Rational Design of Inhibitors of HIV-1 TAR RNAthrough the Stabilisation of Electrostatic “Hot Spots”

Ben Davis1, Mohammad Afshar1, Gabriele Varani2

Alastair I. H. Murchie1, Jonathan Karn2, Georg Lentzen1

Martin Drysdale1, Justin Bower1, Andrew J. Potter1, Ian D. Starkey1

Terry Swarbrick1 and Fareed Aboul-ela1*

1RiboTargets Ltd, Granta ParkAbington, Cambridge CB1 6GBUK

2MRC Laboratory of MolecularBiology, Hills Road, CambridgeCB1 2QH, UK

The targeting of RNA for the design of novel anti-viral compounds hasuntil now proceeded largely without incorporating direct input fromstructure-based design methodology, partly because of lack of structuraldata, and complications arising from substrate flexibility. We propose aparadigm to explain the physical mechanism for ligand-induced refoldingof trans-activation response element (TAR RNA) from human immuno-deficiency virus 1 (HIV-1). Based upon Poisson–Boltzmann analysis ofthe TAR structure, as bound by a peptide derived from the transcriptionalactivator protein, Tat, our hypothesis shows that two specific electrostaticinteractions are necessary to stabilise the conformation. This result contra-dicts the belief that a single argininamide residue is responsible forstabilising the TAR fold, as well as the conventional wisdom that electro-static interactions with RNA are non-specific or dominated by phos-phates. We test this hypothesis by using NMR and computationalmethods to model the interaction of a series of novel inhibitors of the invitro RNA-binding activities for a peptide derived from Tat. A subset ofinhibitors, including the bis-guanidine compound rbt203 and its ana-logues, induce a conformation in TAR similar to that brought about bythe protein. Comparison of the interactions of two of these ligands withthe RNA and structure–activity relationships observed within the com-pound series, confirm the importance of the two specific electrostaticinteractions in the stabilisation of the Tat-bound RNA conformation.This work illustrates how the use of medicinal chemistry and structuralanalysis can provide a rational basis for prediction of ligand-induced con-formational change, a necessary step towards the application of structure-based methods in the design of novel RNA or protein-binding drugs.

q 2003 Elsevier Ltd. All rights reserved.

Keywords: drug design; TAR RNA; NMR; hot spots; structure–activityrelationships (SAR)*Corresponding author

Introduction

The increasing success of protein structure-baseddrug design, together with recent progress inRNA structure determination, represented mostdramatically by a series of three-dimensional (3D)ribosome structures,1 reinforces the imperative toutilise high-resolution structure determination asa tool facilitating the process of RNA-targeteddrug development. RNA represents a largelyunexploited wealth of targets for the designof novel small molecules with anti-infectiveproperties.2 A significant portion of the work in

0022-2836/$ - see front matter q 2003 Elsevier Ltd. All rights reserved.

Supplementary material associated with this articlecan be found at doi: 10.1016/j.jmb.2003.12.046

Present addresses: M. Afshar, Ariana Pharmaceuticals,75 Rue St Charles, Paris 75015, France; J. Karn,Department of Molecular Biology and Microbiology,Case Western Reserve University, Cleveland, OH, USA;G. Varani, Department of Chemistry and Department ofBiochemistry, Box 351700, University of Washington,Seattle, WA 98195-1700, USA; G. Lentzen, BiTop AG,Stockumer Strasse 28, 58453 Witten, Germany.

E-mail address of the corresponding author:f.aboul-ela@vernalis.com

Abbreviations used: TAR, trans-activating responseelement; SAR, structure–activity relationship; SPR,surface plasmon resonance.

doi:10.1016/j.jmb.2003.12.046 J. Mol. Biol. (2004) 336, 343–356

the area of targeting RNA has focused on the trans-activation response element (TAR) RNA from HIV-1.3,4 The interaction of the transcriptional activatorprotein, Tat, with TAR is essential for proliferationof the virus,5 – 13 together with associated cellularfactors.14 Moreover, a number of recent studiesusing peptidic and/or antisense agents haveproved that TAR-binding compounds can showanti-viral activity in HeLa cells, apparently via inhi-bition of transcription,13,15 – 17 although these agentsare problematic as potential drugs.18 Only a limitednumber of studies have appeared applying 3Dstructure-based design to the Tat–TAR system19 – 22

or, indeed, with other RNA systems.20,21,23

The Tat–TAR interaction is known to occur viaan induced fit mechanism, as demonstrated usingTat-derived peptides.24 – 30 In the absence of Tat, thethree-base bulge that constitutes the TAR-bindingsite (Figure 2) shows a significant degree offlexibility.26,29 – 31 Although conformational changescan complicate conventional approaches to struc-ture-based drug design, the Tat-induced bulgeconformation is particularly crucial to targetingTAR. By presenting a unique configuration offunctional groups on TAR, the “functional” confor-mation facilitates specificity in ligand binding.Incorporating an understanding of this phenom-enon into design therefore enhances the prospectof obtaining novel compounds with specific-binding activity.

