SAM

Jul 8, 2010 - SAM-III riboswitch, involved in regulating sulfur metabolic pathways in lactic acid bacteria, is capable of differentiating S-adenosyl-l...
1 downloads 0 Views 2MB Size
Download PDF
9920

J. Phys. Chem. B 2010, 114, 9920–9925

Atomistic Details of the Ligand Discrimination Mechanism of SMK/SAM-III Riboswitch U. Deva Priyakumar† Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India ReceiVed: May 10, 2010; ReVised Manuscript ReceiVed: June 21, 2010

SAM-III riboswitch, involved in regulating sulfur metabolic pathways in lactic acid bacteria, is capable of differentiating S-adenosyl-L-methionine (SAM) from its structurally similar analogue S-adenosyl-L-homocysteine (SAH). Atomic level understanding of the ligand recognition mechanism of riboswitches is essential for understanding their structure-function relationships in general. In the present study, we have employed molecular dynamics (MD) simulations on five model systems to elucidate the discrimination mechanism adopted by the SAM-III riboswitch that enables differential binding of SAM with respect to SAH. The structures of the binding pocket of the riboswitch and the modes of binding of the adenine moiety of SAM obtained from the MD simulations are similar to the experimental structure. However, MD simulations of the riboswitch-SAH complexes lead to partial unbinding of the ligand and structural changes in the RNA binding pocket. Detailed analyses were performed to examine the structural and energetic factors involved in such a differentiation. The calculations reveal a novel mechanism by which the aptamer domain specifically recognizes the adenine moiety of SAM/SAH, but SAM is better stabilized in the binding pocket due to nonspecific electrostatic interactions involving the sulfonium group. Additionally, the results support less dependence of the ligand conformation in the bound form on the effective binding of SAM to the riboswitch. Introduction Riboswitches are mRNA structural elements that are involved in regulating gene expression, a function that has traditionally been attributed to proteins.1-5 They consist of two distinct domains in general, namely, an aptamer domain and an expression platform. The aptamer domain is responsible for binding specific metabolites, and the expression platform is involved in the genetic control. The control at the level of transcriptional termination or translational initiation is achieved by structural changes in the expression platform that is facilitated by conformational changes driven by the binding/unbinding of the metabolite in the aptamer domain. Various riboswitches that sense distinct metabolites have been identified, and X-ray crystal structures of some of these have been reported.1-4 Experimental studies have also been instrumental in investigating the thermodynamics and kinetics of ligand discrimination and binding.6-8 In addition to the experimental studies, computational methods have been successfully used in understanding the structural and dynamic differences in the riboswitch arising due to the presence and the absence of the ligand.9-14 Riboswitches that recognize S-adenosyl-L-methionine (SAM) have been shown to regulate sulfur metabolic pathways in certain bacteria.15 SAM is a cofactor in methylation reactions of proteins, nucleic acids, and other biomolecules; a byproduct of such reactions is S-adenosyl-L-homocysteine (SAH). Structurally, the difference between SAM and SAH is an extra methyl group, and a positive sulfonium group in the former. So far, five distinct classes of riboswitches that respond to intracellular concentrations of SAM have been discovered, namely, SAM-I,16,17 SAM-II,18 SAM-III,19 SAM-IV,20 and SAM-V.21 SAM riboswitches have been shown to exhibit at least 100-fold preferential binding with SAM as compared to SAH.15 Recently, † E-mail: [email protected]. Phone: +91-40-66531161. Fax: +91-4066531413.

Figure 1. (a) Secondary structure of the SMK box. Nucleotide numbering is according to the published data.19,24 The stems (P1, P2, P3, and P4), and the two junctions (J32 and J24) of the RNA are represented in distinct colors, and the SD sequence (G88-G92) is highlighted in the secondary structure. (b) The three-dimensional structural representation of SMK box, and the colored regions represent different stems and junctions. The SAM ligand is given in CPK and surface representations.

