacking energy within the crystal structure geometry. We note that there is not a significant difference between the stacking interactions within the active site of MagIII when 3MeA or 3,9MeA is the substrate. However, there is a large difference from A, where the magnitude of the stacking interaction with PHE doubles and that with TRP increases by 65-70% upon alkylation. These are similar increases to those found in the surface scans. Thus, our results indicate that although the stacking interaction within the crystal structures of DNA glycosylases are reduced compared with the maximum possible stacking interaction, alkylation leads to significant increases in the stacking energy despite nonparallel arrangements of the base and amino acids in the crystal structures. Since more than one stacking interaction simultaneously occurs within the active sites of AlkA, MagIII, and AAG, it is interesting to consider the additivity of the stacking interactions (i.e., how the simultaneous interaction with more than one amino acid compares with the sum of the individual interactions). For

most combinations considered in the present work, we find that the total stacking energy of a complex involving more than one amino acid (∆E, Table 5) is equal to the sum of the individual interactions (additive, Table 5) for both the crystal structure geometry and the optimum orientation as determined from our surface scans. Furthermore, the additivity holds for both neutral and cationic nucleobases. The additivity of stacking interactions has also been reported for benzene dimers.17h Interestingly, the simultaneous interactions of A with HIS and TYR2 in the AAG active site are greater than additive by up to 9 kJ mol-1, which suggests that interactions between the amino acid residues enhance the total interaction energy. These are very interesting findings and, although full consideration is beyond the scope of the present study, future work will address the additivity (or greater than additivity) of stacking interactions. In summary, our study of crystal structures of 3-methyladenine DNA glycosylase indicates that the relative orientations of the base and amino acids in the active site recover a significant portion (up to approximately 75%) of the maximum possible stacking interactions between the relevant molecules. Furthermore, when natural nucleobases are modeled into the active site, we see a significant decrease in the binding strength compared with the damaged nucleobases. These differences may help explain why these enzymes remove normal bases with an efficiency that is several orders of magnitude below the efficiency of removing charged nucleobases.38 Furthermore, the results help explain the low efficiency for removal of some damaged bases (hypoxanthine and 1-N6-ethenoadenine) compared with others (charged alkylated nucleobases).9,39 Conclusions In the present study, computational chemistry was used to characterize the gas-phase stacking interactions utilized by 3-methyladenine DNA glycosylase. Initially, the MP2 potential energy surfaces of stacked dimers between the natural base adenine and the four aromatic amino acid residues were considered as a function of four variables (vertical displacement, angle of rotation, horizontal displacement, and tilt angle).

