ol model(2007)13:121-131 DOI10.1007/s00894-006-0131-1 ORIGINAL PAPER Structure-based 3D-QSAR studies on thiazoles as 5-HT3 receptor antagonists Li-Ping Zhu. De-Yong Ye. Yun tang Received: 2 December 2005/Accepted: 30 June 2006/Published online: 5 September 2006 C Springer-Verlag 2006 bstract Structure-based 3D-QSAR studies were per- Introduction formed on 20 thiazoles against their binding affinities to he 5-HT3 receptor with comparative molecular field Nausea and vomiting are major side effects associated with analysis(CoMFA) and comparative molecular similarity chemotherapy, radiotherapy, and operation [1, 2]. It is now indices analysis (CoMSIA). The thiazoles were well established that serotonin type 3(5-HT3) receptors, docked into the binding pocket of a human 5-HT3A present on vagal afferents in the Gl tract mucosa and in the homology model, constructed on the basis of the crystal brainstem centers, are involved in the vomiting reflex. structure of the snail acetylcholine binding protein Initiation of emesis is probably due to the release of (AChBP), using the GOLd program. The docked con- serotonin from enterochromaffin cells in the small intestine, formations were then extracted and used to build the 3D- which activates vagal afferent nerves via 5-HT3 receptors QSAR models, with cross-validated 2y values 0.785 and [3]. Delayed emesis may involve central 5-HT3 receptors 0.744 for CoMFA and CoMSIA, respectively. An addition- and/or serotonin stored in the enterochromaffin cells al five molecules were used to validate the models further, Specific 5-HT3 receptor antagonists such as Ondansetron giving satisfactory predictive r2 values of 0.582 and 0.804 Granisetron and Tropisetron block for CoMFA and CoMSIA, respectively. The results would probably by competitive inhibition at the 5-HT3 receptor be helpful for the discovery of new potent and selective sites centrally and peripherally [4] 5-HT3 receptor antagonists. Three subtypes of 5-HT3 receptors have been identified (1)5-HT3A, a neuronal receptor directly coupled to cation- Keywords Structure-based 3D-QSAR CoMFA selective channels; (2)5-HT3B, a regulatory subunit able to CoMSIA 5-HT3 receptor antagonists. Homology modeling modulate the intrinsic channel activity of 5-HT3A; and ( 3) 5-HT3c, a subunit that appears to modulate the 5-HT3 receptor responses [5]. The subunit 5-HT3A is functional omo-oligomeric while 5-HT3B is non-functional hetero- loop ligand-gated ion channels (LGICs), whose members LP.Zhu·D-Y.Ye)·Y.Tang share significant structural and functional homology to each Department of Medicinal Chemistry, School of Pharmacy, Fudan University other. Each subtype consists of five subunits, and each 138 Yixueyuan Road, subunit has a large extracellular N-terminal region and four putative transmembrane domains 6, 7]. Early experimental mail: dyyeashmu.edu.cn evidence showed that the ligand-binding site is located at Y Tang(<) the interface of two adjacent subunits. Unfortunately, date the three-dimensional (3D) structure of 5-HT3 recep- East China University of Science and Technology 130 Meilong Road tors has not been elucidated, which seriously limits our Shanghai 200237. China understanding of the antagonistic mechanism of the mail:ytang234@yahoo.com.cn receptor in detail. However, the structure of acetylcholine
ORIGINAL PAPER Structure-based 3D-QSAR studies on thiazoles as 5-HT3 receptor antagonists Li-Ping Zhu & De-Yong Ye & Yun Tang Received: 2 December 2005 /Accepted: 30 June 2006 / Published online: 5 September 2006 # Springer-Verlag 2006 Abstract Structure-based 3D-QSAR studies were performed on 20 thiazoles against their binding affinities to the 5-HT3 receptor with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The thiazoles were initially docked into the binding pocket of a human 5-HT3A receptor homology model, constructed on the basis of the crystal structure of the snail acetylcholine binding protein (AChBP), using the GOLD program. The docked conformations were then extracted and used to build the 3DQSAR models, with cross-validated r2 cv values 0.785 and 0.744 for CoMFA and CoMSIA, respectively. An additional five molecules were used to validate the models further, giving satisfactory predictive r2 values of 0.582 and 0.804 for CoMFA and CoMSIA, respectively. The results would be helpful for the discovery of new potent and selective 5-HT3 receptor antagonists. Keywords Structure-based 3D-QSAR . CoMFA . CoMSIA . 