Article pubs.acs.org/JAFC
Binding Difference of Fipronil with GABAARs in Fruitfly and Zebrafish: Insights from Homology Modeling, Docking, and Molecular Dynamics Simulation Studies Nan Zheng,† Jiagao Cheng,*,†,‡ Wei Zhang,† Weihua Li,‡ Xusheng Shao,† Zhiping Xu,† Xiaoyong Xu,† and Zhong Li*,†,§ †
Shanghai Key Laboratory of Chemical Biology and ‡Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China § Shanghai Collaborative Innovation Center for Biomanufacturing Technology, 130 Meilong Road, Shanghai 200237, China S Supporting Information *
ABSTRACT: Fipronil, which targets GABAA receptors (GABAARs), is the first phenylpyrazole insecticide widely used in crop protection and public hygiene. However, its high toxicity on fishes greatly limited its applications. In the present study, a series of computational methods including homology modeling, docking, and molecular dynamics simulation studies were integrated to explore the binding difference of fipronil with GABAARs from fruitfly and zebrafish systems. It was found that, in the zebrafish system, the H-bond between 6′Thr and fipronil exerted key effects on the recognition of fipronil, which was absent in the fruitfly system. On the other hand, in the fruitfly system, strong electrostatic interaction between 2′Ala and fipronil was favorable to the binding of fipronil but detrimental to the binding in the zebrafish system. These findings marked the binding difference of fipronil with different GABAARs, which might be helpful in designing selective insecticides against pests instead of fishes. KEYWORDS: fipronil, GABAA receptors, homology modeling, docking, molecular dynamics simulation
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mutation in the Rdl subunit on the cross-resistance of fipronil in houseflies. Ffrench-Constant et al.10,13−15 also investigated the relationship between the cross-resistance of many commercial NCAs and the different mutations of A2′ in the Rdl subunit of D. melanogaster. Moreover, many modeling studies were performed to explore the binding mode of fipronil with GABAAR. However, the detailed binding modes of fipronil were still controversial. Cheng et al.16 found that the trifluoromethyl group of the benzene ring pointed to the intracellular domain, whereas Ci et al.17 reported that the trifluoromethyl group showed an opposite orientation. Also, Casida et al.18 observed that the same trifluoromethyl group faced the extracellular domain and considered that fipronil might have multiple interaction types. This indicated that the binding mode of fipronil with GABAAR still needed further illustration. On the other hand, fipronil showed high toxicity on fishes, which deeply limited its applications.19 It was generally considered that fipronil had potent interaction with both insect and fish GABAARs, which resulted in high toxicities against pests and fishes. Better understanding of the binding mode of fipronil with insect GABAARs versus fish GABAARs might be helpful in designing selective insecticides with low fish toxicity. There is a need to further investigate how fipronil elicited high insecticidal activities against pests and potent toxicities to fishes. Computational simulations are very important methods and
INTRODUCTION Fipronil is the first phenylpyrazole insecticide that has been successfully used in crop protection and public hygiene. It showed high insecticidal activity and low mammalian toxicity, which made it superior to other traditional insecticides.1,2 The target of fipronil is γ-aminobutyric acid type A receptors (GABAARs), a chloride channel that belongs to the ligand gated ion channel (LGIC) superfamily, including nicotinic acetylcholine receptors (nAChRs), glycine receptors (GlyRs), serotonin type 3 receptors (5-HT3R), and glutamate-gated chloride channels (GluCl).3 Fipronil bound to the TM2 domain of the channel,4 blocked the normal passage of chloride ions, and then disturbed the normal function of the central nervous system (CNS), leading to convulsions and death of insects. GABAAR comprises five subunits, which coassemble to form a homopentamer or heteropentamer. To date, researchers have cloned eight classes of subunits with multiple isoformers (α1-6, β1-3, γ1-3, ρ1-3, δ, ε, θ, and π) in vertebrates,5 of which the β3 subunit could form a homopentamer and showed higher noncompetitive antagonists (NCAs) sensitivity than other subunits.6 Each subunit contains three main domains: an extracellular domain containing the N- and C-terminals, a transmembrane domain (TMD) that is highly conserved in many species,7 and an intracellular domain. The ion channel pore is enclosed by TM2 helices from the five subunits, which determines the functional properties of GABAAR.8,9 In the case of insect GABAARs, the best studied one was the Rdl (resistant to dieldrin) type, which was first cloned from Drosophila melanogaster.10 It served as a good model of insect GABAARs11 and has been fully used in many toxicology studies of fipronil. For example, Scott et al.12 studied the roles of A2′S © XXXX American Chemical Society
Received: August 9, 2014 Revised: October 9, 2014 Accepted: October 10, 2014
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Figure 1. (a) Homology model of GABAAR: side view (left), top view (right). (b) Index number (above) for the residues (bottom) of TM2 regions. (c) Reported key residues and different residues within the TM2 regions of fruitfly (blue) and zebrafish (red) GABAARs. Ligand Docking. Ligand docking was performed by the Glide approach integrated into Maestro 9.3 (Schrödinger, LLC, 2013), with default settings in standard precision mode. The binding site was set around the centroid of the −2′ and 2′ residues from five chains, with a size of 30 Å. In the docking run, 100 conformations were output and ranked by GlideScore. The superior pose with a reasonable binding orientation was selected as the initial binding conformation for further molecular dynamics (MD) simulation. Molecular Dynamics Simulation. The obtained docking results of the fipronil−GABAAR complex were conducted for MD simulation using the GROMACS 4.5.530−32 package with the GROMOS53a633 force field for all atoms. The topology and other force field parameters for fipronil were obtained using the PRODRG beta server (http:// davapc1.bioch.dundee.ac.uk/prodrg/).34 The ESP partial atom charges were calculated at the B3LYP/6-31G(d,p) level using the Gaussian 09 package (Gaussian, Inc., Wallingford CT, USA; 2009) and determined using the Merz−Singh−Kollman scheme.35,36 On the basis of the calculated electrostatic potential, the restrained electrostatic potential (RESP) charges were produced using the Antechamber module37 of the Amber10 package. The fipronil−GABAAR complex structures were inserted into a pre-equilibrated 1-palmitoyl-2-oleylphosphatidylcholine (POPC) lipid bilayer using the “shrinking” method, where the shrinking cycles were performed with the InflateGRO script.38 The bilayer structure used here was downloaded from Tieleman’s Web site (http://moose.bio.ucalgary.ca/). The cubic periodic box comprising the simple point charge (SPC) water39 model was built. The Cl− ions were inserted randomly into the solvent to preserve the electric neutrality in both systems. The two systems were performed under the NPT ensemble, using the Nosé−Hoover thermostat40,41 and Parrinello−Rahman barostat42 to maintain the pressure at 1.02 bar, with the temperature maintained at 300 K. All bonds were constrained using the LINCS algorithm.43 In the MD simulation, the cutoff distance was set to 1.2 nm for LennardJones interactions. The long-range electrostatic interactions were handled using the particle-mesh Ewald (PME) method.44,45 The time step of the simulation was set to 2 fs. Finally, the fruitfly and zebrafish GABAAR systems in the fipronil-bound state have 1695 and 1680 residues, 71635 and 71932 water molecules, 25 and 5 Cl− ions, and 502 POPC molecules, and the densities of the POPC lipid bilayers were 66.6 and 66.8 Å2, respectively.
have exerted profound influences on the molecular design and interaction mechanism investigations of pesticides.20−23 In the present study, the 3D structures of homopentamer of GABAARs in representative insect (fruitfly Rdl) and fish (zebrafish β3) were established by the homology modeling method based on the open-state structure of an inhibitory glutamate-gated chloride channel24 from Caenorhabditis elegans. The GluCl24 showed high sequence similarity and was a good template for modeling the structures of the GABAARs, which was better than the nAChR and AChBP (acetylcholine binding protein) structures used in previous studies.16−18 Finally, docking and molecular dynamics (MD) simulation studies were performed to explore the binding difference of fipronil with fruitfly Rdl and zebrafish β3 GABAARs.
