Ligand-supported homology modeling of the human angiotensin II type 1 (AT 1 ) receptor: Insights...

Ligand-Supported Homology Modeling of the HumanAngiotensin II Type 1 (AT1) Receptor: Insights into theMolecular Determinants of Telmisartan Binding

Akshay Patny,1,2 Prashant V. Desai,1,2 and Mitchell A. Avery1,2,3,4*1Department of Medicinal Chemistry, School of Pharmacy, University of Mississippi, Mississippi 38677-18482Laboratory for Applied Drug Design and Synthesis, University of Mississippi, Mississippi 38677-18483National Center for Natural Products Research, University of Mississippi, Mississippi 38677-18484Department of Chemistry and Biochemistry; University of Mississippi, Mississippi 38677-1848

ABSTRACT Angiotensin II type 1 (AT1) recep-tor belongs to the super-family of G-protein-coupledreceptors, and antagonists of the AT1 receptor areeffectively used in the treatment of hypertension. Tounderstand the molecular interactions of theseantagonists, such as losartan and telmisartan, withthe AT1 receptor, a homology model of the humanAT1 (hAT1) receptor with all connecting loops wasconstructed from the 2.6 A resolution crystal struc-ture (PDB i.d., 1L9H) of bovine rhodopsin. The ini-tial model generated by MODELLER was subjectedto a stepwise ligand-supported model refinement.This protocol involved initial docking of non-peptide AT1 antagonists in the putative binding site,followed by several rounds of iterative energy mini-mizations and molecular dynamics simulations. Thefinal model was validated based on its correlationwith several structure-activity relationships andsite-directed mutagenesis data. The final model wasalso found to be in agreement with a previously re-ported AT1 antagonist pharmacophore model. Dock-ing studies were performed for a series of non-pep-tide AT1 receptor antagonists in the active site of thefinal hAT1 receptor model. The docking was able toidentify key molecular interactions for all the AT1

antagonists studied. Reasonable correlation was ob-served between the interaction energy values andthe corresponding binding affinities of these ligands,providing further validation for the model. In addi-tion, an extensive unrestrained molecular dynamicssimulation showed that the docking-derived boundpose of telmisartan is energetically stable. Knowl-edge gained from the present studies can be used instructure-based drug design for developing novelligands for the AT1 receptor. Proteins 2006;65:824–842. VVC 2006Wiley-Liss, Inc.

Key words: AT1 receptor; GPCR; homology model-ing; drug design; losartan; telmisartan;docking; molecular dynamics

INTRODUCTION

The angiotensin II type 1 (AT1) receptor belongs to thesuper-family of G-protein-coupled receptors (GPCRs) and

mediates its effects through interaction with heterotri-meric G-protein and subsequent activation of the phos-pholipase C signal transduction pathway. The AT1 recep-tor plays a key role in the renin–angiotensin systeminvolved in the regulation of cardiovascular functionsand the pathophysiology of hypertension.1 The endoge-nous effector molecule for the AT1 receptor is angioten-sin-II, a vasoactive peptide hormone that regulates cardio-vascular homeostasis by modulating both vascular resist-ance, as well as blood volume.2 Antagonism of the AT1

receptor has gained tremendous attention, primarily dueto the therapeutic success of the drugs targeting thisclass of receptors as antihypertensive agents. The use ofdrug design and molecular modeling, accompanied bystructure-activity relationship (SAR) studies, has led tothe optimization of initial lead candidates and given riseto several potent, selective, and orally bioavailable non-peptide AT1 receptor antagonists. Some of the representa-tive drugs in this category include losartan, candesartan,valsartan, irbesartan, eprosartan, tasosartan, telmisar-tan, and at least 20 more compounds, some of which arein various stages of clinical development or are in clinicaluse (see Fig. 1).3

AT1 receptors have been cloned from several species, andconsist of a single polypeptide chain. The human AT1

Abbreviations: AT2, angiotensin II type 2 receptor; A2A, humanadenosine A2a receptor; B2AR, human b2 adrenergic receptor; ELII,extracellular loop II; ELIII, extracellular loop III; fs, femtosecond;GPCR/s, g-protein-coupled receptor/s; hAT1, human angiotensin II type1 receptor; H-bond/ing, hydrogen bond/ing; HVIII, helix VIII; MD, mo-lecular dynamics; NK2, human neurokinin A receptor; ns, nanosecond;PDB, protein data bank; PDF, probability density function; ps, picosec-ond; P_1L9H, bovine rhodopsin; P2U, human purinergic receptor;rmsd, root-mean-squared deviation; SAR, structure-activity-relation-ship; SCR, structurally conserved region; TM, transmembrane; V2,human vasopressin V2 receptor; 3D, three dimensional.

The Supplementary Material referred to in this article can be foundat http://www.interscience.wiley.com/jpages/0887-3585/suppmat/

*Correspondence to: Mitchell A. Avery, Department of MedicinalChemistry, University of Mississippi, MS 38677-1848.E-mail: [email protected]

Received 24 January 2006; Revised 31 May 2006; Accepted 31 July2006

Published online 10 October 2006 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/prot.21196

VVC 2006 WILEY-LISS, INC.

PROTEINS: Structure, Function, and Bioinformatics 65:824–842 (2006)

(hAT1) receptor consists of 359 amino acids and possesses95% sequence identity with rat and bovine AT1 receptors,illustrating the remarkable sequence identity amongst themammalian species.2 The rat and mouse AT1 receptorsare known to exist in two distinct subtypes, AT1A andAT1B, and are encoded by different genes.4,5 Other mam-malian AT1 receptors, including the hAT1 receptor, do notappear to have subtypes. Angiotensin II type II (AT2)receptors have also been cloned, and belong to the GPCRfamily but share only 34% amino acid sequence identity tothe AT1 receptors.

6–8

The AT1 receptor belongs to the class A of the GPCRsuper-family, and includes rhodopsin-like receptors.9 Rho-dopsin is the only GPCR for which a three-dimensional(3D) structure has been elucidated through X-ray crystal-lography,10 and the coordinates have been deposited inthe Protein Data Bank (PDB).11 Structurally, GPCRs arecharacterized by the presence of seven hydrophobictransmembrane (TM) helices (TM1-TMVII), which areconnected through six alternating extracellular and in-tracellular loops.12 The N-terminus is located on theextracellular side of the membrane, whereas the C-termi-nus occupies the intracellular side.12 The 7TM domain isconstituted by seven a-helices, which are known to adopta common folding pattern, and thus, the 7TM domainconstitutes the most conserved region across the GPCRfamily of proteins.13 Several highly conserved functionalmicrodomains and disulfide bridges are known to be pres-ent in the TM helices of the class A GPCRs. Some of theseconserved regions include (a) the disulfide bond linkingTMIII and extracellular loop II (ELII), (b) the ‘‘LAxxD’’motif in TMII, (c) the ‘‘D/ERY’’ motif in TMIII, and (d)the ‘‘NPxxY’’ motif in TMVII. Regions (a)–(d) are consid-ered to play significant role in the structural and func-tional integrity of the class A GPCRs.14

It is important to understand the molecular interac-tions of antagonists, such as losartan and telmisartanwith the AT1 receptor, which may prove useful in deter-mining critical recognition sites within the receptor aswell as ligands. Subsequently, this information can beutilized in structure-based drug design for the identifica-tion and optimization of novel lead compounds. However,drug design efforts in GPCR research have been limitedby the scarcity of available 3D structural information.Structural characterization of bovine rhodopsin provideda major breakthrough in the computer modeling of sev-eral GPCRs, and has proven to be particularly useful formodeling class A receptors.15 It is important to note that

the X-ray crystal structure of bovine rhodopsin repre-sents a snapshot of the protein in an inactivated staticstate, and is believed to be conformationally distinct fromthe active state of the receptor.10 It has been speculatedthat the inactivated state of the receptor is closer to theantagonist-bound conformation, as opposed to the ago-nist-bound conformation (e.g. 11-cis retinal bound to therhodopsin is an inverse agonist).16 Thus, it can be reason-ably extrapolated that 3D models, constructed usinghomology modeling techniques based on the X-ray struc-ture of bovine rhodopsin as the structural template, willyield models closer to the inactivated or antagonist-boundstate of the receptor. These GPCR models would be moreappropriate for explaining the interactions of antagonistsas compared to agonists, as agonist activation of the re-ceptor is governed by a cascade of complex conformationalchanges. It is also believed that the flat nature of 11-cis-retinal (endogenous ligand) makes the binding site of bo-vine rhodopsin too narrow, as a result of the folding of theELII onto the center of the receptor binding site.17 There-fore, the bovine rhodopsin template is often inadequate toaccurately describe the range of GPCRs that can bindligands with volumetric diversity.

In the absence of structural information, homologymodeling has proven to be a valid alternative for con-structing reasonable 3D models of proteins.18 Althoughhomology modeling has been widely used in the case ofGPCRs, the technique faces several limitations for thesereceptors, including poor sequence identity between tar-get and template sequences, as well as availability of onlybovine rhodopsin as a structural template. This empha-sizes the need for incorporating experimental informationavailable from site-directed mutagenesis or SAR studiesduring the process of homology modeling and refinement,in order to develop a reasonable 3D model of a GPCR pro-tein. Some attempts have also been made to develop 3Dmodels of GPCRs from first principles, which do not usehomology or other structural information from bovinerhodopsin.19,20 However, to the best of our knowledge, noapplication of such methods has been reported for model-ing of the AT1 receptor.

Several previous studies have addressed computer-aided modeling of the AT1 receptor, but only a few de-scribe the mode of antagonist interaction within the re-ceptor binding pocket.18–21 Many of these earlier studieswere published before the X-ray crystal structure of bo-vine rhodopsin was elucidated, hence, molecular model-ing of the AT1 receptor was based either on the low reso-lution structure of bacteriorhodopsin,21 or that of bovinerhodopsin.13,22 After the release of the X-ray structure ofbovine rhodopsin, it was evident that the arrangement ofTM helices was quite different from those observed inbacteriorhodopsin, the latter is not even a member of theGPCR family.10 One of the earliest molecular models ofthe AT1 receptor, one using the bacteriorhodopsin struc-ture as a template, was developed at Merck ResearchLaboratories, and the model addressed the mode of bind-ing of several non-peptide AT1 ligands within the recep-tor binding site.23 This was followed by another model of

Fig. 1. Representative AT1 receptor antagonists in clinical use.

