Docking of Protein Kinase B Inhibitors: Implications in the Structure-Based Optimization of a Novel Scaffold

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1 Chem Biol Drug Des 2010; 76: Research Letter ª 2010 John Wiley & Sons A/S doi: /j x Docking of Protein Kinase B Inhibitors: Implications in the Structure-Based Optimization of a ovel Scaffold Alicia Hernández-Campos 1, Israel Velázquez-Martínez 1, Rafael Castillo 1, Fabian López-Vallejo 2, Ping Jia 3, Yongping Yu 3, Marc A. Giulianotti 2 and Jose L. Medina-Franco 2, * 1 Facultad de Química, Departamento de Farmacia, Universidad acional Autónoma de MØxico, MØxico DF 04510, MØxico 2 Torrey Pines Institute for Molecular Studies, SW Village Parkway, Port St. Lucie, FL 34987, USA 3 College of Pharmaceutical Science, Zhejiang University, Hangzhou , China *Corresponding author: Jose L. Medina-Franco, jmedina@tpims.org Protein kinase B (PKB AKT) is an attractive therapeutic target in anticancer drug development. We have recently identified by docking-based virtual screening a low micromolar AKT-2 inhibitor. Additionally, the virtual screening hit represents a novel AKT-2 inhibitor scaffold. In this work, we discuss a structure-based design strategy toward the optimization of this hit. Following this strategy and using a herein validated docking protocol, we conducted the design of novel compounds with expected improved activity over the parent compound. The newly designed molecules have high predicted affinity for AKT-2; are synthetically accessible and are contained within the kinase-relevant property space. Key words: AKT, cancer, drug design, structure activity relationships Abbreviations: HBA, hydrogen bond acceptors; HBD, hydrogen bond donors; IFD, induce-fit docking; MOE, molecular operating environment; MW, molecular weight; RB, number of rotatable bonds; SAR, structure-activity relationships; TPSA, topological surface area; XP, extra precision. Received 6 January 2010, revised 4 March 2010 and accepted for publication 25 May 2010 The serine threonine kinase B, also known as AKT, has several downstream targets that regulate a number of processes associated with cell growth, differentiation and division. AKT is frequently amplified and over-expressed in human cancer cells and its inhibition is a promising therapeutic approach for the treatment of cancers (1,2). There are three known subtypes, AKT-1 PKBa, AKT- 2 PKBb and AKT-3 PKBc. Each one is associated with different types of cancers. In particular, AKT-2 is amplified in pancreatic, breast and ovarian tumors. AKT-3 is over expressed in hormoneinsensitive breast and prostate cancers (1). Aberrations in AKT-1 are less common. AKT has an -terminal pleckstrin homology domain, a hinge region, a central kinase domain, and a C-terminal region (3). The kinase domains have a large similarity of more than 85% and the binding pocket residues are the same (3,4). To date, small molecules targeting the ATP-binding site in the kinase domain, and allosteric inhibitors interfering with the pleckstrin homology domain function have been reported, among others (3 6). AKT inhibitors, either ATP competitors or compounds that interact with regulatory domains, have shown promising activity in cancer treatment. It is thought that subtype-selective inhibitors are needed for optimal efficacy with acceptable toxicity (1). However, it remains to be determined if subtype selective inhibitors have a larger therapeutic window over compounds that inhibit all three subtypes (4). For example, a pan-akt inhibitor with nanomolar activity against the three subtypes has been evaluated as an intravenous agent in clinical trials in patients with cancer (7). Small molecules targeting the ATP-binding site have been reported. These include isoquinoline- 5-sulfonamides (8,9), pyrazole (see below), (10) indazole (11) and aminofurazan analogs (7). Several of these inhibitors haven been developed using structure-based design techniques and are reviewed in Ref. (4). Despite the fact that some current AKT-2 inhibitors have shown promising activity for further development, there are still issues that need to be addressed including toxicity and lack of suitable pharmacokinetic and pharmacodynamic properties (7,12). Thus, there is a critical need to develop novel scaffolds with AKT-2 inhibitory activity. Using fragment-based and iterative structure-based screening methodologies, the activity of the pyrazole derivatives 1 9 was optimized leading to the nanomolar inhibitors 8a and 9 (Figure 1) (10). A crystal structure of the AKT-2 in complex with compound 9 has been published (10). As part of our on-going effort involving anticancer drug discovery (13 15), we recently reported the discovery of the low micromolar AKT-2 inhibitor 11 with a distinct scaffold (Figure 1) (13). In that work, we conducted a multistep dockingbased virtual screening of a large compound database with the crystal structure of AKT-2 in complex with 9. Compound 11 was the top ranked molecule in docking and our next goal is to optimize its activity. Based on previous results (13) and molecular modeling 269