Here we present detailed Poisson–Boltzmanncalculations, which suggest that electrostatic inter-actions between “hot spots” in the major grooveand the ligand are essential for stabilising the TARRNA conformation. The importance of chargeinteractions in the binding of small molecules toRNA has long been recognised, but it has beengenerally assumed that electrostatic contacts withthe backbone phosphates are the dominant inter-actions. Our calculations show that the latter arelargely masked by counterions. We have testedthis hypothesis by synthesising a number of com-pounds that bind to TAR in a mode similar to thatof argininamide and the Tat-derived ligands, andmeasured their ability to disrupt the binding of aTat-derived ligand to TAR RNA.32 We report highresolution structural models of the complexes oftwo of these compounds with TAR RNA. Thestructural models and structure–activity relation-ships (SAR) for the series are consistent with aprediction of the modelling that two specificelectrostatic interactions are required to stabilisethe Tat-bound conformation, in apparent contrastto the well known observation that a singleargininamide is required to induce the confor-mational change.25,33 Surface plasmon resonance(SPR) experiments, measuring ligand stoichio-metry, reconcile this apparent paradox. Moreover,the comparison between the two structures pro-vides an excellent rationale for understanding theSAR observed for the series. The mechanisticunderstanding of coupling between ligand bindingand TAR conformation in this set of ligands facili-

tated the development of more potent ligands32

and provides a foundation for structure-baseddrug design in this system.

Results

We wished to establish an understanding of theprinciples underlying the interactions betweenTAR-binding compounds and the RNA, whichcould be exploited in the development of morepotent inhibitors. As electrostatic interactions areknown to play a crucial role in binding of naturalligands to TAR RNA34 –37 we performed electro-static calculations and used the results to analyseand interpret structural and binding data for aseries of novel TAR-binding ligands.

Energetic analysis of the argininamide-boundTAR conformation

We have analysed the electrostatic characteristicsof the argininamide-bound TAR structure (withligand excluded), which is very similar to thestructure of TAR as bound by ligands from therbt203 series (described below), using Poisson–Boltzmann analysis.38 This method, rather thansimply determining surface charge, calculates theelectrostatic potentials over a three-dimensionalvolume, illuminating “unstable” regions resultingfrom strong potential gradients.

The analysis of the Poisson–Boltzmann electro-static surface of the argininamide bound confor-mation of TAR identifies hot spots39 correspondingto shallow gradients of strong electronegativepotential buried in two pockets under and aboveU23, where electronegative groups from U23 andbases in the major groove, cluster (Figure 1(a)).The former groups include U23 O4 and A22 N7.Thus, the potential is characterised by a non-sym-metrical spread of negative charges around theA22-U23 pocket. The second region in the shallowgroove above the bulge includes U23 O4 and O2and electronegative functionalities on one side ofthe groove juxtaposed with G28 N7, O6, and A27N7 on the other. Figure 1(b) illustrates the firstregion with low electrostatic potential, accessibleto the solvent, viewed looking down from a planespanning G26 N7 and U38 O4. It is noteworthythat the shallow gradient region, corresponding toa large low potential area, is situated between thepoint charges, but away from the surface. Theregion opposite C37 O2P displays also a low poten-tial with a low gradient. This is in contrast tonegatively charged phosphate groups, which arerapidly shielded by solvent counterions, makingthe major groove near the bulge regions the likelyposition for specific interaction by a positivelycharged functional group within a ligand, as seenin argininamide bound TAR structures24,25,27 andother TAR-binding ligands (see below).

344 RNA Structure-based Drug Design

A library of small molecular weight TAR-binding compounds probes minimal elementsrequired for the bound TAR conformation

Initially, potential TAR-binding ligands weresynthesised with positively charged moieties byanalogy to the natural ligands.40 However, wewere anxious to reduce the size and total overallcharge of our compounds, in order to enhancetheir pharmacological properties, but also todetermine minimal elements for stabilising RNAconformation.

A fluorescence resonance energy transfer(FRET)-based assay was developed to facilitate thescreening of a large number of compounds fortheir capacity to disrupt binding to TAR by theTat-derived ligand, ADP-1 (described by Murchieet al.).32 A number of compounds were identifiedwith inhibition constants in the micromolar range,including the series of related compounds listed in

Table 1, and NMR total correlated spectroscopy(TOCSY) fingerprints25 verified that these com-pounds induced a TAR RNA conformation similarto the Tat-bound structure (see below).

A subset of compounds explores the relationshipof compound structure to activity at the R2position (Table 1). The compounds differ by thelength of the R2 chain (relative to RBT 201) by one(for RBT 202) and two methylene groups (for 203).rbt203 was found to bind TAR RNA with thehighest potency of the compounds from thisgroup. The rbt160–162 series probes the samerange of lengths of R2 for a longer ðn ¼ 2Þ chain

Figure 1. Electrostatic potential showing (a) hotspotsfor potential interactions with positively chargedmoieties shown in red on the surface representation ofTAR. (b) Gradients in electrostatic potential across argi-ninamide:TAR bound structure. A thin section of thestructure and the contoured potentials is shown on aplane parallel to the A22 base (approximately, the blueplane shown in (a) and centred on G26 N7 (red, 26;orange, 25; yellow, 24; green, 22). This view looksdown upon the hot spot underneath U23.

Figure 2. (a) Sequence of TAR RNA variant used inthis study. (b) 1D titration showing addition of TARRNA to rbt203 sample at concentrations of 1 mM com-pound and 0 mM, 0.4 mM, 0.8 mM TAR RNA. (c) Regionof the NOESY spectrum showing intermolecular NOEsbetween aliphatic proton resonances from argininamide(black) and guanidinium side-chain resonances withinrbt203 (blue). At least one guanidine (R2) within rbt203shows a pattern of NOEs identical to that found forargininamide on its own. Intermolecular NOEs involvingthe second guanidine residue are apparent in the rbt203spectrum.

RNA Structure-based Drug Design 345

at R1. The additional R1 chain length partlycompensates for a shorter R2, but no improvementis observed over rbt203. The requirement forcoverage of a minimum area via side-chain lengthis reinforced by the relatively weak potency ofrbt158 (Table 1). Replacement of guanidiniumgroups at either R1 or R2 results in loss of activity,most dramatically when positively charged groupsare absent. As these results indicated that rbt203represented an “optimal fit” to the binding siteand bound TAR conformation, we used NMR toprobe the rbt203–TAR interaction in detail.

