Bacterial RNase P RNA Is a Drug Target for AminoglycosideâArginine

1896

Bioconjugate Chem. 2008, 19, 1896–1906

Bacterial RNase P RNA Is a Drug Target for Aminoglycoside-Arginine Conjugates Alexander Berchanski and Aviva Lapidot* Department of Organic Chemistry, The Weizmann Institute of Science, Rehovot 76100, Israel. Received May 14, 2008; Revised Manuscript Received July 29, 2008

The ribonuclease P (RNase P) holoenzymes are RNPs composed of RNase P RNA (PRNA) and a variable number of P protein subunits. Primary differences in structure and function between bacterial and eukaryotic RNase P and its indispensability for cell viability make the bacterial enzyme an attractive drug target. On the basis of our previous studies, aminoglycoside-arginine conjugates (AACs) bind to HIV-1 TAR and Rev responsive element (RRE) RNAs significantly more efficiently than neomycin B. Their specific inhibition of bacterial rRNA as well as the findings that the hexa-arginine neomycin derivative (NeoR6) is 500-fold more potent than neomycin B in inhibiting bacterial RNase P, led us to explore the structure-function relationships of AACs in comparison to a new set of aminoglycoside-polyarginine conjugates (APACs). We here present predicted binding modes of AACs and APACs to PRNA. We used a multistep docking approach comprising rigid docking full scans and final refinement of the obtained complexes. Our docking results suggest three possible mechanisms of RNase P inhibition by AACs and APACs: competition with the P protein and pre-tRNA on binding to P1-P4 multihelix junction and to J19/4 region (probably including displacement of Mg2+ ions from the P4 helix) of PRNA; competition with Mg2+ ions near the P15 loop; and competition with the P protein and/or pre-tRNA near the P15 helix and interfering with interactions between the P protein and pre-tRNA at this region. The APACs revealed about 10-fold lower intermolecular energy than AACs, indicating stronger interactions of APACs than AACs with PRNA.

INTRODUCTION The complexity and diversity of RNA structures offer targets for small molecule ligands to be used as pharmacological agents (1). Ribonucleoprotein complexes (RNPs) are ubiquitous and essential components of all cells and appealing targets for new drugs due to their diverse functional roles in various cellular processes (2, 3). The ribonuclease P (RNase P) holoenzymes are RNPs composed of RNase P RNA (PRNA) and a variable number of P protein subunits: at least 1, 4, and 9 in Bacteria, Archaea and Eukarya, respectively (4, 5). Fundamental differences in structure and function between bacterial and eukaryotic RNase P and its indispensability for cell viability make the bacterial enzyme an attractive drug target candidate (6-10). Bacterial RNase P is composed of one RNA (∼400 nucleotides) and one small P protein (∼120 amino acids). Although the PRNA can catalyze the pre-tRNA-processing reaction in Vitro in the absence of P protein at high salt concentrations (11), the P protein significantly influences multiple aspects of catalysis and is required for function in ViVo (12). P protein plays a central role in RNase P function: it interacts with the 5′ leader of pretRNA substrates, leading to enhanced affinity for substrates (13, 14). In addition, P protein increases metal ion affinity (15) and pre-tRNA cleavage rate constants (16). Cross-linking studies have suggested that the central cleft of the P protein interacts with pre-tRNA 5′ leaders of at least 4 nucleotides in length, which locates the protein in close proximity to the active site (14). Crystal structures (13, 17) and the NMR structures (18) of P proteins reveal a remarkably similar overall topology for P proteins from different bacteria. It was suggested that three regions of the P protein interact with the RNA: the RNR motif, the central cleft, and the metal binding loop. The RNR motif is * Corresponding author. Tel: 972-8-9343413. Fax: 972-8-9344142. E-mail: [email protected].

a highly basic region (K52 to R68, Bacillus subtilis) abundantly conserved among all bacterial P proteins, suggesting that this region is functionally important (19-21). Therefore, inhibition of bacterial RNase P activity could be accomplished with a compound that either interacts directly with the catalytic core in the PRNA or disrupts RNP interactions essential for the assembly of a functional RNase P holoenzyme. Aminoglycosides (e.g., neomycin, neamine, paromomycin, and gentamicin) are small, polycationic molecules. These compounds are used clinically as antibacterial agents because of their ability to specifically bind prokaryotic rRNA and to inhibit bacterial protein synthesis (22). It has become apparent that aminoglycosides as well as their derivatives bind mRNAs (23), tRNAs (24), viral RNAs (25-27), and catalytic (28, 29) RNAs and that the binding of these ligands could alter the function of the RNA target. Aminoglycosides also interact with two essential elements of the human immunodeficiency virus type 1 (HIV-1) genome, Rev responsive element (RRE) and the transactivation responsive element (TAR) (26). Lapidot and co-workers have shown that arginine-aminoglycoside conjugates (AACs, Figure 1) are significantly more efficient antiHIV-1 agents than aminoglycosides, as these conjugates comprise the RNA binding ability of aminoglycosides and the specific binding of arginine moieties to HIV-1 TAR and RRE RNAs (30-36). Significantly, AACs specifically inhibit bacterial rRNA (37). For example, the binding constants (KD) of hexaarginine neomycin B (NeoR6) for TAR and RRE RNAs were 5 and 23 nM, respectively (35). AACs (especially NeoR6) inhibit the binding of trans-activator protein (Tat) to various RNAs by mimicking the conserved binding arginine/lysine-rich motif of the Tat protein (35). Thus, we here propose that AACs, with their multiple arginine moieties, could also mimic the conserved arginine/lysine residues in the RNR motif of the bacterial RNase P protein and disrupt bacterial RNase P