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MATERIALS AND METHODS
Homology Modeling. The target sequences of fruitfly Rdl (UniProt ID P25123) and zebrafish β3 (UniProt ID E7EXG0) subunits were retrieved from UniProtKB (http://www.uniprot.org/). The sequences were subjected to template search using the BLAST program of the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/). Finally, the crystal structure of glutamate-gated chloride channel24 (PDB ID 3RHW) was chosen as the template to build the 3D structures of both GABAARs. As no intracellular portion of the Cys-loop receptor superfamily was resolved, the sequences of the long cytoplasmic loops of the intracellular domain were removed during homology modeling study. The ClustalW2 program25−27 was used for sequence alignment. The identities of two GABAARs of fruitfly and zebrafish with the same template were 40.6 and 37.6%, respectively. On the basis of the aligned sequences (Supporting InformationFigure S1), in which the blue squares stand for the conserved residues of extracellular loop A-F and the Cys-loop, the channel pore of GABAAR formed by the TM2 helices is magenta squares, and the rest of the TM helices are purple squares, the Build Homology Models Module encoded in the Discovery Studio 3.5 software package (Accelrys Inc., 2013) was applied to generate the GABAAR structures of fruitfly and zebrafish species. The quality of the established 3D structures was not only assessed by the PROCHECK28 and the Profile-3D29 approaches but also validated by the comparison between following docking investigations and the previous experimental mutation results within the TM2 domain. B
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RESULTS AND DISCUSSION
Homology Models of GABAARs. The modeled structure of GABAAR is depicted in Figure 1a, of which the β-sheets of extracellular region are shown in magenta and the α-helices are in cyan. The channel pore of GABAAR was surrounded by five TM2 helices. The number for the residues of the TM2 region was indexed and is shown in Figure 1b for a convenient comparison between the two species. The interior residues in the TM2 channel of the GABAAR from fruitfly and zebrafish were −2′Pro (Ala), 2′Ala, 5′Val (Ile), 6′Thr, 9′Leu, and 20′Ala (Glu), which are shown as sticks in Figure 1c. Only three residues were different between the GABAARs of fruitfly and zebrafish, denoted −2′, 5′, and 20′, of which the 20′ residue was close to the extracellular region, the −2′ residue was near the intracellular domain, and 5′ was located in the lower part of the TM2 domain. The quality of both modeled structures was evaluated by using the PROCHECK28 and Profile-3D29 approaches. In the fruitfly model, 99.3% residues were located in the allowed regions, and only 0.7% residues (Thr104 and Ser172 in the extracellular region) were located in the disallowed regions (Supporting Information Figure S2a). In the zebrafish model, 99.7% residues were observed in the allowed regions, whereas only 0.3% residues (Thr101 in the extracellular domain) were found in the disallowed regions (Supporting Information Figure S2b). The self-compatibility score by Profile-3D for the GABAAR structure of fruitfly was 543.87, which was close to the top score of 782.05. The corresponding score of the zebrafish GABAAR structure reached 546.56, which was also close to the top value of 775.07. Moreover, it could be seen that most residues were reasonable with positive score values; only a few residues far from the fipronil binding site, which located in the extracellular and TM3 regions, showed small negative profile-3D values (Supporting Information Figure S2c,d). The above results indicated that the homology models of fruitfly and zebrafish were reliable. Docking Results. Docking studies were performed to explore the binding modes of fipronil with GABAAR. The final docking pose was obtained by considering the GlideScore values and analyzing the binding mode, which is depicted in Figure 2. This showed that fipronil erected in both channels enclosed by the five TM2 helices, with the trifluoromethyl group of the benzene ring facing the intracellular domain, which was consistent with the previous modeling study by Cheng et al.16 Also, the residues 2′Ala, 6′Thr, and 9′Leu were found to play important roles for the binding of fipronil (Supporting Information Figure S3), which was in accordance with the previously published investigations.10−18,46−51 For example, Casida et al.18 showed that the mutation of A2′C or A2′S and T6′C or T6′F, as well as L9′C or L9′S, in the human β3 homopentamer could abolish the binding sensitivity of NCAs. The N−H···O H-bond between the amino group of fipronil and the side chain of 6′Thr was observed in both systems, which has been reported to be very important for binding by other researchers.16−18 Moreover, it was found that the residues −2′Pro (Ala) and 5′Val (Ile) could also form interactions with fipronil (Supporting Information Figure S3). According to the docking results, both GABAARs showed favorable interactions with fipronil. All above docking analyses also confirmed that the modeled 3D structures of GABAARs were reasonable.
Figure 2. Docking poses of fipronil with fruitfly (a) and zebrafish (b) GABAARs. Dotted line, H-bond; stick, fipronil and the key residues.
Molecular Dynamics Simulation. Root Mean Square Deviation (RMSD). To evaluate the stability of the two systems during the MD simulation, the RMSD was plotted versus time. Figure 3 depicts the RMSD values for the backbone atoms of
Figure 3. RMSD plots for the backbone of GABAARs and fipronil during MD simulation.
protein and ligand. The RMSD values for the backbone of fruitfly and zebrafish systems are colored in black and red, respectively; the two systems were stable after 16 ns simulations. However, during the last 14 ns of the simulations, the amplitude of the equilibrium deviation was slightly different in each trajectory. The RMSD values of the fruitfly system showed that the disruption of convergence was at about 0.46 nm, whereas the corresponding value was 0.43 nm for the zebrafish system. Meanwhile, the RMSD values of ligand atoms were also calculated and are depicted in Figure 3. The data indicated that the fipronil in both systems reached equilibrium states after a small fluctuation in the initial period of the simulation. The magnitude of fluctuations for ligand, together with the backbone of protein, led to the conclusion that the C
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Figure 4. Pore diameter analysis at 0 and 30 ns snapshots of fruitfly (a, b) and zebrafish (c, d) systems: distance along the pore axis (Å) versus pore diameter. The key residues in the binding pocket from TM2 helices are shown as sticks.