Rbt203 binding to TAR RNA induces the sameconformation as argininamide/ADP1 binding

An RNA was added to a ligand sample in athree-step titration (starting with free ligand, then0.4 mM and 0.8 mM RNA (Figure 2(b)) and reso-nances in the ligand were observed to shift and

broaden as RNA was added, indicating that bind-ing to the RNA was taking place.

After mixing of the two samples during thetitration experiment, TOCSY and NOESY spectrawere acquired on the complex in 2H2O. TheTOCSY cross-peak pattern in the H5/H6 regionwas very similar to that observed with a freshlyprepared sample of argininamide complexed toTAR RNA (data not shown), and to spectraobserved with ADP-1 complexed to TAR in thepast,25 although resonances in the rbt203 complexare exchange broadened. Such a result wouldindicate that the ligand was inducing the sameconformation in TAR as that induced by arginina-mide or ADP-1, with on/off rates consistent withmicromolar affinity. In addition, in the NOESYspectra the same pattern of NOEs appeared aswas observed with the argininamide and ADP-1bound TAR conformations24,25,27 (data not shown).

Binding of rbt203 to TAR was further confirmed

Table 1. Structure–activity relationships (SAR) for rbt203 and related compounds in FRET assay

rbt no. m n X Y S S1 Ki (mM)

158 na 3 CH2 H H .50

160 2 1 CH2 CH2 H C(NH)NH2 4.88161 2 2 CH2 CH2 H C(NH)NH2 2.66162 2 3 CH2 CH2 H C(NH)NH2 2.62201 1 1 CH2 CH2 H C(NH)NH2 .50202 1 2 CH2 CH2 H C(NH)NH2 3.40203 1 3 CH2 CH2 H C(NH)NH2 1.54

214 na 2 CH2 H C(NH)NH2 Inactive

392 2 3 CH2 CH2 H H 3.2393 2 3 CH2 CH2 CH3C(O) H .50394 1 3 CH2 CH2 H H 14.5396 1 3 CH2 CH2 CH3C(O) H .50402 2 3 C(O) CH2 H H .50442 2 3 CH2 C(O) H H 32541 1 4 CH2 CH2 H C(NH)NH2 2.41

346 RNA Structure-based Drug Design

by the presence of several intermolecular NOEs in2H2O, all of them between resonances on the ligandand the residues at or above the bulge on TAR(Figure 2(c) and summarised in SupplementaryMaterial). The NOEs shown in the Figure immedi-ately suggested a binding mode for rbt203 placingthe R2 guanidinium moiety in a position similarto that observed for argininamide, or an argininewithin ADP-1, underneath U23, with the scaffoldbinding in the major groove of the upper stem.The latter interaction is apparent from NOEsbetween the scaffold and C37. In addition, anNOE is observed between the scaffold of rbt203and the H8 resonance of the flexible A35 loopnucleotide. NOEs from the R1 guanidinium tosugar and amino proton resonances of C37 andC29, indicate that this positively charged groupsits in the major groove of the upper stem, nearthe penultimate base-pair of the stem.

As a result, subsequent calculations (see below)incorporated additional restraints between theR2 guanidinium moiety and the RNA based onanalogy to NOEs observed between argininamideand TAR in H2O, and, in one case, based on nitro-gen chemical shift changes observed in the RNAin the presence of argininamide or ADP-1 (seeMaterials and Methods, Table 2, and Aboul-elaet al.).25 Briefly, these restraints incorporated thefollowing assumptions. (1) A guanidinium sits inthe binding pocket in a manner analogous to theargininamide modelled into the structure of thebound TAR.25,27 In practice, this is a safe assump-tion to within the resolution of the NMR data,

given the pattern of intermolecular NOEs men-tioned above (Figure 2). (2) All of the intermolecu-lar NOEs arise from a single-binding mode at asingle site. We have tested the binding of a numberof compounds to TAR using surface plasmon res-onance, including rbt203 (see below) and observedthat rbt203 binding to TAR involves a preferredstoichiometric-binding mode at micromolar con-centrations, while a weaker affinity non-specificbinding can be observed at higher concentrationsof RNA and excess ligand. However, under thestoichiometric conditions at which NMR measure-ments were observed, the high affinity-bindingmode will be expected to predominate.

Table 2. Summary of restraints used for calculation and refinement of rbt compound

Restraint imposed Rationale Reference

Argininamide/ADP1 bound TAR structure Chemical shift and aromatic-H10 NOE pattern for cyclicpeptide bound TAR ¼ argininamide/ADP1 bound TAR

25

rbt203 R2 and rbt158 R2 guanidine amino protons lessthan 5.5 A from A22 H8, U23 H5, G26 H8-sum averaging

NOEs observed for rbt203 and rbt158 R2 to TAR in2H2O ¼ those observed for argininamide or argininamide

within ADP1 to TAR

25

A-form dihedral angles for residues 17–21, 27–29, 36–38,41–45

NOEs characteristic of Watson–Crick pairing, standardA-form aromatic to sugar NOEs, lack of JH1

0 –H20 scalar

coupling

25

Base triple hydrogen bonding involving U23*A27*U38(U23 H3 to A27 N7 and U23 O4 to A27 N6)

Similarity of spectra to argininamide/ADP1 bound TAR 63

Table 3. Statistical summary of NMR structure calculations

Number of experimental restraints rbt203 rbt158 Comments

Number of RNA–RNA NOEs 775 775 From Aboul-ela et al.25

Number of rbt–rbt NOEs 5 8Number of (intermolecular) rbt–RNA NOEs 13 þ 8 11 þ 8 exp þ “model” (see Table 2)Experimental dihedral restraints 78 78 From Aboul-ela et al.25(X-PLOR stage only)Hydrogen bonding restraints (RNA base pairs) 30 30 Ten base pairs“Modelling” dihedral restraints in A-form regions 72 72 X-PLOR stage onlyBase pair planarity restraints in base-paired regions 9 9 Includes U23:A27:U38 “triple” (see Table 2)Total number of experimental restraints 990 991No. of converged structures (50 starting) 36 11/32 21 “unphysical” binding modes thrown out for rbt158/