825HOMOLOGY MODELING OF THE HUMAN AT1 RECEPTOR

PROTEINS: Structure, Function, and Bioinformatics DOI 10.1002/prot

the AT1 receptor, based on the bacteriorhodopsin tem-plate, and also using the modeled structures of rhodopsinand b2-adrenergic receptors, the model of b2-adrenergicreceptor was used due to difficulties in directly aligningbacteriorhodopsin with the AT1 receptor sequence.24 Arelated approach using electron microscope obtained 3Dstructure of bacteriorhodopsin, together with a b2-adre-nergic receptor model, led to a 3D construct for the ratAT1 receptor.25 Additionally, another rat AT1 receptormodel was developed in which the projection map ofbovine rhodopsin was used to position TM helices into a3D arrangement, but did not include connecting loops asa result of a lack of structural information.26 These ear-lier studies helped in the qualitative assessment of theAT1 receptor binding site and possible ligand–receptorinteractions. However, as the higher resolution X-raycrystal structure of bovine rhodopsin was released,10 itbecame evident that notable differences exist betweenthe earlier structures and bovine rhodopsin, with regardto packing of the TM helices. Keeping this in mind, it islogical that homology models of GPCRs developed using3D coordinates of bovine rhodopsin should be closer tothe conformation adopted by these receptors in a biologi-cal environment, and thus may serve as better tools tounderstand the critical ligand–receptor interactions. Asmall number of recent studies demonstrates the model-ing of the AT1 receptor, using the first reported X-raycrystal structure of bovine rhodopsin (PDB i.d., 1F88) asa structural template, and addresses the possible modesof binding of non-peptide antagonists in the AT1 receptorbinding site.27–29 It should be mentioned here that all ofthese recent AT1 models were used for qualitatively deter-mining the important interactions of the antagonists withresidues of the binding site. Additionally, the majority ofthese AT1 models dealt with explaining binding modes foreither losartan, or similar AT1 receptor antagonists pos-sessing only one heterocyclic ring.The goal of the present study was to develop a 3D

homology model of the hAT1 receptor using the X-raycrystal structure of bovine rhodopsin, with the intentionof explaining molecular interactions of antagonists, suchas telmisartan with hAT1 receptor binding site residues.To our knowledge, this is the first attempt at constructinga homology model of the hAT1 receptor, using the recentlydetermined 2.6 A resolution crystal structure (PDB i.d.,1L9H)30 of bovine rhodopsin as the template. Thus, thedeveloped homology model should be able to explain thebinding mode of telmisartan and of similar AT1 receptorantagonists possessing more than one heterocyclic ring.Hence, knowledge gained from the present study can beused for the identification and design of novel antagonistsof the AT1 receptor.To achieve this, an initial homology model of the hAT1

receptor was constructed and subsequently subjected to astepwise ligand-supported receptor refinement protocol.The refinement involved a series of iterative energy mini-mizations and molecular dynamics (MD) simulations ofthe hAT1 receptor model in the presence of non-peptideligands. The binding modes for several non-peptide antag-

onists including telmisartan with the AT1 receptor areproposed. The modeled antagonist-AT1 receptor complexesare not only in agreement with available site-directedmutagenesis and SAR data (Table V), but also correlatewell with the pharmacophore model described previouslyfor the benzimidazole-type AT1 receptor antagonists.32

Several critical interactions were identified in the hAT1

model, which may serve as molecular determinants ofnon-peptide ligand recognition at the AT1 receptor antago-nist ligand binding domain. Docking studies were carriedout on a series of non-peptide ligands, including losartanand telmisartan, using the refined hAT1 receptor model,and a reasonable correlation was obtained between ligandbinding affinities and interaction energy scores. The bind-ing pose stability of docked poses was observed by monitor-ing the average potential energy of these complexes in thefinal MD simulation. Thus, a reasonable 3D model of thehAT1 receptor has been developed, one which can be use-fully employed in enhancing our understanding of interac-tions of non-peptide antagonists with the AT1 receptor atthe molecular level. The insights gained can prove valua-ble in the identification, design, and optimization of novelAT1 antagonists in structure-based drug design.

METHODSComputational Resources

All computational studies were performed on a SiliconGraphics Origin 350 server, equipped with eight 700 MHzMIPS R16000 parallel processors, and 2 GB memory.Multiple sequence alignment was performed using theHOMOLOGY module of InsightII (Accelrys Inc., SanDiego, CA, USA). Homology modeling was carried outusing MODELLER 6v1.33,34 The geometrical and localenvironment consistency of the model was evaluatedbased on probability density function (PDF) violationsprovided by MODELLER, and PROSTAT analysis usingInsightII. Initial manual docking, followed by energyminimizations and MD simulations, were accomplishedusing interactive graphics and the DISCOVER module ofInsightII using CFF91 forcefield,35 respectively. Rama-chandran plot analysis of the model was carried out usingthe web interface for ‘‘Ramachandran Plot on the web.’’36

Docking of several non-peptide antagonists was carriedout using GOLD v2.2.37–39 Docking poses were visualizedusing graphics facilities of Sybyl v7.0 (Tripos Inc., St.Louis, MO, USA). The energy minimization of the GOLD-derived antagonist-AT1 receptor complexes was performedusing the eMBrAcE module of the MACROMODEL v8.0(Schrodinger Inc., Portland, OR, USA). Subsequently, MDsimulations of the antagonist-AT1 receptor complexeswere carried out using MACROMODEL v8.0 utilizingOPLS-AA forcefield.40 The conformer search was also car-ried out using MACROMODEL v8.0.

Residue Indexing

Amino acids are numbered according to default numbersin sequences retrieved from SWISS-PROT and TrEMBLdatabases.41 Additionally, wherever appropriate, the common

826 PATNY ET AL.


numbering scheme proposed by Ballesteros and Weinstein42

is used, and the corresponding residue numbers are givenin parentheses. The syntax of the numbering system isX1.23, where the first letter denotes a one letter abbrevia-tion for the amino acid, the first number represents theTM helix number, and the second number signifies thenumber of residue relative to the most conserved residue(assigned number 50) in that TM helix.

Multiple Sequence Alignment

The amino acid sequence for the hAT1 receptor(AG2R_HUMAN) was extracted from the SWISS-PROTand TrEMBL databases of the ExPASy Molecular BiologyServer41 (Primary accession number: P30556). The struc-tural template used for homology modeling was the 2.6 Aresolution crystal structure of bovine rhodopsin (PDBi.d., 1L9H).30 Five additional class A GPCR sequenceswere used for multiple sequence alignment, including thehuman b2-adrenergic receptor (B2AR), the human neuro-kinin A receptor (NK2), the human adenosine A2a recep-tor (A2A), the human vasopressin V2 receptor (V2), andthe human purinergic receptor (P2U). Alignment wasfirst performed automatically using the HOMOLOGYmodule of InsightII, using the PAM_120 matrix and de-fault values. Multiple sequence alignment was carried outin two steps. In the first step, the amino acid sequence ofthe hAT1 receptor was aligned with the other class AGPCR sequences (mentioned earlier). This helped to iden-tify conserved residues in each of the TM helices, as wellas other regions of high sequence conservation. Subse-quently, the resultant sequence alignment was realignedwith the amino acid sequence of the bovine rhodopsinusing the parameters as described earlier. The alignmentwas adjusted manually to verify the alignment of thehighly conserved residues present in TM helices across allthe sequences. The presence of these highly conservedresidues helps in unambiguous alignment of the GPCRsequences, despite the low sequence homology across var-ious species. Wherever appropriate, gaps were insertedinto the sequences to find an optimal alignment, ensuringthat no gaps were present in the TM regions. The lengthof the TM helices for the hAT1 receptor was decided, con-sidering the predictions by TMAP,43 SWISS-PROT,41 andthe length of the corresponding bovine rhodopsin helices.

Homology Modeling

The final multiple sequence alignment was submitted toMODELLER 6v1 for generating homology model of thehAT1 receptor. Based on this sequence alignment, 3D mod-els, containing all non-hydrogen atoms were built, usingthe method as implemented in the MODELLER, whichuses sequence alignment to extract a large number of spa-tial restraints for homology modeling of the target protein.These spatial restraints include (a) homology-derivedrestraints on the distances and dihedral angles in the tar-get sequence, based on alignment with template struc-tures, (b) stereochemical restraints, such as bond lengthand bond angle preferences, obtained from CHARMm22

forcefield, and (c) statistical preferences for dihedral anglesand non-bonded interatomic distances, obtained from arepresentative set of protein structures. These spatialrestraints are then expressed as PDFs, which are com-bined into an objective function that is optimized by a com-bination of conjugate gradients and MD-simulated anneal-ing. Six different models were built, including three actualmodels and three corresponding loop refinement models.During the model generation, the level of optimization wasset to high. Two disulfide bridges were explicitly definedbased on known information: the first between Cys18(N-terminus) and Cys274(ELIII), and the second betweenCys101(C3.25) and Cys180(ELII).2

Initial Model Refinement

Hydrogen atoms were added to Model I using the ‘‘AddHydrogens’’ feature of InsightII. At this stage, all aminoacid residues were kept neutral. The N-terminus (His24)was capped as an amine, while the C-terminus (Ile320)was capped as carboxylic acid. This complete all-atommodel was then subjected to an initial stepwise energyrefinement using a distance-dependent dielectric con-stant and non-bond cutoff distance of 8.0 A. Initially, allheavy atoms were kept fixed, and the hydrogen atomswere allowed to optimize their positions using 500 stepsof steepest descent algorithm to a gradient of 0.01 kcal/Afollowed by 1000 steps of conjugate gradient algorithm toa gradient of 0.001 kcal/A. In the subsequent stages, min-imization steps were kept same but differing positionalrestraints were applied at each stage. The second stageinvolved minimization, with the backbone atoms of theentire protein held fixed, which helped to refine the side-chains of the model. In the third stage, the backboneatoms of only the structurally conserved regions (SCRs)were held fixed during minimization, allowing free move-ment of the connecting loops that helped to optimize theirconformation. In the fourth stage, the backbone atoms ofthe SCRs were tethered with a gradually reducing posi-tional restraint of 50, 30, 15, and finally, 5 kcal/A/mol�2.This allowed optimization of the TM regions and yieldedrefined Model II.

Ligand-Supported Model RefinementProtein preparation

Amino acid residues, such as Lys, Arg, Asp, and Glu,are expected to be charged at physiological pH 7.2. Thus,the PPREP script (Schrodinger Inc., Portland, OR, USA)was used, in order to identify charged residues in thebinding pocket. All residues within 6 A of distance fromany atom of losartan constituted the binding pocket (videinfra). Asp74 (D2.50) was also included in the binding site,and was assigned a formal negative charge (�1).Lys199(K5.42) was assigned a formal positive charge (þ1).Arg275(ELIII) and Asp278(ELIII) were observed to form asalt-bridge, and hence were assigned a formal positive anda negative charge, respectively. To make the receptor over-all neutral, Arg167(ELII), lying further away from thebinding site, was assigned a formal positive charge (þ1).



Although the binding site amino acid residues weretreated as charged, nonetheless, the receptor was keptoverall neutral, so as to avoid any undue electrostaticinteractions in vacuum. The acidic groups of the ligands(carboxylate or tetrazole) were treated as charged moieties.

Refinement with losartan

Losartan was manually docked in Model II, using theknown SAR information.32 The ligand was translated androtated using the interactive graphics facility of InsightII,in order to accommodate it in the putative binding pocket ofModel II. A subset of amino acid residues within 6 A fromevery atom of losartan was defined as the binding site. Thelosartan–AT1 complex was first minimized to relieve badcontacts between the non-bonded atoms. The minimizationprotocols for all calculations involved an initial minimiza-tion involving 500 and 1000 steps of steepest descent andconjugate gradient algorithm, up to a gradient of 0.01 and0.001 kcal/A, respectively. The annealed structures wereminimized for 3000 and 5000 steps of steepest descent andconjugate gradient algorithms, respectively, using the gra-dients as mentioned earlier. Several studies in literaturehave utilized some form of positional restraints during MDsimulation of GPCRs, especially in case of vacuum simula-tions in order to avoid undesirable movements of the TM a-helices.44–47 It has been suggested that when MD simula-tions are performed in vacuum, disregard of the membrane-aqueous environment justifies the use of minimal positionalrestraints, which can simulate the natural stabilizingeffects of the lipid bilayer.45 Therefore, in all further calcula-tions, Phi-Psi (/-w) torsions of residues, forming the TM hel-ices and ELII, were restrained to their current values usinga force constant of 100 kcal/A/mol�2 (unless otherwisestated). Additionally, Omega (x) torsions for all protein resi-dues were forced to trans configuration using a force con-stant of 100 kcal/A/mol�2. Phi-Psi (/-w) torsions for the con-necting loops were also restrained to their current valuesusing a mild force constant of 30 kcal/A/mol�2. Hydrogenbonding (H-bonding) interaction between the acidic group ofligand (tetrazole in losartan) and the side-chain amine ofLys199(K5.42) was used as a distance restraint for guidingthe MD simulation. The losartan–AT1 complex was sub-jected to a simulated annealing protocol, where the complexwas ‘‘heated’’ gradually from a temperature of 100 to 600 K,in steps of 100 K, with 10 ps (picosecond) simulation at eachstage. At 600 K, the complex was simulated for another 50ps, followed by a gradual ‘‘cooling’’ to 300 K, in steps of 100K, with 10 ps of simulation at each stage. Finally, a produc-tion phase was carried out involving a 50 ps simulationusing an NVT ensemble at 300 K, with a time-step of 1 fs(femtosecond). The complex was minimized as mentionedearlier. This helped to significantly open the binding site ofthe hAT1 receptor model, resulting in Model III.

