Interaction affinity of Delta and Epsilon class glutathione-s-transferases (GSTs) to bind with DDT for detoxification and conferring resistance in Anopheles gambiae, a malaria vector.
Insecticide resistance is a growing problem in the control of disease spreading insect vectors. The basic mechanisms underlying resistance to commonly used insecticides such as organochlorines, organophosphates, carbamates and synthetic pyrethroids are well-known. Resistance mechanisms are broadly of two types, target site insensitiveness and enzyme-based detoxification (1). In mosquitoes, detoxification is performed by a group of enzymes such as esterases, oxidases and glutathione-stransferases (GSTs). Detoxification of insecticides occurs when enhanced levels of these enzymes prevent the insecticide from reaching its site of action. GSTs are the major family of detoxification enzymes which get activated in the presence of reduced glutathione (GSH) and bind to DDT (Dichlorodiphenyl-trichloroethane) molecules and convert them into a non-toxic lipophilic compound DDE (Dichlorodiphenyl-ethane) (2). Many resistant insects have elevated level of GSTs and such over expression of this enzyme is considered to be responsible for the development of resistance to organochlorine insecticides including DDT, hexachlorocyclohexane (HCH) and cyclodiene (3). Recently, elevated level of GST activity for DDT detoxification has been confirmed in Anopheles culicifacies and An. annularis (4).
Insect GSTs are classified into six classes, viz. Delta, Epsilon, Zeta, Sigma, Omega, and Theta by comparative analysis of Drosophila melanogaster and An. gambiae genomes (5-8). The Delta and Epsilon class GSTs, which are encoded by multiple genes, have been implicated in detoxification, particularly in conferring resistance to organochlorine group of insecticides (9-12). In An. gambiae, an important African malarial vector, the increased rate of DDT dehydrochlorination in the resistant vector strain was associated with quantitative increase of GST enzymes that included Delta and Epsilon classes (13). GSTs consist of a specific-glutathione (GSH)-binding site (G-site) next to a non-specific electrophilic ligand-binding site (H-site). The high level of diversity in this region is responsible for the differences in substrate specificities (14-15).
Based on the studies carried out so far in An. gambiae, Delta class comprises of 12 different genes (D1-D12), out of these D1 gene gives rise to four different transcripts, D7 and D11 genes produce two different transcripts each and each one of the remaining genes (except D9) gives rise to a single transcript and no information is available for D9 gene in the existing databases for An. gambiae. Epsilon class encompasses eight different genes (E1-E8); each gives rise to a single transcript. All the 16 transcripts of Delta class GSTs, except D7-2 and eight transcripts of Epsilon class GSTs have modbase structure deposited in the Swiss-Prot database. Further, structure of one of the transcripts of D1 gene, agGST1-6, was proved experimentally (16) and its affinity with S-hexyl glutathione (GTX), a hexyl glutathione was understood from crystallographic studies. Similarly, the structure of E2 GST was confirmed by X-ray crystallographic analysis (17).
Therefore, the Delta and Epsilon class GSTs produce a total of 24 transcripts that result in the production of corresponding enzyme proteins. However, to detect the development of resistance by mosquitoes to DDT, the conventional biochemical assay estimates the elevated level of total GSTs. Hence, it would be more reliable if the specific class of GST enzyme which has the highest molecular interaction affinity with DDT is estimated and used for screening of field mosquito population for development of DDT resistance.
Therefore, a comparative study was undertaken by docking of Delta and Epsilon class GSTs in their bioconfirmative form (GSTs and reduced GSH [glutathione] complex) with DDT using bioinformatics tools. This information would be useful to improve the biochemical analysis of the specific class GST enzyme that would further lead to design of a more specific molecular tool to determine the expression status of the particular type of GST enzyme.