TAR structures

Table 4. Deviations from NMR experimental data

rbt203 rbt158

A. Average distance restraint violationsDistance restraint violations .0.1 A 2–11 1–3Distance restraint violations .0.2 A 0–3 0–1Distance restraint violations .0.5 A 0 0Dihedral angle restraint violations .5

degrees0 0

B. RMS deviations from ideal stereochemistryBonds ,0.005 ,0.005Angles ,1.1 ,1.1Impropers ,0.8 ,0.8C. Coordinate precisionRMS deviations (all heavy atoms minus

hairpin loop) (A)1.55 1.6

Ligand plus core residues (20–23, 26–29,36–45) (A)

1.2 1.2

RNA Structure-based Drug Design 347

Simulated annealing and minimization: rbt203covers the major groove of the upper stemof TAR

In order to visualise this interaction betweenrbt203 and TAR, molecular dynamics calculationswere carried out using X-PLOR as described(Materials and Methods). The protocol was basedon standard protocols for calculation of RNAstructures41 with an additional final refinementusing Charmm with electrostatic and van derWaals interactions included for analysis of thebinding mechanism.

Statistics regarding the overall precision and

agreement with the data are presented in Tables 3and 4. The ensemble of 36 converged structures isshown (Figure 3(a)).

The calculations consistently place both posi-tively charged side-chains pointing into the majorgroove and making contacts with U23, with theR2 guanidinium placed underneath U23 in a pos-ition to stack on A22, and with the R1 guanidiniumpointing above the U23 residue (Figure 3(b)). TheR2 guanidinium is in position to form a cation–pstacking interaction42 with either U23, A22, orboth. In addition, the R1 guanidinium, though itsgeometry is less well defined, may be able to forma similar interaction above the U23 ring.

Figure 3. (a) Superposition of 36 coordinate sets calculated for the rbt203 TAR complex. Superposition is based uponall heavy atoms. Rbt compound residues are colour-coded as follows: scaffold (green) and R1, R2 and R3 (red). U23and A22 residues on the RNA are highlighted as yellow. (b) Single rbt203:TAR model from ensemble in (a). Guanidineresidues stack on either side of U23, with the scaffold placed in the major groove of the upper stem, perpendicular toWatson–Crick base-paired pyrimidines. (c) Surface representation of RNA shown in (b). Ligand–RNA surface contacts(less than 4 A between atom centres) are highlighted in light green and (less than 3.5 A) yellow.

348 RNA Structure-based Drug Design

The scaffold sits in the major groove perpendicu-lar to the aromatic rings of the RNA bases, asindicated by the NOEs described above. Thecontacts between the surface of the RNA andrbt203 (less than 4 A distance) are highlighted inFigure 3(c).

The unfavourable potential associated with thehot spot regions identified above can be compen-sated by positive charges brought from the ligand.While argininamide and R2 of rbt203 pointstowards the first hot spot, the positively chargedR1 guanidine of rbt203 interacts precisely in thesecond region.

Changing the length of the R2 side-chainreduces affinity for TAR RNA

The data in Table 1 show that rbt201 and rbt202,which contain shorter side-chains at the R2position than rbt203, bind TAR with slightlyreduced affinity, while rbt158, which contains arestrained guanidinium at the same position, losesalmost two orders of magnitude in affinity. NMRspectra of rbt202 bound to TAR suggested thatthis compound induces a similar structure in TARas the other compounds in the series at roomtemperature (data not shown), though somechanges are apparent, especially in the hairpinloop, at lower temperatures. We embarked uponan NMR study of the binding of rbt158 to TARRNA. Again, the RNA was found to adopt thesame conformation as that observed for theargininamide and ADP-1 bound complexes. More-over, intermolecular NOEs were observed betweenthe two positively charged side-chains on theligand, and residues at or above the bulge on theRNA. A subset of the pattern of NOEs was veryclosely analogous to that observed for rbt203 bind-ing to TAR. This set of data immediately suggestedthat the restrained guanidinium was stackedunderneath U23 in TAR, in a position similar tothat observed for the R2 guanidinium in rbt203.

Calculations were carried out for the rbt158:TARcomplex in the identical manner to those for therbt203 complex. Excellent agreement with the datawas obtained again for the calculations withrbt158 (Figure 4(a), Tables 3 and 4), though thebreak between converged and non-convergedstructures was less clean, and amongst the lowenergy structures a subset were discarded becausethey contained an unphysical contact betweenpositively charged R1 and R2 moieties on theligand. For the favoured model (without theunphysical contacts), R2 again inserted betweenA22 and U23 within a favourable stackinggeometry, while the primary amine at R1 pointedabove U23 (Figure 4(b)). Thus these groups againinteract with the two hot spots detected above, asnoted for rbt203. However, there were no inter-molecular NOEs between the scaffold of rbt158and the RNA, suggesting that the scaffold doesnot make the same close contact with the majorgroove as found with rbt203.

Overall, this set of results suggests that the rela-tive lengths of the side-chains, and the positioningof the scaffold of rbt203, contribute significantly toits binding to TAR. A comparison of the two com-plexes shows that the surface of contact of rbt203with the RNA is more widespread than that ofrbt158 (Figures 3(c) and 4(c)), largely due to thescaffold/major groove interaction and a deeperpenetration of the R2 side-chain (Figures 3(b) and4(b)) in the former. This result indicates that thesmaller ligand makes sub-optimal contacts withthe RNA, resulting in lower affinity.