−2′Pro (Ala) for both systems, where the side chain of 9′Leu defined the narrowest point in the middle of the two channels, whereas −2′Pro in the fruitfly system or −2′Ala in the zebrafish system determined the lowest narrow part of the channels. After a 30 ns simulation, the pore radius at 9′Leu that represented the top side of the binding pocket expanded for both systems, as well as the −2′Pro (Ala) that denoted the bottom of binding site. In the zebrafish system, no clear changes were found for the tunnel radius between 5′Ile and 2′Ala after simulation, whereas in the fruitfly system the corresponding radius between 5′Val and 2′Ala enlarged. It was also observed that the pore size between the 5′ and 2′ residues within the binding pocket of fruitfly system was wider than that in the zebrafish system, which might be a result of the smaller volume of 5′Val than of 5′Ile. Moreover, in the fruitfly system the pore radius defined by the 6′Thr narrowed, whereas in the zebrafish system the corresponding tunnel radius widened. The above differences in the binding pockets of the two systems might exert some influences on the binding modes of fipronil with the GABAARs from the two species. Position and Orientation Changes of Fipronil during Simulation. Figure 5a and b show the superposition for fipronil
simulation produced stable trajectories and provided a reliable basis for further analysis. Root Mean Square Fluctuation (RMSF). With the aim of determining the mobility and flexibility of each residue in the MD simulation, the RMSF values were calculated. The RMSF values for the residues of TM domains were small, indicating that they were stable during the entire simulation (Supporting Information Figure S4a), whereas larger values were observed in the extracellular domain and the loops between TM3 and TM4, which implied that residues in these regions were flexible in the MD simulation. The fluctuating residues were observed far from the ligand binding site and might have weak influences on the interaction of fipronil with GABAAR. For detailed analysis, the RMSF for the residues in ligand binding pocket within the TM2 domains is also depicted in Supporting Information Figure S4b. Clearly, the fruitfly system showed higher peaks around the fipronil binding pocket, compared with the zebrafish system, which indicated that such residues from the fruitfly system might undergo larger fluctuation than those from the zebrafish system. The smaller RMSF values in the zebrafish system also coincided with the above RMSD values. Pore Radius. Ion channel radius is an important parameter to characterize the channel opening and closing, which has been widely used to measure the size of a channel pore. In the present study, the pore radius of the GABAAR was conducted using the HOLE program.52−54 The pore radii at the 0, 5, 10, 20, and 30 ns snapshots, as well as on the average structure of the last 5 ns in the equilibrium state, have been calculated and analyzed (Supporting Information Figure S5). It could be observed that the pore radius variations were very similar at the 20 and 30 ns snapshots and on the average structure of the last 5 ns, especially in the region between the −2′Pro (Ala) and 9′Leu residues of the TM2 domain. The calculated pore diameters at 0 and 30 ns snapshots were analyzed and are depicted in Figure 4 to understand the changes of pore size after MD simulation. The ion pores of both GABAARs tilted radially from the extracellular domains down to the TM2 domain. The binding site of fipronil was located in the region between 9′Leu and
Figure 5. Alignment of the TM2 domain in the fruitfly (blue) and zebrafish (red) systems at 0 (a) and 30 ns (b). Cyan and green sticks represent the fipronil in fruitfly and zebrafish systems, respectively. Superimposition of the fipronil in fruitfly (c) and zebrafish (d) systems is shown as 0 ns (cyan), 10 ns (green), 20 ns (yellow), and 30 ns (orange) snapshots. D
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Figure 6. Interactions of fipronil with fruitfly (a) and zebrafish (b) GABAARs at 30 ns snapshot after MD simulation: hydrophobic interactions between fipronil and the residues in fruitfly (c) and zebrafish (d) systems at the 30 ns snapshot.
with GABAARs in fruitfly and zebrafish systems, the key residues for the binding of fipronil were fully analyzed on the structures at the equilibrium state. Panels a and b of Figure 6 depict the interaction between fipronil and the residues in the TM2 channel of GABAAR at the 30 ns snapshots. The potential key residues displayed in sticks could also be observed in the 0, 5, 10, and 20 ns snapshots and in the average structure of the equilibrium state. It was found that residues 2′Ala, 6′Thr, and 9′Leu formed hydrophobic interactions with fipronil (Figure 6c,d), which were important for the binding of fipronil with both GABAARs. The findings were in accordance with the previous modeling studies.17,18 For example, Casida et al.18 reported that 2′Ala, 6′Thr, and 9′Leu could form hydrophobic interactions with diverse antagonists, which had a critical influence on the recognition of NCAs. Moreover, in this study, the residue 5′Val (Ile) was observed forming hydrophobic interactions with fipronil in both. Many researchers have reported that 6′Thr could form an Hbond with fipronil, which played key roles for the ligand− receptor recognition.16−18 In the zebrafish system, an N−H···O H-bond was observed between the amino group of fipronil and the side chain of 6′Thr (Figure 7a). The distance between the
and TM2 helices in the fruitfly and zebrafish systems at the snapshots of 0 and 30 ns of the simulation, respectively. Small position changes of fipronil were observed in the zebrafish system during the entire MD simulation, whereas the position of fipronil in the fruitfly system moved toward the lower part of the TM2 channel, as compared with its initial binding site. In other words, the binding site of fipronil in the fruitfly system was much closer to the intracellular domain than in the zebrafish system (Figure 5b). Figure 5c and d display the superposition of fipronil in the snapshots at 0, 10, 20, and 30 ns in the MD trajectory from the fruitfly and zebrafish systems, respectively. It can be observed that fipronil went through large orientation changes in the fruitfly system relative to the zebrafish system. This might be a result of the different pore radius properties between the two systems. A wider tunnel dimension between 5′Thr and 2′Ala appeared in the binding pocket of the fruitfly system than in the zebrafish system, which might be an important reason for the observed larger position and orientation changes in the fruitfly system. Binding Difference of Fipronil with Fruitfly and Zebrafish GABAARs. To better understand the binding modes of fipronil E
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Figure 7. (a) N−H···O H-bond between fipronil and 6′Thr in zebrafish system; (b) N−H···O H-bond distance during the whole MD simulation.
monitored during the MD simulation of the fruitfly system, the strong electrostatic interaction between 2′Ala and fipronil might compensate the binding force of fipronil with GABAAR. Although 2′Ala and 6′Thr in the two systems, respectively, showed different roles in the recognition of fipronil, the favorable interactions enabled fipronil to erect steadily in both channels, which might contribute to the high toxicities to insects and fishes. All of the data above indicated that residues 5′Val (Ile), 6′Thr, and 9′Leu played important roles in the binding of fipronil with both GABAARs. Moreover, the H-bond between 6′Thr and fipronil in the zebrafish system was very stable during the whole MD simulations, which played a key role in the ligand−receptor recognition. However, such an H-bond was absent in the fruitfly system during simulation, although it could be observed in the docking results and the initial snapshot of the simulation. On the other hand, the electrostatic interaction between 2′Ala and fipronil was favorable to ligand recognition in the fruitfly system, but was detrimental to the binding in the zebrafish system. As a result, the observed strong electrostatic interaction between 2′Ala and fipronil compensated the absent contribution of the H-bond between 6′Thr and fipronil in the fruitfly system. The different roles of 2′Ala and 6′Thr marked the binding difference of fipronil with the GABAARs of fruitfly and zebrafish, which might provide some clues for future design of new selective phenylpyrazole pesticides against insects over fishes.
N and O atoms versus the simulation time was monitored during the whole simulation (Figure 7b). It was found that the N−H···O H-bond was very stable, with an H-bond distance around 3.0 Å in the whole simulation. In the fruitfly system, the corresponding H-bond could be observed in the docking results and the initial snapshot of the simulation. However, it disappeared during the subsequent simulation. The detailed reasons for the disappearance of the N−H···O H-bond are still unclear. One of the reasons might be the above-mentioned large position and orientation changes of fipronil in the fruitfly system. To gain detailed energy contributions of the key residues in the TM2 helices on the binding affinity of fipronil, a per-residue decomposition of the total energy was performed to evaluate the critical residues on the binding, using the Calculate Interaction Energy Protocol encoded in the Discovery Studio 3.5 software package (Accelrys Inc., 2013). The snapshots of two systems in the last 5 ns of MD simulation were extracted, respectively, for energy analysis. The residue-based energy decomposition results characterized the key residues in ligand binding and identified the contributions of different nonbonded interaction forces (van der Waals and electrostatic interactions). The energy contributions of each key residue are displayed in Table 1. They showed that 5′Val (Ile), 6′Thr, and 9′Leu were Table 1. Average Energy of Interaction between Individual Residues and Ligands for the Fruitfly and Zebrafish Systems residue
fruitfly
zebrafish
2′Ala electrostatic 5′Val(Ile) electrostatic 6′Thr electrostatic 9′Leu electrostatic
−1.05 −1.15 −1.19 −1.14 −0.82 −0.66 −0.67 −0.69
1.01 1.03 −1.54 −1.67 −1.94 −1.12 −1.23 −1.12
term term term term
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ASSOCIATED CONTENT
S Supporting Information *
Figures S1−S5. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Authors
*(J.C.) E-mail: [email protected]. Phone: +86-2164251348. Fax: +86-21-64252603. *(Z.L.) E-mail: [email protected].
favorable for the binding of fipronil with both GABAARs. Moreover, the average interaction energy between residue 2′Ala and fipronil, which was originated predominantly by the electrostatic interaction, was beneficial for complexation in the fruitfly system but unfavorable to binding in the zebrafish system. All of the data in Table 1 and Figures 6 and 7 indicated that residues 5′Val (Ile), 6′Thr, and 9′Leu played important roles for the binding of fipronil with both GABAARs. Although the N−H···O H-bond between fipronil and 6′Thr could not be
Funding
This work was financially supported by the National Key Technology R&D Program of China (2011BAE06B05), the National Natural Science Foundation of China (21172070), the National High Technology Research Development Program of China (2011AA10A207), and the Fundamental Research Funds for the Central Universities (222201314006) F
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Notes
cyclodiene insecticide resistance in Drosophila populations. Proc. Natl. Acad. Sci. U.S.A. 1993, 90, 1957−1961. (15) Ffrench-Constant, R. H.; Anthony, N.; Aronstein, K.; Rocheleau, T.; Stilwell, G. Cyclodiene insecticide resistance: from molecular to population genetics. Annu. Rev. Entomol. 2000, 48, 449− 466. (16) Cheng, J.; Ju, X. L.; Chen, X. Y.; Liu, G. Y. Homology modeling of human α1β2γ2 and house fly β3 GABA receptor channels and Surflex-docking of fipronil. J. Mol. Model. 2009, 15, 1145−1153. (17) Ci, S. Q.; Ren, T. R.; Su, Z. G. Modeling the interaction of fipronil-related non-competitive antagonists with the GABA β3receptor. J. Mol. Model. 2007, 13, 457−464. (18) Chen, L.; Durkin, K. A.; Casida, J. E. Structural model for γaminobutyric acid receptor noncompetitive antagonist binding: widely diverse structures fit the same site. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 5185−5190. (19) Wang, X. X.; Zhou, S. L.; Ding, X. F.; Zhu, G. N. Effect of triazophos, fipronil and their mixture on miRNA expression in adult zebrafish. J. Environ. Sci. Health. Part B 2010, 45, 648−657. (20) Hao, G. F.; Wang, F.; Li, H.; Zhu, X. L.; Yang, W. C.; Huang, L. S.; Wu, J. W.; Berry, E. A.; Yang, G. F. Computational discovery of picomolar Q0 site inhibitors of cytochrome bc1 complex. J. Am. Chem. Soc. 2012, 134, 11168−11176. (21) Zhao, P. L.; Wang, L.; Zhu, X. L.; Huang, X. Q.; Zhan, C. G.; Wu, J. W.; Yang, G. F. Subnanomolar inhibitor of cytochrome bc1 complex designed by optimizing interaction with conformationally flexible residues. J. Am. Chem. Soc. 2010, 132, 185−194. (22) Hao, G. F.; Yang, G. F. The role of Phe82 and Phe351 in auxininduced substrate perception by TIR1 ubiquitin ligase: a novel insight from molecular dynamics simulations. PLoS One 2010, 5, No. e10742. (23) Hao, G. F.; Yang, S. G.; Yang, G. F.; Zhan, C. G. Computational gibberellin-binding channel discovery unraveling the unexpected perception mechanism of hormone signal by gibberellin receptor. J. Comput. Chem. 2013, 34, 2055−2064. (24) Hibbs, R. E.; Gouaux, E. Principles of activation and permeation in an anion-selective Cys-loop receptor. Nature 2011, 474, 54−60. (25) Thompson, J. D.; Higgins, D. G.; Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22, 4673−4680. (26) Chenna, R.; Sugawara, H.; Koike, T.; Lopez, R.; Gibson, T. J.; Higgins, D. G.; Thompson, J. D. Multiple sequence alignment with the Clustal series of programs. Nucleic Acids Res. 2003, 31, 3497−3500. (27) Larkin, M. A.; Blackshields, G.; Brown, N. P.; Chenna, R.; McGettigan, P. A.; McWilliam, H.; Valentin, F.; Wallace, I. M.; Wilm, A.; Lopez, R.; Thompson, J. D.; Gibson, T. J.; Higgins, D. G. Clustal W and Clustal X, version 2.0. Bioinformatics 2007, 23, 2947−2948. (28) Laskowski, R. A.; MacArthur, M. W.; Moss, D. S.; Thornton, J. M. PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Crystallogr. 1993, 26, 283−291. (29) Lüthy, R.; Bowie, J. U.; Eisenberg, D. Assessment of protein models with three-dimensional profiles. Nature 1992, 356, 83−85. (30) Berendsen, H. J. C.; Van Der Spoel, D.; Van Drunen, R. GROMACS: a message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 1995, 91, 43−56. (31) Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. GROMACS: fast, flexible, and free. J. Comput. Chem. 2005, 26, 1701−1718. (32) Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theor. Comput. 2008, 4, 435−447. (33) Oostenbrink, C.; Villa, A.; Mark, A. E.; Van Gunsteren, W. F. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J. Comput. Chem. 2004, 25, 1656−1676. (34) Schuttelkopf, A. W.; van Aalten, D. M. F. PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr. 2004, 60, 1355−1363.
The authors declare no competing financial interest.
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ABBREVIATIONS USED GABAARs, γ-aminobutyric acid type A receptors; LGIC, ligand gated ion channel; nAChRs, nicotinic acetylcholine receptors; GlyRs, glycine receptors; 5-HT3R, serotonin type 3 receptors; GluCl, glutamate-gated chloride channels; CNS, central nervous system; NCAs, noncompetitive antagonists; TMD, transmembrane domain; Rdl, resistant to dieldrin; AChBP, acetylcholine binding protein; MD, molecular dynamics; NCBI, National Center for Biotechnology Information; RESP, restrained electrostatic potential; POPC, 1-palmitoyl-2-oleylphosphatidylcholine; SPC, simple point charge; PME, particle-mesh Ewald; RMSD, root-mean-square deviation; RMSF, root-meansquare fluctuation
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REFERENCES
(1) Cole, L. M.; Nicholson, R. A.; Casida, J. E. Action of phenylpyrazole insecticides at the GABA gated chloride channel. Pestic. Biochem. Physiol. 1993, 46, 47−54. (2) Tingle, C. C. D.; Rother, J. A.; Dewhurst, C. F.; Lauer, S.; King, W. J. Fipronil: environmental fate, ecotoxicology, and human health concerns. Rev. Environ. Contam. Toxicol. 2003, 176, 1−66. (3) Novère, N. L.; Changeux, J. P. The Ligand Gated Ion Channel database: an example of a sequence database in neuroscience. Philos. Trans. R. Soc. London B 2001, 356, 1121−1130. (4) Perret, P.; Sarda, X.; Wolff, M.; Wu, T. T.; Bushey, D.; Goeldner, M. Interaction of non-competitive blockers within the γ-aminobutyric acid type A chloride channel using chemically reactive probes as chemical sensors for cysteine mutants. J. Biol. Chem. 1999, 274, 25350−25354. (5) Simon, J.; Wakimoto, H.; Fujita, N.; Lalande, M.; Barnard, E. A. Analysis of the set of GABAA receptor genes in the human genome. J. Biol. Chem. 2004, 279, 41422−41435. (6) Ratra, G. S.; Kamita, S. G.; Casida, J. E. Role of human GABAA receptor β3 subunit in insecticide toxicity. Toxicol. Appl. Pharmacol. 2001, 172, 233−240. (7) Olsen, R. W.; Tobin, A. J. Molecular biology of GABAA receptors. FASEB J. 1990, 4, 1469−1480. (8) Xu, M.; Akabas, M. H. Identification of channel-lining residues in the M2 membrane-spanning segment of the GABAA receptor α1 subunit. J. Gen. Physiol. 1996, 107, 195−205. (9) Horenstein, J.; Wagner, D. A.; Czajkowski, C.; Akabas, M. H. Protein mobility and GABA-induced conformational changes in GABAA receptor pore-lining M2 segment. Nat. Neurosci. 2001, 4, 477−485. (10) Ffrench-Constant, R. H.; Mortlock, D. P.; Shaffer, C. D.; MacIntyre, R. J.; Roush, R. T. Molecular cloning and transformation of cyclodiene resistance in Drosophila: an invertebrate γ-aminobutyric acid subtype A receptor locus. Proc. Natl. Acad. Sci. U.S.A. 1991, 88, 7209−7213. (11) Hosie, A. M.; Aronstein, K.; Sattelle, D. B.; Ffrench-Constant, R. H. Molecular biology of insect neuronal GABA receptors. Trends Neurosci. 1997, 20, 578−583. (12) Gao, J. R.; Kozaki, T.; Leichter, C. A.; Rinkevich, F. D.; Shono, T.; Scott, J. G. The A302S mutation in Rdl that confers resistance to cyclodienes and limited crossresistance to fipronil is undetectable in field populations of house flies from the USA. Pestic. Biochem. Physiol. 2007, 88, 66−70. (13) Ffrench-Constant, R. H.; Rocheleau, T. A.; Steichen, J. C.; Chalmers, A. E. A point mutation in a Drosophila GABA receptor confers insecticide resistance. Nature 1993, 363, 449−451. (14) Ffrench-Constant, R. H.; Steichen, J. C.; Rocheleau, T. A.; Aronstein, K.; Roush, R. T. A single-amino acid substitution in a γaminobutyric acid subtype A receptor locus is associated with G
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(35) Singh, U. C.; Kollman, P. A. An approach to computing electrostatic charges for moleculars. J. Comput. Chem. 1984, 5, 129− 145. (36) Besler, B. H.; Merz, K. M.; Kollman, P. A. Atomic charges derived from semiempirical methods. J. Comput. Chem. 1990, 11, 431− 439. (37) Wang, J. M.; Wang, W.; Kollman, P. A.; Case, D. A. Antechamber: an accessory software package for molecular mechanical calculations. J. Comput. Chem. 2005, 25, 1157−1174. (38) Kandt, C.; Ash, W. L.; Tieleman, D. P. Setting up and running molecular dynamics simulations of membrane proteins. Methods 2007, 41, 475−488. (39) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; Hermans, J. Interaction models for water in relation to protein hydration. Intermolecular Forces; Pullman, B., Ed.; Reidel: Dordrecht, The Netherlands, 1981; pp 331−342. (40) Nosé, S. A molecular dynamics method for simulations in the canonical ensemble. Mol. Phys. 1984, 52, 255−268. (41) Hoover, W. G. Canonical dynamics: equilibrium phase-space distributions. Phys. Rev. A 1985, 31, 1695−1697. (42) Parrinello, M.; Rahman, A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 1981, 52, 7182−7190. (43) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18, 1463−1472. (44) Darden, T.; York, D.; Pedersen, L. Particle mesh Ewald: an N. log(N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98, 10089−10092. (45) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995, 103, 8577−8593. (46) Hosie, A. M.; Baylis, H. A.; Buckingham, S. D.; Sattelle, D. B. Actions of the insecticide fipronil, on dieldrin-sensitive and -resistant GABA receptors of Drosophila melanogaster. Br. J. Pharmacol. 1995, 115, 909−912. (47) Charon, S.; Taly, A.; Rodrigo, J.; Perret, P.; Goeldner, M. Binding modes of noncompetitive GABA-channel blockers revisited using engineered affinity-labeling reactions combined with new docking studies. J. Agric. Food Chem. 2011, 59, 2803−2807. (48) Goff, G. L.; Hamon, A.; Bergé, J. B.; Amichot, M. Resistance to fipronil in Drosophila simulans: influence of two point mutations in the RDL GABA receptor subunit. J. Neurochem. 2005, 92, 1295−1305. (49) Nakao, T.; Naoi, A.; Kawahara, N.; Hirase, K. Mutation of the GABA receptor associated with fipronil resistance in the whitebacked planthopper Sogatella f urcifera. Pestic. Biochem. Physiol. 2010, 97, 262− 266. (50) Casida, J. E.; Tomizawa, M. Insecticide interactions with γaminobutyric acid and nicotinic receptors: predictive aspects of structural models. J. Pestic. Sci. 2008, 33, 4−8. (51) Hisano, K.; Ozoe, F.; Huang, J.; Kong, X.; Ozoe, Y. The channel-lining 6′ amino acid in the second membrane-spanning region of ionotropic GABA receptors has more profound effects on 4′ethynyl-4-n-propylbicyclo-orthobenzoate binding than the 2′ amino acid. Invert. Neurosci. 2007, 7, 39−46. (52) Smart, O. S.; Goodfellow, J. M.; Wallace, B. The pore dimensions of gramicidin A. Biophys. J. 1993, 65, 2455−2460. (53) Smart, O. S.; Neduvelil, J. G.; Wang, X. N.; Wallace, B. A.; Sansom, M. S. P. HOLE: a program for the analysis of the pore dimensions of ion channel structural models. J. Mol. Graphics 1996, 14, 354−360. (54) Wallace, B. A. Recent advances in the high resolution structures of bacterial channels: gramicidin A. J. Struct. Biol. 1998, 121, 123−141.
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Binding Difference of Fipronil with GABAARs in Fruitfly and Zebrafish: Insights from Homology Modeling, Docking, and Molecular Dynamics Simulation Studies Nan Zheng,† Jiagao Cheng,*,†,‡ Wei Zhang,† Weihua Li,‡ Xusheng Shao,† Zhiping Xu,† Xiaoyong Xu,† and Zhong Li*,†,§ †
Shanghai Key Laboratory of Chemical Biology and ‡Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China § Shanghai Collaborative Innovation Center for Biomanufacturing Technology, 130 Meilong Road, Shanghai 200237, China S Supporting Information *
ABSTRACT: Fipronil, which targets GABAA receptors (GABAARs), is the first phenylpyrazole insecticide widely used in crop protection and public hygiene. However, its high toxicity on fishes greatly limited its applications. In the present study, a series of computational methods including homology modeling, docking, and molecular dynamics simulation studies were integrated to explore the binding difference of fipronil with GABAARs from fruitfly and zebrafish systems. It was found that, in the zebrafish system, the H-bond between 6′Thr and fipronil exerted key effects on the recognition of fipronil, which was absent in the fruitfly system. On the other hand, in the fruitfly system, strong electrostatic interaction between 2′Ala and fipronil was favorable to the binding of fipronil but detrimental to the binding in the zebrafish system. These findings marked the binding difference of fipronil with different GABAARs, which might be helpful in designing selective insecticides against pests instead of fishes. KEYWORDS: fipronil, GABAA receptors, homology modeling, docking, molecular dynamics simulation
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mutation in the Rdl subunit on the cross-resistance of fipronil in houseflies. Ffrench-Constant et al.10,13−15 also investigated the relationship between the cross-resistance of many commercial NCAs and the different mutations of A2′ in the Rdl subunit of D. melanogaster. Moreover, many modeling studies were performed to explore the binding mode of fipronil with GABAAR. However, the detailed binding modes of fipronil were still controversial. Cheng et al.16 found that the trifluoromethyl group of the benzene ring pointed to the intracellular domain, whereas Ci et al.17 reported that the trifluoromethyl group showed an opposite orientation. Also, Casida et al.18 observed that the same trifluoromethyl group faced the extracellular domain and considered that fipronil might have multiple interaction types. This indicated that the binding mode of fipronil with GABAAR still needed further illustration. On the other hand, fipronil showed high toxicity on fishes, which deeply limited its applications.19 It was generally considered that fipronil had potent interaction with both insect and fish GABAARs, which resulted in high toxicities against pests and fishes. Better understanding of the binding mode of fipronil with insect GABAARs versus fish GABAARs might be helpful in designing selective insecticides with low fish toxicity. There is a need to further investigate how fipronil elicited high insecticidal activities against pests and potent toxicities to fishes. Computational simulations are very important methods and
INTRODUCTION Fipronil is the first phenylpyrazole insecticide that has been successfully used in crop protection and public hygiene. It showed high insecticidal activity and low mammalian toxicity, which made it superior to other traditional insecticides.1,2 The target of fipronil is γ-aminobutyric acid type A receptors (GABAARs), a chloride channel that belongs to the ligand gated ion channel (LGIC) superfamily, including nicotinic acetylcholine receptors (nAChRs), glycine receptors (GlyRs), serotonin type 3 receptors (5-HT3R), and glutamate-gated chloride channels (GluCl).3 Fipronil bound to the TM2 domain of the channel,4 blocked the normal passage of chloride ions, and then disturbed the normal function of the central nervous system (CNS), leading to convulsions and death of insects. GABAAR comprises five subunits, which coassemble to form a homopentamer or heteropentamer. To date, researchers have cloned eight classes of subunits with multiple isoformers (α1-6, β1-3, γ1-3, ρ1-3, δ, ε, θ, and π) in vertebrates,5 of which the β3 subunit could form a homopentamer and showed higher noncompetitive antagonists (NCAs) sensitivity than other subunits.6 Each subunit contains three main domains: an extracellular domain containing the N- and C-terminals, a transmembrane domain (TMD) that is highly conserved in many species,7 and an intracellular domain. The ion channel pore is enclosed by TM2 helices from the five subunits, which determines the functional properties of GABAAR.8,9 In the case of insect GABAARs, the best studied one was the Rdl (resistant to dieldrin) type, which was first cloned from Drosophila melanogaster.10 It served as a good model of insect GABAARs11 and has been fully used in many toxicology studies of fipronil. For example, Scott et al.12 studied the roles of A2′S © XXXX American Chemical Society
Received: August 9, 2014 Revised: October 9, 2014 Accepted: October 10, 2014
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Figure 1. (a) Homology model of GABAAR: side view (left), top view (right). (b) Index number (above) for the residues (bottom) of TM2 regions. (c) Reported key residues and different residues within the TM2 regions of fruitfly (blue) and zebrafish (red) GABAARs. Ligand Docking. Ligand docking was performed by the Glide approach integrated into Maestro 9.3 (Schrödinger, LLC, 2013), with default settings in standard precision mode. The binding site was set around the centroid of the −2′ and 2′ residues from five chains, with a size of 30 Å. In the docking run, 100 conformations were output and ranked by GlideScore. The superior pose with a reasonable binding orientation was selected as the initial binding conformation for further molecular dynamics (MD) simulation. Molecular Dynamics Simulation. The obtained docking results of the fipronil−GABAAR complex were conducted for MD simulation using the GROMACS 4.5.530−32 package with the GROMOS53a633 force field for all atoms. The topology and other force field parameters for fipronil were obtained using the PRODRG beta server (http:// davapc1.bioch.dundee.ac.uk/prodrg/).34 The ESP partial atom charges were calculated at the B3LYP/6-31G(d,p) level using the Gaussian 09 package (Gaussian, Inc., Wallingford CT, USA; 2009) and determined using the Merz−Singh−Kollman scheme.35,36 On the basis of the calculated electrostatic potential, the restrained electrostatic potential (RESP) charges were produced using the Antechamber module37 of the Amber10 package. The fipronil−GABAAR complex structures were inserted into a pre-equilibrated 1-palmitoyl-2-oleylphosphatidylcholine (POPC) lipid bilayer using the “shrinking” method, where the shrinking cycles were performed with the InflateGRO script.38 The bilayer structure used here was downloaded from Tieleman’s Web site (http://moose.bio.ucalgary.ca/). The cubic periodic box comprising the simple point charge (SPC) water39 model was built. The Cl− ions were inserted randomly into the solvent to preserve the electric neutrality in both systems. The two systems were performed under the NPT ensemble, using the Nosé−Hoover thermostat40,41 and Parrinello−Rahman barostat42 to maintain the pressure at 1.02 bar, with the temperature maintained at 300 K. All bonds were constrained using the LINCS algorithm.43 In the MD simulation, the cutoff distance was set to 1.2 nm for LennardJones interactions. The long-range electrostatic interactions were handled using the particle-mesh Ewald (PME) method.44,45 The time step of the simulation was set to 2 fs. Finally, the fruitfly and zebrafish GABAAR systems in the fipronil-bound state have 1695 and 1680 residues, 71635 and 71932 water molecules, 25 and 5 Cl− ions, and 502 POPC molecules, and the densities of the POPC lipid bilayers were 66.6 and 66.8 Å2, respectively.
have exerted profound influences on the molecular design and interaction mechanism investigations of pesticides.20−23 In the present study, the 3D structures of homopentamer of GABAARs in representative insect (fruitfly Rdl) and fish (zebrafish β3) were established by the homology modeling method based on the open-state structure of an inhibitory glutamate-gated chloride channel24 from Caenorhabditis elegans. The GluCl24 showed high sequence similarity and was a good template for modeling the structures of the GABAARs, which was better than the nAChR and AChBP (acetylcholine binding protein) structures used in previous studies.16−18 Finally, docking and molecular dynamics (MD) simulation studies were performed to explore the binding difference of fipronil with fruitfly Rdl and zebrafish β3 GABAARs.
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MATERIALS AND METHODS
Homology Modeling. The target sequences of fruitfly Rdl (UniProt ID P25123) and zebrafish β3 (UniProt ID E7EXG0) subunits were retrieved from UniProtKB (http://www.uniprot.org/). The sequences were subjected to template search using the BLAST program of the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/). Finally, the crystal structure of glutamate-gated chloride channel24 (PDB ID 3RHW) was chosen as the template to build the 3D structures of both GABAARs. As no intracellular portion of the Cys-loop receptor superfamily was resolved, the sequences of the long cytoplasmic loops of the intracellular domain were removed during homology modeling study. The ClustalW2 program25−27 was used for sequence alignment. The identities of two GABAARs of fruitfly and zebrafish with the same template were 40.6 and 37.6%, respectively. On the basis of the aligned sequences (Supporting InformationFigure S1), in which the blue squares stand for the conserved residues of extracellular loop A-F and the Cys-loop, the channel pore of GABAAR formed by the TM2 helices is magenta squares, and the rest of the TM helices are purple squares, the Build Homology Models Module encoded in the Discovery Studio 3.5 software package (Accelrys Inc., 2013) was applied to generate the GABAAR structures of fruitfly and zebrafish species. The quality of the established 3D structures was not only assessed by the PROCHECK28 and the Profile-3D29 approaches but also validated by the comparison between following docking investigations and the previous experimental mutation results within the TM2 domain. B
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RESULTS AND DISCUSSION
Homology Models of GABAARs. The modeled structure of GABAAR is depicted in Figure 1a, of which the β-sheets of extracellular region are shown in magenta and the α-helices are in cyan. The channel pore of GABAAR was surrounded by five TM2 helices. The number for the residues of the TM2 region was indexed and is shown in Figure 1b for a convenient comparison between the two species. The interior residues in the TM2 channel of the GABAAR from fruitfly and zebrafish were −2′Pro (Ala), 2′Ala, 5′Val (Ile), 6′Thr, 9′Leu, and 20′Ala (Glu), which are shown as sticks in Figure 1c. Only three residues were different between the GABAARs of fruitfly and zebrafish, denoted −2′, 5′, and 20′, of which the 20′ residue was close to the extracellular region, the −2′ residue was near the intracellular domain, and 5′ was located in the lower part of the TM2 domain. The quality of both modeled structures was evaluated by using the PROCHECK28 and Profile-3D29 approaches. In the fruitfly model, 99.3% residues were located in the allowed regions, and only 0.7% residues (Thr104 and Ser172 in the extracellular region) were located in the disallowed regions (Supporting Information Figure S2a). In the zebrafish model, 99.7% residues were observed in the allowed regions, whereas only 0.3% residues (Thr101 in the extracellular domain) were found in the disallowed regions (Supporting Information Figure S2b). The self-compatibility score by Profile-3D for the GABAAR structure of fruitfly was 543.87, which was close to the top score of 782.05. The corresponding score of the zebrafish GABAAR structure reached 546.56, which was also close to the top value of 775.07. Moreover, it could be seen that most residues were reasonable with positive score values; only a few residues far from the fipronil binding site, which located in the extracellular and TM3 regions, showed small negative profile-3D values (Supporting Information Figure S2c,d). The above results indicated that the homology models of fruitfly and zebrafish were reliable. Docking Results. Docking studies were performed to explore the binding modes of fipronil with GABAAR. The final docking pose was obtained by considering the GlideScore values and analyzing the binding mode, which is depicted in Figure 2. This showed that fipronil erected in both channels enclosed by the five TM2 helices, with the trifluoromethyl group of the benzene ring facing the intracellular domain, which was consistent with the previous modeling study by Cheng et al.16 Also, the residues 2′Ala, 6′Thr, and 9′Leu were found to play important roles for the binding of fipronil (Supporting Information Figure S3), which was in accordance with the previously published investigations.10−18,46−51 For example, Casida et al.18 showed that the mutation of A2′C or A2′S and T6′C or T6′F, as well as L9′C or L9′S, in the human β3 homopentamer could abolish the binding sensitivity of NCAs. The N−H···O H-bond between the amino group of fipronil and the side chain of 6′Thr was observed in both systems, which has been reported to be very important for binding by other researchers.16−18 Moreover, it was found that the residues −2′Pro (Ala) and 5′Val (Ile) could also form interactions with fipronil (Supporting Information Figure S3). According to the docking results, both GABAARs showed favorable interactions with fipronil. All above docking analyses also confirmed that the modeled 3D structures of GABAARs were reasonable.
Figure 2. Docking poses of fipronil with fruitfly (a) and zebrafish (b) GABAARs. Dotted line, H-bond; stick, fipronil and the key residues.
Molecular Dynamics Simulation. Root Mean Square Deviation (RMSD). To evaluate the stability of the two systems during the MD simulation, the RMSD was plotted versus time. Figure 3 depicts the RMSD values for the backbone atoms of
Figure 3. RMSD plots for the backbone of GABAARs and fipronil during MD simulation.
protein and ligand. The RMSD values for the backbone of fruitfly and zebrafish systems are colored in black and red, respectively; the two systems were stable after 16 ns simulations. However, during the last 14 ns of the simulations, the amplitude of the equilibrium deviation was slightly different in each trajectory. The RMSD values of the fruitfly system showed that the disruption of convergence was at about 0.46 nm, whereas the corresponding value was 0.43 nm for the zebrafish system. Meanwhile, the RMSD values of ligand atoms were also calculated and are depicted in Figure 3. The data indicated that the fipronil in both systems reached equilibrium states after a small fluctuation in the initial period of the simulation. The magnitude of fluctuations for ligand, together with the backbone of protein, led to the conclusion that the C
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Figure 4. Pore diameter analysis at 0 and 30 ns snapshots of fruitfly (a, b) and zebrafish (c, d) systems: distance along the pore axis (Å) versus pore diameter. The key residues in the binding pocket from TM2 helices are shown as sticks.
−2′Pro (Ala) for both systems, where the side chain of 9′Leu defined the narrowest point in the middle of the two channels, whereas −2′Pro in the fruitfly system or −2′Ala in the zebrafish system determined the lowest narrow part of the channels. After a 30 ns simulation, the pore radius at 9′Leu that represented the top side of the binding pocket expanded for both systems, as well as the −2′Pro (Ala) that denoted the bottom of binding site. In the zebrafish system, no clear changes were found for the tunnel radius between 5′Ile and 2′Ala after simulation, whereas in the fruitfly system the corresponding radius between 5′Val and 2′Ala enlarged. It was also observed that the pore size between the 5′ and 2′ residues within the binding pocket of fruitfly system was wider than that in the zebrafish system, which might be a result of the smaller volume of 5′Val than of 5′Ile. Moreover, in the fruitfly system the pore radius defined by the 6′Thr narrowed, whereas in the zebrafish system the corresponding tunnel radius widened. The above differences in the binding pockets of the two systems might exert some influences on the binding modes of fipronil with the GABAARs from the two species. Position and Orientation Changes of Fipronil during Simulation. Figure 5a and b show the superposition for fipronil
simulation produced stable trajectories and provided a reliable basis for further analysis. Root Mean Square Fluctuation (RMSF). With the aim of determining the mobility and flexibility of each residue in the MD simulation, the RMSF values were calculated. The RMSF values for the residues of TM domains were small, indicating that they were stable during the entire simulation (Supporting Information Figure S4a), whereas larger values were observed in the extracellular domain and the loops between TM3 and TM4, which implied that residues in these regions were flexible in the MD simulation. The fluctuating residues were observed far from the ligand binding site and might have weak influences on the interaction of fipronil with GABAAR. For detailed analysis, the RMSF for the residues in ligand binding pocket within the TM2 domains is also depicted in Supporting Information Figure S4b. Clearly, the fruitfly system showed higher peaks around the fipronil binding pocket, compared with the zebrafish system, which indicated that such residues from the fruitfly system might undergo larger fluctuation than those from the zebrafish system. The smaller RMSF values in the zebrafish system also coincided with the above RMSD values. Pore Radius. Ion channel radius is an important parameter to characterize the channel opening and closing, which has been widely used to measure the size of a channel pore. In the present study, the pore radius of the GABAAR was conducted using the HOLE program.52−54 The pore radii at the 0, 5, 10, 20, and 30 ns snapshots, as well as on the average structure of the last 5 ns in the equilibrium state, have been calculated and analyzed (Supporting Information Figure S5). It could be observed that the pore radius variations were very similar at the 20 and 30 ns snapshots and on the average structure of the last 5 ns, especially in the region between the −2′Pro (Ala) and 9′Leu residues of the TM2 domain. The calculated pore diameters at 0 and 30 ns snapshots were analyzed and are depicted in Figure 4 to understand the changes of pore size after MD simulation. The ion pores of both GABAARs tilted radially from the extracellular domains down to the TM2 domain. The binding site of fipronil was located in the region between 9′Leu and
Figure 5. Alignment of the TM2 domain in the fruitfly (blue) and zebrafish (red) systems at 0 (a) and 30 ns (b). Cyan and green sticks represent the fipronil in fruitfly and zebrafish systems, respectively. Superimposition of the fipronil in fruitfly (c) and zebrafish (d) systems is shown as 0 ns (cyan), 10 ns (green), 20 ns (yellow), and 30 ns (orange) snapshots. D
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Figure 6. Interactions of fipronil with fruitfly (a) and zebrafish (b) GABAARs at 30 ns snapshot after MD simulation: hydrophobic interactions between fipronil and the residues in fruitfly (c) and zebrafish (d) systems at the 30 ns snapshot.
with GABAARs in fruitfly and zebrafish systems, the key residues for the binding of fipronil were fully analyzed on the structures at the equilibrium state. Panels a and b of Figure 6 depict the interaction between fipronil and the residues in the TM2 channel of GABAAR at the 30 ns snapshots. The potential key residues displayed in sticks could also be observed in the 0, 5, 10, and 20 ns snapshots and in the average structure of the equilibrium state. It was found that residues 2′Ala, 6′Thr, and 9′Leu formed hydrophobic interactions with fipronil (Figure 6c,d), which were important for the binding of fipronil with both GABAARs. The findings were in accordance with the previous modeling studies.17,18 For example, Casida et al.18 reported that 2′Ala, 6′Thr, and 9′Leu could form hydrophobic interactions with diverse antagonists, which had a critical influence on the recognition of NCAs. Moreover, in this study, the residue 5′Val (Ile) was observed forming hydrophobic interactions with fipronil in both. Many researchers have reported that 6′Thr could form an Hbond with fipronil, which played key roles for the ligand− receptor recognition.16−18 In the zebrafish system, an N−H···O H-bond was observed between the amino group of fipronil and the side chain of 6′Thr (Figure 7a). The distance between the
and TM2 helices in the fruitfly and zebrafish systems at the snapshots of 0 and 30 ns of the simulation, respectively. Small position changes of fipronil were observed in the zebrafish system during the entire MD simulation, whereas the position of fipronil in the fruitfly system moved toward the lower part of the TM2 channel, as compared with its initial binding site. In other words, the binding site of fipronil in the fruitfly system was much closer to the intracellular domain than in the zebrafish system (Figure 5b). Figure 5c and d display the superposition of fipronil in the snapshots at 0, 10, 20, and 30 ns in the MD trajectory from the fruitfly and zebrafish systems, respectively. It can be observed that fipronil went through large orientation changes in the fruitfly system relative to the zebrafish system. This might be a result of the different pore radius properties between the two systems. A wider tunnel dimension between 5′Thr and 2′Ala appeared in the binding pocket of the fruitfly system than in the zebrafish system, which might be an important reason for the observed larger position and orientation changes in the fruitfly system. Binding Difference of Fipronil with Fruitfly and Zebrafish GABAARs. To better understand the binding modes of fipronil E
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Figure 7. (a) N−H···O H-bond between fipronil and 6′Thr in zebrafish system; (b) N−H···O H-bond distance during the whole MD simulation.
monitored during the MD simulation of the fruitfly system, the strong electrostatic interaction between 2′Ala and fipronil might compensate the binding force of fipronil with GABAAR. Although 2′Ala and 6′Thr in the two systems, respectively, showed different roles in the recognition of fipronil, the favorable interactions enabled fipronil to erect steadily in both channels, which might contribute to the high toxicities to insects and fishes. All of the data above indicated that residues 5′Val (Ile), 6′Thr, and 9′Leu played important roles in the binding of fipronil with both GABAARs. Moreover, the H-bond between 6′Thr and fipronil in the zebrafish system was very stable during the whole MD simulations, which played a key role in the ligand−receptor recognition. However, such an H-bond was absent in the fruitfly system during simulation, although it could be observed in the docking results and the initial snapshot of the simulation. On the other hand, the electrostatic interaction between 2′Ala and fipronil was favorable to ligand recognition in the fruitfly system, but was detrimental to the binding in the zebrafish system. As a result, the observed strong electrostatic interaction between 2′Ala and fipronil compensated the absent contribution of the H-bond between 6′Thr and fipronil in the fruitfly system. The different roles of 2′Ala and 6′Thr marked the binding difference of fipronil with the GABAARs of fruitfly and zebrafish, which might provide some clues for future design of new selective phenylpyrazole pesticides against insects over fishes.
N and O atoms versus the simulation time was monitored during the whole simulation (Figure 7b). It was found that the N−H···O H-bond was very stable, with an H-bond distance around 3.0 Å in the whole simulation. In the fruitfly system, the corresponding H-bond could be observed in the docking results and the initial snapshot of the simulation. However, it disappeared during the subsequent simulation. The detailed reasons for the disappearance of the N−H···O H-bond are still unclear. One of the reasons might be the above-mentioned large position and orientation changes of fipronil in the fruitfly system. To gain detailed energy contributions of the key residues in the TM2 helices on the binding affinity of fipronil, a per-residue decomposition of the total energy was performed to evaluate the critical residues on the binding, using the Calculate Interaction Energy Protocol encoded in the Discovery Studio 3.5 software package (Accelrys Inc., 2013). The snapshots of two systems in the last 5 ns of MD simulation were extracted, respectively, for energy analysis. The residue-based energy decomposition results characterized the key residues in ligand binding and identified the contributions of different nonbonded interaction forces (van der Waals and electrostatic interactions). The energy contributions of each key residue are displayed in Table 1. They showed that 5′Val (Ile), 6′Thr, and 9′Leu were Table 1. Average Energy of Interaction between Individual Residues and Ligands for the Fruitfly and Zebrafish Systems residue
fruitfly
zebrafish
2′Ala electrostatic 5′Val(Ile) electrostatic 6′Thr electrostatic 9′Leu electrostatic
−1.05 −1.15 −1.19 −1.14 −0.82 −0.66 −0.67 −0.69
1.01 1.03 −1.54 −1.67 −1.94 −1.12 −1.23 −1.12
term term term term
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ASSOCIATED CONTENT
S Supporting Information *
Figures S1−S5. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Authors
*(J.C.) E-mail: [email protected]. Phone: +86-2164251348. Fax: +86-21-64252603. *(Z.L.) E-mail: [email protected].
favorable for the binding of fipronil with both GABAARs. Moreover, the average interaction energy between residue 2′Ala and fipronil, which was originated predominantly by the electrostatic interaction, was beneficial for complexation in the fruitfly system but unfavorable to binding in the zebrafish system. All of the data in Table 1 and Figures 6 and 7 indicated that residues 5′Val (Ile), 6′Thr, and 9′Leu played important roles for the binding of fipronil with both GABAARs. Although the N−H···O H-bond between fipronil and 6′Thr could not be
Funding
This work was financially supported by the National Key Technology R&D Program of China (2011BAE06B05), the National Natural Science Foundation of China (21172070), the National High Technology Research Development Program of China (2011AA10A207), and the Fundamental Research Funds for the Central Universities (222201314006) F
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Notes
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The authors declare no competing financial interest.
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ABBREVIATIONS USED GABAARs, γ-aminobutyric acid type A receptors; LGIC, ligand gated ion channel; nAChRs, nicotinic acetylcholine receptors; GlyRs, glycine receptors; 5-HT3R, serotonin type 3 receptors; GluCl, glutamate-gated chloride channels; CNS, central nervous system; NCAs, noncompetitive antagonists; TMD, transmembrane domain; Rdl, resistant to dieldrin; AChBP, acetylcholine binding protein; MD, molecular dynamics; NCBI, National Center for Biotechnology Information; RESP, restrained electrostatic potential; POPC, 1-palmitoyl-2-oleylphosphatidylcholine; SPC, simple point charge; PME, particle-mesh Ewald; RMSD, root-mean-square deviation; RMSF, root-meansquare fluctuation
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