Montage et al. have obtained the crystal structures of SAM-I riboswitch bound to SAM and SAH, and explained the molecular basis of discrimination between SAM and its structurally related analogues.22 SAM-III riboswitch (SMK box) has been shown to regulate the translation of SAM synthetase genes in Lactobacillales by sequestering the Shine-Dalgarno (SD) sequence using an antiShine-Dalgarno (ASD) sequence in the presence of the metabolite (Figure 1).19,23,24 Notably, the SD sequence (GGGGG) of the SMK box was found to directly take part in binding the

10.1021/jp1042427  2010 American Chemical Society Published on Web 07/08/2010

SMK/SAM-III Riboswitch

J. Phys. Chem. B, Vol. 114, No. 30, 2010 9921 TABLE 1: Description of the Five MD Simulations: the Starting Structure, Ligand Present, the Confomation of the Ligand, and the Number of Water Molecules and Ions in the Simulation Systemsa

Figure 2. (a) Overlay of the structures obtained from PDB IDs 3E5C, MM (blue), and 3E5E, HH (red), showing minimal deviations between the two RNA structures. (b) SAM from 3E5C, MM (blue), existing in a compact conformation, and SAH from 3E5E, HH (red), present in an extended conformation. (c) Comparison of the conformations of SAM (MM, MH1, and MH2) and SAH (HH and HM) as present in the initial structures considered for the five MD simulations (see Figure S1 in Supporting Information).

metabolite unlike most other riboswitches. Riboswitches are potential therapeutic targets, and hence molecular level understanding of the recognition of cognate over noncognate ligands by riboswitches is important especially when they are structurally similar.5 Recently, Lu et al. reported the X-ray crystal structure of the SAM-III riboswitch from Enterococcus faecalis.23 The authors hypothesized that the sulfonium group, and a compact conformation adopted by SAM, are specifically recognized by the RNA, which results in the discrimination of the cognate ligand from SAH. Molecular dynamics (MD) simulations are valuable in studying the structure and dynamics of biomolecules in general. Recently, MD simulations have been use to study the on/off mechanism of SAM-I and SAM-II riboswitches.10-12 In the present study, we have performed MD simulations aimed at identifying the structural/energetic determinants that enable the specificity of the SAM-III riboswitch. Computational Details The starting structures for the simulations were obtained based on two crystallographic coordinates obtained from published data (PDB IDs 3E5C and 3E5E, referred to as MM and HH, respectively, in the present paper).23 SAM is bound to the RNA in MM, and SAH is bound to the RNA in HH, which was prepared using nonphysiological concentrations of SAH. The structures of the RNA in these two are essentially the same; however, SAM exists in a compact conformation and SAH in an extended form (MM and HH in Figure 2, a and b). The adenine moieties of SAM and SAH interact with the RNA in a similar fashion in MM and HH, respectively, but their methionine tails form distinct contacts with the RNA. In addition to these two structures, three other models with SAM in an extended form (MH1 and MH2), and with SAH in a compact conformation (HM) were generated and were used as starting structures in the MD simulations (Figure 2c, and Figure S1 in Supporting Information). The method by which these three models were generated is given in Table 1. The model systems were conceived to examine the relative binding ability of SAM in the compact and extended form to the riboswitch, and similarly for SAH. Thus, along with the original two structures, the additional three structures are expected to be good model systems to investigate the atomic details of the role of conformation, and the sulfonium group of SAM in the recognition mechanism of the SAM-III riboswitch. Starting from these

name

PDB ID

original ligand

ligand in MD

conformation

TIP3P

Mg2+

Na+

MM MH1 MH2 HM HH

3E5C 3E5E 3E5E 3E5C 3E5E

SAM SAH SAH SAM SAH

SAM SAM SAM SAH SAH

compact extended extended compact extended

7550 7539 7538 7545 7539

25 25 25 26 26

1 1 1 0 0

a SAM was converted to SAH by deleting the extra methyl group, and SAH was converted to SAM by adding a methyl group to the S atom, followed by 100-step ABNR minimizations. The energy minimizations were done by keeping the non-hydrogen atoms of the RNA constrained. The difference between MH1 and MH2 is the orientation of the methyl group connected to S of SAM; the methyl group can be added to either side of the plane formed by S, and the connecting CH2 groups of SAH.