Stoichiometry of ligands binding to TAR RNA

The requirement for stabilisation of two hotspots in order to induce the Tat-bound TARconformation can be reconciled with the abilityof argininamide, containing a single positivelycharged moiety, to induce the conformation ifmore than one argininamide is bound, as has beensuggested.43 To test this possibility, and to validatethe assumption of a single rbt203 molecule givingrise to the NOEs observed to TAR, we utilisedSPR to measure stoichiometry of binding to TARfor a number of ligands. A biotinylated TAR mol-ecule was attached to a chip, which was subse-quently rinsed with a buffer solution containingligand.

Measurements of ADP1 binding to TAR gavestrong signals and good fits to a binding curvewith a single high affinity site (Figure 5(a)). rbt203also gave data with good fits, but only postulatingthe presence of a second, low affinity-binding siteafter saturation of a high affinity site (Figure 5(b)).This experiment provided us with the most unam-biguous determination we have yet to obtain forspecific versus non-specific binding. Argininamidebinding to TAR could also be measured with abinding constant of 8 mM, in reasonable agreementwith the literature, indicating that, in some circum-stances, binding of very small molecules to sub-strates of up to 10 kDa can be detected in this way.However, the signal response was much largerthan would be expected for a molecule the size ofargininamide, probably due to multiple, non-specific binding (Figure 5(c)).

These experiments demonstrate that under theconditions of the NMR experiments reported hereand elsewhere, argininamide–TAR complexes con-tain multiple ligands bound to the RNA, whereasrbt203 and, most likely, related ligands, bind atone-to-one stoichiometry.

Discussion

We have identified a series of compounds withup to micromolar affinity for binding to TAR RNAin solution. The structures of the complexesbetween two ligands from the series, rbt203 andrbt158, and TAR, have been studied by NMR andmolecular modeling. We have found that both

RNA Structure-based Drug Design 349

ligands induce the same TAR RNA conformationas that found in argininamide or ADP-1 boundcomplexes with the RNA, and guanidinium groupsfrom each ligand bind in a similar pocket in TARunderneath U23. Two conclusions stand out fromthe experimental data presented; all active com-pounds contain two basic centres (including atleast one guanidine) and all of those tested byNMR induce a similar conformation (and bindingmode) in TAR. Our electrostatic hot spot analysisprovides the key to understanding these twoconclusions together with much of the data in theliterature on binding of Tat-related peptides to

TAR RNA, and to the exploitation of this infor-mation for drug design.32

Electrostatics and the mechanism ofconformational change in TAR

A number of studies34,37,44,45 have demonstratedthe importance of electrostatic interactions in thebinding of basic peptides to TAR RNA, as well asto interactions between other arginine-rich RNA-binding proteins and their recognition elements.46–48

The fact that NOEs are observed between twobasic residues in rbt203 or rbt158 and the RNA is

Figure 4. (a) Superposition of lowest energy structures from rbt158:TAR complexes. Conditions of calculation andsuperposition as in Figure 3(a) and in Materials and Methods. (b) and (c), Single lowest energy model from ensemblepresented in a in ball and stick (b) and surface (c) representation for the RNA. The two positively charged side-chainsare placed in similar positions to their rbt203 analogues, but less contact is apparent between the scaffold and the RNA,and the contact surface between U23 and R2 is smaller.

350 RNA Structure-based Drug Design

consistent with a mode of binding in which electro-static interactions involving these two residuesmake a significant contribution to binding to TAR.It is therefore significant that Poisson–Boltzmannmapping of electrostatic potentials in the volume

covering the TAR bulge region has identifiedregions of gradients in electrostatic potential inand around the observed binding sites of the twopositively charged groups (Figure 1). This resultprovides a paradigm for analysis of binding toTAR by many ligands reported here and else-where. The structural “instability” due tounshielded charges in the pockets is consistentwith the hypothesis that these pockets are inducedby the ligand further improving specificity. Thehypothesis is strengthened even further by theSAR within the rbt203 series, which show a prefer-ence for compounds containing a pair of positivecharges, many of which have been shown byNMR to induce the Tat/ADP1 bound TAR confor-mation (data not shown).

This hypothesis also helps to explain the require-ments for TAR binding observed in mutationalanalysis of Tat-derived peptides. Double mutationswhich convert residues within the 52/53 or 55/56di-Arg motifs with Q49 or A50 dramatically reducebinding of HIV-Tat derived peptides to TAR,whereas single point mutations have smallereffects.50 Optimal activity has been reported torequire six to seven charged residues.49 Arginina-mide on its own, but not lysine,51 can induce theconformational change in TAR. Taken together,the binding affinities of Tat-derived peptides andthe rbt203 series of compounds, their respectiveNMR-derived structures, and the Poisson–Boltzmann calculations reported here, all suggesta similar role of the two positively charged groups:to stabilise the two electrostatic hot spots,produced by the cluster of electronegative func-tionalities in the argininamide/ADP1 bound TARconformation.