10.1021/bc800191u CCC: $40.75  2008 American Chemical Society Published on Web 08/20/2008

Drug Target for Aminoglycoside-Arginine Conjugates

Bioconjugate Chem., Vol. 19, No. 9, 2008 1897

Figure 1. (A and B) Schematic representation of AACs, APACs, and aminoglycosides used in this study. R, L-arginine; r, D-arginine. (C) PRNAbound conformations of NeoR6, Neo-r9, and Neo-r6. The aminoglycoside cores of the compounds are colored in yellow and the arginine moieties in blue.

holoenzyme assembly. Already in their report regarding the high potency of NeoR6 and triarginine-gentamicin C conjugate (R3G), Gopalan and Lapidot (7) showed that AACs act as potent and selective peptidomimetics that could prevent RNP assembly. For example, NeoR6 revealed nearly 500-fold higher potency than neomycin B in inhibiting bacterial RNase P (7). Peptides carrying an arginine-rich sequence of Tat and a nonaD-arginine peptide, bind TAR RNA with high affinity and specificity (e.g. ref 38 and 39). Arginine-rich peptides comprise a common motif of RNA recognition by proteins (39). Although the dominant contributions of the arginine side-chains may differ between complexes, the ability of the arginine side chains to be involved in electrostatic interactions, hydrogen bond formation, and stacking interactions makes arginine an important moiety for RNA recognition (39). Attempts to mimic the arginine-rich peptides led to the development of novel RNA ligands (e.g., tetra-arginine kanamycin (R4K) and R3G (30), and NeoR6 (32). Recently, we synthesized a novel set of poly arginine (hexa- and nona-arginines) aminoglycoside conjugates (APACs, Figure 1). Their anti-HIV-1 activities revealed high potency for the hexa-D-arginine-neomycin conjugate (Neo-r6), nona-D-arginine-neomycin conjugate (Neo-r9), and nona-Darginine-neamine conjugate (Neam-r9) (40, 41). Thus, we anticipate that, as well as NeoR6, ParomoR5, and NeoR5, they may also bind PRNA (and other RNAs) and inhibit RNase P activity.

Westhof and co-workers (42, 43) succeeded in making an RNase P model with the aid of computer programs and data from physical-chemical experiments on the P protein (44). Their RNA model is in good agreement with most of the crystallography results (45, 46) including the core of the catalytic site. Thus, we, as well as Fierke and co-workers (47), utilize the whole modeled PRNA molecule for further investigation. This approach avoids complications introduced by unresolved regions and the effects of crystal packing contacts (47). These advances in our understanding of RNase P provide insight into the interface between the RNA and protein worlds. The development of many drugs (e.g., HIV-1 protease inhibitors) was heavily influenced by or based on structure-based design and screening strategies (48). Computational methodologies have become a crucial component of many drug discovery programs (48). The main aim of our present study is predicting the binding modes of AACs and APACs to PRNA. The model presented by Westhof, Gopalan, and co-workers (43) was utilized in this study for docking AACs and APACs. We used a multistep docking approach (Figure 2) containing (i) geometric, geometricelectrostatic, and geometric-hydrophobic docking full scans by MolFit; (ii) intersecting of the lists of predictions from geometric-electrostatic-hydrophobic docking scans for identify-

1898 Bioconjugate Chem., Vol. 19, No. 9, 2008

Berchanski and Lapidot

structure (out of 17) from 1qd3. Neam-r9 was built by trimming aminoglycoside rings III and IV of the Neo-r9 model. All these modeled structures were solvated in water and energy minimized (Figure 2). In general, all the energy minimizations in this study were performed for molecules immersed in a layer of 5 Å of water until the maximum derivative was less than 0.001 using the Discover 3 module of InsightII (Accelrys, Inc., San Diego, CA, USA) and the CVFF force field.

Figure 2. Schematic representation of the molecular modeling and multistep docking procedure followed in this study.

ing putative geometrically and chemically suitable binding sites; and (iii) final refinement of the obtained complexes by Discover3. Several preferred AACs and APACs binding positions were highlighted by this approach. On the basis of these models, we here propose that AACs and APACs can inhibit RNase P activity by (i) interacting with the P protein/pre-tRNA binding site of PRNA; (ii) competing with the P protein for binding PRNA; and/or by (iii) displacing Mg2+ ions near the PRNA P15 loop leading to interference with RNase P catalysis. This molecular docking approach may be useful in drug design.