structures, five independent MD simulations were performed for 50 ns each. All the MD simulations were performed using the NAMD25 and CHARMM26 biomolecular simulation programs. The CHARMM27 all-atom nucleic force field27,28 along with modified TIP3P water model29 was used. Force field parameters for SAH and SAM are available along with the CHARMM biomolecular force fields.27,28,30 Initially, the five starting structures were solvated in a water box (40 × 32 × 25 Å), and water molecules present within 2.2 Å of the non-hydrogen atoms of the RNA/SAM/SAH were eliminated. The size of the water box was chosen so that about 9 Å padding of the solvent exists from all sides. The crystallographic water molecules were retained, and the crystallographic Sr2+ ions were replaced by Mg2+ ions. The whole system was made electrically neutral by adding the required number of Mg2+/Na+ ions. The final systems of (MM, MH1, MH2) and (HM and HH) contained 25 Mg2+ and 1 Na+, and 26 Mg2+ ions, respectively (Table 1). The five solvated systems were subjected to a 500-step adopted basis Newton-Raphson (ABNR) minimization followed by a 100 ps MD simulation in the NVT ensemble for equilibration. During the minimization and equilibration, the non-hydrogen atoms of the RNA, SAM, and SAH were restrained using mass-weighted harmonic constraints of 10 kcal/mol/Å2. The systems then underwent 500-step ABNR minimization after the restraints were removed, which were then used for production simulations. Initial minimizations, equilibrations, and the analysis of the MD trajectories were done using the CHARMM program, and the production simulations were performed using the NAMD program at the NPT ensemble. Particle mesh Ewald summation method31 was used for the calculation of long-range electrostatic interactions. SHAKE algorithm32 was used to constrain all covalent bonds involving hydrogen atoms, which allowed the use of integration time of 2 fs. The production simulations extended for 50 ns for each of the systems, and the coordinates were saved every 5 ps. The analysis of MD trajectories was done on the last 30 ns of the simulations, and the initial 20 ns of the simulations were treated as the equilibration period. The errors presented in the tables represent the standard error of the mean calculated from block averages of every 5 ns from 20 to 50 ns. The interaction energy calculations were done using the “inter” command implemented in the CHARMM program. The values include contributions from both electrostatic and LennardJones terms corresponding to the interacting groups. The threedimensional representations of the structures depicted in this paper were made using the VMD program.33

9922

J. Phys. Chem. B, Vol. 114, No. 30, 2010

Priyakumar

Figure 3. Nucleotides in the binding pocket of the aptamer involved in (a) hydrogen bonding and (b) stacking interactions with the adenine moiety of SAM/SAH and the binding pocket of the RNA. (c) Probability distributions corresponding to the hydrogen bonds obtained from the five MD simulations.

TABLE 2: Interaction Energies (kcal/mol) between the Adenine Moiety of SAM and the Bases That Form the Binding Pocket (BP) MM

MH1

MH2

HM

G26 -9.9 ( 0.3 -11.1 ( 0.0 -11.3 ( 0.1 -2.2 ( 0.2 A73 -0.2 ( 0.0 -1.1 ( 0.2 -0.1 ( 0.0 -0.9 ( 0.6 C25 -1.4 ( 0.1 -0.4 ( 0.0 -0.6 ( 0.0 -1.7 ( 0.6 G90 -6.6 ( 0.3 -3.7 ( 0.1 -5.3 ( 0.2 -7.1 ( 0.5 A64 -0.2 ( 0.0 -2.5 ( 0.1 -1.2 ( 0.2 0.0 ( 0.0 U72 -2.7 ( 0.1 -3.1 ( 0.0 -2.0 ( 0.2 -5.5 ( 0.3 BP -20.9 ( 0.6 -21.8 ( 0.3 -20.6 ( 0.4 -17.4 ( 0.4

