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1 Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Graduate School of Chinese Academy of Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 201203, China
2 Key Laboratory of Proteomics and State Key Laboratory of Molecular Biology, Institute of Biochemistry and Cell Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
3 School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
(RECEIVED March 23, 2006; FINAL REVISION May 26, 2006; ACCEPTED May 31, 2006)
| Abstract |
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Keywords: peptide deformylase; protein crystallization; reverse docking; enzyme inhibitor; Helicobacter pylori
| Introduction |
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Because small organic molecules can alter or perturb the functions of target proteins by inhibiting or activating their normal functions through binding, they have been widely used to illuminate the molecular mechanisms underlying biological processes. This approach is referred to as chemical biology (Stockwell 2004). Compounds with functions of activating or inhibiting cellular cycle should be likely probes to map the protein targets. To this end, proteomics may be an appropriate approach for identifying particular binding proteins of the small molecules by comparing the differences of protein expression profiles between pathological cells and cells treated by chemicals. However, this method is not very successful in target discovery because of its time consuming and slower rate of reproduction (Huang et al. 2004). An alternative approach that has been proved to be promising in recent years is to find the probable binding protein(s) for an active compound from the genomic or protein database by using computational methods, and then to validate the computational results by traditional molecular and/or cell biology methods (Rockey and Elcock 2005).
In the following, we report on the finding of peptide deformylase (PDF) as a potential target for anti-H. pylori agents. The result was discovered by using computational method and verified with bioassay and X-ray crystallography. Briefly, taking the natural product, N-trans-caffeoyltyramine (compound 1), discovered by anti-H. pylori assay as a probe, we searched the in-house potential drug target database (PDTD) by using a reverse docking method (http://www.dddc.ac.cn/tarfisdock/), TarFisDock (Li et al. 2006), and found that Escherichia coli PDF is a binding protein candidate. Sequence alignment indicated that H. pylori PDF (HpPDF) (GenBank NP_223447 [GenBank] ) contains 40% identity to E. coli PDF. Enzymatic assay demonstrated that compound 1 and its derivative compound 2 ((E)-N-phenethyl-3-(3,4-diacetoxyphenyl)acrylamide) are potent inhibitors of HpPDF. Finally, we determined the X-ray crystal structures of the apo-HpPDF and inhibitor-HpPDF complexes, which demonstrated that the two compounds tightly bind to the active site of HpPDF. Our results illuminate that the reverse docking method can facilitate the identification of target protein binding to active compounds.
| Results |
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Figure 2 represents the sequence alignment of HpPDF with the other PDFs, indicating that PDFs are very conservative and they share high percentage of homology; the similarities of PDF sequences range from 50% to 65%. The metallic ions (e.g., Co2+, Fe2+, or Zn2+) in the active site of PDF were predicted to be coordinated with two histidines from the conserved motif HEXXH, a cystine from the conserved motif EGCLS, and a water molecule. Bacterial PDF was first characterized as a Fe2+-containing enzyme that is very labile because of its conversion to Fe3+ by molecular oxygen and H2O2, resulting in inactivation (Rajagopalan and Pei 1998). The Fe2+ can be replaced by other metal ions such as Ni2+, Zn2+, and Co2+. The catalytic activities of different metal forms of PDF have been shown to be of great diversity (Ragusa et al. 1998). Based on the phylogenetic tree analysis and systematic sequence alignment, PDFs can be classified into two types, i.e., type-I (Gram-negative type) and type-II (Gram-positive type) (Guilloteau et al. 2002). HpPDF belongs to the type-I family.