Refinement with telmisartan

The binding pose of losartan in Model III was used tosuperimpose telmisartan, in order to generate a startingstructure for the telmisartan–AT1 receptor complex. The

complex was minimized initially using the protocol de-scribed earlier and then submitted to a simulated anneal-ing protocol. The MD simulation was carried out using anNVT canonical ensemble. The complex was steadilyheated from 100 to 600 K, followed by subsequent coolingto 300 K, in steps of 100 K, with 10 ps of simulation ateach stage and a final 80 ps of simulation at 300 K. Adistance-dependent dielectric constant was used with anon-bond cutoff distance of 7.0 A for the van der Waals(vdW) interactions and 12.0 A for the electrostatic interac-tions. A SHAKE algorithm48 was used with a time-step of1.5 fs. The entire protein was kept free during these simu-lations, except for a mild positional restraint of 10.0 kJ/A/mol�2 on the backbone atoms, in order to preserve the 3Dfold of the TM helices. The complex obtained after MDwas minimized, as described earlier, to get the final telmi-sartan-refined hAT1 receptor model (Model IV).

Docking and Binding Pose Validation

A total of 13 non-peptide AT1 antagonists weresketched and then minimized, using MMFF charges andthe MMFF forcefield49 in Sybyl 7.0 (Supplementary infor-mation, Table S1). The negatively and positively ionizablefunctional groups of ligands were assigned a formal nega-tive (�1) and a formal positive (þ1) charge, respectively.Thus, the ligands were modeled as charged moieties, aswould be expected at the normal physiological pH of 7.2.The final refined hAT1 receptor model (Model IV) wasused for the docking studies. GOLD v2.2 was used fordocking, which uses a genetic algorithm, and allows rota-tion of the side-chain hydrogen atoms of polar residues tooptimize H-bonding interactions. The binding site wasdefined based on the bound conformation of telmisartanin Model IV, and all amino acid residues within 3 A fromevery atom of telmisartan constituted the binding site.Visual inspection was done to make sure that all impor-tant residues were included in the definition of bindingsite. The docking of non-peptide AT1 antagonists was car-ried out using the GOLD standard mode settings. Foreach ligand, a total of 20 genetic algorithm runs werespecified and early termination criteria was set to 1.5 Aroot-mean-squared deviation (rmsd) value. H-bonding re-straints, based on known SAR data and site-directed mu-tagenesis information (Table V), were applied during thedocking protocol. All ligand poses obtained after dockingof each AT1 antagonist were carefully analyzed for validityof the pose and critical H-bonding interactions. TheGOLD-derived antagonist-AT1 receptor complexes weresubmitted to an energy minimization using the eMBrAcEmodule of MACROMODEL v8.0. The eMBrAcE minimiza-tion was performed in the ‘‘energy difference mode,’’ whichinvolves energetic calculations on the ligand–receptorcomplexes. The difference between the minimized energyof both the individual ligand and receptor subtracted fromthe minimized energy of the complex was reported foreach antagonist–AT1 receptor complex. Minimization wascarried out using OPLS-AA forcefield, a distance-dependentdielectric constant, and the non-bond cutoff value of 7.0 A

828 PATNY ET AL.


for vdW, and 12.0 A for electrostatic interactions. A conju-gate gradient minimization was performed for each com-plex for 2500 steps until a gradient of 0.01 kJ/A wasreached. The binding site, comprising of all the residueswithin 14.0 A from Val108 (V3.32), was allowed free move-ment, while the remainder of the protein was kept fixed.In addition, GOLD-derived telmisartan–AT1 receptor

complex was used as the starting structure for further MDsimulations, in order to check the stability of the boundpose of telmisartan in the hAT1 model (Model IV) bindingpocket. The following protocol was employed for MD simu-lation of the telmisartan–AT1 receptor complex. The com-plex was first minimized, and then ‘‘heated’’ graduallyfrom 50 to 300 K in steps of 50 K, with 5 ps of simulationat each step. A positional restraint of 10 kJ/A/mol�2 wasapplied on the backbone atoms to preserve the 3D fold ofthe TM helices. This was followed by another 40 ps of MDsimulation at 300 K, with a gradually decreasing posi-tional restraint of 10, 5, 2, and 1 kJ/A/mol�2. Subse-quently, the positional restraint was removed completelyand an equilibration of 20 ps was carried out for theligand–receptor complex. Finally, the ligand–receptorcomplex was subjected to an unrestrained 1 ns (nano-second) simulation (production phase) at 300 K to assessthe stability. The MD simulation was carried out using anNVT ensemble and a distance-dependent dielectric con-stant, with non-bond cutoff distances, as described earlier,and a time-step of 1.5 fs. At the end of simulation, thecomplex was minimized to obtain reasonable conforma-tion. The average potential energy of the telmisartan-AT1

receptor (Model IV) complex was monitored during thefinal 1 ns production phase of the MD simulation.

Conformer Search

Conformational search was carried out for telmisartanusing the mixed MCMM/Low mode method available inMACROMODEL v8.0. The OPLS-AA forcefield with dis-tance-dependent dielectric constant was used. Non-bondcutoff distances of 7.0 A for the van der Waals and 12.0 Afor the electrostatic interactions were used. The torsionangles and ring closures for telmisartan were defined auto-matically. All conformers within 50 kJ/mol of the energy ofthe global minimum were saved. The number of allowedmonte-carlo steps was set to 10,000. The conformationswere minimized for 2500 iterations using a conjugate gra-dient algorithm to a gradient of 0.01 kJ/A. All the otherparameters were left to the respective default values.

RESULTS AND DISCUSSIONMultiple Sequence Alignment

An accurate multiple sequence alignment is of utmostimportance in building a useful 3D homology model. Thisbecomes even more important in the case of GPCRs,where the only available structural template is bovinerhodopsin, and the identity with the target sequence fallsto even less than 20% in several cases. The pairwisesequence identity between the hAT1 receptor and bovinerhodopsin is �18%. However, the similarity value

increases as the comparison criterion is extended fromsequence identity to sequence similarity. The correspond-ing sequence similarity values for the SCRs, includingindividual TM regions, Helix VIII (HVIII), and for ELIIare listed in Table I. The percentage similarity values forthese SCRs, between the hAT1 receptor and bovine rho-dopsin, range from 42 to 63%. Multiple sequences of classA GPCRs were used during the alignment process to mini-mize the errors emanating from the availability of only asingle structural template for model building. Class AGPCRs contain highly conserved residues in every TM he-lix, including Asn46(N1.50) in TMI, Asp74(D2.50) inTMII, Arg126(R3.50) in TMIII, Trp153(W4.50) in TMIV,Pro207(P5.50) in TMV, Pro255(P6.50) in TMVI, Pro299(P7.50)in TMVII, and Phe309(F8.50) in HVIII of the AT1 receptor(amino acid residue numbers in parentheses represent theBallesteros and Weinstein numbering scheme forGPCRs42 and is described in Methods section). All of thesehighly conserved residues of the AT1 receptor were care-fully aligned with corresponding residues of the bovinerhodopsin, as well as the other class A GPCR sequences(see Fig. 2). Additionally, the cysteine residues known to beinvolved in disulfide bridge formation for class A GPCRswere also aligned.50 These amino acid residues includeCys18 (N-terminus) and Cys274(ELIII), and Cys101(C3.25)and Cys180(ELII).

Based on the careful alignment of the conserved resi-dues, a reasonably accurate multiple sequence alignmentof the hAT1 receptor, bovine rhodopsin, and five otherclass A GPCRs was obtained. Several functional microdo-mains, such as the LAxxD motif in TMII, the D/ERY motifin TMIII, and the NPxxY motif in TMVII are known to beconserved across the members of the class A GPCR super-family15 and are also present in the hAT1 receptor. Thefinal multiple sequence alignment was checked to ensurethe optimal alignment of these microdomains (see Fig. 2).

Homology Modeling

In the present work, the backbone atoms of the bovinerhodopsin structure were assumed to be a reasonablestarting point for building a model of the 7TM domain of

TABLE I. Sequence Identity and Similarity BetweenConserved Regions of the hAT1 Receptor and the

Bovine Rhodopsin

% Identity % Similarity Color codea Lengthb

TMI 18.18 51.51 Pink 33TMII 34.37 62.50 Orange 32TMIII 22.22 52.77 Yellow 36TMIV 16.66 45.83 Aqua 24TMV 14.28 53.57 Brick 28TMVI 13.88 61.11 Blue 36TMVII 23.07 42.31 Green 26HVIII 25.00 58.33 Brown 11ELII 16.00 48.00 Grey 25

aColor code represents respective colors of the TM helices as shownin Figure 2.bLength represents number of amino acid residues.



the hAT1 receptor. The ligand binding domain of the AT1

receptor is proposed to be located primarily in the TMregions, with a few interactions with amino acid residuesof extracellular loops.51 It is also known that the foldingpattern for the 7TM domain is highly conserved across themembers of the GPCR family.13 Based on these observa-tions, and successful modeling of other class A GPCRs,15 itappears that bovine rhodopsin is a suitable structural tem-plate for homology modeling of the hAT1 receptor. Somerecent GPCR modeling studies have suggested that model-ing of the loop regions of GPCRs could provide additionaltopological constraints, and may facilitate in determining

the overall packing of the TM helices.52 Additionally, ex-tracellular loop regions have been reported to participatein binding and recognition of ligands by several peptidebinding GPCRs.15 Hence, a complete model of the hAT1 re-ceptor, including the TM helices and the connecting loops,was built using the X-ray crystal structure of the bovinerhodopsin.

The multiple sequence alignment given in Figure 2 wasused as an input for the generation of homology models ofthe hAT1 receptor. The six different models generated byMODELLER were carefully analyzed for energy value,PDF violations, and violations of geometrical features

Fig. 2. Multiple sequence alignment of the hAT1 receptor (AT1) with the bovine rhodopsin (P_1L9H) and the other class A GPCR sequences. TMhelices, HVIII, and ELII of the hAT1 receptor, and the bovine rhodopsin are enclosed in boxes of varying colors (B2AR, human b2-adrenergic receptor;NK2, human neurokinin A receptor; A2A, human adenosine A2a receptor; V2, human vasopressin V2 receptor; P2U, human purinergic receptor). Themost conserved residue for each helix across all the species is enclosed in a vertical box with blue border.

TABLE II. PROSTAT and MODELLER Analysis of Six Different Models of the hAT1 Receptor

MODELBond

lengthsaBondanglesa

HelixPhi/Psia Omegaa Ca-chiralitya

PDFviolations

MODELLERenergy

AT1_1 4 16 6 1 2 2,793 1,189AT1_2 4 22 2 1 1 2,871 1,190AT1_3 3 19 2 1 1 2,819 1,202AT1_L1 11 32 6 2 2 6,318 4,842AT1_L2 16 46 2 4 2 7,197 5,481AT1_L3 18 50 2 2 2 10,322 6,540

aThe values represent the number of violations found (with standard deviation >5 from reference values) for respective geometrical parame-ters. The last three models represent the corresponding loop refinement models for the first three hAT1 receptor models.

830 PATNY ET AL.


(Table II). The loop refinement models (AT1_L1 to AT1_L3)displayed higher PDF violations, violations of geometricalfeatures, and larger MODELLER energy values. Amongfirst three original models (AT1_1 to AT1_3), which werequite similar with respect to violations and energy values(Table II), the first model, AT1_1, possessing the least rmsdvalue with the backbone atoms of bovine rhodopsin wasselected for further studies. No significant information hasbeen reported for the folding pattern of the N-terminal andthe C-terminal regions of GPCRs, possibly as a result ofpoor sequence homology in these regions. Furthermore, itis known that the N-terminus and the C-terminus of thehAT1 receptor contributes little toward the binding ofsmall molecule non-peptide AT1 ligands.51 Based on theabove considerations, the amino acid residues of the N-terminus, Met1 to Arg23, and the C-terminus, Pro321 toGlu359, were truncated from the selected model of thehAT1 receptor. This crude hAT1 receptor model (Model I)was subjected to further refinement, as described later.The disulfide bridges, incorporated at the time of modelbuilding, furnished two external constraints, which helpedto define the conformation of these otherwise flexible

regions of the receptor. The overview of the protocol usedfor homology modeling, refinement, and validation of thehAT1 receptor model is outlined in Figure 3.