EXPERIMENTAL PROCEDURES AACs and APACs. The synthesis, purification, and analysis of the following compounds NeoR6, ParomoR5, R3G, hexaD-arginine-neomycin conjugate (Neo-r6), nona-D-arginine-neomycin conjugate (Neo-r9), and nona-D-arginine-neamine conjugate (Neam-r9) (biologically stable enantiomers) (Figure 1) were previously described (30-36, 41). General Procedure of Docking. We docked aminoglycosides and their arginine conjugates as well as RNase P protein to the three-dimensional (3D) model structure of the PRNA. A multistep docking procedure was used: exhaustive rotationtranslation docking scans by MolFit, followed by intersecting lists of predictions and flexible ligand docking by Discover3 (Figure 2). We used the model coordinates of bacterial RNase P holoenzyme of B. subtilis described by Westhof and coworkers (43). This RNA-protein complex consists of RNA component (nucleotides 4-395), pre-tRNA molecule (includes nucleotides -9 to 72), and P protein. Molecular docking was performed with free PRNA (without P protein and pre-tRNA). Models of NeoR6, ParomoR5, NeoR5, Neo-r9, and Neo-r6 were constructed by addition of arginines to neomycin B (its 3D coordinates were taken from PDB entry 1qd3 (49)) using the Biopolymer module of InsightII. We used the first NMR

Full Rigid-Body Docking of Ligands to PRNA. AACs (NeoR6, NeoR5, and ParomoR5), APACs (Neo-r9, Neo-r6, and Neam-r9), neomycin B (PDB entry 1qd3 (49)), and P protein were docked to PRNA using the program MolFit (50). MolFit treats the molecules as rigid bodies. They are represented by 3D grids in which each grid point carries information concerning its position with respect to the surface/interior of the molecule. The surface grid points carry chemical information such as the electrostatic potential or the hydrophobicity of the surface. MolFit performs an exhaustive scan of the relative rotations and translations of the molecules and produces a list of models. Since PRNA consists of many negative charges, while AACs and APACs are highly positively charged compounds, at first we performed full geometric-electrostatic scans (51) of these ligands against PRNA. The electrostatic potential of each molecule was calculated using the program Delphi as implemented in the InsightII package. Each full docking scan tested 8760 relative orientations (angular grid interval of 12°), and for each orientation, one best scoring solution was saved. These solutions were further sorted by their geometric-electrostatic complementarity score. Geometric, geometric-hydrophobic (50), and geometricelectrostatic docking scans were performed for all ligands. Geometric-electrostatic-hydrophobic (GEH) complementarity scores were obtained by intersecting the lists of predictions from geometric, geometric-electrostatic, and geometric-hydrophobic docking scans, as described previously (50) (Figure 2). The nearly correct solutions are likely to be included in each of the three lists, that is, in a subset of common solutions. For this subset of solutions, it is possible to combine the geometric, electrostatic, and hydrophobic scores to obtain a combined geometric-electrostatic-hydrophobic score, Sgeo+elec+hydro ) Sgeo + e · Selec + h · Shydro, where Selec is the difference between the geometric-electrostatic and the geometric scores, and Shydro is the difference between the geometric-hydrophobic and geometric scores for a given solution. The combination of electrostatic and hydrophobic complementarity with geometric complementarity improves the docking results for complexes of proteins. This improvement is due, in some cases, to the higher combined score for the nearly correct solution. Some of the improvement in rank is also due to the elimination of false solutions, which are found in only one of the 3 lists (geometric, geometric-electrostatic, or geometric-hydrophobic) and are eliminated in the intersection process (50). Flexible Docking of Ligands to PRNA. The top-ranked GEH MolFit scan solutions were used for input to the flexible ligand docking performed by the program Discover3 (Figure 2). We added the hydrogens to PRNA by using the Biopolymer module of InsightII. The PRNA was immersed in a layer of 5 Å of water and energy minimized in complex with each ligand represented by its top-ranked GEH MolFit scan solution using the Discover 3 module of InsightII. We tested several possible binding sites of each ligand to PRNA formed by GEH MolFit clusters. The intermolecular energy of the finally refined complexes was measured by the Docking module of InsightII


according to maximal radii of ligands. The best models were selected by the lowest intermolecular energy.