MATERIAL & METHODS
The computational models of eight Epsilon (E1-E8) and 15 Delta class GSTs (D1-D8 and D10-D12) (except D9 and D7-2), that are reported to be responsible for DDT resistance in An. gambiae were retrieved from the Swiss-Prot database (http://www.expasy.ch/sprot/). The Delta class GST, D9 was not considered in the present study as its corresponding gene has no information in the data bank. But, for D7-2, while there was no structural model deposited in the Swiss-Prot database, its sequence details are available. Hence, the D7-2 GST protein that consists of 191 amino acid residues, with an ID of A0NDD6 was subjected for modeling. The NCBI, BLAST was used to select a template for the D7-2 query sequence based on the highest sequence identity. As a result, the sequence of An. dirus B with a PDB ID of 1R5A having an identity of 95% was chosen as the template and a homology model of D7-2 was developed using MODELLER. The stereo chemical quality of the model was determined by the Structure Analysis and Verification Server (http://nihserver.mbi.ucla.edu/SAVS/). The other modeled proteins of Epsilon and Delta class GSTs retrieved from the database were also reassessed for their quality using the same server (PROCHECK analysis). The modeled D7-2 was examined by superimposing it on the template 1R5A in Chimera Visualizer (Fig. 1a). Subsequently, to establish the correctness of the model, its RMSD details (Fig. 1b) were obtained using the Superpose online server tool (http:/wishart.biology.ualberta.ca/SuperPose/) (18).
CASTp (http://sts-fw.bioengr.uic.edu/castp/) was used to find out the surface pockets of the retrieved as well as the modeled proteins and Q-site Finder (http://www.bioinformatics.leeds.ac.uk/qsitefinder/help.html), an online tool and a new method of ligand binding site prediction, was used to predict the active sites of the proteins. Additionally, Fuzzy-Oil-Drop (http://www.bioinformatics.cm-uj.krakow.pl/activesite/) was also used to confirm the active sites predicted by the CASTp and Q-site Finder. The G-site (an active site for reduced GSH) and H-site (an active site for DDT) of GST enzymes were predicted using the three online servers. Since, reduced glutathione is necessary for the activation of GST, its chemical structure was taken from the PUBCHEM database (http://pubchem.ncbi.nlm.nih.gov/). Similarly, the chemical structure of DDT was also retrieved from the PUBCHEM database and their corresponding PDB files were obtained by uploading the smiles notations of the compounds to the online molecular format converter (http://www.molecular-networks.com/online_demos/corina). The transcript models that were validated using PROCHECK analysis were initially docked with GSH (Fig. 2) and the resulted (GSH + GST) (Fig. 3) complex was subsequently docked with the ligand, DDT using AutoDock to rank the transcript showing the highest interaction affinity. Labeled molecular level close up of the hydrogen bonds between GSH and GSTs has been shown in Fig. 4 and hydrophobic patch was established by DDT interaction with GST at position PHE 117 (Fig. 5).
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RESULTS & DISCUSSION
This current in-silico analysis was carried out based on the observation made in a wet lab study that confirmed the involvement of GSTs in conferring DDT resistance in the malaria vectors, An. culicifacies and An. Annularis (4). There was a 3-fold increase in GST activity in DDT-resistant An. annularis compared with its susceptible population. In An. culicifacies, the median GST activity (71.8 [micro]mol/min/mg) was almost the same as estimated in the DDT-resistant An. annularis (74.6 [micro]mol/min/mg), suggesting that the GST activity estimated in An. culicifacies could be an elevated level for detoxification of DDT. Furthermore, the GST activity in DDT-resistant An. culicifacies and An. annularis was significantly higher than that in the DDT-susceptible An. fluviatilis, which had a GST activity of 20 [micro]mol/min/[mg.sup.4].
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In total, structural models are available for 24 GSTs, eight of Epsilon class and 16 of Delta class. Among these, 23 were the retrieved ones and the remaining one was developed during the current study. The overall quality factor of the model developed for D7-2 was 92.4% as obtained from the Ramachandran plot (Fig. 6). The quality factor for all the retrieved models was around 90% as revalidated using PROCHECK analysis (Table 1).
Finding out the active site residues of GST showing the highest affinity for GSH interaction and subsequently of GST + GSH complex for DDT interaction is an important step to carry out the docking process. In an earlier crystallographic study, one of the transcripts of Delta class D1 gene (D1-1) was examined in relation to GSH binding with GST and, based on formation of more number of hydrogen bonds, identified ILE 52 as the active site residue showing the highest affinity for GSH binding (16). This residue is present in the G-site of the D1-1 transcript. The G-site consists of 19 amino acid residues (LEU 6, SER 9, ALA 10, PRO 11, LEU 33, MET 34, HIS 38, HIS 50, ILE 52, GLU 64, SER 65, ARG 66, TYR 105, PHE 108, TYR 113, ILE 116, PHE 117, PHE 203, and PHE 207) and out of these, ILE 52 showed the highest interaction affinity with GSH (15). Hence, ILE 52 was considered in the current study as the suitable active site for carrying out the docking of GSH with the GSTs of both the Epsilon and Delta classes.