HH -4.1 ( 0.8 -0.5 ( 0.1 0.0 ( 0.0 -0.2 ( 0.0 0.0 ( 0.0 -5.1 ( 0.2 -9.9 ( 0.9

Results and Discussion The analysis of the MD trajectories primarily focused on identifying the factors that control recognition of SAM over SAH, and those responsible for the stronger binding of SAM in the binding pocket. In the following sections, the ability of the RNA to recognize the cognate ligand, the role of the ligand conformation and the sulfonium group in such a discrimination, and the associated RNA structural changes are discussed. Differentiation of SAM from SAH by the SMK Box. The adenine base part of the ligand in all the five starting structures interact with the RNA in a similar fashion. Such interactions via hydrogen bonding and stacking are depicted in Figure 3a,b. The interaction energies of each of the bases given in Figure 3a,b with the adenine moiety of the ligands are given in Table 2. The overall interaction energy involving the binding pocket is more favorable in the presence of SAM compared to SAH, though the sites of interactions in the initial configurations are the same in both the cases. G26 plays a major role in stabilizing the ligand in the binding pocket via hydrogen bonding, contributing about 50% or more of the overall energies in MM, MH1, and MH2. The contribution from G26 reduces substantially in the presence of SAH ligand as observed in both the MD simulations (HM and HH). On the contrary, the other base involved in hydrogen bonding with the adenine moiety of SAM/ SAH, A73, seems to have a weak interaction in all the simulations with a minimum value of only -1.1 kcal/mol. Such

a minor contribution of A73 toward the binding energy seems to imply that this hydrogen bond may not be crucial for the stabilization of the ligand in the binding pocket,but however, may play a different role. Lu et al. have suggested that it is possible that A73 is important for the formation of the binding pocket rather than for ligand stabilization.23 The crystal structure of the riboswitch showed that the adenine moiety of SAM/SAH is positioned in such a way that it connects U72 of P1 and G90 of P2 via stacking to form a continuous single RNA strandlike structure (Figure 3b). Bases, G90 along with C25, and U72 along with A64, form the ceiling and floor for the adenine moiety of SAM/SAH, respectively, that possibly contribute to the stabilization of the ligand in the binding pocket via stacking type interactions. The interaction energies show major contribution from U72 and G90 bases toward ligand stabilization compared to the other two nucleotides (C25 and A64) emphasizing their importance. Notably, experimental studies showed that mutations of either G90 or U72 result in loss of SAM binding activity.23 The probability distributions corresponding to the four hydrogen bonds from each of the five MD simulations are depicted in Figure 3c. The three hydrogen bonds between G26 and SAM (MM, MH1, and MH2) are well maintained throughout the MD simulations with minor deviation from the optimal hydrogen bond distance involving O2′ of G26 in MM (Figure 3c). However, these hydrogen bonds sample longer distances in the simulations involving SAH, indicating weaker binding compared to SAM consistent with experiments. Thus, both geometric and energetic parameters confirm that the interactions between G26 and the adenine moiety of SAM are retained, while those of SAH are partially lost. More details on the structural changes of the RNA and sampling of longer distances in the presence of SAH are discussed below. The single hydrogen bond involving A73 reveals contrasting trends, where it is well maintained in MH1 and HH and exhibits nonzero probabilities for longer distances in the other three simulations (Figure 3c). As discussed above, the stabilization energy due to the interaction of A73 with the adenine part of the ligand is insignificant compared to the other key hydrogenbonding and stacking-type interactions. Overall, the adenine moiety of SAM is more favorably bound to the binding pocket of the RNA compared to that of SAH (Table 2). SAH gradually moves out of the binding pocket in both the simulations (HH and HM), with both SAH and the RNA sampling alternate conformational spaces than the ones given in Figure 3. Thus, the riboswitch is capable of discriminating SAM over SAH, and the apparent difference between the two ligands, the sulfonium group, is expected to play a role in such a selectivity. Structure of the RNA. Inspection of the MD trajectories reveals structural changes in the RNA, especially in the simulations carried out in the presence of SAH. The average root-mean-square deviations (rmsd), and root-mean-square fluctuations (rmsf) calculated for the RNA and the binding pocket are given in Table 3. The time series of the rmsd values and the residue level fluctuation data are presented in the Supporting Information (Figures S2 and S3). The structures of the aptamers closely resemble the crystal structure in the presence of the SAM ligand. The rmsd values of the whole RNA are similar in the three cases (MM, MH1, and MH2) further confirming our hypothesis that the RNA retains its threedimensional structure irrespective of the conformation of the ligand. The binding pocket undergoes minimal structural deviations (1.3 Å) in MH1 with respect to the crystal structure. In MM and MH2, A73 base of the aptamer moves away from the