RESULTS Rationale. The increased (i) affinity of AACs to HIV-1 TAR and RRE (35), and (ii) potency in disrupting RNP interactions and inhibiting bacterial RNase P, compared to aminoglycosides (7), led us to hypothesize that NeoR6 and other structurally similar AACs and APACs may inhibit RNase P activity by interacting with PRNA. Therefore, our main objective was deciphering the structure-function relationships of the two families of aminoglycoside-arginine conjugates (AACs and APACs) in the context of their interactions with PRNA, with the aim of developing effective novel antimicrobial drugs. A structural model proposed for Bacillus subtilis holoenzymesubstrate complex (43) was employed. The predicted binding sites of AACs and APACs to several regions of PRNA obtained by docking as well as their interference with the holoenzyme-pretRNA interaction for the cleavage process of pre-tRNA are described below. Rigid-Body Docking of P Protein, APACs, and AACs to PRNA. We assume that AACs and APACs structurally mimic arginine/lysine-rich P protein (19-21) and may disrupt the formation of the RNase P holoenzyme complex by preventing binding of the P protein to the RNA moiety. Thus, the most potent compounds of AACs and APACs were docked to the naked PRNA molecular model. Geometric, geometric-hydrophobic, and geometric-electrostatic docking scans were performed for P protein, APACs, and AACs to PRNA using the program MolFit (see Experimental Procedures and Figure 2). Each predicted MolFit solution is a plausible position of ligand on PRNA. Since geometric-electrostatic docking does not always suggest the nearly correct solution at the first ranked position, the intersection of the lists of predictions from geometric, geometric-electrostatic, and geometric-hydrophobic docking scans was also performed according to a procedure previously described (50). The use of this procedure (i) improves the rank of solutions, which not only have good electrostatic contacts with macromolecule but also increase the significance of geometric and hydrophobic contacts (in case they exist); (ii) drastically reduces the number of putative solutions; and (iii) forms clusters. After intersecting GEH MolFit scans of several top-ranked solutions for each cluster, optimal matches with PRNA are obtained, which are very useful for following analysis and final refinement. We docked the P protein to PRNA (GEH MolFit scans with intersection of the results). We obtained a cluster of putative MolFit solutions (which includes the top ranked ones) exactly at the site that was predicted by Westhof and co-workers (43) and confirmed by Fierke and co-workers (47) (Figure 3 B). Our top ranked solution was slightly rotated relative to the predicted position of the P protein within the RNase P holoenzyme structure (43) since the P protein consists of many arginines and lysines, not only at the RNR motif but also at other regions. (a) Docking of APACs. The geometric-electrostatic docking scans of APACs (Neo-r9, Neam-r9, and Neo-r6) revealed two very large clusters and several smaller ones (Figure 3 C, E and G). The 60 top ranked solutions were within these two clusters. The first cluster was situated at the region of PRNA (P4, P3, P2, and J19/4, Figure 3 C); this region interacts with P protein and pre-tRNA (43, 47). The second cluster was located proximal to the PRNA P15 helix. The intersection of the lists of predictions from GEH MolFit docking scans drastically reduced the number of putative solutions (from 8760 to 32 for Neo-r9 and from 8760 to 43 for Neam-r9). The first ranked solutions of Neo-r9, Neam-r9, and Neo-r6 were within cluster 1 (PRNA region of P4, P3, P2, and J19/4; Figure 3 D, F, and H). This


PRNA region contacts RNR and neighboring motifs of P protein and pre-tRNA (43, 47). Therefore, our suggestion, that APACs structurally mimic an RNR motif of the P protein, is supported. Cluster 2 (proximal to P15), which also consists of several high ranked docking solutions, must also be considered for a binding site. (b) Docking of AACs. The full geometric-electrostatic docking scans of AACs (NeoR6, ParomoR5, NeoR5, and R3G) and neomycin B (Figure 4A, C, E, G, and I) revealed more disperse patterns (there are many more clusters of the putative solutions) than for APACs; however, cluster 1 at the region P4, P3, P2, J19/4, and cluster 2 near P15, which include the 10-20 high ranked solutions, are also present for NeoR6, ParomoR5, and NeoR5 (but not for neomycin B and R3G), similar to that for APACs (Figure 3). The intersection of the lists of predictions from GEH MolFit docking scans reduced the number of putative solutions, but not as markedly as for the APACs (Figure 4B, D, F, H, and J). The first ranked solution of all AACs is within cluster 1 (PRNA region P4, P3, P2, and J19/4). Cluster 2 (near P15) also consists of several high ranked solutions. In contrast to APACs, there are many additional clusters for AACs. In general, these clusters that are not situated near PRNA regions P4, P3, P2, and J19/4 or P15 helices consist of solutions with lower MolFit GEH scores. Therfore, the preference of AACs to bind PRNA at the regions P4, P3, P2, and J19/4 or P15 is significantly weaker than that of APACs. The pattern of neomycin B binding is even more disperse than for the arginine conjugates, suggesting lower binding specificity (Figure 4B). The top ranked MolFit solutions of neomycin B are not at P4, P3, P2, and J19/4 or P15 helices, and it is difficult to prefer one cluster over the others. Refinement of APACs-PRNA Complexes. The bestscoring representatives of several predicted MolFit clusters were used for final the refinement by Discover3 (see Experimental Procedures and Figure 2). The PRNA and ligands were immersed in water, and the complex was energy minimized. Therefore, both PRNA and ligand were hydrated and flexible. The nucleotides of PRNA regions that were distant from a ligand were fixed. The ranges of intermolecular docked energies (kcal/ mol) measured according to maximal radii of the ligands for Neo-r9-PRNA complexes are from -15283 to -14386 at cluster 1, from -14441 to -12645 at cluster 2, and from -13211 to -12354 at other clusters (Table 1). Similar values were found for Neam-r9-PRNA complexes from -15897 to -13988, -14331 to -12645, and -13047 to -12211, respectively. The average values of intermolecular docked energies for Neo-r9-PRNA and Neam-r9-PRNA complexes at cluster 1 are almost the same (Table 1). To determine the PRNA nucleotides that interact with the P protein and pre-tRNA, we calculated the distances between the P protein or pre-tRNA and the PRNA atoms in the RNase P holoenzyme-pre-tRNA complex (43). The distances between all docked ligands and PRNA were also calculated. We took into consideration intermolecular distances within 4 Å between heavy atoms. The results of comparisons between binding sites of our docked ligands and those of P protein and pre-tRNA are summarized in Tables 2 and 3. The Neo-r9-PRNA complex with the lowest energy (-15283 kcal/mol) refers to the PRNA region, which binds protein P and pre-tRNA (P2, P3, P4, J18/2, and J19/4) (Figure 5A and B, and Table 2). The best Neam-r9-PRNA complex is situated exactly at this site with some different contacts. All arginine residues of Neo-r9 and Neam-r9 have electrostatic interactions with the PRNA nucleotides. Already, the MolFit scans highlighted that rings I and II of Neo-r9 neomycin core have more contacts with PRNA in comparison to rings III and IV (Figure 1). The final refinement by Discover 3 strengthens this observation. Our results reveal similar ranges



