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Aromatic Interactions in the Binding of Ligands to HMGCoA Reductase Emily A. Kee, Maura C. Livengood, Erin E. Carter, Megan McKenna, and Mauricio Cafiero* Department of Chemistry, Rhodes College, 2000 N. Parkway, Memphis, Tennessee 38112 ReceiVed: May 14, 2009; ReVised Manuscript ReceiVed: September 28, 2009
3-Hydroxy-3-methyglutaryl-coenzyme A (HMGCoA) reductase is the enzyme that catalyzes the ratedetermining step in cholesterol synthesis; it is also the target for statin drugs, which are competitive inhibitors of the enzyme. We examine potentially important enzyme-ligand interactions currently not incorporated into statin drug design: weak, induction/dispersion interactions between ligands and residue tyrosine 479 in the HMGCoA reductase active site. HMGCoA is a large molecule with a long coenzyme A “tail”, and in order to study the interactions of interest, it was necessary to find the smallest possible portion of the HMGCoA molecule that would serve as a reasonable model for the entire molecule. Using this minimal model, we calculated BSSE-corrected electronic interaction energies between the residue and the ligand molecule using several DFT methods (local, hybrid, and gradient-corrected DFT methods) as well as MP2. We also performed several in silico mutations of the tyrosine 479 residue to determine the potential effects of these changes on protein-ligand interaction energies. Our work shows that this previously unexploited protein-ligand interaction between tyrosine residue 479 and HMGCoA can be important in the design of future statin drugs. Per our previous work, our results show that local DFT methods more closely match MP2 energy values for aromatic binding than do hybrid or gradient-corrected DFT methods. Introduction In the second step of the 13-step cholesterol synthesis pathway, 3-hydroxy-3-methyglutaryl-coenzyme A (HMGCoA, Figure 1) is activated by enzyme HMGCoA reductase and converted into mevalonic acid. Cholesterol-lowering drugs known as statins bind to the active site of HMGCoA reductase, inhibiting its ability to activate HMGCoA and ultimately lowering LDL cholesterol levels. Statins primarily use dipole/ dipole and hydrogen bonds to bind to the active site of the reductase, focusing on the portion of the active site dominated by lysine 691 (K691), lysine 692 (K692), aspartic acid 690 (D690), and serine 684(S684), with minimal explicit incorporation of hydrophobic side-chain interactions. However, our previous work has shown that in protein-substrate binding, induction and dispersion forces and aromatic ring-ring binding can be important.1 Thus, in the current work we focus on the ring-ring interaction between HMGCoA and HMGCoA reductase at tyrosine residue 479 (Y479) to determine if this traditionally weaker interaction plays a significant role in protein-substrate binding. We believe that if this aromatic interaction is important in binding the natural substrate, HMGCoA, to the enzyme then it can play an important role in binding novel statin drugs to the same active site in the enzyme. Because of the immense profitability of statin drugs, there has been much recent interest in binding to the HMGCoA reductase active site. Istvan and Diesenhofer2 show the crystal structures of six different statin drugs in complex with HMGCoA reductase, identifying important amino acid interactions in the binding of the ligands to the active site (mentioned above). Pfefferkorn et al.3 demonstrated structural modifications that aided in binding drugs to the active sites of HMGCoA reductase, increasing the potential efficacy of statin drugs to inhibit cholesterol synthesis. da Silva et al.4 performed modifications on a variety of statin drugs and evaluated the resulting binding affinities through computer modeling and experimental evaluation.
Figure 1. HMGCoA molecule structure from the crystal structure where it is bound to HMG-CoA reductase.