Initial Model Refinement and Validation

Model I, after the addition of hydrogen atoms, wasrefined in a stepwise manner involving rounds of consec-utive minimizations, in order to relieve any steric clashesor improper geometries in the structure. The positionalrestraints were not removed completely from the back-bone atoms of the SCRs, in order to avoid undesirablemovement of these regions, movement likely to occur incase of vacuum simulations. The packing quality of themodel was assessed by the absence of steric clashesbetween any pair of atoms. The overall rmsd fit value forthe backbone atoms of the minimized hAT1 model wasfound to be 1.82 A, with that of the bovine rhodopsincrystal structure (calculated as per ‘‘Alignment by Struc-ture’’ feature in InsightII), highlighting the overall simi-larity of the folding pattern, especially for the highly con-served TM domain. This initially refined hAT1 receptor

Fig. 3. Stepwise protocol for the hAT1 receptor homology modeling, refinement, and validation.



model (Model II) was further subjected to ligand-sup-ported model refinement.

Ligand-Supported hAT1 Model Refinement

In most cases, homology models of GPCRs derived frombovine rhodopsin are not directly suitable for use instructure-based drug design and require targeted itera-tive refinement of the receptor binding site. It has beensuggested that the binding sites of GPCR homology mod-els are often too small to accommodate known ligands.This narrow nature of the binding pocket is possibly aresult of (1) flat nature of 11-cis retinal in the bindingpocket of bovine rhodopsin crystal structure, and (2) mis-placement of side-chains of binding site residues duringhomology model generation. To address this problem, aballoon potential involving a systematic MD based meth-odology to expand and refine the binding sites of modelshas been reported and applied successfully to severalGPCR receptors.53–55 In the current work, the hAT1 re-ceptor model (Model II) was subjected to a similar andextensive ligand-supported homology model refinementprotocol described later.Given our interest in the telmisartan-type non-peptide

AT1 receptor antagonists, such AT1 ligands were dockedin the Model II. The idea was to manually place theseligands in the putative binding site of the Model II, usingavailable SAR information,32,43 followed by refinement ofthe antagonist-receptor complexes. This was achieved bya series of minimizations and MD simulations on theantagonist–receptor complexes. Extensive SAR data hasbeen reported for AT1 receptor antagonists, includingtelmisartan-type ligands.32,43 A pharmacophore modelwas generated based on the low energy conformations ofthe benzimidazole-type AT1 receptor antagonists, capableof explaining the observed SAR data, and has beenreported elsewhere.32 The critical pharmacophoric fea-tures of this model included the presence of a negativelyionizable group, two H-bond acceptors, and two lipohilicfeatures (discussed in detail later).32

Refinement with losartan

Based on the SAR information, losartan was manuallydocked in the approximate binding site of Model II. Themanual docking of losartan was based on the knowledgethat its acidic tetrazole group should point toward the pos-itive charge in the receptor, Lys199(K5.42), in case of thehAT1 receptor.31 The heterocyclic imidazole ring of losar-tan was placed in the proximity of Asn111(N3.35) andAsn295(N7.46).26 However, as expected, the initial boundpose of losartan had some steric clashes with certain bind-ing site residues, as a result of the narrow and closednature of the binding pocket of Model II (see Fig. 4). Thesesteric clashes were resolved in the following refinementprotocol. The losartan–AT1 complex was submitted to min-imization with positional restraints applied to the Phi-Psi(/-w) torsions of the protein. The idea was to preserve thecritical a-helical geometry of the SCRs (TM helices), while

simultaneously allowing these regions to move, relative toeach other, in order to create space for the docked ligand.The minimized losartan–AT1 complex did not show someof the critical ligand–receptor interactions, for example,the tetrazole group was pointing in a direction away fromthe Lys199(K5.42) side-chain amine. In addition, theacceptor nitrogen atom and the hydroxyl substituents onthe imidazole ring were not seen to interact with theamino acid residues, Asn111(N3.35), or His256(H6.51), orAsn295(N7.46), as anticipated from the SAR and mutationdata.26,32

It is known that minimization alone might not be suffi-cient to refine the conformation of the ligand–receptorcomplex. In the case of GPCRs, MD simulations havebeen reported to successfully evolve the conformation ofthe ligand–receptor complex in an alternate manner.17

Thus, the resultant losartan–AT1 complex was subjectedto a series of restrained MD simulations. An iterativeprotocol, wherein the output of one simulation was fed inas input for the subsequent MD simulation, was followeduntil the modeled complex displaying anticipated ligand–receptor interactions was obtained.

The general protocol followed for various MD simulationsis described in the methods section. The refined losartan–AT1 complex (Model III) showed significant correlationwith known SAR information. The Lys199(K5.42) side-chain amino group exhibited H-bonding, as well chargedinteractions with the acidic tetrazole moiety of losartan.This interaction is known to be one of the key determi-nants of molecular recognition, and is common to bothagonists, as well as antagonists of the AT1 receptor.

51 Theacceptor nitrogen atom of the heterocyclic imidazole ringalso showed H-bonding interactions with the side-chainsof Asn111(N3.35) and Asn295(N7.46). Additionally,His256(H6.51) donor hydrogen atom was within H-bond-ing distance with the hydroxyl group of losartan. The n-butyl and the biphenyl moieties of losartan showedhydrophobic interactions with the binding site residues,Val108(V3.32), Leu112(L3.36), Trp253(W6.48), and Ala291(A7.42).

The binding site of the hAT1 receptor model wasexpanded during the MD simulation of the losartan–AT1

complex. A significant increase in the volume of the bind-ing site was observed in transition from Model II (withoutany ligand) to Model III (losartan-bound) as shown inFigure 4. However, at this stage, it was still not possibleto explain the binding of relatively larger ligands, such astelmisartan. Hence, this losartan-refined model of thehAT1 receptor (Model III) was subjected to further refine-ment with telmisartan.

Refinement with telmisartan

The losartan-refined hAT1 receptor model (Model III) wasused as the starting structure for the manual docking of tel-misartan. Telmisartan possesses similar pharmacophoricfeatures as present in losartan. In comparison to losartan,the imidazole moiety is replaced by a bis-benzimidazole,and the tetrazole moiety is replaced by a carboxylate group

832 PATNY ET AL.


in telmisartan. The presence of common pharmacophoricfeatures helped to superimpose telmisartan onto the boundconformation of losartan in Model III. As expected, the rela-tively bigger bis-benzimidazole substituent in telmisartandisplayed steric clashes with some of the binding site aminoacid residues. The initial telmisartan–AT1 complex was sub-jected to an energy minimization, and a reasonable startingcomplex with low energy was obtained. The complex wasthen subjected to a simulated annealing protocol involvingheating to 600 K, cooling to 300 K, and final minimization.

The refined telmisartan–AT1 complex (Model IV) displayeddesirable ligand–receptor interactions (vide infra). The bind-ing pose of telmisartan in the Model IV revealed the pres-ence of critical H-bonding interaction of Lys199(K5.42) side-chain amine with the carboxylate moiety.

The rmsd values for the complete hAT1 model, as wellas for the binding site residues, for Model II, Model III,and Model IV are listed in Table III. Significant changesoccurred in the backbone orientation of the hAT1 model,in transition from Model II (apo) to Model III (losartan-

Fig. 4. Binding site expansion during the ligand-supported hAT1 model refinement. (A) Initially refined hAT1 model (Model II, without ligand). (B)Losartan-refined hAT1 model (Model III). (C) Telmisartan-refined hAT1 model (Model IV). TM helices are shown as cyan ribbons. Binding site is shownas yellow mesh. Lys199(K5.42) is shown colored by atom types, and ligands are represented as space filling CPK models colored by atom types.Hydrogen atoms are displayed off for clarity.



bound), highlighted by an rmsd value of 2.25 A for thebackbone atoms. However, the transition from Model III(losartan-bound) to Model IV (telmisartan-bound) primar-ily entailed significant movement of the side-chains of thebinding site residues, represented by an rmsd value of3.10 A. The side-chains of several residues, including aro-matic residues, Phe204(F5.47), Trp253(W6.48), His256(H6.51), and Tyr292(Y7.43), tilted outwards to accommo-date telmisartan in the binding pocket of Model IV. Thus,Model IV possessed an altered binding site, in order toaccommodate telmisartan efficiently, as seen in Figure 4.The overall orientation of the backbone did not change sig-nificantly in transition from Model III to Model IV, andhad an rmsd value of only 0.60 A for the entire hAT1

model.

Refined hAT1 Receptor Model: Characteristicsand Validation

The AT1 receptor homology modeling was followed by astrategic ligand-supported model refinement (see Fig. 3),in order to arrive at the final refined hAT1 receptor model(Model IV). A significant expansion in the size and vol-ume of the binding pocket was observed in transitionfrom the initially refined hAT1 model (Model II) to thelosartan-refined hAT1 model (Model III), and finally, tothe telmisartan-refined hAT1 model (Model IV) (see Fig. 4).The ligand-supported model refinement was able to suc-cessfully expand the binding site, and thus the refinedmodel can now explain ligand–receptor interactions forseveral non-peptide AT1 antagonists, including losartanand telmisartan. These non-peptide ligands of varyingsizes would otherwise have not fit in the binding site ofModel I. Appropriate care was taken, throughout therefinement protocol, to maintain the conserved a-helicalgeometry of the TM helices. The final hAT1 receptormodel (Model IV) was analyzed for geometrical and ster-eochemical quality. All of the geometrical and the stereo-chemical violations observed in the initial model (AT1_1:Table II) were resolved in the current Model IV. TheRamachandran plot (see Fig. 5) revealed that 98% of thetotal residues were in the allowed regions. The detailsare tabulated in Table IV. Out of the five residues seenoutside the allowed regions, three were glycine residues,which are known to occupy all four quadrants of theRamachandran plot. Thus, only two non-glycyl residues,Ile276 and Thr190, were observed lying outside theallowed regions. These residues are situated further awayfrom the non-peptide binding site in the extracellular loopregions.

Conserved Microdomains in GPCRs: bovineRhodopsin Vs AT1 ReceptorInter-helix H-bonding interactions

Several interhelical interactions are known to be con-served across the GPCR super-family.50 The interhelicalinteractions discussed for the hAT1 receptor are asobserved in Model IV (unless mentioned otherwise). In thecrystal structure of bovine rhodopsin, the side-chain ofAsn55(N1.50) interacts with the backbone carbonyl

TABLE III. RMSD Comparison Between the hAT1 Receptor Models

Complete model (A) Binding site (A)

Backbone atoms Heavy atoms Backbone atoms Heavy atoms

Model II–Model III 2.25 2.82 1.65 2.12Model III–Model IV 0.60 3.16 0.57 3.10Model II–Model IV 2.32 3.96 1.72 3.58

Fig. 5. Ramachandran plot of the final telmisartan-refined hAT1 re-ceptor model (Model IV).