Figure 3. (A) Structural model of B. subtilis RNase P holoenzyme-pre-tRNA complex (43). The PRNA is shown as a ribbon. The important PRNA regions for interactions with pre-tRNA or P protein (according to Westhof and co-workers (43) and Fierke and co-workers (47)) are colored: P1 (black), P2 (yellow), P3 (green), P4 (cyan), and J19/4 (orange). P15 is colored magenta. P protein (dark blue) and pre-tRNA (red) are shown as ribbons. The colors and representation of PRNA, PRNA regions, pre-tRNA, and P protein are the same in Figures 4 and 5. (B) Results of P protein-PRNA GEH MolFit scans with intersection of the prediction lists. Each solution is the plausible position of ligand on PRNA, represented by the center of ligand mass (colored red). The top ranked solutions are shown in CPK representation. The colors and representation of MolFit solutions are the same for all ligands in this figure and Figure 4. (C-H) Results of MolFit geometric-electrostatic scans (C, E, and G) and GEH MolFit scans with intersection of the prediction lists (D, F, and H) for APACs (Neo-r9, Neam-r9, and Neo - r6, respectively).

of intermolecular energy for Neo-r9 and Neam-r9 (Table 1), which may be due to the fact that the number of contacts for common neomycin and neamine rings (I and II) is approximately equivalent. The refined complexes between Neo-r9 (Figure 5D) or Neamr9 with PRNA near the P15 region (cluster 2) reveal ranges of intermolecular energy similar to those of cluster 1 representatives. The complexes between Neo-r9 or Neam-r9 with PRNA had significantly higher interaction energy within clusters other than 1 and 2, indicating that the interactions of these ligands at other sites are less favorable than with the P2, P3, P4, J18/2, and J19/4 or P15. Therefore, all the docking results point that

Neo-r9 and Neam-r9 bind PRNA preferably at the protein/pretRNA binding site (or at P15) than at the other possible sites. Refinement of AACs-PRNA complexes. The ranges of intermolecular docked energies (kcal/mol) for NeoR6-PRNA complexes were from -1457 to -1403 at cluster 1, from -1427 to -1358 at cluster 2, and from -1394 to -1179 at the other clusters (Table 1). The ranges of these values for complexes of ParomoR5 and NeoR5 with PRNA were relatively similar. Figure 5C depicts the NeoR6-PRNA complex with the lowest energy (-1457 kcal/mol). For all three AACs, NeoR6, ParomoR5, and NeoR5, as well as for APACs, the complex with the lowest energy was derived from cluster 1 (P2, P3, P4, J18/



Figure 4. Results of MolFit geometric-electrostatic scans (A, C, E, and G) and GEH MolFit scans with intersection of the prediction lists (B, D, F, and H) for neomycin B and AACs (NeoR6, ParomoR5, and NeoR5, respectively). The colors and representation of PRNA and MolFit solutions are as described in Figure 3. Table 1. Intermolecular Binding Energies (kcal/mol) for Final Ligand-PRNA Complexes clusters compounds Neo-r9 Neam-r9 NeoR6 ParomR5 NeoR5 Neomycin B

cluster 1 from from from from from from

-15283 to -14386 -15897 to -13988 -1457 to -1403 -1327 to -1278 -1346 to -1304 -501 to -435

2, and J19/4). However, the other complexes with low energy were situated near P15 (cluster 2, e.g., Figure 5E). ParomoR5 and NeoR5 consistently showed somewhat higher ranges of intermolecular energies.

cluster 2 from from from from from from

-14431 to -12837 -14331 to -12645 -1427 to -1358 -1285 to -1211 -1301 to -1167 -489 to -439

other clusters from from from from from from

-13211 to -12354 -13047 to -12211 -1394 to -1179 -1156 to -1096 -1177 to -1078 -526 to -486

In contrast to the aminoglycoside-arginine conjugates (AACs and APACs), the value of intermolecular energy of the best neomycin-B-PRNA complex was -525 kcal/mol. We did not obtain significant differences in intermolecular



Table 2. Putative Ligand Interaction Sites on PRNA Based on Structural Analysis of Refined PRNA-Ligand Complexes at the P1-P4 multi-helix Junction PRNA regions Ca P3