19662 J. Phys. Chem. B, Vol. 110, No. 39, 2006 Subsequently, a comparison was made to 3-methyladenine, which represents a major form of DNA alkylation damage. The dependence of the stacking interaction between the aromatic amino acids and 3-methyladenine on the relative orientation of the monomers is very similar to the dependencies found for adenine. Specifically, we find that changes in the angle of rotation lead to the largest changes in the stacking energy compared with the other variables considered. The trend in the stacking with respect to the amino acid (TRP > TYR ≈ HIS > PHE) is also the same for both nucleobases since the trend is primarily dictated by the magnitude of the dipole moment and surface area of the amino acid. However, we find that the magnitude of the stacking interaction significantly increases upon methylation. Using a variety of basis sets and extrapolation schemes, we estimate the maximum possible stacking interactions between the amino acids and (undamaged) adenine to range between 25 and 45 kJ mol-1. This range increases to 50-80 kJ mol-1 upon methylation, which represents a 50-115% enhancement and is due to both electrostatic and correlation effects. Our calculations therefore suggest that alkylation of the nucleobase likely plays a much greater role than the nature of the active site amino acid in substrate identification and excision. Crystal structures of DNA repair enzymes cocrystallized with damaged nucleobases were used to explore the influence of local geometrical changes on the stability of stacked nucleobaseamino acid dimers. We find that the relative orientations of the nucleobases and amino acids in the active sites of these enzymes account for up to approximately 75% of the maximum possible stacking energy as estimated from our surface scans. Furthermore, modeling natural nucleobases into the active sites of these enzymes indicates that increases in stacking upon methylation similar to those found for our surface scans occur in the crystal structure orientations. Interestingly, simultaneous consideration of interactions with more than one amino acid residue in the active site indicates that the stacking interactions are additive. In summary, stacking interactions have been identified to play an important role in many biological functions. To the best of our knowledge, this is the first study that considers the stacking interactions between amino acids and damaged nucleobases, and thereby determines the effect of the damage on the stacking properties of the natural nucleobase. This information is particularly useful since the magnitudes of stacking interactions are difficult to obtain directly from experiments, where it is hard to separate stacking interactions from, for example, hydration, hydrogen bonding, conformational changes, or other effects. Future work will consider other environmental effects and interactions in the active site of this class of DNA glycosylase, such as the influence of additional discrete (hydrogen bonding, T-shaped, or edgewise) contacts with neighboring amino acid residues. Acknowledgment. We thank the Research Corporation, the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), and the New Brunswick Innovation Foundation (NBIF) for financial support. We also gratefully acknowledge the Mount Allison Cluster for Advanced Research (TORCH) for generous allocations of computer resources. References and Notes (1) (a) Seeberg, E.; Eide, L.; Bjoras, M. Trends Biochm. Sci. 1995, 20, 391-397. (b) Wood, R. D.; Mitchell, M.; Sgouros, J.; Lindahl, T. Science 2001, 291, 1284-1289.