2 Hernández-Campos et al. Figure 1: Chemical structures and IC 50 values of AKT-2 inhibitors considered in this study. Activity of 6a and 6b corresponds to the racemic mixture. Compounds 1 10 were assayed under the same experimental conditions (10). Compound 11 was discovered recently by docking-based virtual screening (13). studies discussed in this work, we hypothesize that the crystal structure of AKT-2 in complex with 9 can be used to conduct the structure-guided optimization of 11. In this work, we report the docking of the eleven AKT-2 inhibitors in Figure 1 with the crystal structure of AKT-2 in complex with compound 9 using the program Glide. Compounds 1 10 were obtained from the literature (8,10). We also docked the virtual screening hit 11 (Figure 1). As part of the validation of the docking protocol, we found that docking with Glide was able to reproduce the binding mode of the co-crystal pyrazole. In addition, the docking scores of the eleven compounds had an excellent agreement with the experimental activity. Comparison of the predicted binding mode of 11 with the co-crystal inhibitor 9 suggested modifications to the chemical structure of the virtual screening hit to increase its potency. ewly designed compounds showed the expected binding mode in docking and have a more favorable docking energy than the parent compound. In addition, the new molecules are contained within the kinase-relevant property space and are synthetically accessible. Details of the docking of AKT-2 inhibitors and molecular modeling studies toward the optimization of the activity of compound 11 are presented in the following paragraphs. Methods and Materials In order to conduct the docking studies, the structures of all the ligands were prepared using Molecular Operating Environment (MOE), version a The crystal structure of AKT-2 in complex with the pyrazole-based inhibitor 9 was retrieved from the Protein Data Bank (PDB entry 2UW9) (16). Docking was performed with the Glide (Grid-based Ligand Docking with Energetics) program, version 5.0. b The Protein Preparation Wizard module of Maestro was used to prepare the protein. c During protein preparation, water molecules and peptide substrate (GSK-3b) were deleted. For docking, the scoring grids were centered on the crystal structure of 9 using the default bounding box sizes; with an inner box of 10 Š on each side and an outer box of 24 Š on each side. Flexible docking with default parameters was used. Glide XP (extra precision) was employed for all docking calculations (17). The best docked poses were selected as the ones with the lowest GlideScore; the more negative the Glide Score, the more favorable the binding. In order to explore the putative binding interactions of the ligands with AKT-2, the top ranked binding mode found by Glide in complex with the binding pocket of the enzyme were subjected to full energy minimization using the MMFF94x force field implemented in MOE 270 Chem Biol Drug Des 2010; 76:

3 Docking of Protein Kinase B Inhibitors until the gradient was reached. The default parameters implemented into the MOE's LigX application were used. a Results and Discussion Before docking compounds in Figure 1 with AKT-2, the docking protocol was validated. The co-crystal inhibitor 9 was removed from the active site and docked back into the binding site. The root mean square deviation between the predicted conformation and the observed X-ray crystallographic conformation was 0.40, indicating the ability of the docking protocol to reproduce the binding mode of 9 (Figure 2A). Docking of AKT-2 inhibitors Pyrazole derivatives 1 9 (10), the isoquinoline-5-sulfonamide 10 (8), and the lead compound 11 (13) were docked into the ATP binding site of AKT-2. The docking scores and the biological activity are summarized in Table 1. The biological activity of compounds 1 11 was obtained from the literature (10,13). Activities were converted A B Figure 2: (A) Comparison between the binding position of 9 found within the crystal structure (yellow) and the binding mode predicted by Glide (red). (B) Comparison of the binding