SMK/SAM-III Riboswitch

J. Phys. Chem. B, Vol. 114, No. 30, 2010 9923

TABLE 3: Mean Rmsd (Å) of the Overall Structure of the RNA and of the Nucleotides That Form the Binding Pocket (BP) with Respect to the X-ray Crystal Structure, and the Average Rmsf Values (Å) of the RNA and the Binding Pocket Calculated with Respect to the Average Structure from the MD Simulations rmsd, RNA rmsd, BP rmsf, RNA rmsf, BP

MM

MH1

MH2

HM

HH

3.20 ( 0.14 2.24 ( 0.03 2.07 1.59

2.93 ( 0.07 1.29 ( 0.01 1.40 1.01

2.92 ( 0.10 2.67 ( 0.05 1.59 1.39

4.11 ( 0.09 3.19 ( 0.12 2.02 1.75

6.90 ( 0.50 4.55 ( 0.49 2.98 3.03

binding pocket leading to marginally larger values of rmsd than that in MH1. As discussed above, the single hydrogen bond formed by A73 with the ligand is weak (∼-1 kcal/mol), which leads to its disruption (Figure 3), and is capable of sampling a large conformation space. This effect is also reflected in the fluctuation data (Figure S3 in the Supporting Information), where A73 is less flexible in MH1 than in the other two simulations done in the presence of SAM. The overall RNA structure and the binding pocket underwent larger structural deviations in the presence of SAH as compared to SAM. In both HM and HH, the ligand undergoes partial unbinding from the binding pocket, leading to the sampling of longer hydrogen bond donor-acceptor distances as discussed above. For example, SAH along with A73 moves from the binding pocket leaving G26 in its original position in HM. As a next step, G26 moves in the opposite direction, and finally the single hydrogen bond involving A73 is also disrupted. Such structural changes lead to the larger rmsd values of the binding pocket with respect to the crystal structure. In addition to these transitions, nucleotides consisted in the SD region and the base-paired ASD regions deviate significantly from the crystal structure in HH. The rmsf indicates that nucleotides of the loops of P3 and P4, and J32 junction are more flexible than the other parts of the nucleotide, especially in the presence of SAH. Similarly, the nucleotides in the binding region are more flexible in the presence of SAH than in SAM, since the weakened interactions in the latter leads to sampling of larger conformation space. Marginally higher flexibility of the binding pocket nucleotides in MH2 and MM compared to MH1 is due to A73 as discussed above. Nonspecific Interactions are Key for the Stabilization of SAM in the Binding Pocket. Lu et al. proposed that the compact conformation of SAM found in the crystal structure is crucial for favorable RNA-ligand interactions, in addition to the specific recognition of the sulfonium group by the riboswitch.23 They also suggested that such a conformation would be unfavorable for SAH, and hence the discrimination between the two was possible. The preceding section showed that the present results remarkably reproduce the ability of SMK box to specifically recognize SAM over SAH consistent with their observation within the simulation time scale. However, the current results also suggest that SAM is stabilized in the binding pocket of the RNA in all the three conformations (MM, MH1 and MH2), and SAH is not stabilized in either compact (HM) or extended (HH) form. In other words, the RNA seems to accomplish ligand selectivity irrespective of the conformation of the ligand. This would also mean that the sulfonium group of SAM in the three different conformations interacts with alternative sites on the RNA with respect to each other. The interatomic distances between S of SAM and O/N atoms of RNA were calculated to identify the electrostatic interaction sites on the RNA. All distances less than 5 Å and those sampled for more than 10% of the simulation time in anyone of the three MD simulations (MM, MH1, and MH2) are tabulated in Table

TABLE 4: Percentage of the Simulation Time Where the S Atom of SAM Was Found within 5 Å from the Oxygen/ Nitrogen Atoms of the RNA in at Least One of the Three MD Simulations (MM, MH1, and MH2)a

a

RNA atom

MM

MH1

MH2

U72:O2P U72:O5′ U72:O4 U72:O2′ A74:N6 C75:N4 G88:O6 G88:N7 G89:O1P G89:O2P G89:O5′ G89:O6 G89:N7 G90:O2P G90:O5′ G90:O4′ G90:N9

12.0 27.6 64.4 17.4 1.0 38.4 64.6 75.8 11.7

7.6 0.4 1.0 0.4 0.9 75.4 64.2 23.2 1.2 99.0 82.3 0.2 -

88.3 25.6 2.0 15.4 21.7 18.7 30.2 21.3 6.5 98.7 93.2 1.8 -

Values of 10% or more are tabulated.