Rutledge et al. (2) For a review of studies related to the DNA glycosylases, see, for example: (a) David, S. S.; Williams, S. D. Chem. ReV. 1998, 98, 12211261. (b) Stivers, J. T.; Drohat, A. C. Arch. Biochem. Biophys. 2001, 396, 1-9. (c) Stivers, J. T.; Jiang, Y. L. Chem. ReV. 2003, 103, 2729-2759. (d) Berti, P. J.; McCann, J. A. B. Chem. ReV. 2006, 106, 506-555. (3) Parikh, S. S.; Mol, C. D.; Hosfield, D. J.; Tainer, J. A. Curr. Opin. Struct. Biol. 1999, 9, 37-47. (4) See, for example: (a) Drabløs, F.; Feyzi, E.; Aas, P. A.; Vaagbø, C. B.; Kavli, B.; Bratlie, M. S.; Pena-Diaz, J.; Otterlei, M.; Slupphaug, G.; Krokan, H. E. DNA Repair 2004, 3, 1389-1407. (b) Mishina, Y.; Duguid, E. M.; He, Chuan, Chem. ReV. 2006, 106, 215-232, and references therein. (5) For a review of the biological importance of 3-methyladenine DNA glycosylases, see: Wyatt, M. D.; Allan, J. M.; Lau, A. Y.; Ellenberger, T. E.; Samson, L. D. BioEssays 1999, 21, 668-676. (6) (a) Zoltewicz, J. A.; Clark, F. D.; Sharpless, T. W.; Grahe, G. J. Am. Chem. Soc. 1970, 92, 1741. (b) Fujii, T.; Saito, T.; Nakasaka, T. Chem. Pharm. Bull. 1989, 37, 2601. (c) Fujii, T.; Itaya, T. Heterocycles 1988, 48, 1673. (7) See, for example: (a) Yamagata, Y.; Kato, M.; Odawara, K.; Tokuno, Y.; Nakashima, Y.; Matsushima, N.; Yasumura, K.; Tomita, K.; Ihara, K.; Fujii, Y.; Nakabeppu, Y.; Sekiguchi, M.; Fujii, S. Cell 1996, 86, 311-319. (b) Labahn, J.; Scharer, O. D.; Long A.; Ezaz-Nikpay, K.; Verdine, G. L.; Ellenberger, T. E. Cell 1996, 86, 321-329. (c) Lau, A. Y.; Scha¨rer, O. D.; Samson, L.; Verdine, G. L.; Ellenberger, T. Cell 1998, 95, 249-258. (8) Teale, M.; Symersky, J.; DeLucas, L. Bioconjugate Chem. 2002, 13, 403-407. (9) Eichman, B. F.; O’Rourke, E. J.; Radicella, J. P.; Ellenberger, T. EMBO J. 2003, 22, 4898-4909. (10) Lau, A. Y.; Wyatt, M. D.; Glassner, B. J.; Samson, L. D.; Ellenberger, T. Proc. Natl. Acad. Sci. 2000, 97, 13573-13578. (11) (a) Ishida, T.; Shibata, M.; Fujii, K.; Inoue, N. Biochemistry 1983, 22, 3571-3581. (b) Ishida, T.; Doi, M.; Inoue, M. Nucleic Acid Res. 1988, 16, 6175-6190. (12) For a review on the calculation of stacking interactions between the natural DNA nucleobases, see, for example: (a) Hobza, P.; Sponer, J. Chem. ReV. 1999, 99, 3247-3276. (b) Sponer, J.; Leszczynski, J.; Hobza, P. J. Mol. Struct (THEOCHEM) 2001, 573, 43-53. (c) Sponer, J.; Leszczynski, J.; Hobza, P. Biopolymers (Nucleic Acid Science) 2002, 61, 3-31. (d) Hobza, P. Annu. Rep. Prog. Chem., Sect. C: Phys. Chem. 2004, 100, 3-27. (13) (a) Hobza, P.; Sponer, J.; Polasek, M. J. Am. Chem. Soc. 1995, 117, 792-798. (b) Sponer, J.; Leszczynski, J.; Hobza, P. J. Phys. Chem. A 1997, 101, 9489-9495. (c) Kratochvil, M.; Engkvist, O.; Sponer, J.; Jungwirth, P.; Hobza, P. J. Phys. Chem. A 1998, 102, 6921-6926. (14) (a) Sponer, J.; Leszczynski, J.; Hobza, P. J. Phys. Chem. 1996, 100, 5590-5596. (b) Sponer, J.; Hobza, P. Chem. Phys. Lett. 1997, 267, 263-270. (c) Jurecka, P.; Nachtigall, P.; Hobza, P. Phys. Chem. Chem. Phys. 2001, 3, 4578-4582. (d) Leininger, M. L.; Nielsen, I. M. B.; Colvin, M. E.; Janssen, C. L. J. Phys. Chem. A 2002, 106, 3850-3854. (e) Jurecka, P.; Sponer, J.; Hobza, P. J. Phys. Chem. B 2004, 108, 5466-5471. (15) (a) Hobza, P.; Sponer, J. J. Am. Chem. Soc. 2002, 124, 1180211808. (b) Jurecka, P.; Hobza, P. J. Am. Chem. Soc. 2003, 125, 1560815613. (c) Sponer, J.; Jurecka, P.; Hobza, P. J. Am. Chem. Soc. 2004, 126, 10142-10151. (16) See, for example: (a) Sponer, J.; Gabb, H. A.; Leszczynski, J.; Hobza, P. Biophys. J. 1997, 73, 76-87. (b) Alhambra, C.; Luque, F. L.; Gago, F.; Orozco, M. J. Phys. Chem. B 1997, 101, 3846-3853. (c) Hunter, C. A.; Lu, X.-J. J. Mol. Biol. 1997, 265, 603-619. (d) Hill, G.; Forde, G.; Hill, N.; Lester, J., W. A.; Sokalski, W. A.; Leszczynski, J. Chem. Phys. Lett. 2003, 381, 729-732. (e) Sponer, J.; Florian, J.; Ng, H.