5-HT3 receptor antagonists . Homology modeling Introduction Nausea and vomiting are major side effects associated with chemotherapy, radiotherapy, and operation [1, 2]. It is now well established that serotonin type 3 (5-HT3) receptors, present on vagal afferents in the GI tract mucosa and in the brainstem centers, are involved in the vomiting reflex. Initiation of emesis is probably due to the release of serotonin from enterochromaffin cells in the small intestine, which activates vagal afferent nerves via 5-HT3 receptors [3]. Delayed emesis may involve central 5-HT3 receptors and/or serotonin stored in the enterochromaffin cells. Specific 5-HT3 receptor antagonists such as Ondansetron, Granisetron and Tropisetron block nausea and vomiting, probably by competitive inhibition at the 5-HT3 receptor sites centrally and peripherally [4]. Three subtypes of 5-HT3 receptors have been identified: (1) 5-HT3A, a neuronal receptor directly coupled to cationselective channels; (2) 5-HT3B, a regulatory subunit able to modulate the intrinsic channel activity of 5-HT3A; and (3) 5-HT3C, a subunit that appears to modulate the 5-HT3 receptor responses [5]. The subunit 5-HT3A is functional homo-oligomeric while 5-HT3B is non-functional heteromeric. 5-HT3 receptors belong to the superfamily of Cysloop ligand-gated ion channels (LGICs), whose members share significant structural and functional homology to each other. Each subtype consists of five subunits, and each subunit has a large extracellular N-terminal region and four putative transmembrane domains [6, 7]. Early experimental evidence showed that the ligand-binding site is located at the interface of two adjacent subunits. Unfortunately, to date the three-dimensional (3D) structure of 5-HT3 receptors has not been elucidated, which seriously limits our understanding of the antagonistic mechanism of the receptor in detail. However, the structure of acetylcholine J Mol Model (2007) 13:121–131 DOI 10.1007/s00894-006-0131-1 L.-P. Zhu : D.-Y. Ye (*) : Y. Tang (*) Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 138 Yixueyuan Road, Shanghai 200032, China e-mail: dyye@shmu.edu.cn Y. Tang School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China Y. Tang (*) School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China e-mail: ytang234@yahoo.com.cn
J Mol model(2007)13:121-131 Scheme 1 Structures and actual pKi values of molecules used Ar Ar 2.O- MoOCH4(9.377) 21.O-MeOC6H4(9.538) 3.C6H5(8.745) 22. Quinolin-8-y1(9.509) 4. Quinolin-8-yl(9000) 23. Indol-3yl(7.848) 5.0-FC6H4(8.712) 60- EtoH4(9022) 7.o-HOCH4(8.824) C6H4(8.061) H4(9 10.m- MeEcH4(8.699) 12.m-BrCH4(8.699) 13.p-FC6H4(8.310) 14. p-MeCh4(6.959) 16.p-CIGH4(7.469) 2425 17. 1-Methoxynaphth-2-yl(7.022) 18. 2-Methoxynaphth-l-yl(6.398) 19.2,6-(MeO)4C6H3(6.367) 24.CH2(8481) 25. COOCHCH2(8.149) binding protein(AChBP) found in the snail Lymnaea CoMFA (comparative molecular field analysis)[10 and stagnalis has been determined by X-ray crystallography. CoMSIA(comparative molecular similarity indices analy This protein is a member of the LGICs, and shares 19% sis)[1l] are two of the most widely used 3D-QSAr homologous sequence with the extracellular domain of the methods. In both approaches, molecular property fields are 5-HT3A receptor [8]. Therefore, a homology model of the evaluated between a probe atom and each molecule of a extracellular domain of the human 5-HT3A receptor was dataset at the intersections of a regularly spaced grid built based on the crystal structure of AChBP, and known CoMFA calculates steric and electrostatic properties accord selective antagonists were docked into the binding site to ing to Lennard-Jones and Coulomb potentials, while validate the model. During the course of this work, a CoMSIA considers five different similarity fields: steric, similar study using a range of antagonists was published electrostatic, hydrophobic, hydrogen-bond donor, and hy drogen-bond acceptor properties. When the 3D-structure QSAR and 3D-QSAR have long been used to elucidate a receptor is also available, ligand-and structure-based drug the mechanisms of drug action and for lead optimization. design methods can be combined. The structure-based 3D-
binding protein (AChBP) found in the snail Lymnaea stagnalis has been determined by X-ray crystallography. This protein is a member of the LGICs, and shares 19% homologous sequence with the extracellular domain of the 5-HT3A receptor [8]. Therefore, a homology model of the extracellular domain of the human 5-HT3A receptor was built based on the crystal structure of AChBP, and known selective antagonists were docked into the binding site to validate the model. During the course of this work, a similar study using a range of antagonists was published [9]. QSAR and 3D-QSAR have long been used to elucidate the mechanisms of drug action and for lead optimization. CoMFA (comparative molecular field analysis) [10] and CoMSIA (comparative molecular similarity indices analysis) [11] are two of the most widely used 3D-QSAR methods. In both approaches, molecular property fields are evaluated between a probe atom and each molecule of a dataset at the intersections of a regularly spaced grid. CoMFA calculates steric and electrostatic properties according to Lennard-Jones and Coulomb potentials, while CoMSIA considers five different similarity fields: steric, electrostatic, hydrophobic, hydrogen-bond donor, and hydrogen-bond acceptor properties. When the 3D-structure of a receptor is also available, ligand- and structure-based drug design methods can be combined. The structure-based 3DN S Ar NH N H3C N S Ar NH N N S X NH N H 1-19 20-23 24-25 Ar 1. Indol-3-yl (7.921) 2. o-MeOC6H4 (9.377) 3. C6H5 (8.745) 4. Quinolin-8-yl (9.000) 5. o-FC6H4 (8.712) 6. o-EtOC6H4 (9.022) 7. o-HOC6H4 (8.824) 8. o-MeC6H4 (8.061) 9. m-ClC6H4 (9.056) 10. m-MeOC6H4 (8.699) 11. m-FC6H4 (8.432) 12. m-BrC6H4 (8.699) 13. p-FC6H4 (8.310) 14. p-MeC6H4 (6.959) 15. p-BrC6H4 (6.569) 16. p-ClC6H4 (7.469) 17. 1-Methoxynaphth-2-yl (7.022) 18. 2-Methoxynaphth-1-yl (6.398) 19. 2,6-(MeO)2C6H3 (6.367) Ar 20. C6H5 (9.000) 21. o-MeOC6H4 (9.538) 22. Quinolin-8-yl (9.509) 23. Indol-3-yl (7.848) X 24. CH2 (8.481) 25. COOCH2CH2 (8.149) HN NH2 Scheme 1 Structures and actual pKi values of molecules used for 3D-QSAR studies [12, 13] 122 J Mol Model (2007) 13:121–131
J Mol Model(2007)13:121-131 12 Scheme 2 Sequence alignment AChBP(I) L DRADILYNIROTSRPDVIPTORD.RPVAVSVSLKFINILE of the extracellular domain 5-TA(32) PALLRLSDYLLTNYRKGVRPVRDWRKPTTVSIDVIVYAILN subunit with that of AchBP The crystal structure of AChBP AChBP(41) VNEITNEVDVVEWOOTTWSDRTLAWNSSHS.PDQVSVPIS 5-HT3A(73) VDEKNOVLTTYIWYROYWTDEFLOWNPEDFDNITKLSI D of AChBP(a-helix, red B-strand, blue; 310-helix, green) indicated A ChBP(SO) SLWVPDLAAYN.AISKPEVITPQLARVVSDGEVLYMPSIRO 5-TsA(I14) SIWVPDILINEEVDVGKSP.NIPYVYIRHOGEVONYKPLOV A ChBP(120) RESCDVSGVDTESG. ATCRIKIGSWTHHSREISVDPTTE 5-HTA(154) VTACSLDIYNFPFDVONCSLTFTSWLHTIQDINISLWRLP AChBP(l58) NSDDSEYESQYSRFEILDVTOKKNSVTYSCCPEAYEDVE 5-HT3A(194) EKVKSDRSVFMNQGEWELLGVLPYEREES. MESSNYYAEMK AChBP(97) VSLNFRKKGRSEIL 5HT3A(234) FYVVIRRRPLFYVV QSAR method is the result of such a combination, and it replacement of [HI-Tropisetron binding to NG-108-15 could provide more information for lead optimization cells. The compounds were divided into two sets: 20 In order to understand the antagonistic mechanism and molec randon guide the discovery of more potent ligands, a series of whereas the remaining five molecules served as an external highly potent and selective 5-HT3 receptor antagonists, test set reported by Nagel et al. [ 12, 13] were chosen to perform 3D-QSAR studies with both CoMFA and CoMSIA meth- Molecular modeling ods, based on their docking conformations on the structural model of human 5-HT3A receptor in this paper. The All molecular modeling studies were carried out on ar molecules chosen contain a thiazole moiety linking an R14000 SGI Fuel workstation using the molecular aromatic group and a nitrogenous basic region(Scheme 1); modeling software package SYBYL v6.9[14]. The three the thiazole group appears to be acting as a carbonyl dimensional model of the extracellular region of human bioisostere in this system. By mapping the CoMFA and 5-HT3A receptor was built using the module bIOPOlY- CoMSIA contour plots onto the structural model of the MER based on the crystal structure of AChBP determined eceptor, the results of this study might be conversely at 2.7 A(PDB entry code: 119B)[8]. The pentamer was validate the 3D-structural model of the receptor generated by replacing each amino acid of AChBP with the corresponding one of human 5-HT3A receptor's extracellu lar regions, ensuring the conformation of the templates Materials and methods backbone unchanged. The model generated was fixed using the Biopolymer command Fix Proline and Fix Sidechains, Sequence alignment to relieve all bad van der waals contacts. Then the mode was minimized using the AMBER4 1 force field [15] with a The sequence alignment of the extracellular domain of distance-dependent dielectric constant of 5.0 and a gradient human 5-HT3A receptor with AChBP is shown in Scheme 2 convergence value of 0.05 kcal mol in 2,000 cycles Atomic charges were calculated using the AMBER41 method. Then subunit a and b were extracted and used Dataset as the initial model for further docking studies. Sixteen 5-HT Twenty-five thiazoles were collected from literature docked into the binding pocket of the initial model, and reported by Nagel [12, 13]. The binding affinities of these the residues within 10 A of the ligand of the ligand-receptor compounds to the 5-HT3 receptor were evaluated with complex were minimized. Finally, the model was validated
QSAR method is the result of such a combination, and it could provide more information for lead optimization. In order to understand the antagonistic mechanism and guide the discovery of more potent ligands, a series of highly potent and selective 5-HT3 receptor antagonists, reported by Nagel et al. [12, 13] were chosen to perform 3D-QSAR studies with both CoMFA and CoMSIA methods, based on their docking conformations on the structural model of human 5-HT3A receptor in this paper. The molecules chosen contain a thiazole moiety linking an aromatic group and a nitrogenous basic region (Scheme 1); the thiazole group appears to be acting as a carbonyl bioisostere in this system. By mapping the CoMFA and CoMSIA contour plots onto the structural model of the receptor, the results of this study might be conversely validate the 3D-structural model of the receptor. Materials and methods Sequence alignment The sequence alignment of the extracellular domain of human 5-HT3A receptor with AChBP is shown in Scheme 2 [8]. Dataset Twenty-five thiazoles were collected from literature reported by Nagel [12, 13]. The binding affinities of these compounds to the 5-HT3 receptor were evaluated with replacement of [3 H]-Tropisetron binding to NG-108-15 cells. The compounds were divided into two sets: 20 molecules selected randomly to form the training set, whereas the remaining five molecules served as an external test set. Molecular modeling All molecular modeling studies were carried out on an R14000 SGI Fuel workstation using the molecular modeling software package SYBYL v6.9 [14]. The threedimensional model of the extracellular region of human 5-HT3A receptor was built using the module BIOPOLYMER based on the crystal structure of AChBP determined at 2.7 Å (PDB entry code: 1I9B) [8]. The pentamer was generated by replacing each amino acid of AChBP with the corresponding one of human 5-HT3A receptor’s extracellular regions, ensuring the conformation of the template’s backbone unchanged. The model generated was fixed using the Biopolymer command Fix Proline and Fix Sidechains, to relieve all bad van der Waals contacts. Then the model was minimized using the AMBER4.1 force field [15] with a distance-dependent dielectric constant of 5.0 and a gradient convergence value of 0.05 kcal mol−1 in 2,000 cycles. Atomic charges were calculated using the AMBER4.1 method. Then subunit A and B were extracted and used as the initial model for further docking studies. Sixteen 5-HT3 receptor antagonists, known as ‘setrons’, were docked into the binding pocket of the initial model, and the residues within 10 Å of the ligand of the ligand-receptor complex were minimized. Finally, the model was validated Scheme 2 Sequence alignment of the extracellular domain of human 5-HT3A receptor subunit with that of AChBP. The crystal structure of AChBP was taken from the PDB file (1I9B). Secondary structure elements of AChBP (α-helix, red; β-strand, blue; 310-helix, green) were indicated [8] J Mol Model (2007) 13:121–131 123
J Mol model(2007)13:121-131 by ProcHeck and Verify 3d(hTtp: //nihserver. mbi. ucla table was constructed from similarity indices calculated at edu/SAvS/, [16]) the intersections of a regularly spaced lattice(2 A grid)in The 16 setrons, compounds 2 and 24 were retrieved from CoMSIA. themDdrdatabasefromMdl(htTp://www.mdli.com).The 2D-structures were subsequently converted into 3D-struc- PLS analysis and validation of QSAR models tures with CoriNa(htTp: //www2. ccc. uni-erlangen. de/ software/corina/free struct. html). All the other 23 com- The CoMFA/CoMSIA fields combined with observed pounds were constructed based on the structure of com- biological activities(pki) were included in a molecular pound 2. All molecules were set in their unprotonated state spreadsheet, and partial least square(PLS) methods [20] and Gasteiger-Huickel charges were added in SYBYL were used to generate 3D-QSAR models. To check the statistical significance of the models, cross-validations were Ligand docking done to choose the optimum number of components(M)by means of the leave-one-out ( LOo)[21] procedure using the The binding site of the 5-HT3 receptor was defined as enhanced version of PLs, the SAMPLS method [221 atoms within a radius of 16 A of the Ca atom of Trp178 in subsequently used to derive the final QSAR models. The the binding pocket to ensure that most of the residues optimal numbers of components were selected on the basis critical for ligand binding verified/revealed by previous of the highest cross-validated correlation coefficient(2) experimental data were included. All molecules were which is defined as follows set with v2.2[17-19]. The default settings of GOLD were used, and 2=_2(Ypredicted-Yactmal) (1) no flipping was allowed CoMFA and comsia Where Predicted, Actual, and Ymean are predicted, actual and mean values of the target property (pki), respectively First,the docked conformations of the molecules in the The non-cross-validated PLS analyses were performed with training set were placed into a 3D cubic lattice with 2a a column filter value of 2.0. The CoMFA/CoMSIA results grid. CoMFA fields were generated using an sp carbon were interpreted graphically by field contribution maps probe atom carrying +1 charge to generate steric(Lennard- using theSTDEVxCOEFF' field type Jones potential) and electrostatic( Coulomb potential) fields To assess the predictive power of the 3D-QS CoMFA-Standard method in SYBYL. A 30 kcal mol-1 test set molecules were predicted. The predictive rrof the at each grid point. The CoMFA fields were scaled by the derived using the training set, biological activities value is calculated as follows energy cutoff was applied. The steric, electrostatic, hydrophobic, hydrogen-bond pred=(SD-PRESS) donor and acceptor CoMSIA fields were derived according to Klebe et al. [10]. A distance-dependent Gaussian type Where SD is the sum of squared deviations between the functional form was used. The default value of 0.3 was biological activity of the test set and the mean activity of used as the attenuation factor. Similar to CoMFA, a data training-set molecules, and PRESS is the sum of squared Fig. 1 (a)Overview of the entameric structure of the ini- D C tial model. In this presentation each monomer has a different clockwise with A-B. B-C. C-D D-E and E-A forming the plus Details of ligand binding site. especially the residues approved to be important for ligand B entation), are shown in theA E and B interface of the model
by PROCHECK and Verify_3D (http://nihserver.mbi.ucla. edu/SAVS/, [16]). The 16 setrons, compounds 2 and 24 were retrieved from the MDDR database from MDL (http://www.mdli.com). The 2D-structures were subsequently converted into 3D-structures with CORINA (http://www2.ccc.uni-erlangen.de/ software/corina/free_struct.html). All the other 23 compounds were constructed based on the structure of compound 2. All molecules were set in their unprotonated state and Gasteiger–Hückel charges were added in SYBYL. Ligand docking The binding site of the 5-HT3 receptor was defined as atoms within a radius of 16 Å of the Ca atom of Trp178 in the binding pocket to ensure that most of the residues critical for ligand binding verified/revealed by previous experimental data were included. All molecules were docked into the binding pocket with the program GOLD v2.2 [17–19]. The default settings of GOLD were used, and no flipping was allowed. CoMFA and CoMSIA First, the docked conformations of the molecules in the training set were placed into a 3D cubic lattice with 2 Å grid. CoMFA fields were generated using an sp3 carbon probe atom carrying +1 charge to generate steric (LennardJones potential) and electrostatic (Coulomb potential) fields at each grid point. The CoMFA fields were scaled by the CoMFA-Standard method in SYBYL. A 30 kcal mol−1 energy cutoff was applied. The steric, electrostatic, hydrophobic, hydrogen-bond donor and acceptor CoMSIA fields were derived according to Klebe et al. [10]. A distance-dependent Gaussian type functional form was used. The default value of 0.3 was used as the attenuation factor. Similar to CoMFA, a data table was constructed from similarity indices calculated at the intersections of a regularly spaced lattice (2 Å grid) in CoMSIA. PLS analysis and validation of QSAR models The CoMFA/CoMSIA fields combined with observed biological activities (pKi) were included in a molecular spreadsheet, and partial least square (PLS) methods [20] were used to generate 3D-QSAR models. To check the statistical significance of the models, cross-validations were done to choose the optimum number of components (N) by means of the leave-one-out (LOO) [21] procedure using the enhanced version of PLS, the SAMPLS method [22], subsequently used to derive the final QSAR models. The optimal numbers of components were selected on the basis of the highest cross-validated correlation coefficient r2 cv , which is defined as follows: r 2 cv ¼ P Ypredicted Yactual 2 Σð Þ Yactual Ymean 2 ð1Þ Where Ypredicted, Yactual, and Ymean are predicted, actual, and mean values of the target property (pKi), respectively. The non-cross-validated PLS analyses were performed with a column filter value of 2.0. The CoMFA/CoMSIA results were interpreted graphically by field contribution maps using the ‘STDEV×COEFF’ field type. To assess the predictive power of the 3D-QSAR models derived using the training set, biological activities of the test set molecules were predicted. The predictive r2 r2 pred value is calculated as follows: r 2 pred ¼ ð Þ SD PRESS =SD Where SD is the sum of squared deviations between the biological activity of the test set and the mean activity of training-set molecules, and PRESS is the sum of squared Fig. 1 (a) Overview of the pentameric structure of the initial model. In this presentation each monomer has a different color. Subunits are labeled anticlockwise, with A-B, B-C, C-D, D-E and E-A forming the plus and minus interface side. (b) Details of ligand binding site, especially the residues approved to be important for ligands binding (ball-and-stick representation), are shown in the A and B interface of the model 124 J Mol Model (2007) 13:121–131