Figure 4. Probability distributions corresponding to the electrostatic interactions between the S atom of SAM and O/N atoms of the RNA corresponding to Table 4. Data from MM, MH1, and MH2 simulations are given in blue, green, and red, respectively.

4, and the corresponding probability distributions are given in Figure 4. Comparison of the probability distributions indicates two diverse sets of contacts by which the sulfonium interacts with the RNA (MM vs MH1/MH2). For example, the S atom of SAM was found to be within 5 Å of O2P of G89, O5′ of G90 and O4′ of G90 for about 65% or more of the simulation time in MM. However, the sulfonium group of SAM in MH1

9924

J. Phys. Chem. B, Vol. 114, No. 30, 2010

Priyakumar

Figure 5. Oxygen/nitrogen atoms of the RNA that were present within 5 Å of the S atom of SAM for 10% or more of the simulation time (blue represents the interactions in MM, red in MH1 and red/green in MH2).

and MH2 exhibits negligible or no interaction with this set of atoms of the RNA during the whole of 50 ns. The electrostatic interactions of the S+ in MH1 and MH2 also display considerable diversity. For example, S of SAM has strong interactions with phosphate oxygen of U72 of MH2 (distance less than 5 Å during 88% of the simulation time) and not in MH1 (8%). In each of the three simulations, the methionine tail was found to be flexible, and the S atom was found to exhibit nonspecific interactions with the RNA (Figure 5) depending on the conformation of the SAM ligand. Figure 5 depicts the electronegative atoms of the RNA that take part in electrostatic interactions with the ligand and their relative positions in the structure. Using NMR spectroscopy and MD simulations, Markham et al. have showed that SAM is quite flexible and can adopt a variety of conformations in different environments.34 They have also suggested that the solvent-accessible surface area of the sulfonium group may depend on the conformation of SAM, which in turn influences the methylation processes. The solvent-accessible surface areas of the sulfur atom and the methyl group of SAM in MH1 and MH2 are almost similar to or less than that in MM (17.0 and 2.7 vs 18.7 Å2. respectively), indicating that the methyl group is equally/better protected in the extended conformations with respect to the compact conformation within the context of the binary complexes. Thus, the sulfonium group is able to participate in nonspecific electrostatic interactions in the distinct conformations studied here. SMK Box Recognizes SAM and SAH, but Stabilizes Only SAM in the Binding Pocket. Ke and co-workers have obtained crystal structures of SAM-III riboswitch bound to both SAM and SAH.23 As discussed above, the nonbond contacts of the adenine part of the ligands with the RNA are the same in both the crystal structures (Figure 2). Hence, binding of both SAM and SAH in the crystallographic conditions was possible because the RNA is capable of sensing both these ligands, especially the adenine moiety of either SAM or SAH. The RNA is able to recognize the adenine moiety primarily using G26, U70, and G90 via hydrogen-bonding and stacking interactions as discussed above. However, the riboswitch is able to stabilize only SAM in the binding pocket leading to a higher binding affinity compared to SAH, which is accomplished by the sulfonium group. The current results confirm the sulfonium group playing a major role in favorable RNA-ligand interactions via electrostatic interactions (Table 4 and Figure 5). More importantly, the findings suggest that these interactions are nonspecific, and they lead to stabilization irrespective of the conformation