-L.; Sponer, J. E.; Spadkova, N. a. Nucleic Acids Res. 2000, 28, 4893-4902. (f) Dabkowska, I.; Gonzalez, H. V.; Jurecka, P.; Hobza, P. J. Phys. Chem. A 2005, 109, 1131-1136. (g) Cysewski, P.; Czy_nikowska-Balcerak, J. Mol. Struct. (THEOCHEM) 2005, 757, 29-36. (h) Matta, C. F.; Castillo, N.; Boyd, R. J. J. Phys. Chem. B 2006, 110, 563-578. (17) (a) Hobza, P.; Selzle, H. L.; Schlag, E. W. J. Phys. Chem. 1996, 100, 18790-18794. (b) Sinnokrot, M. O.; Valeev, E. F.; Sherrill, C. D. J. Am. Chem. Soc. 2002, 124, 10887-10893. (c) Tsuzuki, S.; Honda, K.; Uchimaru, T.; Mikami, k. M.; Tanabe, K. J. Am. Chem. Soc. 2002, 124, 104-112. (d) Sinnokrot, M. O.; Sherrill, C. D. J. Phys. Chem. A 2003, 107, 8377-8379. (e) Sinnokrot, M. O.; Sherrill, C. D. J. Am. Chem. Soc. 2004, 126, 7690-7697. (f) Sinnokrot, M. O.; Sherrill, C. D. J. Phys. Chem. A 2004, 108, 10200-10207. (g) Riley, K. E.; Merz, K. M., Jr. J. Phys. Chem. B 2005, 109, 17752-17756. (h) Tauer, T. P.; Sherrill, C. D. J. Phys. Chem. A 2005, 109, 10475-10478. (i) Waller, M. P.; Robretazzi, A.; Platts, J. A.; Hibbs, D. E.; Williams, P. A. J. Comput. Chem. 2006, 27, 491-504. (18) (a) Biot, C.; Buisine, E.; Kwasigroch, J.-M.; Wintjens, R.; Rooman, M. J. Biol. Chem. 2002, 277, 40816-40822. (b) Biot, C.; Buisine, E.; Rooman, M. J. Am. Chem. Soc. 2003, 125, 13988-13994. (c) Biot, C.; Wintjens, R.; Rooman, M. J. Am. Chem. Soc. 2004, 126, 6220-6221. (d) Caue¨t, E.; Rooman, M.; Wintjens, R.; Lie´vin, Biot, C. J. Chem. Theory. Comput. 2005, 1, 472-483.

Nucleobase-Amino Acid Stacking Interactions (19) (a) Kumar, N. V.; Govil, G. Conform. Biol. 1983, 313-321. (b) Kumar, N. V.; Govil, G. Biopolymers 1984, 23, 2009-2024. (c) Kumar, N. V.; Govil, G. Prog. Clin. Biol. Res. 1985, 172, 91-104. (d) Mitchell, J. B. O.; Nandi, C. L.; McDonald, I. K.; Thornton, J. M.; Price, S. L. J. Mol. Biol. 1994, 239, 315-331. (e) Chelli, R.; Gervasio, F. L.; Procacci, P.; Schettino, V. J. Am. Chem. Soc. 2002, 124, 6133-6143. (f) Morozov, A. V.; Misura, K. M. S.; Tsemekhman, K.; Baker, D. J. Phys. Chem. B 2004, 108, 8489-8496. (20) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Montgomery, J. A., Jr.; Vreven, T.; Kudin, K. N.; Burant, J. C.; Millam, J. M.; Iyengar, S. S.; Tomasi, J.; Barone, V.; Mennucci, B.; Cossi, M.; Scalmani, G.; Rega, N.; Petersson, G. A.; Nakatsuji, H.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Klene, M.; Li, X.; Knox, J. E.; Hratchian, H. P.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Ayala, P. Y.; Morokuma, K.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Zakrzewski, V. G.; Dapprich, S.; Daniels, A. D.; Strain, M. C.; Farkas, O.; Malick, D. K.; Rabuck, A. D.; Raghavachari, K.; Foresman, J. B.; Ortiz, J. V.; Cui, Q.; Baboul, A. G.; Clifford, S.; Cioslowski, J.; Stefanov, B. B.; Liu, G.; Liashenko, A.; Piskorz, P.; Komaromi, I.; Martin, R. L.; Fox, D. J.; Keith, T.; Al-Laham, M. A.; Peng, C. Y.; Nanayakkara, A.; Challacombe, M.; Gill, P. M. W.; Johnson, B.; Chen, W.; Wong, M. W.; Gonzalez, C.; Pople, J. A. Gaussian 03, Revisions B.05 and C.02; Gaussian, Inc.: Wallingford, CT, 2004. (21) Hobza, P.; Sponer, J. Chem. Phys. Lett. 1998, 288, 7-14. (22) Polarizabilities decrease with the surface area according to TRP (80.8) > TYR (57.6) > PHE (54.0) > HIS (36.4) (where the HF/6-31G(d,p) polarizabilities are provided in brackets in units of bohr3). (23) Dipole moment vectors were calculated with MP2/6-31G(d) using Spartan ‘02 (Build 115 built under Linux 2.2), Wavefunction Inc.: Irvine, CA, 1999-2001. (24) We also note that the orientation in the TYRf and TRP dimers that leads to the largest stacking interaction energy (Figure 2b) is rotated by 30 deg. with respect to the structure obtained via alignment of the dipole vectors (Figure 6b). However, these structures differ in energy by less than 2 kJ mol-1. Consideration of twist intervals smaller than 30° may yield better agreement. (25) It should be noted that the centers of mass of adenine and 3-methyladenine are slightly different, which also leads to small changes in the preferred angle of rotation.