TABLE IV. Ramachandran Plot Analysis of the FinalTelmisartan-Refined hAT1 Receptor Model (Model IV)

Ramachandran Plot analysisTotal amino acid residues 262 (100.00%)Fully allowed Region (FAR) 158 (60.31%)Additionally allowed region (AAR) 90 (34.35%)Generously allowed region (GAR) 9 (3.44%)Outside regions 5 (1.91%)Non-glycyl residues outside AAR 2 (0.77%)

834 PATNY ET AL.


groups of Ala299(A7.46) and Asp83(D2.50).10 Similarly, inthe hAT1 Model I, the side-chain of Asn46(N1.50) formed aH-bond with the backbone carbonyl of Asn295(N7.46) andthe side-chain carboxylate of Asp74(D2.50). However, inthe hAT1 Model IV, the side-chain of Asn46(N1.50) hadmoved toward TMI, thereby retaining H-bond with thebackbone carbonyl of Asn295(N7.46), but not with the car-boxylate of Asp74(D2.50). It was also noticed that theside-chain of Asn295(N7.46) moved toward TMIII duringrefinement, and was seen to point toward the putativebinding site of the non-peptide antagonists (vide infra).Asn78(N2.45) in bovine rhodopsin forms H-bonds withSer127(S3.42) , Thr160(T4.49), and Trp161(W4.50).10 Cor-respondingly, in the hAT1 receptor model, Asn69(N2.45)displayed interactions with hydrophobic Leu118(L3.42)and Ile152(I4.49), instead of the corresponding polar resi-dues in bovine rhodopsin, while, Trp153(W4.50) is con-served. Thus, similar to rhodopsin, the side-chain ofAsn69(N2.45) appeared to form a H-bond with the side-chain of Trp153(W4.50) in the hAT1 receptor model. The‘‘(D/E)R(Y/W)’’ motif is a highly conserved microdomianfound in several class A GPCRs.15 In bovine rhodopsin,the carboxylate of Glu134(E3.49) forms a salt-bridge withthe guanidinium moiety of the adjacent Arg135(R3.50).10

Additionally, Arg135(R3.50) may form H-bonds with eitherone, or both, of the two residues, Glu247(E6.30) orThr251(T6.34), both positioned in TMVI in several GPCRs.In bovine rhodopsin, the side-chain of Arg135(R3.50) formsa H-bond with the side-chain hydroxyl of Thr251(T6.34).10

These molecular interactions between the amino acid resi-dues of TMIII and TMVI are believed to help restrain therelative positions of these TM helices and maintain the re-ceptor in its inactive state.15 Likewise, in the hAT1 recep-tor model, the D/ERY motif was found to be conserved (seeFig. 6). In Model I, the side-chain of Arg126(R3.50) pointedaway from Asp125(D3.49). However, during refinement,movement of the guanidinium group of Arg126(R3.50) wasenergetically driven to form a salt-bridge with the carboxy-late of Asp125(D3.49). Additionally, as in bovine rhodopsin,Arg126(R3.50) in the hAT1 receptor model appeared tohave H-bonding interactions with the amino acid residuesof TMVI, Asn235(N6.30), and Phe239(F6.34). Analogous tobovine rhodopsin, the backbone carbonyl of Asn235(N6.30)appeared to interact, via a H-bond, with the backbone am-ide of Phe239(F6.34) in the hAT1 model. Another highlyconserved microdomain observed in several class A GPCRsis the NPxxY motif in TMVII (see Fig. 6). In bovine rhodop-sin, the hydroxyl group of Tyr306(Y7.53) is in proximity tothe side-chain carbonyl of Asn73(N2.40). The NPxxY motifwas found to be conserved in the hAT1 receptor model,except that Asn73(N2.40) of bovine rhodopsin is mutatedto Ser64(S2.40) in the hAT1 receptor. The LAxxD motif inTMII is also found to be conserved in several class A orrhodopsin-like GPCRs (see Fig. 6). The corresponding resi-dues in the hAT1 receptor, for example, Leu70(L2.46) andAsp74(D2.50), appeared to have their side-chains facing to-ward the core of the receptor in a fashion observed in bo-vine rhodopsin. TMIII is characterized by the presence ofanother highly conserved residue, which is Leu119(L3.43)

in the hAT1 receptor, and has its side-chain pointing to-ward the center of the receptor, similar to that in bovinerhodopsin. Yet another highly conserved residue of TMIIIis Cys101(C3.25) in the hAT1 receptor, which is known toform a disulfide bridge with Cys180(ELII). This disulfidebridge is known to be conserved across numerous class AGPCRs and is believed to play role in maintaining the rela-tive orientation of these otherwise flexible regions.50

Hydrophobic interactions

The 7TM bundle of the hAT1 receptor model is addi-tionally stabilized by a network of highly conserved resi-dues involved in hydrophobic and p-stacking interactions.Trp253(W6.48) in the hAT1 receptor, corresponding toTrp265(W6.48) in bovine rhodopsin, is one of the highlyconserved residues within class A GPCRs. In the hAT1 re-ceptor model, Trp253(W6.48) appeared to undergo p-stack-ing interactions with Phe249(F6.44) on one side, andHis256(H6.51) on the other (see Fig. 7). In addition, one ofthe key aromatic interactions in bovine rhodopsin involvedinteraction between Tyr306(Y7.53) and Phe313(F8.50).10 Asimilar aromatic p-stacking interaction between Tyr302(Y7.53) and Phe309(F8.50) was also observed in the hAT1

receptor model.

Non-Peptide Antagonist Binding Site

The putative antagonist binding site of the hAT1 recep-tor was located and subsequently refined with the aid ofligand-supported model refinement using non-peptide AT1

antagonists, losartan, and telmisartan. The binding cavityfor non-peptide antagonists was observed to be formed byTMII and TMIII on one side and TMVI and TMVII on theother, with some involvement of amino acid residues ofTMV. TMI and TMIV do not seem to have significant inter-actions with the non-peptide antagonists. Mutational anal-ysis has also suggested that the non-peptide antagonistbinding site for the hAT1 receptor involves primarily theamino acid residues of TMIII, TMVII, and a few residuesin TMII, TMV, and TMVI, with no significant contributionfrom the extracellular domains.51

The hAT1 receptor (TM helices and connecting loops)modeled with telmisartan, a benzimidazole-type AT1 re-ceptor antagonist, is shown in Figure 6. Telmisartan wasseen to be placed between the TM helices, closer to theextracellular domain of the receptor. In addition, ELIIseemed to lie in the vicinity of the proposed binding site.This loop has been reported to be folded onto the ligand-binding site in bovine rhodopsin, and is speculated to beinvolved in the entry of ligands and ligand recognition,and particularly for the binding of agonists, such as angio-tensin-II in case of the hAT1 receptor.16 Detailed analysisof the refined hAT1 receptor model (Model IV) revealedseveral critical ligand-receptor interactions, which are inagreement with the known SAR and mutational data(Table V), providing validation in support of the developedhAT1 receptor model. As mentioned earlier, a pharmaco-phore model has been proposed for benzimidazole-typeAT1 receptor antagonists consisting of following five fea-



tures: (1) a H-bond acceptor corresponding to the lone pairof nitrogen atom on proximal benzimidazole ring, (2) anegatively ionizable feature represented by the acidic car-boxylate or tetrazole moiety attached to biphenyl frag-ment, (3) a lipophilic aromatic feature corresponding tothe phenyl ring, (4) a lipophilic vdW feature representedby the n-alkyl chain on the heterocyclic moiety, (5) anadditional H-bond acceptor corresponding to the acceptornitrogen atom of the distal benzimidazole ring.32 The de-veloped model of the hAT1 receptor appears to be in agree-ment with this previously reported ligand-based pharma-cophore model for the non-peptide AT1 antagonists.

It appeared from the binding pose of telmisartan thatthe bis-benzimidazole fragment occupied a region primar-ily between TMIII and TMVII, displaying a few interac-tions with amino acid residues of TMII and TMVI (seeFig. 6). The amino acid residues Ile288(I7.39), Ala291(A7.42),and Tyr292(Y7.43) appeared to form a hydrophobic flooron one side of the bis-benzimidazole, while Leu81(L2.57)and Ala104(A3.28) lying in the vicinity of the bis-benzim-idazole fragment provide additional hydrophobic interac-tions from the other side (see Fig. 7). The n-propyl chain oftelmisartan lies in the lipophilic cavity formed by TMIIand TMIII on one side and TMVI on the other side (seeFig. 6). This cavity appeared to extend downwards towardthe center of the TM bundle (see Fig. 4). It is lined byamino acid residues Phe77(F2.53), Phe248(F6.43), Phe249(F6.44), and Trp253(W6.48) on the top (see Fig. 7) and sur-rounded by the side-chains of hydrophobic residues,Leu70(L2.46), Ala73(A2.49), Cys76(C2.52), Ala114(A3.38),Leu118(L3.42), Trp153(W4.50), and Ile245(I6.40). Fur-

Figure 6.

Figure 7.

836 PATNY ET AL.


thermore, the pharmacophore model also highlighted therequirement of a lipophilic vdW feature represented by then-alkyl chain on the heterocyclic moiety.32 The biphenylfragment of telmisartan was seen to lie in the regionformed between TMIII and TMVI (see Fig. 6), and is in-volved in aromatic-stacking interactions, sandwichedbetween Phe249(F6.44), Trp253(W6.48), and His256(H6.51)residues (see Fig. 7). Additional aromatic interactions wereobserved between the phenyl ring and the Phe204(F5.47)(see Fig. 7). This is also in agreement with the lipohilic aro-matic feature of the pharmacophore model represented bythe biphenyl fragment.32 In addition, amino acid residues,Val108(V3.32) and Leu112(L3.36), appear to be involved inhydrophobic interactions with the biphenyl moiety (seeFig. 7). Val108Ile and Val108Ser mutation had been shownto cause significant loss in the binding affinity of losartanfor the AT1 receptor.31 Thus, the close proximity of theside-chain of Val108(V3.32) to the biphenyl moiety of thenon-peptide antagonists (see Fig. 7) may explain the loss inbinding affinity on mutating Val108(V3.32) to amino acidresidues with bulkier side-chains (Val108Ile mutation),which might hinder the binding of non-peptide antagonists

in bioactive conformations. Additionally, the loss in bindingaffinity by replacement with a polar side-chain at this posi-tion (Val108Ser mutation) underscores the importance ofhydrophobic interaction in this region. The carboxylate oftelmisartan appeared to be in proximity to amino acid resi-dues, Lys199(K5.42), His256(H6.51), and Gln257(Q6.52). Itis seen to be involved in ion-pair interactions, as well ascharge reinforced H-bonding with the protonated amineside-chain of Lys199(K5.42) (see Fig. 7). A H-bond betweenthe carboxylate and the side-chain of His256(H6.51) wasalso observed (see Fig. 7). The side-chain of Gln257(Q6.52)seemed to point towards the binding cavity in the initialModel I; nonetheless, in the final refined Model IV, itappeared to point away from the binding cavity. Lys199(K5.42) has been shown to be one of the key amino acid res-idues involved in the molecular recognition of the AT1 re-ceptor antagonists.31,51 This is also in accordance with therequirement of an ionic interaction fulfilled by the acidic(carboxylate/tetrazole) group on the biphenyl fragment, asproposed by the pharmacophore model.32 Polar residues,such as Asn295(N7.46) and Asn111(N3.35), have beenshown to play an important role in non-peptide antagonistbinding.26 It has also been suggested that polar residues,such as Asn111(N3.35), Ser252(S6.47), and Asn294(N7.45),can alternate, serving as potential hydrogen bond donors tointeract with the acceptor heteroatom of the non-peptideantagonists.28 Correspondingly, in Model IV, 30N atom ofproximal benzimidazole ring appeared to form H-bondswith Asn111(N3.35) and Asn295(N7.46) (see Fig. 7). Thisis also verified by the H-bond acceptor requirement at thisposition suggested by the aforementioned pharmacophoremodel.32 The pharmacophore model also characterized thepresence of another heteroatom as a potential H-bondacceptor, the acceptor nitrogen atom on the distal benzim-idazole ring.32 In the final refined hAT1 receptor model(Model IV), the corresponding 3N acceptor atom of telmi-

TABLE V. Correlation Between the Non-peptide Antagonist–AT1 Receptor Interactions (Model IV)and the Reported SAR and Site-directed Mutagenesis Data

AT1 residue TM helixReported SAR/mutational

data

Type of interaction(observed in

the hAT1 model)

Non-peptide antagonistmoiety (involved in

interaction)

Val108(V3.32) TMIII (a) Replacement with a largerhydrophobic side-chain(V108I); (b) Replacementwith a polar side-chain(V108S). Both decreasesbinding affinity31

Hydrophobic Biphenyl moiety of thenon-peptide ligands

Asn111(N3.35) TMIII Critical role in non-peptideantagonist binding26

H-Bond Acceptor in Heterocyclicmoiety (3’N in Telmisartan)a

Lys199(K5.42) TMV K199A mutation decreasesbinding affinity fornon-peptide antagonists31

Multiple H-Bond,ion-pair

Carboxylate/Tetrazole onbiphenyl fragment ofnon-peptide ligands

His256(H6.51) TMVI Proposed H-bond donor32 H-Bond Polar substituient at 5-positionin heterocyclic moiety(3N in Telmisartan)�

Asn295(N7.46) TMVII Critical role in non-peptideantagonist binding26

H-Bond Acceptor in Heterocyclic moiety(3’N in Telmisartan)�

aRefer Figure 1.