The bis-arginine motif

The requirement for two positively chargedgroups, and preference for at least one guanidine,does involve more complex electrostatic inter-actions than a simple charge neutralisation.27,28

Brodsky and Williamson pointed out that the argi-nine in the argininamide–HIV-2 TAR complex liesin a “sandwich” stacking between A22 and U23,and it has been suggested26,52 that such a configu-ration stabilizes the complex via cation–pinteractions.42 The R1 guanidinium in the rbt203complex which protrudes above U23 also has thepossibility of forming a similar cation–p inter-action above U23, though without the additionalinformation available from the literature the datahere are not of the resolution to allow any defini-tive conclusion. The cation–p interaction wouldbe sensitive to details of the charge distributionwithin the positively charged amino acid side-chain moiety. Significantly, a compound in whichthe R1 guanidinium has been replaced by a pri-mary amine (rbt392, Table 1) loses only a factor ofthree in binding relative to rbt203, while othercompounds in the series which replace the guani-dinium groups at both R2 and R1 are virtually

Figure 5. (a) SPR response curves showing ADP-1binding to biotinylated TAR RNA. Slow associationand dissociation kinetics are visible at t ¼ 0 s andt ¼ 180 seconds, respectively. Ligand concentration wasvaried from 12.5 nM (cyan) to 150 nM (red). The Kd wascalculated to be 40 nM. Kon and Koff were also calculatedfrom the observed slow kinetics, and were found to be1 £ 105 M21 s21 and 3 £ 1023 s21, respectively. (b) SPRresponse curves showing RBT203 binding to biotinylatedTAR RNA. Ligand concentrations were varied from200 mM (in red) to 100 nM (light green). Rapid associa-tion and dissociation kinetics are visible. Analysis of thebinding curve suggests the presence of two bindingevents, one in the low mM range with a relatively smallresponse and a second above 100 mM with a relativelylarge response (see c). This would be consistent with asingle high affinity binding site and a number of lowaffinity binding sites. (c) Binding curves for arginina-mide binding to biotinylated TAR RNA. The responsewas calculated as the average response for the steady-state binding event, with ligand concentrations rangingfrom 100 mM to 100 mM. A Kd of approximately 8 mMwas calculated from these binding data. For such asmall ligand, the magnitude of the response implies mul-tiple binding.

RNA Structure-based Drug Design 351

inactive in the ADP-1 displacement assay (data notshown).

The binding mode shown in Figures 3 and 4 isreminiscent of a di-Arg or “Arg sandwich” motifobserved in the BIV Tat peptide:TAR complex53,54

and in models of the ADP-1 TAR interaction(F. A. et al., unpublished results).

Comparison between rbt203 and rbt158 boundTAR structures

TAR RNA forms the same conformation whenbound by rbt203 or rbt158, making similar electro-static contacts and participating in cation–p inter-actions. However, rbt203 binds to TAR with nearlytwo orders of magnitude tighter affinity than thatof rbt158. The difference in binding energy resultsfrom lack of optimal contacts between theconstrained guanidinium side-chain in rbt158 andits binding pocket in TAR, and additional affinityarising from rbt203 appears to result from anexpanded surface area of contact with the RNA(compare Figures 3(c) and 4(c)). The evidence forthis conclusion rests with the TAR-binding affinityof rbt201, which contains side-chains of similarlength to those of rbt158. The expanded surface ispartly a consequence of the interaction of therbt203 scaffold with the major groove of theupper stem of the RNA, and possibly a favourableinteraction involving the methoxy group at R3 orthe unpaired A35 loop residue. This interactionwould be less favourable or require more strain incomplexes between TAR and rbt203 derivativeswith shorter R1 or R2 side-chains, henceleading to the reductions in affinity for the othercompounds in this series. In rbt158, for example,the R2 side-chain fails to make optimal contactswith U23 and A22 (Figure 4(c)). Moreover, othercompounds with bulky substituents in place ofthe methoxy group either show reduced affinityfor TAR due to steric clashes (data not shown),or bind to different TAR conformations.Inducing alternate conformations proved to bethe key to enhancing potency in the series(see Murchie et al.),32 as rbt203 represents anoptimisation of the binding mode observed in thecurrent series.

Relation between RBT compound binding andargininamide or Tat/ADP1 binding to TAR RNA

It has been suggested25,43 that multiple arginineresidues are required to adequately mimic thewild-type Tat–TAR interaction.7,55 Our hot spothypothesis for the TAR conformational changewould imply that the positions bound by R2 andR1 in the rbt203 and rbt158–TAR complexes, forexample, may be covered by two or more distinctargininamide molecules under the conditions usedfor NMR measurements in previous studies ofexcess argininamide bound to HIV-1 TAR24,25,33

and HIV-2 TAR.27,28 Evidence for this proposalarises from surface plasmon resonance measure-

ments, which demonstrate response changes inimmobilised TAR RNA upon addition of arginin-amide far in excess of those consistent withstoichiometric binding, though following otherstudies we have formed self-consistent models forthe argininamide–TAR complex based upon theassumption that observed NOEs arise from a singleargininamide. Nonetheless, the concept that asingle amino acid residue can mould TAR RNAconformation must be amended to acknowledgethe role of at least one additional amino acidinteraction.

TAR RNA flexibility

There are now a number of examples of TARconformations observed in the literature withligands bound,22,56 with the larger number ofstudies focusing on the argninamide/ADP1bound conformation. This conformational flexi-bility complicates virtual docking by multiplyingthe number of potential docked conformations tobe considered, but using a paradigm to predictligand-induced structural change can aid thisprocess. Electrostatic interactions and cation–pstacking are required to stabilise a bound TARconformation. With this understanding of thedynamics of the TAR RNA-binding mode, wewere able to obtain a significantly enhanced hitrate from in silico docking experiments (M. Afshar& D. Morley, unpublished results).