P4

compounds

33

34

35

36

P protein Pre-tRNA Neo-r9 Neam-r9 NeoR6 ParomoR5 NeoR5

R/Kb

R/K

R/K

R/K

49

+ + + +

50

51

+ + + + + +

+ + + + + + +

52

53

54

55

56

+ + +

+ + +

+

+ +

+

Sc

C

J11/12 Pre-tRNA Neomycin B

P11

P15

185

186

188

189

191

227

230

231

246

247

258

259

+

+

+

+

+

+

+ +

+ +

+ +

+ +

+

+

C P15 260 P protein Pre-tRNA Neo-r9 Neam-r9 NeoR6 ParomoR5 NeoR5

J18/2 261

318

319

P2 320

321

322

+

+ +

P19 354

357

366

367

368

+

+

+

+

+

+ +

+ + + + +

+ + + +

+ C

P19 369 P protein Pre-tRNA Neo-r9 Neam-r9 NeoR6 ParomoR5 NeoR5 a

J19/4 371

+

372 + +

+ +

+ + +

P4 373

374

R/K

+

+ + + + +

+ + + + +

375

+ + + +

376

+

b

C: catalytic domain of PRNA. R/K: P protein arginine or lysine interact with PRNA. c S: specificity domain of PRNA.

energy between neomycin-B-PRNA complexes in the different tested regions.

DISCUSSION Validation of the RNase P Holoenzyme Model. A previously published model of the PRNA from the PRNA-proteinpre-tRNA complex, based on biochemical, phylogenetic, and biophysical studies (43), was employed in this study. In addition, data obtained from a recent RNase P holoenzyme model (47) were also considered. The constructed model of PRNA by Westhof and co-workers (43) from the RNase P holoenzymesubstrate complex (Figure 3A) of B. subtilis was significantly modified without drastically altering the overall architecture of their previous model of the PRNA (42), especially the positioning of various highly conserved nucleotides proximal to the cleavage site. Moreover, the resulting enzyme-substrate complex model is in excellent agreement with various biochemical and biophysical studies (43). The recent findings regarding detailed distance constraints within the holoenzyme-substrate complex (47) are also in accordance with the complex of Westhof/Gopalan and coworkers (43). These groups (43, 47) applied a large amount of data from previous biochemical investigations of RNase P structure in solution to construct their models. Although Fierke

and co-workers (47) claim that the biochemical model differs in details from recently published crystal structures of PRNA, the topology and relative orientations of PRNA helices of interest for our docking study (P1-P4) are similar. Fierke and co-workers (47) mapped their affinity cleavage data from B. subtilis RNase P onto the crystal structure of PRNA from B. stearothermophilus (47) and compared the relevant parts (P1-P4, J18/2, and J19/4) of these two RNA structures. This comparison suggests that, within the resolution of their model (∼10 Å), the structural model and crystal structure yield comparable results. The final model of Fierke and co-workers (47) is generally in accordance with the RNase P holoenzymesubstrate complex (43), and it is consistent with all their cleavage results, except those observed in P19. Interference of AACs and APACs with the Binding of P Protein and/or Pre-tRNA to the PRNA P1-P4 Region. It has been proposed that the PRNA catalytic domain recognizes the pre-tRNA acceptor stem, cleavage site, and the conserved CCA sequence on the 3 end of the pre-tRNA (52). Furthermore, Pan and co-workers demonstrated that the PRNA specificity domain interacts with the T-stem loop of pre-tRNA (53). RNase P needs Mg2+ ions for many functions including folding, substrate binding, and catalysis (15). The Mg2+ ions binding sites have not yet been clearly defined, although several sites,



Table 3. Putative Ligand Interaction Sites on PRNA Based on Structural Analysis of Refined PRNA-Ligand Complexes at the P15 Region PRNA regions C P15 compounds Pre-tRNA Neo-r9 NeoR6 NeoR5

255 +

256 +

257

258

259

261

+ +

+

+

+ +

+ +

262

263

264

+ +

+ +

+

C P15.1 NeoR6 NeoR5

P18

266

268

314

315

316

+ +

+

+ +

+ +

+

Table 4. IC50 Values (nM) for the Inhibition of RNase P Holoenzyme by Neomycin B and AACs IC50 (nM) compound

E. coli

Neomycin B NeoR1 NeoR5 NeoR6 Paromomycin R3G

6 × 104a 4 × 103b 500c 125d 19 × 104a 300 d

N. gonorrheoae

1e

a Ref 28. b Lapidot and Gopalan, unpublished results. c Ref 10. 7. e Lapidot and Eder, unpublished results.

d

Ref

including positions in helix P4, have been implicated in metal binding (54). It was suggested that Mg2+ ion specifically binds to a site in helix P4, at the same region of PRNA that crosslinks to the P protein, and where the putative catalytic site of the enzyme is located (47). It was reported that the formation of the P1-P4 multihelix junction is dependent on a cluster of metal ions and that this structure contributes to catalysis (55). Further corroboration for metal binding in P4 comes from NMR studies that demonstrate specific Mg2+ binding sites in a stemloop that serves as a model for the P4 helix (56). The experimental data (47, 57) and structural holoenzyme models placing the P protein near PRNA helix P4 suggest that the P protein could stabilize the PRNA structure to enhance the affinity of one or more metal ions binding to helix P4 and to facilitate catalysis (47). Therefore, the P1-P4 multihelix junction and J19/4 are the most important regions for catalytic activity of PRNA because both P protein and pre-tRNA bind to this region. Our docking studies reveal that cluster 1 of geometricelectrostatic and intersection of GEH MolFit predictions lists for all tested AACs and APACs is situated near the P1-P4 multihelix junction and J19/4 region (Figures 3-4). Cluster 1 consists of the top ranked solutions, including the first one, indicating that all tested AACs and APACs prefer binding to this region and compete with the P protein and/or pre-tRNA. Moreover, the final refined complexes with lowest energy are also derived from this cluster (Tables 1 and 2). Interference of AACs and APACs with RNase P Activity near P15. It was reported that inhibition of E. coli PRNA by neomycin B was partially attributed to its capability to displace Mg2+ ions from P15 loop (L15); this inference was based on the moderately decreased susceptibility of P15 loop mutants to inhibition by neomycin B (28). P15 loop in the bacterial PRNA plays a role in substrate recognition, cleavage site selection, and metal ion binding (58). Biochemical data support that P15 loop is an autonomous metal (Mg2+) ionbinding domain (59). Our results reported here suggest that