conformations of the pyrazole 8a (green) and isoquinolin-5-sulfonamide 10 (cyan) predicted by Glide. Crystallographic 9 (yellow) is shown as a reference with hydrogen bonds displayed as magenta dashes. onpolar hydrogen atoms are omitted. Table 1: Results of docking of the AKT-2 inhibitors 1 11 a Compound Docking score (kcal mol) Docking score rank pic 50 pic 50 rank 1 ) ) ) ) ) a ) b 5.5 6b ) b ) a ) b ) ) ) ) a All pic 50 values were obtained from Ref. (10) except for 11 that was obtained from Ref. (13). b Approximated as the activity reported for the racemic 6 (10). into the corresponding )logic 50 (pic 50 ) values, were IC 50 is the effective concentration of the compound required to achieve 50% of inhibition of AKT-2. To note, the activity reported for compounds 1 10 was determined using the same conditions (10). The activity reported for compound 11 was measured by a different group (13). The activity of compounds 6a and 6b in Table 1 was approximated as the activity reported for the racemic 6 (10). In contrast, the activity for compounds 8a and 8b corresponds to the activity reported for the (R)- and (S)-enantiomers, respectively. The docking scores calculated with Glide had an excellent correlation with the biological activity, particularly with the rank ordering of the compounds (Table 1); compounds with the highest activities such as 9 (pic 50 = 7.74; IC 50 =18nM) and 8a (pic 50 = 7.47; IC 50 =34nM) also displayed the top-ranked docking scores ()9.07 and )9.12 kcal mol, respectively). In contrast, compounds with the lowest activities such as 1 (pic 50 = 4.1; IC 50 =80lM) and 5 (pic 50 = 3.87; IC 50 = 135 lm) showed the lowest docking scores ()6.41 and )6.05 kcal mol, respectively). The isoquinoline-5-sulfonamide 10 was included in this work as a control; its activity was measured under the same experimental conditions as the pyrazole derivatives; however, compound 10 has a different scaffold. Interestingly, 10 was ranked in position twelve by docking (docking score of )6.37 kcal mol); this is in good agreement with its ranking position of ten according to its experimental activity (pic 50 = 5.12; IC 50 = 7.5 lm). In turn, compound 11, also with a distinct scaffold, showed a better docking score than the isoquinoline-5-sulfonamide 10 and pyrazoles 1 and 5. This is also consistent with the superior AKT-2 inhibitory activity of 11 over 1, 5 and 10 (Table 1). Moreover, compound 11 showed a lower docking score than the submicromolar or nanomolar pyrazole inhibitors 6 9, in further agreement with the experimental activities. Taken together, these observations suggest that the binding modes predicted with Glide for compounds 1 11 are reasonable. A comparison of the docking models for compounds 8a and 10 is depicted in Figure 2B. Crystallographic 9 is shown as a Chem Biol Drug Des 2010; 76:

4 Hernández-Campos et al. reference. Two-dimensional representations of the optimized docking models of 1 10 are shown in Figure S1. Compounds 8a and 9 (Figure 2B) and all other pyrazole derivatives, have a similar binding mode. The pyrazole ring forms hydrogen bonds with the backbone H of Ala232 and backbone carbonyl of Glu230 (Figure S1). This is in agreement with the observations derived from crystallographic structure of AKT-2 in complex with 9 and the crystallographic structures of the PKA-PKB chimera in complex with 3 and 8b (10). A hydrogen bond between the nitrogen atom of the isoquinoline ring of compound 10 and the backbone H of Ala232 was also predicted by Glide. Compounds 2 4 showed two additional hydrogen bonds with the side chain of Glu236 and the backbone carbonyl of Glu279 (Figure S1). These observations are also consistent with the crystallographic structure of the PKA-PKB chimera in complex with 3. As suggested previously, the interactions of the basic amine with the electronegative pocket of AKT-2 formed by residues Glu236, Glu279, Asn280 and Asp293 explain the increased activity of 2 4 over 1 and 5 (10). Similar hydrogen bonds with Glu236 and Glu279 were predicted for the low micromolar inhibitor 7 and the nanomolar inhibitors 8a and 8b, respectively (Figure S1). A comparison of the binding model of 11 obtained with Glide and the crystallographic position of 9 is shown in Figure 3A. The 1,3- benzoxazol-2(3h)-one ring of 11 occupies the same binding pocket as the pyrazole ring of 9 making hydrogen bonds with the side chains of Thr213 and Thr292 (13). The 2H-1,4-benzoxazin-3(4H)-one ring of 11 partially overlaps the chlorophenyl ring of 9 making and hydrogen bond with Asp293. A very similar binding model for 11 was obtained previously