We suggest that statin drugs should incorporate induction and dispersion interactions explicitly, so we are evaluating the importance of these interactions in the statin target enzyme using the natural substrate HMGCoA. We have used several DFT methods (local, hybrid, and gradient-corrected or GGA) and second-order Moller-Plesset perturbation theory (MP2) to calculate the interaction energies between the HMGCoA ligand and a truncated portion of HMGCoA reductase. MP2 was selected on the basis of convenience and speed and it was used asthereferencetocompareinteractionenergiesofsubstrate-protein interactions calculated by DFT methods. Because of time and computing constraints, calculating the electronic structure for larger portions of the protein would be unfeasible with methods other than DFT. Thus, looking toward larger-scale calculations in the future, we evaluate a suite of DFT methods for their ability to mimic MP2 results. Contrary to what would typically be
10.1021/jp904508j CCC: $40.75 2009 American Chemical Society Published on Web 10/13/2009
Binding of Ligands to HMGCoA Reductase
Figure 2. HMG portion of HMGCoA in complex with amino acid residues D690, K691, K692, and S684.
expected, the more rigorous semilocal DFT methods were less accurate in predicting interaction energies than local DFT methods when compared to MP2 energy values. This is due to a diffuse, slowly varying density found between the molecules in the ring-ring interaction, which compensates for gradient overcorrection in the GGA methods. Truhlar et al. used two DFT methods5,6 that they developed, PWB6K and M05-2X, to approximate interaction energies of models that are similar in structure and orientation to the aromatic interactions in the binding of ligands to HMGCoA reductase that we have studied. These results mirror our findings that local DFT methods and the meta DFT methods PWB6K and M05-2X best approximate aromatic π-π stacking interactions, such as the ring interactions that we studied in the present work. Because of a lack of availability of the methods developed by Truhlar et al., we have not been able to incorporate PWB6K or M05-2X into our calculations; however, the incorporation of these methods in future work is a possibility.
J. Phys. Chem. B, Vol. 113, No. 44, 2009 14811 the B3LYP/6-31 g level of theory. The interaction energies of all mutant models were calculated as above. The in silico mutation from Y479 to F479 was performed on the basis of the strong likelihood of occurrence (this requires only a point mutation to occur naturally) and demonstrates the importance of the hydroxyl group on tyrosine in binding because phenylalanine is just tyrosine without the hydroxyl group. The in silico point mutation to A479 was chosen on the basis of a smaller likelihood of occurrence and, more interestingly, to analyze the contribution to ligand binding from the phenol group in tyrosine. Alanine is essentially tyrosine without the phenol, so this mutation allows us to determine how much binding comes from the ring and how much comes from the backbone of the residue. L479 represents a likely mutation and is interesting because its side chain can have only dispersion interactions with the ligand. All calculations were made using Gaussian0325 on Pentium dual core processors. Electrostatic Interactions between HMGCoA and HMGCoA Reductase Table 1 lists the interaction energies between the HMG portion of HMGCoA and four HMGCoA reductase residues commonly accounted for in statin design: D690, K691, K692, and S684. Figure 2 shows these four residues in complex with the portion of HMGCoA used in the calculation of interaction energies. It should be noted that the interactions possible between the residues and the ligands are dominated by dipole/ dipole interactions and hydrogen bonds between the terminal amino, hydroxyl, and carboxylic acid groups on the amino acid residues and the hydroxyl and carboxylic acid groups on HMG. The pairwise interactions between each residue and HMG are on the order of 1-5 kcal/mol, and the work below demonstrates that the tail end of the molecule involved in induction and dispersion has significant interactions that rival these electrostatic interactions in magnitude and thus has excellent potential for novel statin design.