AACs can inhibit RNase P primarily by binding to P4, J18/2, and J19/4 (near the protein/pre-tRNA binding); although AACs can also interfere with RNase P function by binding to P15, all our docking results (rigid body docking by MolFit and final refinement by Discover3) show consistent preference of AACs to bind P4, J18/2, and J19/4 somewhat stronger than to P15, and binding to both of these sites is much stronger than that to all other tested putative sites (other clusters). The pattern of APACs binding is generally similar to that of AACs, but with stronger preference to interact with the protein/pre-tRNA binding site (P3, P4, J18/2, P2, J19/4). Although recent findings (10) suggest that NeoR5 could inhibit wild-type E. coli RNase P holoenzyme by binding to the P15 loop, the E. coli RNase P ∆L15/P16/P17 mutant must offer an alternative binding site for NeoR5 that still permits its interference with RNase P function. Our docking results suggest that AACs and APACs may also competitively interfere with the interactions between PRNA and pre-tRNA (and/or P protein) near the helix P15 (Figure 5). The holoenzyme preference for binding pre-tRNA over mature tRNA by B. subtilis RNase P holoenzyme suggests the formation of a direct contact between the pre-tRNA 5′ leader and P protein in the holoenzyme (14). This interaction is confirmed by photo-crosslinking and affinity cleavage studies demonstrating that the 5′ leader of pre-tRNA is in close proximity to the central cleft, but not to the RNR motif or metal binding loop of the P protein (47). Time-resolved fluorescence resonance energy transfer studies show that the 5′ leader contacts the P protein in B. subtilis RNase P holoenzyme (60). Thus, it was suggested (47) that interactions between the P protein and pre-tRNAs contribute to the uniformity of the binding affinity for RNase P for pre-tRNAs. According to our docking results AACs and APACs can interact with PRNA at the region of P15 and therefore interrupt interactions between P protein and pre-tRNA at this region (Figure 5 and Table 3). Structure-activity Relationships of AACs in Comparison to APACs. The structure-function relationship of AACs and APACs with respect to RNA binding is important for their development as possible drugs. Previously, we designed and synthesized a set of different conjugates of neomycin B, paromomycin, neamine, and gentamicin with different numbers (1-6) of arginines (31-34). We also reported the ability of AACs to inhibit RNA translation in direct relation to the number of arginine groups linked to the aminoglycoside backbone and on the nature of the aminoglycoside (37). The strong interaction between the R-amino of the arginine moiety of NeoR6 and the TAR RNA phosphate group was a modeling prediction, which was experimentally supported (30, 31). Indeed, the affinity of tetra-γ-guanidinobutyrate kanamycin A derivative (GB4K), lacking an R-amino acid group in the linker, to TAR RNA was very low compared to that of the tetra-arginine derivative, R4K (30, 31). Also, the anti-HIV activity of GB4K in cell culture (61) and antiequine infectious anemia virus (EIAV) activity in equine dermal fibroblasts (ED) (31) were very low. Thus, all of the above may explain the very low antiviral activities and affinity of GB4K and other guanidino conjugates for HIV-1 TAR RNA (30) and for HIV-1 RRE RNA (e.g., ref 62). Neomycin B that binds RRE IIB with the highest affinity (KD of 1.18 µM (63)) among the aminoglycosides is about 240 times weaker than NeoR6 and 6-7 times weaker than monoarginine derivative (NeoR1) (35). These results indicate that even one arginine conjugated to neomycin B already significantly increases its binding affinity to HIV-1 regulatory RNAs. Other aminoglycoside conjugates, e.g., guanylated aminoglycosides (e.g., ref 62), bind TAR or RRE RNAs much weaker than AACs. Similarly, their anti-HIV-1 activities are much lower than the respective AACs (31-34). Thus, the recent finding (10) of low inhibition of RNase P catalytic activity



Figure 5. (A) Extended view of the catalytic domain of the structural model of B. subtilis RNase P holoenzyme-pre-tRNA complex (43). (B) Final Neo-r9-PRNA complex near the P1-P4 multihelix junction. (C) Final NeoR6-PRNA complex near the P1-P4 multihelix junction. (D) Final Neo-r9-PRNA complex near the P15 helix. (E) Final NeoR6-PRNA complex near the P15 helix. The colors and representation of PRNA and PRNA regions are as decribed in Figures 3 and 4. Neor9 and NeoR6 are shown in stick representation and colored blue.