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-helix possessing a unique spatial orientation compared with the other PDFs. The subsequent refinements were preformed with the program CNS, including rigid body refinement, energy minimization, and B factor refinement. Manual building of the model was carried out with the program O (Jones et al. 1991) according to the 2Fo-Fc map. After several cycles of model rebuilding and refinement, most of the residues were clearly positioned in the 2Fo-Fc map. The cobalt ion in the active site was unambiguously distinguished by direct examination of the Fo-Fc map. Water molecules were added automatically with CNS using 3
peaks in the Fo-Fc map and hydrogen bonding requirements, and the uncertain water molecules were removed manually by inspecting the electron density map. After incorporating the cobalt ion and water molecules, some previously unrecognizable regions of the electron density map were greatly improved (e.g., the flexible loop of residues 6671), but the last 10 residues of the C terminus (residues 165174) were still disordered in the map. The final R-factor is 20.9% (free R-factor 24.4%), and statistics show that the final model of native HpPDF is a well-refined structure (Table 1). The positions of inhibitors were determined based on the Fo-Fc map of the complexes, using the solved structure of HpPDF as the model. Similar to the structure of apo-HpPDF, the last seven C-terminal residues (residues 168174) of the complexes were not found in the electron density maps. The R-factors of HpPDF-1 complex and HpPDF-2 complex are 20.4% and 20.1%, respectively. The crystal structures are shown in Figures 4 and 5.
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-helices, seven
-strands, and four 310 helices (Fig. 4A). A cobalt ion is located at the active site of the enzyme, which is tetrahedrally coordinated with His138 and His142 from the motif HEXXH, Cys96 from the motif EGCLS, and a water molecule (Figs. 2, 4A). Detailed structural comparison of HpPDF with several currently determined X-ray crystal structures of PDFs (Hao et al. 1999; Guilloteau et al. 2002; Kumar et al. 2002; Yoon et al. 2004; Zhou et al. 2004) reveals some distinct structural differences (Fig. 4B). One distinctive difference comes from the CD loop composed of Asn62Cys75 between the
C and
D, which is structurally different from any of the other PDFs (Fig. 4C). This is consistent with the phenomenon that the CD loops of PDFs are conformationally flexible (Fig. 4B,C). Another difference comes from the C terminus. Leu152 and Ser153 before the C-terminal helix fold into a conformation different from either that of type-II PDF or that of type-I PDF (Fig. 4B).
Inhibitor-HpPDF interactions
Like the binding pockets of the other PDFs, the substrate-binding pocket of HpPDF consists of S1', S2', and S3' subsites (see Supplemental Fig. 1). S1' and S3' are two cavities, and S2' is a "saddle" linking S2' and S3'. We made a comparison of the binding pockets of different PDFs. The surfaces of the pockets are also shown in Supplemental Figure 1. The shapes of the binding pockets of PDFs are diverse, reflecting the selectivity and specificity for substrate or inhibitor binding.
X-ray data for trigonal crystals of HpPDF soaked with compounds 1 or 2 were also collected and refined to 2.2 Å resolutions (Table 1). After several cycles of refinements, the structure of HpPDF in complex with compound 2 could be fitted unambiguously in the electron density map (Fig. 5B), whereas the structure of HpPDF in complex with compound 1 is partially disordered with an average B-factor of 59.8 Å2 and has a weak broken electron density (Fig. 5A). This suggests that the occupation of compound 1 at the binding pocket of HpPDF is not 100%, which is consistent with its weak binding affinity to HpPDF. Structure superposition shows that both compounds 1 and 2 adopt a similar orientation and conformation in the substrate-binding pocket. The heads for both compounds (phenyl group for compound 1 and phenol group for compound 2) enter into the S1' subsite, and the tails extend along the pocket entrance (Fig. 6A). For either compound 1 or compound 2, the acylamide oxygen atom forms two hydrogen bonds to the main-chain nitrogen atoms of Ile45 and Gly46, respectively, and the acylamide nitrogen atom hydrogen bonds to the carbonyl oxygen atom of Gly95 (Fig. 6B,C). The tail ring (3,4-diacetoxyphenyl) of compound 2 flips