Computational Methods
Interaction Model System
The structures of all ligand-amino acid complexes studied here were isolated from the crystal structure of HMGCoA bound to HMGCoA reductase;2 these include the complex of the HMG portion of HMGCoA with each of the four amino acids S684, D690, K691, and K692 (Figure 2) and the complex of HMGCoA with Y479 (Figure 3). Hydrogen atoms were added to all free valences in these structures, and oxygen atoms and hydroxyl groups were added where necessary to cap free amino acids. We optimized the positions of all added atoms using the B3LYP7/6-31 g8 level of theory. When truncating the HMGCoA molecule (see Figure 3 for truncated complexes), we replaced the excised atoms with a hydrogen atom and reoptimized all hydrogen atoms. The full HMGCoA-Y479 complex was broken down into two portions for further analysis: a complex between Y479 and the ring portion of HMGCoA and a complex between Y479 and the phosphate group of HMGCoA (these two portions lead to what we call the ring interaction and phosphate group interactions; see Figure 4). Counterpoise-corrected interaction energies for all molecular complexes were computed using MP2 and density functional theory methods9,10 HF, B3LYP, SVWN,11,12 HCTH407,14-16 PBE,23,23 TPSS,24 PW91,17 and SPL,18-20 using the 6-31++G** and 6-311+g* basis sets. Mutant amino acid residues were created by replacing the Y479 side chain with the appropriate new side chains (phenylalanine (F), leucine (L), and alanine (A); see Figure 5) and optimizing the resulting mutants using
To model the electronic interaction energies of Y479 in complex with HMGCoA, we wanted to identify the smallest possible portion of HMGCoA necessary to maintain a calculated interaction energy with Y479 consistent with what would be obtained by using the entire HMGCoA molecule. In Figure 3, we see Y479 in complex with several portions of HMGCoA. (See Figure 1 for the entire HMGCoA molecule.) In our first effort to calculate the binding energy, we truncated the HMGCoA molecule at the first point illustrated in Figure 3. The HMGCoA molecule was cut off at the first oxygen-carbon bond coming down from the top of the molecule, and the bond to carbon was replaced by a bond to a hydrogen atom; this molecular complex is referred to as truncation scheme 1. For this first truncation scheme, we computed the interaction energies using MP2 and three DFT methods: SVWN, B3LYP, and HCTH407 (Table 2). From these results, we observed that the local DFT method, SVWN, produced qualitatively similar results to MP2 (this was the only DFT method that showed attraction), and it was quantitatively similar to MP2 as well (-11.83 kcal/mol compared to -8.24 kcal/mol, respectively). A second truncation (truncation scheme 2, Figure 3) was performed in an attempt to remove more of the CoA tail without drastically changing the interaction energies calculated in truncation scheme 1. In truncation scheme 2, only DFT methods SVWN, B3LYP, and HCTH407 were used to model interaction energies. Because the energies observed in truncation scheme
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Figure 3. Tyrosine 479 in complex with truncated portions of the coenzyme A tail of HMGCoA. Truncation schemes are described in the text.
Protein-Ligand Binding: Theoretical Results
Figure 4. Two components of the total complex made up of the side chain of tyrosine 479 and the ring portion of HMGCoA: the ring interaction and the phosphate interaction.
1 for SVWN produced similar results to MP2 interaction energies, we used SVWN as a standard for comparison. With the second truncation, no significant change in interaction energy calculated by SVWN was observed (-11.83 kcal/mol for truncation scheme 1 and -11.99 kcal/mol for truncation scheme 2). This led to a third truncation scheme; however, the resulting interaction energies for the Y479-HMGCoA complex interaction were significantly different from those observed in previous truncation schemes (SVWN calculated an interaction energy of -9.88 kcal/mol). From Figure 3, we can see that in truncation scheme 3 a phosphate group directly across from the hydroxyl group on the tyrosine residue was removed (this was not all that was removed in going from truncation scheme 2 to 3; see Figure 3), and this is what we believe caused the significant change in interaction energy. In truncation scheme 4, we reattached the phosphate group that was removed in truncation scheme 3 and recalculated the interaction energies using MP2 and the DFT methods. This truncation scheme produced similar interaction energies (-7.73 kcal/mol for MP2 and -11.59 kcal/ mol for SVWN) to truncation scheme 1 (-8.24 kcal/mol for MP2 and -11.83 kcal/mol for SVWN), with each method giving a decrease in interaction energy of 5% or less. Thus, we determined that truncation scheme 4 would be the optimal balance of size and accuracy. All of the following work is based on truncation scheme 4.