Fig. 6. Proposed binding pose of telmisartan in the final telmisartan-refined hAT1 receptor model (Model IV). The backbone of the AT1 receptoris represented as oval ribbon in yellow. Lys199 (K5.42) is shown as ma-genta stick with its side-chain nitrogen atom colored blue. Telmisartan isshown as space filling CPK model colored by atom types. Hydrogen atomsare displayed off for clarity. The red, blue, and cyan ribbons represent the‘‘DRY’’ motif, the ‘‘LAxxD’’ motif, and the ‘‘NPxxY’’ motif, respectively.

Fig. 7. Proposed binding site interactions of telmisartan in the finalrefined hAT1 receptor model (Model IV) [(A) side view and (B) top view].Telmisartan is shown as thick sticks colored by atom types. Critical polarresidues of the binding site are shown as sticks in magenta and hydro-phobic residues as brown sticks. Hydrogen bonds are shown as dottedgreen lines. Non-polar hydrogens are displayed off for clarity.



sartan formed a H-bond with the side-chain donor hydro-gen atom of His256(H6.51) (see Fig. 7). Similarly, in thelosartan-refined hAT1 receptor model (Model III), thehydroxyl oxygen displayed H-bonding interactions withthe side-chain of His256(H6.51). Thus, based on ourmodel, we hypothesize that presence of this additional H-bond with His256(H6.51) may be crucial for high affinitybinding to the AT1 receptor. In the refined hAT1 receptormodel (Model IV), the n-propyl side-chain of telmisartan isin the vicinity of the following hydrophobic residues:Phe77(F2.53), Phe248(F6.43), Phe249(F6.44), Trp253(W6.48),and Ala291(A7.42) (see Fig. 7). His183 in the ELII (closeto the extracellular side of TMV) is implicated in interac-tions with the side-chain carboxylate of Asp1 of angioten-sin-II.51 In the current hAT1 receptor model, the side-chain of His183 was seen close to the carboxylate group oftelmisartan, highlighting the overlapping nature of thebinding site for agonists and antagonists of the AT1 recep-tor. These observations clearly indicate a close correlationbetween the observed ligand–receptor interactions in thetelmisartan-refined hAT1 receptor model and the reportedSAR, as well as site-directed mutagenesis data. This, inturn, provides additional validation for the developedhAT1 receptor model. It should be recognized that it ischallenging to explain every mutation result with one par-ticular model, since many mutational studies on GPCRs,including the structure-function of the receptor, are basedon a loss of function strategy that can be a result ofchanges in the trafficking efficiency of the receptor to thecell surface, or even the misfolding of the receptor.56,57

Docking and Binding Pose Stability

Docking was carried out in order to understand the mo-lecular interactions of several AT1 antagonists, and toassess the suitability of the refined hAT1 model for use instructure-based drug design. Owing to our interest intelmisartan-type AT1 receptor antagonists, 13 non-peptideAT1 receptor antagonists, including losartan and telmisar-tan, with binding affinities values ranging from 150 lM to1 nM, were docked in the final refined hAT1 receptormodel (Model IV) (chemical structures and binding affin-ities are provided in the Supplementary Information:Table S1). The docking revealed similar binding poses forall of the AT1 antagonists studied. For a majority of theligands, top scoring pose showed relevant binding interac-tions, including the formation of key H-bonds with Asn111(N3.35), Lys199(K5.42), His256(H6.51), and Asn295(N7.46).The GOLD-derived antagonist-AT1 receptor complexeswere scored using an extensive forcefield based energyminimization protocol (details in the Methods section).The eMBrAcE module in the MACROMODEL v8.0 wasused to calculate the energy difference values for theantagonist-AT1 receptor complexes utilizing the OPLS-AAforcefield. The plot of the empirical Interaction Energyscores (eMBrAcE scores) vs. the binding affinities (pIC50)for the AT1 antagonists is shown in Figure 8. TheeMBrAcE energy scores for the non-peptide AT1 antago-nists are provided in the supplementary information

(Table S1). A correlation value of 0.73 was obtained afterremoving one outlier. This appears to be quite reasonable,keeping in mind that a homology-derived GPCR modelwas used for the docking study. Similar correlation valuehas been recently reported for docking studies carried outon the GPCR model of human Ghrelin receptor.58 Itshould be emphasized that the primary goal of the currentdocking study was not to utilize the developed hAT1 modelfor quantitatively predicting the binding affinities forligands, but to test the ability of this model to identify keymolecular interactions, and thus, guide the structure-based drug design. The docking study was able to success-fully identify molecular interactions for several non-peptideAT1 antagonists, known to be critical for binding to theAT1 receptor.

The binding poses of losartan, carboxylate derivative oflosartan (EXP7711), telmisartan, and tetrazole derivativeof telmisartan were analyzed, in order to understand theeffects of different acidic groups (carboxylate/tetrazole) interms of receptor interactions, leading to differing bindingaffinities for losartan and telmisartan derivatives (Supple-mentary Information: Table S1, Figure S1). It was seenfrom the binding poses of these ligands, that the acidicgroup on the distal phenyl ring occupied similar 3D space,and was in proximity to the side-chains of residues,Lys199(K5.42) and His256(H6.51). In case of losartan andEXP7711, it was shown that Lys199Gln and Lys199Alamutation greatly decreased the binding affinity forEXP7711, but that for losartan was not altered to a greatextent.59 Thus, it was hypothesized that the binding oftetrazole moiety with the AT1 receptor involve multiplecontacts with residues, such as Lys199(K5.42) and His256(H6.51), and does not solely depend on Lys199(K5.42)interaction. It was also reported that the Lys199Gln andHis256Ala double mutant decreased the binding affinityfor non-peptide AT1 antagonists, losartan and candesar-tan.29 In addition to formation of critical H-bonds by theseligands, the tetrazole moiety of losartan seemed to liewithin H-bonding distance from His256(H6.51), unlike forcarboxylate group in case of EXP7711. It has also beenshown that potency in the losartan-type non-peptideantagonists could be enhanced by increasing the size ofthe acidic group (carboxylic acid < tetrazole ¼ acylsulfona-

Fig. 8. Correlation plot of binding affinity vs. eMBrAcE energy scorefor non-peptide AT1 receptor antagonists. Binding affinity is representedas pIC50 values [�log (IC50)]. eMBrAcE energy values shown are multi-plied by (�1).

838 PATNY ET AL.


mide) at the -ortho position of the distal phenyl ring.60

This may explain higher binding affinity of losartan com-pared to EXP7711. Conversely, the binding affinitydecreased for tetrazole derivative of telmisartan comparedto telmisartan.32 The binding pose for telmisartan and tet-razole derivative of telmisartan showed that the carboxy-late in the former is able to form additional H-bondinginteraction with His256(H6.51); however, no such H-bondwas seen in case of the latter. The acidic group was seenpointing toward the bis-benzimidazole in the bound con-formation of telmisartan and derivative compounds (seeFig. 7). In case of tetrazole derivative of telmisartan, thebis-benzimidazole fragment was seen to be tilted back-wards, possibly as a result of the intramolecular sterichindrance posed by relatively bigger tetrazole group, com-pared to the carboxylic acid in case of telmisartan. To-gether, the observations from the experimental data, aswell as those suggested by the binding poses of the ligandsin the developed hAT1 receptor model, may explain the dif-ferential effects of carboxylate/tetrazole substitution forlosartan and telmisartan derivatives.As expected, GOLD-derived docked poses of losartan

and telmisartan in Model IV, differed significantly fromthe poses obtained based on the manual docking of theseligands in Model II, and Model III, respectively. In themanually docked pose of losartan in Model II, the tetra-zole moiety was seen pointing in a direction away fromthe center of the binding pocket, and the side-chain ofVal108(V3.32) was pointing away from the biphenyl moi-ety. The side-chain of Asn295(N7.46) pointed toward theimidazole ring; however, the side-chain of Asn111(N3.35)pointed in a direction away from the binding pocket. Inthe refined Model IV, the tetrazole moiety of losartanformed charge-reinforced H-bonds with the side-chain ofLys199(K5.42), as mentioned earlier. In addition, theside-chain of Asn111(N3.35) also moved toward the bind-ing pocket, and the acceptor nitrogen atom of the imidaz-ole formed H-bonds with the side-chains of both, Asn111(N3.35) and Asn295(N7.46). The n-butyl chain of losartanoccupied the hydrophobic region formed between TMII,TMIII, and TMVI. Hydroxyl group of losartan formed H-bond with the side-chain of His256(H6.51) in Model IV.The heavy atom rmsd value between the manuallydocked losartan in Model II and losartan docked in ModelIV was 3.14 A. The manually docked pose of telmisartanwas based on superimposition onto the refined pose of los-artan in Model III. In this binding pose, both the bis-benzimidazole and biphenyl fragments of telmisartanappeared planar, assuming an open V shaped conforma-tion. Close contacts between telmisartan and certainbinding site residues were observed, especially in the vi-cinity of the distal benzimidazole ring, due to the bulkiersubstitution at this position compared to losartan. Thedocked conformation of telmisartan in Model IV wasquite similar to that of losartan in Model IV. The phenylrings were orthogonal relative to each other, and the dis-tal benzimidazole ring also rotated with respect to theproximal ring, allowing telmisartan to occupy a tighter Vshaped conformation in the non-peptide antagonist bind-

ing pocket. Majority of the critical interactions with thebinding site residues, such as Asn111(N3.35), Lys199(K5.42), His256(H6.51), and Asn295(N7.46), were con-served for telmisartan in Model IV. The heavy atom rmsdvalue between the manually docked telmisartan in ModelIII and telmisartan docked in Model IV was 1.26 A.

To assess the stability of the GOLD-derived binding poseof telmisartan in the Model IV, an extensive MD simula-tion was carried out. In this MD simulation, the GOLD-derived telmisartan–AT1 receptor complex was used as thestarting structure. The average potential energy value forthe telmisartan–AT1 complex during the final productionphase simulation of 1 ns, plotted against the simulationtime, is shown in Figure 9. The average potential energy ofthe telmisartan–AT1 complex decreased initially for thefirst 300 ps, and then remained stable over the last 700 psof the simulation. The heavy atom and backbone atomrmsd values between the starting telmisartan-Model IVcomplex and the final minimized complex obtained afterthe simulation were 1.15 and 0.89 A, respectively. To-gether, these results indicated that the telmisartan–AT1

receptor complex was stable during the course of the MDsimulation. The final minimized complex of telmisartan–AT1 receptor after MD simulation was analyzed, in orderto ensure the presence of key interactions with the bindingsite residues. The complex was also analyzed using PRO-STAT and Ramachandran plot analysis, to ensure appro-priate geometrical features. Thus, the GOLD-derived tel-misartan–AT1 receptor complex appeared to be stable.