180° in comparison with that of compound 1 (3,4-dihydroxyphenyl) to avoid the steric hindrance between the 3-acetoxy and the enzyme (Fig. 6A). This led to different hydrogen bonding models for the tails of compounds 1 and 2 to HpPDF. The oxygen atom of 3-hydroxyl of compound 1 forms hydrogen bonds to the main-chain nitrogen atom of Gly101, the main-chain nitrogen atom of Cys96, and the main-chain oxygen atom of Phe102 through a water molecule. The tail end of compound 2 only forms one hydrogen bond to HpPDF through the 4-acetoxy carbonyl oxygen atom with the hydroxyl of Tyr103. Therefore, the hydrogen bonding of compound 1 to HpPDF might be stronger than that of compound 2 to HpPDF, which is not in agreement with the inhibitory activities (compound 2 is more potent than compound 1). Further analysis reveals that the binding pocket of HpPDF, especially S1' subsite (Fig. 6A; Supplemental Fig. 1), is hydrophobic, and compound 2 is structurally more hydrophobic (XlogP = 2.87) than compound 1 (XlogP = 2.78). Accordingly, compound 2 may form a more favorable hydrophobic interaction than compound 1 does. This conclusion is confirmed by the component analysis for the interaction energies of compounds 1 and 2 with HpPDF (see Supplemental Table 2). The result demonstrates that van der Waals interaction dominates the binding of the two compounds with HpPDF, suggesting that the interactions of the compounds with HpPDF are driven by hydrophobic force. In addition, compared with the structure of HpPDF, Tyr92 in HpPDF-1 complex moves toward solvent due to the repulsive interaction between the hydroxyl group in the head of compound 1 and the hydroxyl of Tyr92 (Fig. 7). In the HpPDF-2 complex, Tyr92 and the phenyl group of compound 2 close up together due to the hydrophobic interaction. The movement of Tyr92 makes room for a water molecule, which forms a hydrogen bond to the hydroxyl group of Tyr92 (Fig. 7). This hydrogen bond may stabilize the protein structure. Therefore, we can conclude that the hydrophobic interaction dominates the activity difference between 1 and 2.
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| Discussion |
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We verified that HpPDF is a target of compound 1 by enzymatic assay and crystal structure determination. Before that, compound 2, one analog of compound 1, was found as a more potent inhibitor of H. pylori. The FDH-coupled assay indicated that compounds 1 and 2 are exact inhibitors of HpPDF, and the IC50 values of these two compounds are, respectively, 10.8 and 1.25 µM, which are in agreement with the MIC values. The X-ray crystal structures indicated that compounds 1 and 2 fit well into the binding pocket of HpPDF, demonstrating at the atomic level that PDF is the binding protein of these two compounds. However, enzymatic assay indicated that DC is not a real target protein for compounds 1 and 2.
For the first time, we determined the crystal structure of HpPDF. The overall structure of HpPDF folded in a similar way to the other PDFs, and a cobalt ion tetrahedrally coordinated with two histidines, one cystine, and a water molecule. The CD loop of HpPDF adopted a conformation different from any other PDF, and the C-terminal helix shifted away from its original position as in the other type-I PDFs. The binding pocket of HpPDF is different from those of the other PDFs, implying that the selective HpPDF inhibitors could be designed. As a matter of fact, compounds 1 and 2 are the selective inhibitors of the type-I PDFs. Moreover, these two compounds, especially compound 1, may be modified as selective HpPDF inhibitors, because the predicted binding affinities of these two compounds to HpPDF are higher than those of them to the other PDFs, and enzymatic assay also demonstrated that these two compounds cannot inhibit EcPDF. In addition, different from the other inhibitors of PDF (e.g., actinonin), compounds 1 and 2 bind to HpPDF noncovalently, and these two compounds have novel and simple chemical scaffolds. Therefore, these two compounds can be used as leads for developing new anti-H. pylori agents.