J Mol Model(2007)13:121-131 Table 1 5-HT3 receptor antag between aromatic side-chains of the receptor (Trp178- onists selected for docking Group A Group B Tyr229, Tyr138-Tyr148); while the basic centers interact with Glu231 or Glul24(ionic interaction), and/or Trp85 Bemesetron (cation-7 interaction) of the receptor [9] Dolasetron Granisetron In our study, the docking conformations with highest Indisetror score of setrons (one per setron) fell broadly into two Galdansetron Palonosetron groups, which we have designated A and B (Table 1). Ramosetron However, the observations fitted the result recently pub- Tropisetron Zatosetron lished by Lummis et al. [24]. In group A, the azabicyclic g of setrons was located between Trp178 and Tyr229 and the aromatic rings lay near Phe221. In group B, the deviations between the actual and the predicted activities of orientation of setrons was reversed, and consequently the romatic rings was located between Trp178 and Tyr229 of components, the conventional correlation coefficient r2 and the azabicyclic ring lay near Phe221. Representatives and its standard error were also computed for each model. from each group are shown in Fig. 2 The final model was validated by PROCHECK and erify 3D. The results are shown in Fig. 3. 75.9% of the Results and discussion residues were located in the darkest core'regions(marked A, B, and L) in the Ramachandran Plot, which fitted the Sequence identity of the extracellular region of human majority of PDB (72.9% in most favored regions for 2.7 5-HT3 receptor with AChBP is about 19%. When the X-ray structures)[25]. As for the Verify_3D results, conservative replacements are considered, their sequence 71.70% of the final model residues had an averaged 3D- homology is beyond 30%, which could result in at least ID score >0.2, hile the initial model showed 62.26% of 80% identity with the secondary structure of AChBP [9]. the residues had an averaged 3D-lD score >0. 2. Above Homology modeling resulted in a B-sandwich structure the model could be accepted for further studies. ( Fig. 1)similar to that of AChBP. Twenty-five molecules extracted from Nagel et al.were docked into the binding pocket of the final model Ligand docking and validation of the model Conformations (one per compound) were selected manually in 3D-QSAR analysis, considering both the docking score Sixteen selective 5-HT3 receptor antagonists were docked and the conformation reliability(Fig 4). The superposition into the binding pocket of the initial model. The setrons showed reasonable fit to the binding pocket consisting of eported to date may be expressed with such a pharmaco- residues that had been proven to be critical for ligand phore: a carbonyl-containing side chain flanked by a binding. The imidazole ring of most ligands seemed to form lipophilic aromatic group and a nitrogenous basic moiety 7-T interactions with Trp85, Trpl78 and Tyr229 of the [23]. As mentioned above, a similar study using a range of receptor. The nh moiety of the imidazole ring of most antagonists was published, which suggested that the ligands donated hydrogen bonds to Tyr148 and Trp178 of aromatic groups of antagonists were supposed to intercalate the receptor. However, these observations differed from Fig. 2(a) The docked confor mation of Tropisetron together the bindin TYR148 5-HT3Al TYR148 TRP178 RPI case of setrons in NTYR229 TYR229 conformation of granisetron TRP85 together with the binding site of human 5-HT3A receptor, as is ASN123 ASNI23 the case of setrons in Group B GLU231 The ligand is shown in orange (All hydrogen atoms were omit ted for a better view) GLU124 PHE221 GLU124 PHE221 a)