with two different docking programs (13). otably, the phenyl ring of 11 is close to the secondary amine of 9 and to Glu236 in the electronegative pocket discussed above. It is also worth mentioning the three-dimensional similarity of 9 and 11 (Figure 3A); both compounds have a Y-shape and similar flexibility (e.g., three rotatable bonds). In view of the fact that 11 was a top-ranked hit in virtual screening with the crystallographic structure of AKT-2 bound to 9 (13) and that the predicted binding mode for 11 is similar to the co-crystal inhibitor 9, we hypothesize that the predicted binding interactions of 11 with AKT-2 can be the basis to initiate a structure-based optimization program. To further test this hypothesis considering the protein flexibility, we conducted induce-fit docking (IFD) for compound 11 with the same crystallographic structure used during the rigid-receptor docking with Glide. We used the validated IFD protocol developed by Schrçdinger Inc. with default parameters. d The IFD approach implemented in Schrçdinger iteratively combines rigid receptor docking using Glide with sampling side chain degrees of freedom in the receptor while allowing backbone movements through minimization with the program Prime (18). For the Glide component, Glide XP was employed. We observed a very similar binding mode for compound 11 predicted by induce-fit and rigidreceptor docking (data not shown). These observations further supported the approach of using this crystal structure of AKT-2 (e.g., PDB code 2UW9) to guide the optimization of 11. The protocol discussed earlier to explain the structure activity relationships (SAR) of the pyrazole derivatives, and the good agreement between the experimental activity and docking scores, including the parent A B C Figure 3: (A) Comparison of the predicted binding mode of compound 11 (cyan) with the crystallographic position of 9 (yellow). (B) Comparison of the binding modes of 11 (cyan) with the representative designed molecules 16 (purple), 20 (gray) and 21 (orange). (C) Comparison of the crystallographic position 9 (yellow) with the predicted binding modes of 16 (purple) and 21 (orange). Hydrogen bonds for 21 are displayed as magenta dashes. on-polar hydrogen atoms are omitted. 272 Chem Biol Drug Des 2010; 76:

5 Docking of Protein Kinase B Inhibitors compound 11, supports the use of docking to guide the structurebased optimization of 11. Molecular modeling studies toward the structure-based optimization of the virtual screening hit 11 The overall goal of the design was to identify synthetically accessible analogs of 11 with docking scores better than 11 and, preferably, scores close to or better than the nanomolar inhibitor 9. In addition, we confirmed that the predicted binding modes for the new molecules showed the expected binding interactions with the protein as derived from the SAR of experimentally known AKT-2 inhibitors. The structure-based design was divided into two main parts. In the first part, a series of compounds containing the same or similar heterocyclic rings present in 11 such as 1,3-benzoxazol-2(3H)-one, 2H-1,4-benzoxazin-3(4H)-one, or 3,4-dyhidroquinoxalin-2(1H)-one were designed. To note, 11 is a nearly symmetric molecule (Figure 1). At this stage, we decided to keep two heterocyclic rings in the designed molecules because, as discussed earlier, the 1,3-benzoxazol-2(3H)- one and 2H-1,4-benzoxazin-3(4H)-one ring in 11 seem to form key hydrogen bonds with Thr213, Thr292 and Asp293. Following this approach, compounds such as 12 and 17 in Table 2 were designed. These two molecules are very similar to 11 with the only difference being that 12 and 17 have two identical heterocyclic rings, either 2H-1,4-benzoxazin-3(4H)-one or 3,4-dihydroquinoxalin-2(1H)-one, respectively. Docking models of 12 and 17 with AKT-2 (see below) are very similar to the binding model of 11 indicating that the core scaffold for the new molecules (Table 2) is reasonable. In the second part of the design, the replacement of the phenyl ring of 11 with polar groups was proposed. This is based on the docked position of the phenyl ring of 11 in the electronegative pocket of AKT-2, and the proximity of the phenyl group to the secondary amine of 9 as discussed earlier (Figure 3B). Representative molecules are depicted in Table 2 along with their corresponding molecular weight (MW) and docking scores. Following this approach, the phenyl group is replaced, for instance, by a hydroxymethyl group (13 and 18), pyrrolidin-2-yl (14 and 19), pyrrolidin-1-ylmethyl (15 and 20) or and aminomethyl group (16 and 21). The series