We have observed a second series of compoundsthat have stabilised a novel, non-functional confor-mation of TAR RNA.32

Implications for drug design

While large-scale conformational changes areconsidered to be problematic for traditionalmethods of virtual screening and structure-aideddrug design, which assume limited flexibility inthe binding site, restricting drug design efforts torelatively “rigid” targets will exclude many,perhaps the majority, of therapeutic targets fromstructure-based approaches. Utilising a theoreticalframework for ligand-induced conformationalchange provides a strategy for focussing a syn-thetic library. Thus one may “tune” a chemicalseries to maintain a desired conformation, facili-tating more traditional structure-based method-ologies. During a focused in silico docking of alibrary of compounds related to rbt203, we wereable to obtain a significant enhancement in hitrate,57 when the library was chosen to include com-pounds likely to satisfy the criteria for inducing therbt203 bound conformation. Alternatively, ligandscan be designed to search for novel, inactiveconformations.32 The power of ligand-inducedRNA conformation for providing specificity isillustrated not only in systems like TAR, but alsoin aptamers.

352 RNA Structure-based Drug Design

Materials and Methods

Poisson–Boltzmann analysis

Electrostatic calculations described here are based on anumerical solution to the non-linear Poisson–Boltzmannequation using Delphi 2.5. Structures and surfaces weredisplayed with INSIGHT II (Accelrys). The AMBER(Accelrys) charge set was used. No bound water or ionmolecules were used in the calculation. The molecularsurface of RNA was calculated using a 1.4 A probe. Theinterior dielectric constant was set to four and surround-ing solvent to 80. A 2.0 A exclusion radius was added tothe surface of the RNA to account for ion size. A uni-valent salt concentration of 50 mM (structure determi-nation conditions) was used. The 3D structure wasmapped to a grid. Approximate boundary potentialswere calculated using the Debye–Huckel equation andpotential focussing was used as implemented in Delphi.

RNA sample

An RNA oligonucleotide corresponding to the wild-type TAR sequence (see Figure 2(a)) was prepared usingthe phage T7 RNA polymerase in vitro transcriptionsystem.57 The RNA sequence used was 50-GGCAGAUCUGAGCCUGGGAGCUCUCUGCC-30. This sequencehas two base pairs differing from the wild-type sequencein the lower stem and folds into a hairpin as shown(Figure 2(a)). These modifications were made in order toincrease transcription efficiency.

The RNA was purified by 20% (w/v) polyacrylamidegel electrophoresis, electroeluted from gel slices, dia-lysed exhaustively, desalted on a NAP-10 column(Amersham-Pharmacia) and dialysed against water.Samples were dried under vacuum and resuspended inthe NMR buffer (20 mM potassium phosphate (pH 6.1),2 mM EDTA) containing 3,3,3-trimethylsilylpropionate(TSP) as an internal standard. The RNA concentrationwas determined from the UV absorbance at 260 nm.58

Under the conditions of the NMR experiments, theRNA folds into the secondary structure shown inFigure 1.

rbt sample

The synthesis of rbt compounds is describedelsewhere.59

Binding affinities by FRET displacement assay

Binding affinities have been measured as described.32

Briefly, the assay detects disruption of the ADP-1–TARinteraction by monitoring the change in FRET signalthat takes place when a fluorescein-labelled peptide dis-sociates from dabcyl-labelled TAR RNA. Increasingamounts of unlabelled RNA are titrated into the systemin the presence of a fixed amount of competitor ligand.This format has a number of advantages with respectto controlling for artifacts arising from compoundfluorescence, among other factors.32

NMR spectroscopy

NMR spectra were recorded on either a BrukerAMX500, DMX600 or DRX800 spectrometer at 298 K(2H2O) or 278 K (H2O). Samples contained approximately

1 mM ligand. All spectra of the rbt compound:TAR com-plexes were obtained with samples containing 0.8 mMRNA, 1 mM rbt compound. Where titrations were per-formed, RNA was added in aliquots to the rbt compoundsample to give concentrations of RNA of 0.2 mM,0.4 mM and 0.8 mM. The final titration point containeda slight excess of ligand.

Spectra were acquired in both 100% 2H2O and in 90%H2O/10% 2H2O using either presaturation or the Water-gate sequence for solvent suppression. After the mixingof the two samples during the titration experiment,TOCSY, COSY and NOESY spectra were recorded asdescribed,41 with NOESYs acquired at three mixingtimes (75 ms, 150 ms and 300 ms). In addition, a 1H–1HNOESY was collected in H2O. Resonance assignmentswere by standard methods.41 Assignments of the freerbt compound resonances were based on interpretationof COSY, TOCSY (tm ¼ 60 ms) and ROESY (tm ¼ 250 ms)data obtained in 90% H2O/10% 2H2O. Assignments forthe bound ligand were extrapolated from the assign-ments of the free ligand and titrations, and checked forconsistency with intramolecular signals observed inNOESY and TOCSY spectra of the complex.

The conformation of the TAR RNA was verifiedas similar to the “arginine-bound” structure after theidentification of characteristic cross-peaks in NOESYand TOCSY spectra of the rbt203 and rbt158 compound:TAR complexes (see below). Intermolecular NOEs wereassigned only where both ligand and RNA resonanceassignments were unambiguous.

All spectra were processed using NMRPipe60 andassignment aided using the program Sparky.†

Distance restraints

NOEs were classified as either strong, medium orweak (upper distance bounds of 3.0 A, 4.0 A or 5.0 A,respectively) depending on peak intensity, and, if notredundant, were used as distance restraints in the struc-ture calculation process. No intermolecular NOEs wereassigned to the sugar region of the RNA spectrumbecause of the extreme overlap present in this region.Intermolecular NOEs or ligand–ligand NOEs thatdid not impose a conformational constraint were notincluded in the calculations. Restraint statistics aresummarised in Table 3.

Additional restraints for structure calculations

Assignment of all NOEs in the aromatic-H10 region ofthe NOESY spectra indicated that an essentially identicalconformation was being adopted by the RNA in rbtcompound:TAR complexes to that observed in theargininamide:TAR complex.25 The RNA constraintsobtained from the argininamide:TAR complex, includingredundant NOEs, were therefore fixed during allX-PLOR calculations.