by guanidino conjugates of neomycin (hexa-guanidinium-neomycin B conjugate) in comparison to that of arginines conjugated to neomycin (e.g., NeoR5 and NeoR6), supporting our previous reports, is not surprising. To determine the importance of the number of arginines conjugated to neomycin B, we compared anti-RNase P activities of NeoR1 with NeoR6 to free neomycin B. The findings that E. coli RNase P activity is inhibited with IC50 values of 60 µM (28), 4 µM, and 125 nM (7) by neomycin B, NeoR1, and NeoR6, respectively (Table 4), suggest that the number of conjugated arginine residues to neomycin B is important. Of note, using RNase P of Neisseria gonorrheae revealed the specifically high potency of NeoR6 (IC50 of 1 nM), (Table 4). The differences in IC50 observed for the two bacterial RNase P holoenzymes indicate the susceptibility of this inhibitor. Thus, NeoR6 is a more efficient inhibitor against RNase P of Neisseria gonorrheae. In accordance with our previous results, NeoR6 does not inhibit eukaryotic translation initiation, indicating its ability to discriminate between the eukaryotic and the bacterial translational machinery (37). Similarly, NeoR6 inhibits bacterial RNase P activity significantly (about 10-fold) more effectively than human RNase P activity (7). The sphere-like NeoR6-PRNA binding conformer reveals different structure in comparison to the extended structure of Neo-r9, Neam-r9, and Neo-r6 in complex with PRNA, as depicted in Figure 5. The APACs revealed about 10-fold lower intermolecular energy than AACs, indicating stronger interactions of APACs than AACs with PRNA (Table 1). Interestingly, no significant differences in intermolecular energy between Neor9 and Neam-r9 complexes with PRNA were found. The docking results point to the fact that only rings I and II of the neomycin core of Neo-r9 interact with PRNA, similar to neamine rings I and II of Neam-r9. Additional studies are needed to correlate our docking results of AACs and APACs to their inhibition of bacterial RNase P

activity. Our preliminary results regarding antimicrobial activity of AACs and APACs against a variety of Gram-positive and Gram-negative bacterial strains, including clinical and gentamicin-resistant isolates, indicate that most of these compounds are active, but not the free nona-D-arginine (64).

CONCLUSIONS Our docking results suggest three possible mechanisms of action of AAC and APAC inhibition of RNase P: (i) the most likely mechanism of RNase P inhibition is AAC and APAC competition with the P protein and pre-tRNA on the P1-P4 multihelix junction and J19/4 region (probably including displacement of Mg2+ ions from P4 helix); (ii) competition with Mg2+ ions near the P15 loop; and (iii) competition with the P protein and/or pre-tRNA near the P15 helix and interference with interactions between the P protein and pre-tRNA at this region are also considered. Structure-function relationships of the molecules described above with respect to PRNA binding is important for further drug design. Indeed, while the free neomycin B showed very low anti-RNase P activity (IC50 60 µM (28)), already one arginine conjugated to neomycin B revealed much stronger activity (∼15-fold) and was extremely better when 6 arginines conjugated to each amino group of neomycin-NeoR6 (∼500fold) (7). Notably, guanidinium or lysyl conjugates of neomycin showed significantly weaker potency against RNase P (10) in comparison to that of AACs (7). Our rigid-body docking results suggest that the binding pattern of aminoglycoside conjugates with short arginine peptide chains (APACs) to the P protein/ pre-tRNA binding site (P1-P4 and J19/4) and near the P15 loop is generally similar to that of the sphere-like AACs (e.g., NeoR6). Importantly, APACs prefer to interact with the P protein/pre-tRNA binding site (Figures 3 and 4). The ranges of


intermolecular energy of APACs (after refinement) are about 10-fold lower than those of AACs, especially at the P protein/ pre-tRNA binding site (Table 1), indicating stronger interactions of APACs than AACs with PRNA. Thus, the novel compounds, APACs, can be predicted as more potent RNase P inhibitors than AACs, by preventing P protein binding with PRNA (probably including displacement of Mg2+ ions from P4 helix). AACs interact with these two PRNA binding sites approximately with comparable potency. The competition of AACs with Mg2+ ions near the P15 loop is also important, almost as competition with P protein binding on PRNA. The ranges of intermolecular energy of AACs and APACs are considerably better than those of neomycin B (Table 1). Thus, arginines conjugated to aminoglycosides extremely improved their interaction with PRNA. All of the above designate that the affinity of a ligand for a target PRNA can be enhanced synergistically by fusing two different functionalities capable of RNA-binding (i.e., aminoglycosides and arginine-rich peptides). Our docking approach described in this article, in combination with RNase P holoenzyme models of Westhof and co-workers (43) and Fierke and co-workers (47), may be used for predicting the binding modes of AACs and APACs in different specific sites of PRNA and for ligand interference with RNase P activity. This approach also can be extended for the future design of new molecules.

ACKNOWLEDGMENT We thank Dr. G. Borkow and Dr. M. Eisenstein for critical remarks and discussions. The docking program MolFit was downloaded from http://www.weizmann.ac.il/Chemical_ Research_Support/molfit.

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