The crystallographic study with An. dirus confirmed that either PHE (117 and 203) or TYR (105 and 113) residues of the bioactively conformed GST form the hydrophobic pathway for binding with DDT (19), and out of these four residues, according to the docking results obtained in the current study, PHE 117 was found to show a higher interaction with DDT. Further, the studies with An. gambiae have illustrated that the H-site, which is meant for DDT (ligand) binding, composed of 12 amino acid residues, including those four residues that were related to DDT binding in the study with An. dirus (19). So PHE and TYR could be the residues involved in DDT binding in the case of An. gambiae also. Thus, involvement of these two residues, with PHE showing a higher interaction, in DDT binding with GSH + GST complex is clearly confirmed. Based on this information, PHE 117 could be considered as the suitable active site residue for DDT interaction. However, literature evidence did not explain about the position of ILE 52 (G-site residue) and PHE 117 (H-site residue), i.e. whether both are located in the same pocket or not. Our results from CASTp, Q-SITE FINDER and Fuzzy Oil Drop analysis confirmed that both the G-site residue (ILE 52) (Fig. 7a) and the H-site residue (PHE 117) (Fig. 7b) are present in the same pocket, but at different sites. The residues PHE and ILE are, respectively at position 117 and 52 in both D1-1 and D1-3. Apart from these two transcripts, in all others, PHE and ILE are present at different positions not at 52 and 117; these two positions are occupied by other amino acid residues. It has been reported that all the 24 Epsilon and Delta class GSTs have been implicated in the process of detoxification of DDT8. The pocket prediction analysis done in the current study also confirmed the presence of PHE and ILE in the same pocket in all the 24 computational GST models. Therefore, though present at different positions in different transcripts, considering their presence within the same pocket, the two residues, PHE and ILE should be considered as the key residues involved in DDT cleavage and hence, significance was given to the residues and not to the position they occupy. Further, the pocket having both PHE and ILE residues was taken as the active site for the interaction of GSH + GST with DDT.
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The energy budget obtained as the output from the docking of the 24 models of Epsilon and Delta class GSTs with DDT in the presence of reduced GSH is given in (Table 2). Out of the 24 modeled GSTs, Delta 6 had shown the lowest binding energy followed by Delta 4 and Epsilon 2, indicating their highest degree of affinity with DDT in order. Therefore, these three proteins could be considered to be the major factor for the detoxification of DDT.
Based on the degree of interaction affinities, the modeled GST from D6 transcript, which showed the highest affinity with DDT, is likely to get over-expressed on mosquito exposure to the insecticide. Following further confirmation through wet lab studies, it would be possible to design a specific molecular assay to determine the expression level of such high affinity transcript(s) and this could be used for detection/monitoring of resistance more reliably among the field vector populations.
The investigators wish to thank Dr P. Jambulingam, Director and Dr S. Sabesan, Chief, Division of Human Resource Development, Vector Control Research Centre, Puducherry for the facilities and the support provided. The investigators are also thankful to Dr K. Tyagesan, Principal, AVC College, Mayiladuturai, Tamil Nadu for reviewing the manuscript. Mrs Sundarambal, Library and Information Officer, Mrs T. Sumathy and Mr V.K. Suresh Kumar, Vector Control Research Centre, are also gratefully acknowledged for their help during the course of the study.
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V. Aravindan , S. Muthukumaravel  & K. Gunasekaran 
 School of Chemical and Biotechnology, SASTRA University, Thanjavur; (2) Vector Control Research Centre (ICMR), Indira Nagar, Puducherry, India
Correspondence to: Mr S. Muthukumaravel, Division of Vector Biology and Control, Vector Control Research Centre (ICMR), Indira Nagar, Puducherry-605 006, India.