A number of additional modelling restraints, whichwere not determined by the specific experimentsreported here, were also included. These distancerestraints are based on previous literature and aredescribed below and in Table 2. In spectra of theargininamide:TAR complex, large changes in the 15Nchemical shifts of G26 N7 and U23 N1 were observed.25

† T. D. Goddard & D. G. Kueller (http://www.cgl.ucsf.edu/home/sparky/)

RNA Structure-based Drug Design 353

These chemical shift changes were interpreted as result-ing from the presence of a charged guanidinium moietyin close proximity to these bases, and a guanidiniummoiety was therefore restrained to be within 5 A of bothG26 N7 and U23 N1. The aromatic-H10 region of 1Hspectra of the rbt203:TAR and argininamide:TAR (andrbt158) complexes are essentially identical, and although15N shifts were not measured in the rbt203:TAR and inthe rbt158:TAR complexes, it is likely that the geometryof the guanidine binding is very similar in both cases.After preliminary calculations indicated that a specificguanidine side-chain was interacting with the U23/A22pocket, a restraint between Ch and G26 N7/U23 N1 wasapplied, though ambiguity was maintained to allowthe latter restraint to be satisfied by contacts with otherpositively charged moieties.

Based on the similarity in intermolecular NOE pat-terns involving guanidinium groups and the arginin-amide:TAR complex, distance restraints between fourexchangeable protons of the guanidinium and TARwere included by analogy to those observed in H2Ospectra of the argininamide:TAR complex.

Recent nitrogen–nitrogen couplings observedbetween U23 N1 and A27 N761 have provided directevidence for a base triple hydrogen bonding interactioninvolving U23. In addition to hydrogen bondingrestraints for Watson–Crick base-pairs, hydrogen-bonding restraints were imposed between U23 N1 andA27 N7, and between U23 O4 and the non-Watson–Crick hydrogen bonded amino proton of A27. Planarityrestraints were placed on base pairs with a very lightweighting. During simulated annealing, dihedral angleswithin the two stem regions of TAR that are known toform A-form duplex structures were restrained to withinten degrees of idealised A-form values as measured froma model duplex created in silico using the Insight97 Bio-polymer module (MSI/Accelrys). These restraints weretightened to within two degrees during refinement.Overall, calculations without base-triple, planarity, andA-form conformational restraints produce similar resultsto those with such restraints, but with somewhat lowerconvergence rates.

During a final stage of gentle refinement of rbt203 andrbt158 complexes using the program Charmm 2.5 (seebelow) the RNA structure was allowed to move withina list of distance restraints obtained earlier for theargininamide:TAR complex.25 The other experimentaland “modelling” restraints used in the X-PLOR calcu-lations were maintained during the Charmm refinement.

Figures 3 and 4 have been generated using INSIGHTII2000 (MSI/ACCELRYS). Ensembles (Figures 3(a) and4(a)) have been generated through superpositions ontothe lowest energy structure for the ligand and for coreresidues, here defined as 21–23, 26–28, and 37–41.

Structure calculations

A set of structures of the rbt compound:TAR complexwas calculated using X-PLOR 3.851 (MSI/Accelrys). Atotal of 50 (rbt203 and rbt158) starting structures weregenerated using randomised coordinates for the ligand,the RNA,41 and randomised starting positions for theligand relative to the RNA. Standard protocols forrestrained molecular dynamics/simulated annealing fol-lowed by energy minimisation were used as described.41

A final round of gentle energy minimisation (SD andABNR) in the presence of electrostatic and van derWaals potentials, was carried out on the modelled

rbt203/TAR and rbt158/TAR structures using the pack-age Charmm (version 25 MSI). Both RNA and peptideconformations were allowed to move in order tooptimise interactions, but intramolecular RNA andligand, as well as intermolecular NOE restraints weremaintained with Kmax ¼ 100: Altogether 750 steps ofminimisation were included in the energy minimisationusing Charmm. Energies were computed for the outputstructures, divided by residue and by type of interaction(NOE, electrostatic, van der Waals, as well as intra-molecular and intermolecular). The full script used isavailable as Supplementary Material.

Final structure RMS analysis

Average structures and root mean square deviationsfrom the average structures for each final ensemblewere determined using the program clusterpose.62 – 64

RMSD values reported use the definition termed “R2”by Diamond,62 in other words, based upon the RMS dif-ference from the mean average structure. This calcu-lation was carried out using atom lists based on allheavy atoms, heavy atoms associated only with theligand and RNA residues near the binding site (see thetext) or on the RNA residues near the binding site only.Essentially the RMS in all three cases is very similarwith and without the ligand included in the calculations.

Surface plasmon resonance measurements

Surface plasmon resonance experiments were per-formed using a Biacore X system. Biotinylated TARRNA was obtained from Dharmacon and was immobi-lised onto a Sensor Chip SA (Biacore) using standardprotocols. The reference flow cell was blocked bywashing with 1 mM biotin. Compound binding wasdetermined by titrating the ligand concentration atconstant DMSO concentration and observing the SPRresponse. A flow rate of 20 ml/minute was used for bind-ing experiments, and all experiments were performed at258 C.

Acknowledgements

We thank Giovanna Esposito, Paul Cole, HeatherSimmonite, and Adam Hold for technical helpwith preparation of samples, and Mike Gait, GeofHarrison, Philippe Vaglio and Horst Kessler forhelpful discussions.

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Edited by J. Doudna

(Received 14 November 2003; received in revised form10 December 2003; accepted 12 December 2003)

Supplementary Material comprising one Figureand a CHARMM script is available on ScienceDirect

356 RNA Structure-based Drug Design