Counterpoise-corrected interaction energies of the four complexes (Y479 in complex with HMGCoA in truncation scheme 4 and the three mutant complexes based on this same truncation scheme) were first calculated using the 6-31++g** basis set (Table 3). The counterpoise-corrected interaction energies were then computed again at the 6-311+g* level to test for basis set convergence. The results (Table 4) were very similar to those observed using the smaller basis set, 6-31++g**, and differed by less than 0.1 kcal/mol in most calculations. We can thus conclude that polarization and the diffuse function on hydrogen atoms are not crucial at this level of analysis; furthermore, we surmised that no further expansion of the basis set was necessary. The following analysis thus references interaction energy values from Table 4 only. MP2 is used as an accurate point of reference for comparison, though historically MP2 slightly overestimates these types of interaction energies when compared to coupled-cluster calculations.26-30 This work emphasizes differences in interaction energies rather than absolute energies, and thus MP2 is considered to be of sufficient accuracy. Table 4 shows the interaction energies between the Y479 residue and the entire HMGCoA truncation scheme 4 (labeled “complex”). In Figure 3, we see that the ring on Y479 is in close proximity to both the ring from HMGCoA and a phosphate group. We decomposed the interaction from the total complex into the contributions from each of these two pieces by creating two subcomplexes (Figure 4): Y479 and the ring portion of HMGCoA only (labeled “ring”) and Y479 and the phosphategroup-containing moiety (labeled “phosphate”). Tables 3 and 4 show interaction energies for the entire complex and for each of the two pieces. The MP2 interaction energy values for Y479-HMGCoA show that Y479 and HMGCoA are bound (negative, attractive energy value) fairly strongly for a nonbonded interaction. The decomposition in the ring portion of the complex shows that the ring-ring interaction is attractive and comprises the bulk of the total complex interaction energy. The phosphate interaction is actually weakly repulsive according to the MP2 calculations. The interaction energies for the mutant models show that
Binding of Ligands to HMGCoA Reductase
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Figure 5. Mutated residues (F, L, and A) at position 479 in full complex with the ring portion of HMGCoA.
TABLE 1: Counterpoise-Corrected Interaction Energies (kcal/mol) between Various Residues in HMGCoA Reductase and the HMG Portion of HMGCoAa 6-311+g* D690 K691 K692 S684 a
HF
MP2
SVWN
SPL
B3LYP
HCTH407
PW91
PBE
TPSS
-0.28 0.53 0.02 -3.51
-2.10 -3.45 -1.53 -5.17
-7.52 -3.89 -3.46 -13.28
-7.25 -3.76 -3.35 -12.88
-0.69 -0.64 -0.41 -5.38
-0.77 -1.56 -1.08 -4.00
-2.70 -1.88 -1.48 -7.04
-2.18 -1.46 -1.22 -6.40
-0.90 -0.75 -5.62
All calculations were performed using 6-311+g*.
TABLE 2: Counterpoise-Corrected Interaction Energies (kcal/mol) between Tyrosine 479 and Various Truncated Portions of the Coenzyme A Tail of HMGCoAa truncation scheme
MP2
SVWN
B3LYP
HCTH407
1 2 3 4
-8.24
-11.83 -11.99 -9.88 -11.59
6.01 5.83 2.93 6.17
8.47 8.31 3.25 8.7
-7.73
a See Figures 2-5 for truncation schemes. All calculations were performed using 6-311+g*.