Target identification and validation is the first key stage in the drug discovery pipeline. Numerous technologies for addressing targets have been developed recently (Wang et al. 2004). Genomics and proteomics approaches, including bioinformatics analysis, are the major tools for target identification. Chemical biology, which generally uses small molecules as probes to map the genomic functions, is an emerging tool for target identification (Stockwell 2004). In this study, we provided an alternative approach for target identification, i.e., discovering the potential binding protein candidates of active compounds (natural products or existing drugs) from the protein databases (e.g., PDTD or PDB) by using the reverse docking method TarFisDock, a computational method we developed. The computational clues were verified by enzymatic assay and even X-ray crystallography determination. The result of the present study demonstrated that this approach is effective and can be used as a complementary approach of genomics and chemical biology in target identification for other systems. However, the reverse docking approach TarFisDock still has certain limitations (Li et al. 2006). The major one is that the protein entries are not enough to cover all the protein information of disease-related genomes. The second one is that TarFisDock has not considered the flexibility of proteins during docking simulation. These two aspects will produce a false negative. Another limitation is that the scoring function for reverse docking is not accurate enough, which will produce a false positive.
| Materials and methods |
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In vitro anti-H. pylori determination
The in vitro anti-H. pylori activities of compounds or crude extracts of herbs were estimated by determining the MIC with agar dilution method. A series of agar plates were prepared with the base of Campylobacter selective agar (Merck) containing 5% of fetal bovine serum. Then, various concentrations of twofold diluted test compounds or crude extracts of herbs were dispersed into the prepared agar plates. Cells of H. pylori strain SS1, suspended in saline at the density of 108 cfu/mL, were added to the well-prepared agar plates and were incubated at 37°C for 96 h under an atmosphere of 5% O2, 10% CO2, and 85% N2. Blank controls and positive controls were performed using the same conditions as described above, except that in the case of blank controls no compound or crude extract was dispersed into the agar plates, while in the case of positive controls various concentrations of twofold diluted metronidazole were dispersed. The MIC value was defined as the lowest concentration of the compound or crude extract for inhibiting the visible growth.
Reverse molecular docking
Taking compound 1 as a probe, we searched our in-house potential drug target database (PDTD). PDTD contains 698 protein structures isolated from PDB. Missing residues and atoms of each protein structure were repaired using the Biopolymer module of Sybyl 6.8 (Tripos Associates), and Kollman (Weiner et al. 1986; Cornell et al. 1995) charges were assigned to the protein. A grid of each protein binding pocket (site) was constructed by using the grid module of DOCK4.0 (Kuntz 1992; Ewing and Kuntz 1997), which was mapped onto the original protein structure deposited in PDTD. Afterward, compound 1 was docked into the binding site of each protein using DOCK4.0, and interaction energies between compound 1 and the proteins were calculated using the scoring function of DOCK4.0. Proteins with interaction energies to compound 1 < 35.0 kcal/mol were selected for further analysis. Recently, based on this computational method, we developed a Web-based tool, TarFisDock (Target Fishing Dock), for searching the probable binding proteins for active small molecules (Li et al. 2006), which can be accessed through http://www.dddc.ac.cn/tarfisdock/.
Homologous proteins search
Reverse docking produced a series of binding protein candidates for compound 1. Homology search was performed to identify the homologous proteins of these candidates from H. pylori genome. The candidates were selected as queries for searching the GenBank database (http://www.ncbi.nlm.nih.gov/).
Enzyme inhibition assay
Recombinant HpPDF and EcPDF were overexpressed and purified from E. coli strain BL21(DE3) as described previously (Rajagopalan et al. 1997; Han et al. 2004). A FDH-coupled assay was used to determine the inhibitory activity of the compounds (Lazennec and Meinnel 1997). The formate generated by PDF from its substrate N-formyl-Met-Ala-Ser is oxidized by the enzyme FDH, reducing NAD+ to NADH, which causes specific absorption at 340 nm (
M = 6300 M1cm1). All assays were conducted at 37°C in a 96-well plate system (Tecan GENios reader) by measuring the increase in absorbance at 340 nm. The reaction mixture contained 50 mM HEPES (pH 7.5), 10 mM NaCl, 0.2 mg/mL BSA (Roche), 8 mM NAD+ (Roche), 0.5 U/mL FDH (Fluka), and 2 mM N-formyl-Met-Ala-Ser (Sangon). To determine IC50 (the concentration needed to inhibit 50% of enzyme activity) of a compound, PDF activity was measured in the presence of increasing concentrations of the compound in the presence of an f-MAS concentration corresponding to Km value (Han et al. 2004). Compounds were added to assay mixtures from concentrated stocks dissolved in dimethyl sulfoxide (Me2SO). The final Me2SO concentration in all assays was 0.1% (v/v). IC50 value was obtained by fitting the data to a sigmoid dose-response equation using the Origin software (OriginLab). The reaction was initiated by the addition of the diluted HpPDF (or EcPDF) enzyme.
Recombinant HpDC was expressed and purified in E. coli system. A double-enzyme coupled assay was used to determine the inhibitory effect of compounds 1 and 2 (Scriven et al. 1988; Ray et al. 2002). In this assay, HpDC activity was estimated by monitoring the decrease of specific absorption at 340 nm caused by NADH. The degassed assay buffer contained 100 mM Tris (pH 8.0), 10 mM MgCl2, 2 mM phosphoenolpyruvate (Fluka), 2 mM 2,6-diaminopimelic acid (Fluka), 0.7 mM NADH (Fluka), 0.2 U/mL phosphoenolpyruvate carboxylase, and 1.25 U/mL malate dehydrogenase. Compounds dissolved in Me2SO were added to assay mixtures. The final Me2SO concentration in all assays was 0.1% (v/v). All assays were conducted at 37°C in a 96-well plate system. The reaction was initiated by the addition of the diluted HpDC enzyme.
Crystallization and X-ray structure determination
The purified HpPDF protein was prepared in buffer A (10 mM Tris-HCl at pH 8.0, 0.1 M NaCl, 1 mM DTT). Prior to crystallization, the protein was concentrated to 2030 mg/mL and stored at 4°C. Initial screening was performed at 4°C by the hanging-drop vapor-diffusion method. Drops were prepared by mixing 1 µL of protein solution with 1 µL of reservoir solution, and were equilibrated against 500 µL of reservoir solution. The conditions yielding small crystals were further optimized by variation of the buffer pH and precipitant concentration. The best crystals were grown at a reservoir solution of 60%70% MPD in 0.1 M HEPES (pH 7.8). The crystals of HpPDF in complex with compounds 1 and 2 were obtained by soaking method.
All diffraction data were collected in-house on a Rigaku rotating-anode X-ray generator operated at 50 kV and 100 mA (
= 1.5418 Å). Diffraction images were recorded by a Rigaku R-AXIS IV++ imaging-plate detector with an oscillation step of 1°. The crystal-to-detector distance was set to 15 cm. The crystals were picked up with a nylon loop and flash-cooled in liquid nitrogen. Data collection was performed at 100 K using the original reservoir solution as cryoprotectant. All data were processed and scaled using the CrystalClear program (Pflugrath 1999).
The structures of both apo-enzyme and the inhibitor-enzyme complexes were solved by molecular replacement method using the program CNS (Brunger et al. 1998), taking the X-ray crystal structure of P. aeruginosa PDF (PDB code 1IX1; Yoon et al. 2004) as the initial model. Refinement was performed by using CNS, and the atomic models were built by using the computer graphics program O (Jones et al. 1991). The Ramachandran statistics of the final models were listed in Table 2. The resolved structures of both apo-enzyme and the inhibitor-enzyme complexes have been deposited in the PDB database (codes 2EW5, 2EW6, and 2EW7).
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| Electronic supplemental material |
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| Footnotes |
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Supplemental material: see www.proteinscience.org
Reprint requests to: Xu Shen, Hualiang Jiang, or Jianmin Yue, Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Graduate School of Chinese Academy of Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 201203, China; e-mail: xshen{at}mail.shcnc.ac.cn, hljiang{at}mail.shcnc.ac.cn, or jmyue{at}mail.shcnc.ac.cn; fax: 86-21-50807088.
Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi/doi/10.1110/ps.062238406.
Abbreviations: MIC, minimal inhibitory concentration; PDF, peptide deformylase; PDTD, potential drug target database; DC, diaminopimelate decarboxylase; FDH, formate dehydrogenase.
| Acknowledgments |
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