adopted by the SAM ligand in the binding pocket. It is possible that the compact conformation of SAM observed in the crystal structure is preferred over the other possible conformations in the crystal environment due to crystal packing and contacts. Similarly, stabilization of SAH in the SMK box in the crystal environment was possible as the lack of such electrostatic interactions due to the absence of sulfonium group that is proposed to be necessary for the stabilization of the ligand in the binding pocket is most likely compensated by crystal packing. A recent molecular dynamics study on the adenine riboswitch showed that certain nonbonded interactions that are not stable in solution may be stabilized in crystal environment.9 The electron density of the adenosine moiety of SAM bound to SMK box was well-defined, while that of the rest of the molecule was not, and the authors suggested that the RNA does not recognize the methionine tail.23 Examination of the available crystal structure of SAM-bound SAM-I, SAM-II, and SAMIII23,35,36 riboswitches indicate that the conformations of the bound ligands are distinct. A previous study on the conformational analysis of SAM also concluded that, while it prefers an anti conformation in solution, the preference is not so straightforward when bound to proteins.34 Recently, Montage et al. obtained the crystal structures of SAM-I riboswitch bound to SAM and SAH.22 They have showed that both SAM and SAH are bound to the RNA in a compact conformation, indicating that SAH is capable of assuming such a conformation similar to SAM. On the basis of the results discussed above and the available experimental results, we propose that the conformation of SAM in the SMK box may not be crucial for binding as long as the sulfonium group has favorable electrostatic interactions with the RNA. Accordingly, the recognition of the ligand is based only on the adenine moiety (present in both SAM and SAH), and the selection of SAM and the overall discrimination of SAM over SAH are due to nonspecific interactions involving the sulfonium group. High-resolution NMR experiments may be able to verify the conformational diversity of the ligand in the context of the SMK box-SAM complex. The ligand discrimination mechanism proposed here is based on the structure and dynamics of the SMK box, and the same may not be applicable for the other classes of SAM riboswitches. Conclusions MD simulations were used to understand the ligand recognition mechanism adopted by the SAM-III riboswitch, in particular the discrimination of SAM over SAH. The geometric and energy

SMK/SAM-III Riboswitch analyses indicate stronger binding of SAM in the binding pocket of the RNA and partial unbinding of SAH during the simulations, consistent with experimental results. The partial unbinding of SAH is associated with structural rearrangement of the nucleotides of the binding pocket leading to larger rmsd values. The calculations along with the available experimental data suggest that both SAM and SAH are specifically recognized by the riboswitch using G26, U72, and G90 via hydrogenbonding and stacking-type interactions. SAM was found to be stabilized in the binding pocket in all the three distinct conformations considered in the present study. The methionine tail of SAM was found to be flexible, and the sulfonium group was found to interact with several electronegative atoms of the RNA. Hence, we propose that the preferential stabilization of SAM in the binding pocket is not because of the ability of the aptamer to specifically recognize the sulfonium sulfur, but due to nonspecific interactions. Acknowledgment. This paper is dedicated to Professor J. Subramanian on the occasion of his 70th birthday. U.D.P. thanks Prof. Alexander D. MacKerell Jr., University of Maryland, Baltimore, for his support and encouragement. Department of Atomic Energy (India) and Department of Science & Technology (India) are acknowledged for financial assistance. Supporting Information Available: Figures of starting structures, root-mean-square deviations, and root-mean-square fluctuations of the SAM-III riboswitch. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Roth, A.; Breaker, R. R. Annu. ReV. Biochem. 2009, 78, 305–334. (2) Serganov, A. Curr. Opin. Struct. Biol. 2009, 19, 251–259. (3) Henkin, T. Genes DeV. 2008, 22, 3383–3390. (4) Garst, A. D.; Batey, R. T. BBAsGene Regul. Mech. 2009, 1789, 584–591. (5) Vicens, Q. J. Inclusion Phenom. Macrocyclic Chem. 2009, 65, 171– 188. (6) Greenleaf, W. J.; Frieda, K. L.; Foster, D. A. N.; Woodside, M. T.; Block, S. M. Science 2008, 319, 630–633. (7) Rieder, R.; Lang, K.; Graber, D.; Micura, R. ChemBioChem 2007, 8, 896–902. (8) Lemay, J. F.; Penedo, J. C.; Tremblay, R.; Lilley, D. M. J.; Lafontaine, D. A. Chem. Biol. 2006, 13, 857–868. (9) Priyakumar, U. D.; MacKerell Jr., A. D. J. Mol. Biol. 2010, 396, 1422–1438. (10) Kelley, J. M.; Hamelberg, D. Nucleic Acids Res. 2010, 38, 1392– 1400. (11) Whitford, P.; Schug, A.; Saunders, J.; Hennelly, S.; Onuchic, J.; Sanbonmatsu, K. Biophys. J. 2009, 96, 7–9.

J. Phys. Chem. B, Vol. 114, No. 30, 2010 9925 (12) Huang, W.; Kim, J.; Jha, S.; Aboul-ela, F. Nucleic Acids Res. 2009, 37, 6528–6539. (13) Villa, A.; Wohnert, J.; Stock, G. Nucleic Acids Res. 2009, 37, 4774– 4786. (14) Sharma, M.; Bulusu, G.; Mitra, A. RNA 2009, 15, 1673–1692. (15) Wang, J.; Breaker, R. Biochem. Cell Biol. 2008, 86, 157–168. (16) Epshtein, V.; Mironov, A.; Nudler, E. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 5052–5056. (17) McDaniel, B.; Grundy, F.; Artsimovitch, I.; Henkin, T. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 3083–3088. (18) Corbino, K.; Barrick, J.; Lim, J.; Welz, R.; Tucker, B.; Puskarz, I.; Mandal, M.; Rudnick, N.; Breaker, R. Genome Biol. 2005, 6, R70. (19) Fuchs, R. T.; Grundy, F. J.; Henkin, T. M. Nat. Struct. Mol. Biol. 2006, 13, 226–233. (20) Weinberg, Z.; Regulski, E.; Hammond, M.; Barrick, J.; Yao, Z.; Ruzzo, W.; Breaker, R. RNA 2008, 14, 822–828. (21) Poiata, E.; Meyer, M.; Ames, T.; Breaker, R. RNA 2009, 15, 2046– 2056. (22) Montange, R.; Mondrago´n, E.; van Tyne, D.; Garst, A.; Ceres, P.; Batey, R. J. Mol. Biol. 2009, 396, 761–772. (23) Lu, C.; Smith, A.; Fuchs, R.; Ding, F.; Rajashankar, K.; Henkin, T.; Ke, A. Nat. Struct. Mol. Biol. 2008, 15, 1076–1083. (24) Fuchs, R.; Grundy, F.; Henkin, T. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 4876–4880. (25) Phillips, J. C.; Braun, R.; Wang, W.; Gumbart, J.; Tajkhorshid, E.; Villa, E.; Chipot, C.; Skeel, R. D.; Kale, L.; Schulten, K. J. Comput. Chem. 2005, 26, 1781–1802. (26) Brooks, C. L.; Brooks, B. R., III; Mackerell, A. D.; Nilsson, L.; Petrella, R. J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A. R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R. W.; Post, C. B.; Pu, J. Z.; Schaefer, M.; Tidor, B.; Venable, R. M.; Woodcock, H. L.; Wu, X.; Yang, W.; York, D. M.; Karplus, M. J. Comput. Chem. 2009, 30, 1545–1614. (27) Foloppe, N.; MacKerell, A. D., Jr. J. Comput. Chem. 2000, 21, 86–104. (28) MacKerell, A. D., Jr.; Banavali, N. K. J. Comput. Chem. 2000, 21, 105–120. (29) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. J. Comput. Chem. 1983, 79, 926–935. (30) MacKerell, A. D.; Bashford, D.; Bellott, M.; Dunbrack, R. L.; Evanseck, J. D.; Field, M. J.; Fischer, S.; Gao, J.; Guo, H.; Ha, S.; JosephMcCarthy, D.; Kuchnir, L.; Kuczera, K.; Lau, F. T. K.; Mattos, C.; Michnick, S.; Ngo, T.; Nguyen, D. T.; Prodhom, B.; Reiher, W. E.; Roux, B.; Schlenkrich, M.; Smith, J. C.; Stote, R.; Straub, J.; Watanabe, M.; Wiorkiewicz-Kuczera, J.; Yin, D.; Karplus, M. J. Phys. Chem. B 1998, 102, 3586–3616. (31) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T. A.; Lee, H.; Pedersen, L. G. J. Chem. Phys. 1995, 103, 8577–8593. (32) Ryckaert, J.-P.; Ciccotti, G.; Berendsen, H. J. C. J. Comput. Phys. 1977, 23, 327–341. (33) Humphrey, W.; Dalke, A.; Schulten, K. J. Mol. Graphics 1996, 14, 33–38. (34) Markham, G.; Norrby, P.; Bock, C. Biochemistry 2002, 41, 7636– 7646. (35) Montange, R.; Batey, R. Nature 2006, 441, 1172–1175. (36) Gilbert, S.; Rambo, R.; Van Tyne, D.; Batey, R. Nat. Struct. Mol. Biol. 2008, 15, 177–182.

JP1042427