J. Phys. Chem. B, Vol. 110, No. 39, 2006 19663 (26) We note that the tilt angle is not considered since the tilt dependence is only significant in the case of 3MeA:HIS dimer. (27) (a) Halkier, A.; Helgaker, T.; Jørgensen, P.; Klopper, W.; Koch, H.; Olsen, J.; Wilson, A. K. Chem. Phys. Lett. 1998, 286, 243-252. (b) A. Halkier, T. Helgaker, Jørgensen, P.; Klopper, W.; Olsen, J. Chem. Phys. Lett. 1999, 302, 437-446. (28) Truhlar, D. G. Chem. Phys. Lett. 1998, 294, 45-48. (29) See, for example: (a) Berdal, K. G.; Johansen, R. F.; Seeberg, E. EMBO J. 1998, 17, 363. (b) Asaeda, A.; Ide, H.; Asagoshi, K.; Matsuyama, S.; Tano, K.; Murakami, A.; Takamori, Y.; Kubo, K. Biochemistry 2000, 39, 1959-1965. (c) Abner, C. W.; Lau, A. Y.; Ellenberger, T.; Bloom, L. B. J. Biol. Chem. 2001, 276, 13379-13387. (d) O’Brien, P. J.; Ellenberger, T. J. Biol. Chem. 2004, 279, 26876-26884. (e) O’Brien, P. J.; Ellenberger, T. J. Biol. Chem. 2004, 279, 9750-9757. (30) See, for example: (a) Singer, B.; Grunberger, D. Molecular Biology of Mutagens and Carcinogens; Plenum Press: New York, 1983; pp 1922. (b) Nair, V.; Chamberlain, S. D. Synthesis 1984, 401-403. (c) Caulfield, J. L.; Wishnok, J. S.; Tannenbaum, S. R. J. Biol. Chem. 1998, 273, 1268912695 and references therein. (31) See, for example: (a) Guengerich, F. P.; Kim, D. H.; Iwasaki, M. Chem. Res. Toxicol. 1991, 4, 168-179. (b) Guengerich, F. P. Chem. Res. Toxicol. 1992, 5, 2-5. (c) Persmark, M.; Humphreys, W. G.; Okazaki, O.; Raney, V. M.; Guengerich, F. P. IARC Sci. Publ. 1994, 125, 437-441. (32) The tilt angle was not further investigated for these modified bases since this consistently led to a very small, if any, increase in the stacking interaction for A and 3MeA complexes. (33) Drohat, A. C.; Kwon, K.; Krosky, D. J.; Stivers, J. T. Nat. Struct. Biol. 2002, 9, 659-664. (34) Cao, C.; Kwon, K.; Jiang, Y. L.; Drohat, A. C.; Stivers, J. T. J. Biol. Chem. 2003, 278, 48012-48020. (35) O’Brien, P. J.; Ellenberger, T. Biochemistry 2003, 42, 1241812429. (36) It should be noted that A was suggested to bind to MagIII in two different orientations (see ref 9). (37) It should be noted that two atoms in hypoxanthine were mislabeled in the crystal structure of free hypoxanthine cocrystallized with AlkA (ref 8); however, this does not affect our overlay process. (38) Bjelland, S.; Seeberg, E. FEBS Lett. 1996, 397, 127-129. (39) Saparbaev, M.; Laval, J. Proc. Natl. Acad. Sci. U.S.A. 1994, 91, 5873-5877.

Characterization of Nucleobaseâ Amino Acid Stacking Interactions

Recommend Documents

Characterization of Nucleobaseâ Amino Acid Stacking Interactions