A conformer search for telmisartan was carried out tostudy the existence of conformations similar to the GOLD-derived docked conformation of telmisartan in the hAT1

receptor model (Model IV). A total of 315 unique conforma-tions were obtained, out of which 242 conformations mini-mized with good convergence within the limits of minimi-zation parameter set (see Methods section). The globalminimum obtained was repeated 75 times and had anenergy value of 96.4 kcal/mol. The heavy atom rmsd valuebetween the docked conformation of telmisartan and theglobal minimum was 1.69 A. The energy of the docked con-formation of telmisartan was found to be 63.0 kcal/mol.Thus, a conformation close to the GOLD-derived dockedconformation of telmisartan was identified in the gener-ated set of conformers and was approximately within30 kcal/mol of the global minimum. These findings sug-gested the energetic stability of the binding pose of telmi-

Fig. 9. Potential energy fluctuation of the telmisartan-AT1 receptorcomplex during MD simulation.



sartan in the hAT1 receptor model, as obtained by thedocking studies.

Comparison With Previous AT1 Receptor Models

A few recent studies have used recently available X-raycrystal structure of bovine rhodopsin as a template forbuilding 3D models of the AT1 receptor. Karnik et al.developed a homology model of the rat AT1A receptor usingthe bovine rhodopsin (PDB i.d.:1F88) template.29 In thismodel, the non-peptide AT1 antagonist, candesartan, wasdocked in a conformation wherein its acidic tetrazolegroup interacted with the backbone of Lys199(K5.42) andthe side-chain of Gln257(Q6.52). The side-chain of Gln257(Q6.52) also appeared to interact with the a-carboxylicacid of candesartan, and also with the His256(H6.51). Itwas hypothesized that this tight network of interactionswas responsible for the insurmountable behavior of cande-sartan. In the current hAT1 receptor model (Model IV),the side-chain of Gln257(Q6.52) appeared to point in adirection away from the biphenyl acidic group of the non-peptide antagonists. The ligand binding site for this ratAT1A model was surrounded by amino acid residues,Lys199(K5.42), His256(H6.51), and Gln257(Q6.52), butdid not seem to span the region in the vicinity ofAsn111(N3.35) and Asn295(N7.46). Hence, this bindingpocket would be unable to accommodate telmisartan,which requires a comparatively bigger pocket in order tobind (Model IV, Fig. 4). Another report from the samegroup suggested that Lys199(K5.42) and His256(H6.51)interact with the tetrazole group of non-peptide ligands,and also showed that the Lys199Gln and His256Ala dou-ble mutant decreased the affinity for both the insurmount-able and the surmountable antagonists, candesartan andlosartan, respectively.29 This suggested that His256(H6.51)side-chain might compensate for the Lys199(K5.42) muta-tion to varying degrees. It is relevant to mention here thatdocking poses of certain non-peptide ligands, for example,telmisartan in the current Model IV, also displayed H-bonding interactions between the carboxylate (tetrazole)group and His256(H6.51), in addition to the interactionswith Lys199(K5.42) (see Fig. 7). This additional H-bondinginteraction might explain the compensation of Lys199(K5.42) side-chain by His256(H6.51), as observed in theaforementioned study. Another recent model of the ratAT1 receptor was developed from the 2.8 A resolution crys-tal structure of bovine rhodopsin.28 Proposed binding posesof non-peptide antagonists in this model suggested thatligands would span a vertical distance of nearly 8–10 Afrom the extracellular side near the basic Lys199(K5.42),toward deeply located polar residues, Asn111(N3.35),Ser252(S6.47), Asn294(N7.45), and Asn295(N7.46), closeto the pendant heterocyclic moiety of the ligands. Similarbinding poses were seen in the current hAT1 receptormodel (Model IV), where the acidic group on the distalphenyl ring interacted with the Lys199(K5.42), and theheterocyclic moiety interacted via H-bonds with polar resi-dues, Asn111(N3.35) and Asn295(N7.46). Another studyinvolved the generation of homology models of several

class A receptors, including the AT1 receptor from the bo-vine rhodopsin X-ray crystal structure.27 The study con-cluded that bovine rhodopsin could serve as an excellenttemplate for building models of GPCRs, having the abilityto explain the interactions of antagonists with the recep-tor. The hydroxyl group of losartan in this AT1 receptormodel appeared to be pointing toward Lys199(K5.42),which was suggested to account for the higher affinity ofEXP3174 (active metabolite of losartan) with hydroxylsubstituent replaced by a carboxylate group. However, inthe current hAT1 receptor model (Model IV), the hydroxylsubstituient of losartan appeared to interact with the side-chain of His256(H6.51) via a H-bond. Thus, the carboxy-late group of EXP3174 may be involved in stronger inter-action with the His256(H6.51), explaining its higher bind-ing affinity (as per the current Model IV).

CONCLUSIONS

Homology modeling was used to develop a 3D model ofthe hAT1 receptor, utilizing the 2.6 A resolution crystalstructure of the bovine rhodopsin. Recently, X-ray crystalstructure of bovine rhodopsin has been determined to aresolution of 2.2 A in the presence of 11-cis-retinal.61

However, current work was completed prior to the releaseof this new structure of bovine rhodopsin. It has beenobserved that GPCR models obtained using bovine rho-dopsin as a structural template are not directly suitablefor use in structure-based drug design, and requirerefinement of the receptor binding site. Therefore, theinitial hAT1 model (Model II) was subjected to a strategicligand-supported receptor refinement protocol. The nar-row binding pocket of Model II was expanded successfullythrough iterative energy minimizations and MD simula-tions, in the presence of non-peptide AT1 antagonists, los-artan and telmisartan. The refinement led to the finalhAT1 receptor model (Model IV), capable of explainingseveral known SAR and site-directed mutagenesis data.The Model IV is also in agreement with the previouslydescribed pharmacophore model for the benzimidazole-type AT1 receptor antagonists.

The hAT1 model helped to identify several criticalligand–receptor interactions (other than already observedLys199(K5.42) interaction in previous models) in thebinding site, which may serve as key molecular determi-nants of non-peptide antagonist recognition by the AT1

receptor. The binding site residues that were observed tointeract with majority of non-peptide AT1 antagonists,including telmisartan, via H-bonding interactions includeAsn111(N3.35), Lys199(K5.42), His256(H6.51), andAsn295(N7.46). The binding site residues seen to be in-volved in hydrophobic or aromatic interactions includePhe77(F2.53), Leu81(L2.57), Ala104(A3.28), Val108(V3.32),Leu112(L3.36), Phe204(F5.47), Phe248(F6.43), Phe249(F6.44), Trp253(W6.48), His256(H6.51), Ile288(I7.39), Ala291(A7.42), and Tyr292(Y7.43). It appeared that non-peptideantagonist binding site of the AT1 receptor is comprised ofboth polar/charged, as well as hydrophobic/aromatic resi-

840 PATNY ET AL.


dues. It was also observed that ELII moved upwards dur-ing the model refinement, leading to opening of the bind-ing site, which helped in accommodating ligands of vary-ing sizes. However, certain residues such as His183 ofELII were observed to lie in vicinity of the binding site.His183 is known to interact with the side-chain carboxy-late of Asp1 of angiotensin-II.51 This indicated the overlap-ping nature of the binding site of agonists and antagonistsof the AT1 receptor.The present hAT1 model (Model IV) was further vali-

dated by docking a series of non-peptide antagonists inthe binding site. The docking study was able to identifykey ligand–receptor interactions for all of the AT1 antago-nists used in the study. This suggested that the currenthAT1 model (Model IV) could reproduce critical ligand–receptor interactions of the non-peptide antagonists, andthus could be used in structure-based drug design. Inaddition, a reasonable correlation value of 0.73 was ob-tained between the binding affinities and the interactionenergy values of the docked AT1 antagonists. This high-lighted that the hAT1 receptor model (Model IV) coulddistinguish between weak and potent non-peptide AT1 re-ceptor antagonists, at least within a chemical class ofligands. The binding pose stability of the GOLD-derivedantagonist-AT1 receptor complex for telmisartan wasassessed by performing an extensive unrestrained MDsimulation of 1 ns. The GOLD-derived bound pose of tel-misartan complexed with the hAT1 receptor model wasfound to be stable during the course of the MD simula-tion, suggesting the reliability of the docked pose. A con-former search performed for telmisartan identified a con-formation similar to the docked pose of telmisartan, con-firming the energetic stability of the GOLD-deriveddocked pose of telmisartan in Model IV.The hAT1 receptor model highlighted critical molecular

interactions of telmisartan with the AT1 receptor bindingsite residues. Telmisartan (a structurally distinct AT1 re-ceptor antagonist and marketed antihypertensive drug)has recently been reported to act as a partial agonist ofthe PPARg receptor, and thus reduced glucose, insulin,and triglyceride levels in rats.62 This finding can haveuseful implications for the treatment of metabolic syn-drome characterized by the clustering of multiple riskfactors for cardiovascular disease and diabetes. Thus,knowledge gained from the developed 3D model of thehAT1 receptor, and the modeled telmisartan–AT1 receptorcomplex, can prove beneficial in the identification anddesign of novel antihypertensive agents bearing potentialof use in the management of metabolic syndrome.

ACKNOWLEDGMENTS

We thank Dr. Christopher R. McCurdy for his construc-tive comments during manuscript preparation. In addi-tion, we thank Brenda Robertson, Director of the Univer-sity Writing Center and Sharron Eve Sarthou, Instructorand PhD candidate, Department of English at The Uni-versity of Mississippi, for their timely help in refining thelanguage of this manuscript.

REFERENCES

1. Wexler RR, Greenlee WJ, Irvin JD, Goldberg MR, PrendergastK, Smith RD, Timmermans PB. Nonpeptide angiotensin II recep-tor antagonists: the next generation in antihypertensive therapy.J Med Chem 1996;39:625–656.

2. de Gasparo M, Catt KJ, Inagami T, Wright JW, Unger T. Interna-tional union of pharmacology. XXIII. The angiotensin II recep-tors. Pharmacol Rev 2000;52:415–472.

3. Schmidt B, Schieffer B. Angiotensin II AT1 receptor antagonists.Clinical implications of active metabolites. J Med Chem 2003;46:2261–2270.

4. Kakar SS, Sellers JC, Devor DC, Musgrove LC, Neill JD. Angio-tensin II type-1 receptor subtype cDNAs: differential tissue ex-pression and hormonal regulation. Biochem Biophys Res Commun1992;183:1090–1096.

5. Sasamura H, Hein L, Krieger JE, Pratt RE, Kobilka BK, Dzau VJ.Cloning, characterization, and expression of two angiotensin re-ceptor (AT-1) isoforms from the mouse genome. Biochem BiophysRes Commun 1992;185:253–259.

6. Kambayashi Y, Bardhan S, Takahashi K, Tsuzuki S, Inui H,Hamakubo T, Inagami T. Molecular cloning of a novel angiotensinII receptor isoform involved in phosphotyrosine phosphatase inhi-bition. J Biol Chem 1993;268:24543–24546.

7. Mukoyama M, Nakajima M, Horiuchi M, Sasamura H, Pratt RE,Dzau VJ. Expression cloning of type 2 angiotensin II receptorreveals a unique class of seven-transmembrane receptors. J BiolChem 1993;268:24539–24542.

8. Tsuzuki S, Ichiki T, Nakakubo H, Kitami Y, Guo DF, Shirai H,Inagami T. Molecular cloning and expression of the gene encodinghuman angiotensin II type 2 receptor. Biochem Biophys Res Com-mun 1994;200:1449–1454.

9. Gether U. Uncovering molecular mechanisms involved in activa-tion of G protein-coupled receptors. Endocr Rev 2000;21:90–113.

10. Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H,Fox BA, Le Trong I, Teller DC, Okada T, Stenkamp RE, YamamotoM, Miyano M. Crystal structure of rhodopsin: a G protein-coupledreceptor. Science 2000;289:739–745.