all mutations considered result in less attraction in the total complex. Likewise, the analysis of the ring interactions alone shows that all of the mutations result in less attraction (and repulsion in the case of A479) for this portion of the complex. This decrease in binding for the Y479F mutation results from the loss of polarization across the aromatic ring upon removal of the hydroxyl group. The decrease in binding for the Y479L mutation results from the replacement of a delocalized electron system in tyrosine to a saturated hydrocarbon chain in leucine. Finally, the decrease in binding for the Y479A mutation results from simply going to a much smaller side chain with many fewer electrons. MP2 values for the interaction energies of the phosphate portions of the complexes are weakly repulsive for the wild type and slightly attractive (on the order of 1 kcal/mol) for all mutations made. The phosphate group is strongly polar and polarizable, which would account for its strong attractive interaction with the mutant models. The repulsion in the wild type is likely the result of the phosphate being too close to the hydroxyl group on tyrosine, causing steric repulsion. The removal of the hydroxyl group in the Y479F mutation results
in the interaction energy going from slightly repulsive to slightly attractive, supporting this reasoning. HF calculations show the interaction energies to be repulsive for all complex and ring models (wild type and mutants), disagreeing with MP2 values that are attractive for all but one of these energies. This nicely illustrates the necessity of incorporating electron correlation when computing interaction energies in these weak, nonbonded systems. We found that nonlocal DFT methods, which mostly resulted in repulsive interaction energies, did not typically agree with MP2 results. The local DFT methods considered, which generally resulted in attractive interaction energies, were often in close agreement with MP2 values. These results regarding local versus nonlocal DFT methods are atypical of what is traditionally expected. The ring interactions (which are dominated by dispersion and typically require a rigorously nonlocal method) are better approximated by local DFTs because of the cancellation of errors between the diffuse, slowly changing electron densities and the exchange/correlation energy functional. Protein-Ligand Binding: Physiological Implications Y479 in HMGCoA reductase binds to HMGCoA strongly. The computed interaction energy of -7.73 kcal/mol is comparable to the dipole-dipole and hydrogen bonds that bind the HMG portion of HMGCoA to the enzyme via residues D690, K691, K692, and S684 (between -1.53 and -5.17 kcal/mol). Most statin drug molecules, which are competitive inhibitors of this binding site in the enzyme, are small and have been found to bind primarily to D690, K691, K692, and S684 and a few surrounding residues. We suggest that the Y479 interaction in the binding site should be considered in statin drug design.
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TABLE 3: Counterpoise-Corrected Interaction Energies (kcal/mol) between Amino Acid Residues at the 479 Position and Two Different Portions of the Coenzyme A Tail of HMGCoA mutation Y479 Y479F Y479A Y479L
6-31++g**
HF
MP2
SVWN
SPL
B3LYP
HCTH407
PW91
PBE
TPSS
ring interactions phosphate interactions complex ring interactions phosphate interactions complex ring interactions phosphate interactions complex ring interactions phosphate interactions complex
3.96 4.24 8.55 4.38 1.62 7.82 1.96 -0.47 0.87 4.15 -1.06 2.99
-4.86 0.58
-4.31 -4.99 -12.07 -3.8 -4.83 -10.62 -1.62 -0.24 -2.72 -3.63 -1.10 -5.47
-4.07 -4.62 -11.36 -3.58 -4.57 -10.03 -1.5 -0.24 -2.58 -3.38 -1.08 -5.19