E mail: firstname.lastname@example.org
Received: 6 March 2013 Accepted in revised form: 6 January 2014
Table 1. Quality factor for Delta and Epsilon classes GSTs as validated by PROCHECK analysis Transcripts of Query Template sequence GST genes sequence (An. gambiae) length Length/ PDB ID Organism (residues) Delta class GSTs D1-1 209 209/1pn9 An. gambiae D1-2 216 218/1r5a An. dirus B D1-3 209 209/1pn9 An. gambiae D1-4 219 219/1jlw An. dirus B D2 209 209/1pn9 An. gambiae D3 210 210/1v2a An. dirus B D4 212 210/1v2a An. dirus B D5 216 210/1v2a An. dirus B D6 222 210/1v2a An. dirus B D7-1 218 218/1r5a An. dirus B D7-2 191 218/1r5a An. dirus B D8 223 209/1pn9 An. gambiae D10 211 210/1v2a An. dirus B D11-1 214 209/1jlv An. dirus B D11-2 217 209/1jlv An. dirus B D12 211 209/1v2a An. dirus B Epsilon class GSTs E1 224 218/1r5a An. dirus B E2 221 209/1pn9 An. gambiae E3 223 209/1pn9 An. gambiae E4 225 209/1pn9 An. gambiae E5 230 209/1pn9 An. gambiae E6 227 218/1r5a An. dirus B E7 225 209/1pn9 An. gambiae E8 217 218/1r5a An. dirus B Transcripts of Sequence Swiss-Prot Residues in GST genes identity Model ID most favoured (An. gambiae) (%) region (quality factor) (%) Delta class GSTs D1-1 100 Q93113 96.2 D1-2 43 Q7PH26 92.4 D1-3 84 Q93112 95.1 D1-4 84 O77462 93 D2 52 Q94999 94 D3 86 Q7PQ95 94.1 D4 62 Q5TT03 94.7 D5 60 Q7QB59 92.1 D6 42 Q7PQB4 92.2 D7-1 95 O76483 * 93.1 D7-2 95 A0NDD6 92.4 D8 46 Q5TTE5 92.5 D10 56 Q7QA79 91.9 D11-1 56 Q7PQ57 94.7 D11-2 47 Q5TT04 89.5 D12 41 Q7QA80 94.1 Epsilon class GSTs E1 32 Q7PVS5 90.6 E2 41 Q9GPL8 91.8 E3 36 Q7PVS2 93.5 E4 39 Q7PVS7 95.7 E5 41 Q7PVS8 92.8 E6 27 A0NG89 89.1 E7 36 Q7PVS4 96.2 E8 27 Q8WQJ5 93.1 * The primary accession code: AF 251478. Table 2. Energy budget output from the docking of GST with DDT bound with reduced GSH GST class/ Binding energy DDT interactive transcripts (kcal/mol) residue Delta class D1-1 -9.19 PHE 117 D1-2 -6.42 PHE 210 D1-3 -7.37 PHE 117 D1-4 -7.82 PHE 123 D2 -6.38 PHE119 D3 -6.60 PHE194 D4 -32.60 PHE97 D5 -9.00 PHE157 D6 -34.47 PHE105 D7-1 -8.02 PHE115 D7-2 -8.17 PHE115 D8 -8.78 PHE3 D10 -7.68 PHE196 D11-1 +1.44e+05 PHE108 D11-2 +3.04e+05 PHE211 D12 -7.61 PHE181 Epsilon class E1 -8.18 PHE 111 E2 -10.35 PHE 108 E3 -6.31 PHE 117 E4 -10.07 PHE 113 E5 -7.52 PHE 112 E6 -7.94 PHE 109 E7 -7.02 PHE 110 E8 -7.72 PHE 119 Fig. 1b: RMSD details of the superimposed model D7-2 on the template, 1R5A. SuperPose used the sequence alignment to guide the supersposition Local RMSD Alpha carbons Back bone Heavy All RMSD 0.14 0.19 0.76 0.76 Atoms 190 760 1532 1532 Structure Residues 1R5A chain 'A' 2-191 PDBB 2-191 Global RMSD Alpha carbons Back bone Heavy All RMSD 0.14 0.19 0.76 0.76 Atoms 190 760 1532 1532 Structure Residues 1R5A chain 'A' 2-191 PDBB 2-191 SuperPose output images WebMol MolScript superposition image Difference distance matrix SuperPose output text files Sequence alignment Difference distance matrix Superposition (PDB) RMSD report Back to SuperPose home page
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|Author:||Aravindan, V.; Muthukumaravel, S.; Gunasekaran, K.|
|Publication:||Journal of Vector Borne Diseases|
|Date:||Mar 1, 2014|
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