deviations between the actual and the predicted activities of the test set molecules. In addition, the r2 cv, r2 pred and number of components, the conventional correlation coefficient r2 and its standard error were also computed for each model. Results and discussion Sequence identity of the extracellular region of human 5-HT3 receptor with AChBP is about 19%. When the conservative replacements are considered, their sequence homology is beyond 30%, which could result in at least 80% identity with the secondary structure of AChBP [9]. Homology modeling resulted in a β-sandwich structure (Fig. 1) similar to that of AChBP. Ligand docking and validation of the model Sixteen selective 5-HT3 receptor antagonists were docked into the binding pocket of the initial model. The setrons reported to date may be expressed with such a pharmacophore: a carbonyl-containing side chain flanked by a lipophilic aromatic group and a nitrogenous basic moiety [23]. As mentioned above, a similar study using a range of antagonists was published, which suggested that the aromatic groups of antagonists were supposed to intercalate between aromatic side-chains of the receptor (Trp178– Tyr229, Tyr138–Tyr148); while the basic centers interact with Glu231 or Glu124 (ionic interaction), and/or Trp85 (cation–π interaction) of the receptor [9]. In our study, the docking conformations with highest score of setrons (one per setron) fell broadly into two groups, which we have designated A and B (Table 1). However, the observations fitted the result recently published by Lummis et al. [24]. In group A, the azabicyclic ring of setrons was located between Trp178 and Tyr229, and the aromatic rings lay near Phe221. In group B, the orientation of setrons was reversed, and consequently the aromatic rings was located between Trp178 and Tyr229, and the azabicyclic ring lay near Phe221. Representatives from each group are shown in Fig. 2. The final model was validated by PROCHECK and Verify_3D. The results are shown in Fig. 3. 75.9% of the residues were located in the darkest ‘core’ regions (marked A, B, and L) in the Ramachandran Plot, which fitted the majority of PDB (72.9% in most favored regions for 2.7 Å X-ray structures) [25]. As for the Verify_3D results, 71.70% of the final model residues had an averaged 3D– 1D score >0.2, while the initial model showed 62.26% of the residues had an averaged 3D–1D score >0.2. Above all, the model could be accepted for further studies. Twenty-five molecules extracted from Nagel et al. were docked into the binding pocket of the final model. Conformations (one per compound) were selected manually in 3D-QSAR analysis, considering both the docking score and the conformation reliability (Fig. 4). The superposition showed reasonable fit to the binding pocket consisting of residues that had been proven to be critical for ligand binding. The imidazole ring of most ligands seemed to form π–π interactions with Trp85, Trp178 and Tyr229 of the receptor. The NH moiety of the imidazole ring of most ligands donated hydrogen bonds to Tyr148 and Trp178 of the receptor. However, these observations differed from Fig. 2 (a) The docked conformation of Tropisetron together with the binding site of human 5-HT3A receptor, as is the case of setrons in Group A, which was above-mentioned in the paper. (b) The docked conformation of Granisetron together with the binding site of human 5-HT3A receptor, as is the case of setrons in Group B. The ligand is shown in orange (ball-and-stick representation). (All hydrogen atoms were omitted for a better view) Group A Group B Alosetron Azasetron Cilansetron Bemesetron Dolasetron Granisetron Fabesetron Indisetron Galdansetron Palonosetron Lurosetron Ramosetron Ondansetron Ricasetron Tropisetron Zatosetron Table 1 5-HT3 receptor antagonists selected for docking studies J Mol Model (2007) 13:121–131 125