2.76 2.96 5.85 3.21 0.89 4.85 1.49 -0.29 0.49 3.02 -0.46 2.06
2.1 4.76 8.64 2.63 1.62 6.46 0.95 -0.35 -0.11 3.10 -1.41 1.22
0.32 1.28 1.63 0.78 -0.46 0.88 0.36 -0.35 -0.82 0.96 -1.14 -0.59
0.88 1.84 2.58 1.29 -0.058 1.63 0.67 -0.31 -0.35 1.39 -0.86 0.08
2.22 2.91 5.43 2.65 0.85 4.32 1.3 -0.38 0.22 2.49 -0.71 1.33
-4.19 -0.9 0.14 -0.34 -1.3 -1.39 -1.05 -3.76
TABLE 4: Counterpoise-Corrected Interaction Energies (kcal/mol) between Amino Acid Residues at the 479 Position and Two Different Portions of the Coenzyme A Tail of HMGCoA mutation Y479 Y479F Y479A Y479L
6-311+g*
HF
MP2
SVWN
SPL
B3LYP
HCTH407
PW91
PBE
TPSS
ring interactions phosphate interactions complex ring interactions phosphate interactions complex ring interactions phosphate interactions complex ring interactions phosphate interactions complex
3.69 3.98 8.27 4.32 1.54 7.22 1.99 -0.4 0.91 4.19 -0.75 3.01
-5.18 0.71 -7.73 -4.51 -0.79 -7.66 0.2 -0.33 -1.24 -1.37 -1.04 -3.73
-4.33 -5.1 -12.03 -3.8 -4.82 -10.44 -1.59 -0.53 -2.86 -3.57 -1.05 -5.34
-4.09 -4.74 -11.31 -3.57 -4.56 -9.86 -1.47 -0.52 -2.72 -3.33 -1.03 -5.06
2.75 2.68 5.63 3.23 0.84 4.88 1.5 -0.29 0.54 3.08 -0.52 2.11
2.1 4.68 8.54 2.66 1.7 6.59 1.05 -0.5 -0.028 3.2 -1.39 1.34
0.28 1.13 1.55 0.77 -0.45 0.93 0.34 -0.54 -0.88 0.91 -1.2 -0.56
0.85 1.72 2.53 1.29 -0.027 1.74 0.71 -0.57 -0.49 1.02 -0.85 0.15
2.18 2.83 5.44 2.62 0.89 4.42 1.31 -0.4 0.2 2.2 -0.72 0.00
In the likely event of mutation from Y479 to F479, our data predicts that cholesterol synthesis will remain fairly unaffected on the basis of small changes in interaction energies. For the small yet finite possibility that tyrosine would naturally mutate to either alanine or leucine, we can conclude that there would be a significant drop in interaction energies, which may adversely affect cholesterol synthesis. Thus, we see that the π-π interactions specifically are necessary for the binding of HMGCoA to HMGCoA reductase. Conclusions and Future Work Through an analysis of interactions between ligands and the truncated HMGCoA molecule, we were able to conclude that the interactions between Tyr 479 and HMGCoA are very important (8 kcals/mol). We believe that this π-π-stacking aromatic interaction between the protein and ligand deserves to be given more attention in the design of drugs that inhibit the action of this enzyme. We have begun some molecularlevel rational drug design on an HMGCoA inhibitor, and our next paper describes statin drug design using this weak interaction explicitly. Preliminary work on this had included the design of drug candidates and docking calculations that show that conventional statins modified to take advantage of this interaction can fit into the active site and dock competitively. References and Notes (1) Hofto, M. E.; Cross, J. N.; Cafiero, M. J. Phys. Chem. 2007, 111, 9651. Hofto, L. R.; Van Sickle, K.; Cafiero, M. Int. J. Quantum Chem. 2007, 108, 112. Hofto, M. E.; Godfrey-Kittle, A.; Cafiero, M. THEOCHEM 2007, 809, 125. Van Sickle, K.; Culberson, L. M.; Holzmacher, J. L.; Cafiero, M. Int. J. Quantum Chem. 2007, 107, 1523. Godfrey-Kittle, A.; Cafiero, M. Int. J. Quantum Chem. 2006, 106, 2035. Van SickleK., Shroyer, M.; CafieroM. J. Phys Chem B,submitted for publication. Hofto, L. R.; Lee, C.; CafieroM. J. Comput. Chem. 2007, 30, 1111. (2) Istvan, E. S.; Deisenhofer, J. Science 2001, 292, 1160. (3) Pfefferkorn, J. A.; et al. Bioorg. Med. Chem. Lett. 2007, 17, 4531.
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Binding of Ligands to HMGCoA Reductase 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, revision C.02; Gaussian, Inc.: Wallingford, CT, 2004. (26) Sinnokrot, M. O.; Sherrill, C. D. J. Phys. Chem. A 2006, 110, 10656–10668.
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