of 2H-1,4-benzoxazin-3(4H)-ones and 3,4-dihydroquinoxalin-2(1H)-ones were docked with AKT-2 using the same validated docking protocol described earlier. Docking results are summarized in Table 2. oteworthy, the docking scores of compounds were more favored (i.e., more negative) than the docking score of the parent inhibitor 11, )6.72 kcal mol (Table 1). Furthermore, docking scores of compounds 20 ()8.82 kcal mol) and 21 ()9.14 kcal mol) were similar to the docking score of the nanomolar inhibitor 9 ()9.07 kcal mol). We also docked bis-1,3-benzoxazol- 2(3H)-ones but these molecules showed lower docking scores than the corresponding 3,4-dihydroquinoxalin-2(1H)-ones and 2H-1,4-benzoxazin-3(4H)-ones (data not shown). Based on these observations and the good agreement between the docking scores with the experimental rank-order of compounds 1 10 and the parent inhibitor 11 discussed earlier, it is expected that compounds will be more active than 11. We want to emphasize that that the docking scores of the newly designed analogs of 11 were obtained in Table 2: Chemical structure, molecular weight (MW) and docking scores with AKT-2 of representative newly structure-based designed analogs of 11 R O H X Compound X R MW 12 O ) O HO ) O 15 O H docking experiments with the crystallographic structure of a different scaffold 9. o quantitative predictions of potency for each designed compound are made. Tridimensional binding models obtained with docking representative 2H-1,4-benzoxazin-3(4H)-ones and 3,4-dihydroquinoxalin-2(1H)-ones are depicted in Figure 3B. Two-dimensional representations of the optimized docking models are shown in Figure S2. According to the optimized binding models, all analogs adopt a very similar binding mode to the parent 11. The corresponding 2H-1,4-benzoxazin- 3(4H)-one or 3,4-dihydroquinoxalin-2(1H)-one rings make hydrogen bonds with side-chain atoms of Thr213, Thr292 and Asp293, similar to the hydrogen bonds predicted for 11. In addition, compounds with polar groups at the fourth position of the pyridine ring (13 16 and 18 21) make a hydrogen bond with the side chain of Glu236 (Figure S2). A similar hydrogen bond is observed in the crystallographic structure of 9, and it is also predicted for other submicromolar and nanomolar AKT-2 inhibitors. This hydrogen bond H X O ) ) O H ) H ) H HO ) H 20 H H ) ) H H )9.14 Docking score (kcal mol) Chem Biol Drug Des 2010; 76:

6 Hernández-Campos et al. is not observed in the docking model of 11. Based on the SAR discussed for compounds 1 9, it is hypothesized that these polar groups will be responsible for the expected increased activity of the new analogs. Figure 3C shows the comparison of the binding model for 16 and 21 with the crystallographic binding model of 9. The three-dimensional models are very similar between 9 and 16, and 9 and 21, in particular the position of the amino groups that make hydrogen bond with Glu236. In fact, a ligand-based three-dimensional overlay of 9 and 21 and other compounds in Table 2 with the program Rapid Overlay of Chemical Structures e further revealed the high similarity of these molecules (Figure S3). oteworthy, all the compounds in Table 2 have a MW lower than 500. Further comparison of the MW as well as five other physicochemical properties for the 2H-1,4-benzoxazin-3(4H)-ones and 3,4- dihydroquinoxalin-2(1h)-ones with known kinase inhibitors was conducted. Figure 4 depicts a visual representation of the property space (19) comparing compounds in Table 2 with a set of known kinase inhibitors obtained from the Binding Database (20). The parent compound 11 is also included as a reference. The property space was obtained by principal component analysis of six-scaled physicochemical properties computed with MOE. a namely MW, number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), number of rotatable bonds (RB), SlogP and topological surface area (TPSA). The property space of other compound databases has been compared by our group using the same physicochemical properties (21). The first two principal components with eigenvalues 2.42 and 1.33, respectively, account for 69.5% of the variance and are depicted in Figure 4 (components with eigenvalues less than 1.0 were not considered). This analysis clearly revealed that, in general, the newly designed compounds are contained within the kinase-relevant property space and are suitable research tools to explore the space covered by kinase inhibitors. It should be emphasized that this analysis does not indicate the likelihood of the proposed compounds to become marketed drugs. For example, compounds such