11. Berman HM,Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H,Shindyalov IN, Bourne PE. The protein data bank. Nucleic AcidsRes 2000;28:235–242.

12. Baldwin JM. The probable arrangement of the helices in G pro-tein-coupled receptors. EMBO J 1993;12:1693–1703.

13. Baldwin JM, Schertler GF, Unger VM. An a-carbon template forthe transmembrane helices in the rhodopsin family of G-protein-coupled receptors. J Mol Biol 1997;272:144–164.

14. Ballesteros J, Palczewski K. G protein-coupled receptor drug dis-covery: implications from the crystal structure of rhodopsin. CurrOpin Drug Discov Dev 2001;4:561–574.

15. Filipek S, Teller DC, Palczewski K, Stenkamp R. The crystallo-graphic model of rhodopsin and its use in studies of other G protein-coupled receptors. Annu Rev Biophys Biomol Struct 2003;32:375–397.

16. Oliveira L, Hulsen T, Lutje Hulsik D, Paiva AC, Vriend G. Heavier-than-air flying machines are impossible. FEBS Lett 2004;564:269–273.

17. Bissantz C, Bernard P, Hibert M, Rognan D. Protein-based virtualscreening of chemical databases. II. Are homology models of G-protein coupled receptors suitable targets? Proteins 2003;50:5–25.

18. Hillisch A, Pineda LF, Hilgenfeld R. Utility of homology models inthe drug discovery process. Drug Discov Today 2004;9:659–669.

19. Zhang Y, Devries ME, Skolnick J. Structure modeling of all iden-tified G protein-coupled receptors in the human genome. PLoSComput Biol 2006;2:e13.

20. Vaidehi N, Floriano WB, Trabanino R, Hall SE, Freddolino P,Choi EJ, Zamanakos G, Goddard WA, III. Prediction of structureand function of G protein-coupled receptors. Proc Natl Acad SciUSA 2002;99:12622–12627.

21. Henderson R, Baldwin JM, Ceska TA, Zemlin F, Beckmann E,Downing KH. Model for the structure of bacteriorhodopsin basedon high-resolution electron cryo-microscopy. J Mol Biol 1990;213:899–929.

22. Schertler GF, Villa C, Henderson R. Projection structure of rho-dopsin. Nature 1993;362:770–772.

23. Underwood DJ, Strader CD, Rivero R, Patchett AA, Greenlee W,Prendergast K. Structural model of antagonist and agonist bind-



ing to the angiotensin II, AT1 subtype, G protein coupled recep-tor. Chem Biol 1994;1:211–221.

24. Joseph MP, Maigret B, Bonnafous JC, Marie J, Scheraga HA. Acomputer modeling postulated mechanism for angiotensin IIreceptor activation. J Protein Chem 1995;14:381–398.

25. Yamano Y, Ohyama K, Kikyo M, Sano T, Nakagomi Y, Inoue Y,Nakamura N, Morishima I, Guo DF, Hamakubo T, Tadashi I.Mutagenesis and the molecular modeling of the rat angiotensinII receptor (AT1). J Biol Chem 1995;270:14024–14030.

26. Balmforth AJ, Lee AJ, Warburton P, Donnelly D, Ball SG. Theconformational change responsible for AT1 receptor activation isdependent upon two juxtaposed asparagine residues on trans-membrane helices III and VII. J Biol Chem 1997;272:4245–4251.

27. Bondensgaard K, Ankersen M, Thogersen H, Hansen BS, WulffBS, Bywater RP. Recognition of privileged structures by G-protein coupled receptors. J Med Chem 2004;47:888–899.

28. Cappelli A, Pericot Mohr Gl G, Gallelli A, Rizzo M, Anzini M,Vomero S, Mennuni L, Ferrari F, Makovec F, Menziani MC, DeBenedetti PG, Giorgi G. Design, synthesis, structural studies, bio-logical evaluation, and computational simulations of novel potentAT(1) angiotensin II receptor antagonists based on the 4-phenyl-quinoline structure. J Med Chem 2004;47:2574–2586.

29. Takezako T, Gogonea C, Saad Y, Noda K, Karnik SS. ‘‘Networkleaning’’ as a mechanism of insurmountable antagonism of theangiotensin II type 1 receptor by non-peptide antagonists. J BiolChem 2004;279:15248–15257.

30. Okada T, Fujiyoshi Y, Silow M, Navarro J, Landau EM, Shichida Y.Functional role of internal water molecules in rhodopsin revealedby X-ray crystallography. Proc Natl Acad Sci USA 2002;99:5982–5987.

31. Hoe KL, Saavedra JM. Site-directed mutagenesis of the gerbiland human angiotensin II AT(1) receptors identifies amino acidresidues attributable to the binding affinity for the nonpeptidicantagonist losartan. Mol Pharmacol 2002;61:1404–1415.

32. Ries UJ, Mihm G, Narr B, Hasselbach KM, Wittneben H, EntzerothM, van Meel JC, Wienen W, Hauel NH. 6-Substituted benzimida-zoles as new nonpeptide angiotensin II receptor antagonists: syn-thesis, biological activity, and structure-activity relationships.J Med Chem 1993;36:4040–4051.

33. Sali A, Blundell TL. Comparative protein modelling by satisfac-tion of spatial restraints. J Mol Biol 1993;234:779–815.

34. Fiser A, Do RK, Sali A. Modeling of loops in protein structures.Protein Sci 2000;9:1753–1773.

35. Maple JR, Dinur U, Hagler AT. Derivation of force fields for mo-lecular mechanics and dynamics from ab initio energy surfaces.Proc Natl Acad Sci USA 1988;85:5350–5354.

36. Sheik SS, Sundararajan P, Hussain AS, Sekar K. Ramachandranplot on the web. Bioinformatics 2002;18:1548,1549.

37. Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD.Improved protein-ligand docking using GOLD. Proteins 2003;52:609–623.

38. Jones G, Willett P, Glen RC, Leach AR, Taylor R. Developmentand validation of a genetic algorithm for flexible docking. J MolBiol 1997;267:727–748.

39. Jones G, Willett P, Glen RC. Molecular recognition of receptorsites using a genetic algorithm with a description of desolvation.J Mol Biol 1995;245:43–53.

40. Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL. Eval-uation and reparametrization of the OPLS-AA force field for pro-teins via comparison with accurate quantum chemical calcula-tions on peptides. J Phys Chem B 2001;105:6474–6487.

41. Bairoch A, Apweiler R. The SWISS-PROT protein sequence data-base and its supplement TrEMBL in 2000. Nucleic Acids Res 2000;28:45–48.

42. Visiers I, Ballesteros JA, Weinstein H. Three-dimensional repre-sentations of G protein-coupled receptor structures and mecha-nisms. Methods Enzymol 2002;343:329–371.

43. Persson B, Argos P. Topology prediction of membrane proteins.Protein Sci 1996;5:363–371.

44. Gutierrez-de-Teran H, Centeno NB, Pastor M, Sanz F. Novelapproaches for modeling of the A1 adenosine receptor and itsagonist binding site. Proteins 2004;54:705–715.

45. Boeckler F, Lanig H, Gmeiner P. Modeling the similarity anddivergence of dopamine D2-like receptors and identification of vali-dated ligand-receptor complexes. J Med Chem 2005;48:694–709.

46. Kim SK, Gao ZG, Van Rompaey P, Gross AS, Chen A, Van Calen-bergh S, Jacobson KA. Modeling the adenosine receptors: com-parison of the binding domains of A2A agonists and antagonists.J Med Chem 2003;46:4847–4859.

47. Lavecchia A, Cosconati S, Novellino E. Architecture of thehuman urotensin II receptor: comparison of the binding domainsof peptide and non-peptide urotensin II agonists. J Med Chem2005;48:2480–2492.

48. Ryckaert JP, Ciccotti G, Berendsen HJC. Numerical integrationof the cartesian equations of motion of a system with constraints:molecular dynamics of n-alkanes. J Comp Phys 1977;23:327–341.

49. Halgren TA. Merck molecular force field. I. Basis, form, scope,parameterization, and performance of MMFF94. J Comp Chem1996;17:490–519.

50. Mirzadegan T, Benko G, Filipek S, Palczewski K. Sequence anal-yses of G-protein-coupled receptors: similarities to rhodopsin.Biochemistry 2003;42:2759–2767.

51. Hunyady L, Balla T, Catt KJ. The ligand binding site of the an-giotensin AT1 receptor. Trends Pharmacol Sci 1996;17:135–140.

52. Zhang Y, Sham YY, Rajamani R, Gao J, Portoghese PS. Homol-ogy modeling and molecular dynamics simulations of the muopioid receptor in a membrane-aqueous system. Chembiochem2005;6:853–859.

53. Tebben A, Kimura SR, Carter PH, Zhao Q, Krystek SR, Jr.Bind-ing site xpansion and induced fit docking for GPCR ligand bind-ing mode prediction: application to the b-adrenergic and chemo-kine receptors. Abstracts of Papers, Presented at 231st ACSNational Meeting, Atlanta, GA, United States, March 26–30,2006 (2006:COMP-124).

54. Kimura SR, Rajamani R, Langley D.Opening up binding sites ofhomology models via a balloon potential: a molecular dynamicsrefinement approach. Abstracts of Papers, Presented at 230thACS National Meeting, Washington, DC, United States, Aug 28–Sept 1, 2005 (2005:COMP-336).

55. Kimura SR, Krystek S, Jr, Tebben A, Langley DR.Systematicactive site refinement of GPCR models through molecular dy-namics simulation. Abstracts of Papers, Presented at 231st ACSNational Meeting, Atlanta, GA, United States, March 26–30,2006 (2006:COMP-218).

56. Pepin MC, Yue SY, Roberts E, Wahlestedt C, Walker P. Novel‘‘restoration of function’’ mutagenesis strategy to identify aminoacids of the d-opioid receptor involved in ligand binding. J BiolChem 1997;272:9260–9267.

57. Gether U, Ballesteros JA, Seifert R, Sanders-Bush E, WeinsteinH, Kobilka BK. Structural instability of a constitutively active Gprotein-coupled receptor. Agonist-independent activation due toconformational flexibility. J Biol Chem 1997;272:2587–2590.

58. Pedretti A, Villa M, Pallavicini M, Valoti E, Vistoli G. Constructionof human ghrelin receptor (hGHS-R1a) model using a fragmentalprediction approach and validation through docking analysis.JMed Chem 2006;49:3077–3085.

59. Noda K, Saad Y, Kinoshita A, Boyle TP, Graham RM, Husain A,Karnik SS. Tetrazole and carboxylate groups of angiotensin re-ceptor antagonists bind to the same subsite by different mecha-nisms. J Biol Chem 1995;270:2284–2289.

60. Chakravarty PK, Naylor EM, Chen A, Chang RS, Chen TB,Faust KA, Lotti VJ, Kivlighn SD, Gable RA, Zingaro GJ, SchornTW, Schaffer LW, Broten TP, Siegl PKS, Patchett AA, GreenleeWJ. A highly potent, orally active imidazo[4,5-b]pyridine biphe-nylacylsulfonamide (MK-996; L-159,282): a new AT1-selectiveangiotensin II receptor antagonist. J Med Chem 1994;37:4068–4072.

61. Okada T, Sugihara M, Bondar AN, Elstner M, Entel P, Buss V. Theretinal conformation and its environment in rhodopsin in light of anew 2.2 A crystal structure. J Mol Biol 2004;342:571–583.

62. Benson SC, Pershadsingh HA, Ho CI, Chittiboyina A, Desai P, Pra-venec M, Qi N, Wang J, Avery MA, Kurtz TW. Identification of tel-misartan as a unique angiotensin II receptor antagonist with selec-tive PPARg-modulating activity. Hypertension 2004;43:993–1002.

842 PATNY ET AL.


Date post:	28-Jan-2023
Category:	Documents
Upload:	olemiss
View:	0 times
Download:	0 times

Ligand-supported homology modeling of the human angiotensin II type 1 (AT 1 ) receptor: Insights...

Documents