as 16 and 21 are unlikely to become approved drugs. However, these compounds are suitable research tools to explore the SAR of 11 and are part of the development of a new scaffold as AKT-2 inhibitors. Taken together, the results mentioned earlier suggest that the strategy presented here to design the 2H-1,4-benzoxazin-3(4H)-ones and 3,4-dihydroquinoxalin-2(1H)-ones exemplified in Table 2 will lead to promising AKT-2 inhibitors with better activity than the parent compound 11. It is likely that the new compounds will be active against other kinases. In fact, 11 not only inhibits AKT-2 (IC 50 = 1.5 lm) but also AKT-1 (IC 50 = 2.6 lm) and AKT-3 (IC 50 = 4.0 lm) (13). At this point, one also needs to consider, however, that multiple kinase inhibitors with specific multiple activity profiles represent a major area of interest in the pharmaceutical industry (22). The next step of this work is the synthesis and biological evaluation of designed compounds following the strategy discussed herein. This includes compounds in Table 2 and other molecules synthetically accessible with polar groups at R. This is being conducted by our group and will be reported in due course. It is expected that the biological activity of the designed molecules, including activity with multiple kinases, will provide insights into the structural requirements of the parent inhibitor 11 for activity and selectivity. Conclusions and Future Directions Figure 4: Property space of compound 11 (black circle), representative 2H-1,4-benzoxazin-3(4H)-ones (12 16; light gray squares), 3,4-dihydroquinoxalin-2(1H)-ones (17 21; dark gray triangles) and 4796 kinase inhibitors obtained from the Binding Database (20) (gray circles). The visual representation of the property space was obtained by principal component analysis of six scaled physicochemical properties (MW, RB, HBA, HBD, TPSA and SlogP). The first two PCs account for 69.5% of the variance. See text for details. We report the docking of AKT-2 inhibitors and molecular modeling studies toward the optimization of the virtual screening hit 11 recently reported by our group. The docking protocol with the program Glide was able to reproduce the experimental binding position of the co-crystal inhibitor (9). Docking-based ranking of the AKT-2 inhibitors showed an excellent agreement with the experimental rank-order. Using the aforementioned validated docking protocol and based on the SAR of AKT-2 inhibitors, we designed a series of 2H- 1,4-benzoxazin-3(4H)-ones and 3,4-dihydroquinoxalin-2(1H)-ones. The new molecules are synthetically accessible and are contained within the kinase-relevant property space. The new compounds will provide valuable information to explore the SAR of 11 and it is expected that a number of them will have better activity than the parent compound. Currently, we are working on the synthesis and biological evaluation of the new compounds following the strategy discussed in this work. Acknowledgments We thank Dr. arender Singh for preparing the dataset of kinase inhibitors used in Figure 4. This work was supported by the State 274 Chem Biol Drug Des 2010; 76:

7 Docking of Protein Kinase B Inhibitors of Florida, Executive Office of the Governor's Office of Tourism, Trade, and Economic Development. J.L.M.-F. wishes to thank the Osteoporosis & Breast Cancer Research Center for funding. Yongping Yu thanks the ational atural Science Foundation of China (o and o ). The authors are grateful to OpenEye Scientific Software, Inc., for providing ROCS. References 1. Hennessy B.T., Smith D.L., Ram P.T., Lu Y.L., Mills G.B. (2005) Exploiting the PI3K AKT pathway for cancer drug discovery. at Rev Drug Discovery;4: Cheng J.Q., Lindsley C.W., Cheng G.Z., Yang H., icosia S.V. (2005) The AKT PKB pathway: molecular target for cancer drug discovery. Oncogene;24: Cheng G.Z., Park S., Shu S.K., He L.L., Kong W., Zhang W.Z., Yuan Z.Q., Wang L.H., Cheng J.Q. (2008) Advances of AKT pathway in human oncogenesis and as a target for anti-cancer drug discovery. Curr Cancer Drug Targets;8: Lindsley C.W., Barnett S.F., Layton M.E., Bilodeau M.T. 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8 Hernández-Campos et al. Supporting Information Additional supporting information may be found in the online version of this article. Figure S1. 2D-interaction maps of the optimized docking models of compounds Figure S3. 3D-overlap of compounds 9 21, 9 19, 9 20 and 9 11 generated with ROCS. Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article. Figure S2. 2D-interaction maps of the optimized docking models of compounds Chem Biol Drug Des 2010; 76: