Chemosphere 93 (2013) 2568–2577

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Chemosphere

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Molecular docking: A potential tool to aid ecotoxicity testingin environmental risk assessment of pharmaceuticals

0045-6535/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.chemosphere.2013.09.074

⇑ Corresponding author. Tel.: +44 07847 381539.E-mail address: Samantha.d.walker@ntlworld.com (S.D. Walker).

Samantha Dawn Walker ⇑, Sharron McEldowneyDepartment of Life Sciences, University of Westminster, 115 New Cavendish St., London W1W 6UW, United Kingdom

h i g h l i g h t s

�Molecular docking could aid environmental risk assessment of pharmaceuticals.� O. mykiss and X. tropicalis COX2 homologues bind diclofenac and ibuprofen.� X. laevis & D. rerio progesterone receptor homologues bind levonorgestrel.� Molecular docking can aid sensitive species selection in ecotoxicity tests for ERA.� Mode of action ecotoxicity test end points can be selected using molecular docking.

a r t i c l e i n f o

Article history:Received 12 March 2013Received in revised form 12 September 2013Accepted 23 September 2013Available online 25 October 2013

Keywords:LevonorgestrelDiclofenacIbuprofenEnvironmental risk assessment (ERA)Molecular docking

a b s t r a c t

A cocktail of human pharmaceuticals pollute aquatic environments and there is considerable scientificuncertainty about the effects that this may have on aquatic organisms. Human drug target proteinscan be highly conserved in non target species suggesting that similar modes of action (MoA) may occur.The aim of this work was to explore whether molecular docking offers a potential tool to predict theeffects of pharmaceutical compounds on non target organisms. Three highly prescribed drugs, diclofenac,ibuprofen and levonorgestrel which regularly pollute freshwater environments were used as examples.Their primary drug targets are cyclooxygenase 2 (COX2) and progesterone receptor (PR). Molecular dock-ing experiments were performed using these drugs and their primary drug target homologues forDanio rerio, Salmo salar, Oncorhynchus mykiss, Xenopus tropicalis, Xenopus laevis and Daphnia pulex. Theresults show that fish and frog COX2 enzymes are likely to bind diclofenac and ibuprofen in the sameway as humans but that D. pulex would not. Binding will probably lead to inhibition of COX functionand reduced prostaglandin production. Levonorgestrel was found to bind in the same binding pocketof the progesterone receptor in frogs and fish as the human form. This suggests implications for thefecundity of fish and frogs which are exposed to levonorgestrel. Chronic ecotoxicological effects of thesedrugs reported in the literature support these findings. Molecular docking may provide a valuable tool forecotoxicity tests by guiding selection of test species and incorporating the MoA of drugs for relevantchronic test end points in environmental risk assessments.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Substantial mixtures of human pharmaceuticals have been de-tected in surface waters at concentrations in the ng L�1 to lowmg L�1 range for each individual compound (Ashton et al., 2004;Redshaw et al., 2008; Santos et al., 2009; Pal et al., 2010; Boundand Voulvoulis, 2006). A number of reviews have been publishedwhich summarise known ecotoxicological effects of human phar-maceuticals, for example, Santos et al. (2009) and Fent et al.(2006). However, there is still considerable uncertainty as to the ef-fects that pharmaceuticals, their metabolites and transformation

products may have on aquatic organisms (Fent et al., 2006;Kummerer, 2009; Fatta-Kassinos et al., 2011a). Aquatic organismsare exposed to a continuous cocktail of human pharmaceuticals,at least a dozen different pharmaceuticals have been measuredin a single surface water sample (Daughton and Brooks, 2011). Thisis highly likely to be a substantial underestimate because of limita-tions in analysis. Human pharmaceuticals can often disrupt keybiological functions in aquatic organisms such as reproductionand growth (Fent et al., 2006). The presence of the synthetic hor-mone contraceptive 17a ethinylestradiol (EE2) in sewage effluentand surface waters has been clearly linked with the endocrine dis-ruption of fish and frogs (Desbrow et al., 1998; Jobling et al., 2002;Caldwell et al., 2008; Gyllenhammar et al., 2009). Fish are particu-larly sensitive to EE2, the predicted no effect concentration (PNEC)

S.D. Walker, S. McEldowney / Chemosphere 93 (2013) 2568–2577 2569

for EE2 is <1 ng L�1 (Lange et al., 2001; Caldwell et al., 2008). Thisdetrimental effect on aquatic organisms was not foreseen, despitethe human mode of action (MoA) for EE2 being via the oestrogenreceptor which is highly conserved in other vertebrates such as fish(Christen et al., 2010).

Veterinary medicines have also been the cause of a dramaticdetrimental effect on non target organisms. The use of diclofenacin cattle has caused a major decline in vultures in India and Paki-stan. The Gyps genus of vulture were surprisingly sensitive to res-idues of diclofenac in deceased carrion on which they fed, leadingto acute renal failure and visceral gout (Oaks et al., 2004). Diclofe-nac has since been withdrawn as a veterinary medicine in India,Nepal, Bangladesh and Pakistan (Kumar, 2006). However, it is stillused widely as an analgesic in human medicine; it is persistentduring sewage treatment and is regularly detected in effluentand surface waters around the world (Hoeger et al., 2005).

There are several examples of chronic effects on aquatic organ-isms at environmentally relevant concentrations. The antidepres-sant fluoxetine (Prozac) has been shown to effect innatebehavioural responses of fish (Painter et al., 2009; Schultz et al.,2011) and alterations in reproduction patterns have also been ob-served (Brooks et al., 2003).

Although it is widely accepted that some of these compoundsare associated with adverse developmental effects at environmen-tally relevant concentrations (Khetan and Collins, 2007; Fatta-Kas-sinos et al., 2011a), chronic ecotoxicity data is lacking for mostpharmaceuticals. A key difficulty in assessing the toxic effects ofthese low concentration pollutants is that it is not yet establishedwhich organisms and which endpoints are relevant for risk assess-ment (Fatta-Kassinos et al., 2011b).

The EU the guidelines for environmental risk assessment (ERA)of medicinal products for human use are laid down by EMEA//CHMP/SWP/4447/00, Directive 2004/27/EC. These guidelines statethat if the predicted exposure concentration exceeds 10 ng L�1,ecotoxicological tests using OECD guidelines are required. If a drugaffects reproduction of vertebrates or lower animals at concentra-tions lower than 10 ng L�1, then ecotoxicological tests are also re-quired. Three problems have been identified with the standardisedecotoxicity tests specified in the guidelines. The first is that the rel-atively narrow range of species used i.e. algae, Daphnia and onefish, may not include the most sensitive species exposed in naturalwater courses. Many types of organisms, such as amphibians arenot considered.

The second problem is that there is no specification for chronictests that reflect the MoA of the drug. Pharmaceuticals are de-signed to have a specific biological effect (Dorne et al., 2007; Chris-ten et al., 2010; Kar and Roy, 2010). They interact with specifichuman target proteins and metabolic pathways. These may behighly conserved and therefore cause analogous effects in otherorganisms (Gunnarsson et al., 2008). Many chronic ecotoxicologi-cal studies using MoA related end points have revealed effect con-centrations that are substantially lower than standardised studies(Crane et al., 2006; Boxall and Greenwood, 2010). Several authorshave suggested that testing could be improved by including tar-geted strategies based on known pharmacological properties andMoA to decrease uncertainties (Fent et al., 2006; Ankley et al.,2007).

The third potential failing of the ecotoxicity tests is that mixtureeffects are not considered. Several compounds in the aquatic envi-ronment may affect the same metabolic pathway or process in nontarget organisms and may produce additive or synergistic or antag-onistic effects (Schnell et al., 2009). This could lead to effects inaquatic organisms that would not occur if exposed to a compoundin isolation.

These problems have led many authors to highlight a need foran intelligent ecotoxicity testing strategy for pharmaceuticals

(Lange and Dietrich, 2002). This includes the use of informationon the MoA of a substance to predict or anticipate effects in a rangeof species and based on this tailor the tests and select species aspart of ERA (Montforts et al., 2007). The use of ‘omics’ based ap-proaches using extrapolation of evolutionary sequence conserva-tion of drug targets could prove a useful method for guiding sucha strategy. In a study by Gunnarsson et al. (2008), a high numberof conserved human drug targets were identified in other species.It is important to note that the existence of a similar protein se-quence in an organism does not automatically mean that the hu-man MoA of the drug will occur. Further work on the 3Dstructure of the proteins is needed to predict drug–protein interac-tions in order to make this information relevant to ecotoxicologicaltests and ERAs (Gunnarsson et al., 2008). In a recent review of tox-icological studies of pharmaceuticals in the aquatic environment,Brausch et al. (2012) highlights the potential and need for furtherresearch of computational toxicology approaches. Molecular dock-ing may be a potential tool in the design of an intelligent test strat-egy as part of the ERA by identifying sensitive species, selectingappropriate test species, selecting MoA related chronic test endpoints for toxicity studies and interpreting the relevance of exist-ing toxicological data.

Molecular docking is frequently used to predict the bindingorientation of small molecule drug candidates to their protein tar-gets in order to predict the affinity and activity of the small mol-ecule. Recently there have been several studies which highlightthe potential of molecular docking to predict the effects of chem-ical pollutants. For example Yang et al. (2011) found that molec-ular docking and post docking analysis can serve as an efficientpre-screening technique for identifying potential chemical estro-gens. Wu et al. (2010) found that homology modeling and molec-ular docking might be a potential tool to predict interactionsbetween contaminants and associated receptors in different tro-phic levels in a study investigating flame retardants and theandrogen receptor in several vertebrate species. Wu et al.(2009) found the results of their AutoDock molecular dockingstudy consistent with those of animal experiments reported inthe literature, indicating that molecular docking would have thepotential to predict the nuclear hormone receptors of environ-mental pollutants.

Two analgesics diclofenac and ibuprofen and the synthetic pro-gesterone levonorgestrel were chosen for investigation into the po-tential for molecular docking to predict ecotoxicological effects ofhuman pharmaceuticals on non target organisms. The rationalefor selection of these drugs were their high usage (Roos et al.,2012), high detection frequency in surface waters (Ellis, 2006)and adverse ecotoxicological effects reported in the literature atenvironmentally relevant concentrations (Cleuvers, 2004; Mehintoet al., 2010; Safholm et al., 2012; Svensson et al., 2013).

In humans, the analgesics diclofenac and ibuprofen act byinhibiting (reversibly or irreversibly) the cyclooxygenase (COX) en-zymes which catalyze the synthesis of prostaglandins (Vane andBotting, 1998). In humans prostaglandins are involved in inflam-mation, pain regulation, regulation of blood circulation especiallyin the kidney, coagulation processes, synthesis of gastric mucosa,vascular permeability and kidney function including ion retentionand ovulation (Mercure and Van Der Kraak, 1996; Sorbera et al.,2001; Fent et al., 2006). There is divided opinion in the literatureas to whether these effects occur in non target organisms such asfish (see Section 4).

Levonorgestrel is a potent testosterone-derived progestin whichbinds to the progesterone receptor (Petit-Topin et al., 2009). It isused, often combined with EE2, as a contraceptive and also for hor-mone replacement therapy. It mimics the effects of the naturalhormone progesterone, involved in regulating the menstrual cycle,pregnancy, and embryogenesis in humans and other species

2570 S.D. Walker, S. McEldowney / Chemosphere 93 (2013) 2568–2577

(Runnalls et al., 2013). Although there has been substantial workdone in assessing the endocrine disruption caused by environmen-tal exposure to EE2, the effects of synthetic progestin’s has hadvery little attention (Runnalls et al., 2013). Levonorgestrel has beenshown to affect reproduction in fish and frogs at environmentalconcentrations. The progesterone receptor is the primary drug tar-get for levonorgestrel but it also affects the androgen, estrogen,glucocorticoid, and mineralocorticoid receptors.

The aim for this work was to carry out molecular docking exper-iments involving the drugs diclofenac, ibuprofen and levonorge-strel with primary drug target homologues found in aquaticorganisms and establish if the results reflected known chronic eco-toxicological effects of the drugs reported in literature.

2. Methods

The bioinformatics software and databases used in this studyare all freely available for academic use.

2.1. Homology search

The primary human drug target protein sequences for prosta-glandin endoperoxide H synthase 2 (PGHS2 or COX2) for diclofe-nac and ibuprofen and the progesterone receptor (PR) forlevonorgestrel were identified using Drug Bank (http://drug-bank.ca/). The order of drug targets listed in DrugBank generallyreflects their importance regarding therapeutic indication or phys-iological effect (Wishart et al., 2008). PR and COX2 are the firstlisted target receptor proteins for these pharmaceuticals. These se-quences were then used in a sequence homology search using theBasic Local Alignment tool, NCBI BLAST (http://blast.ncbi.nlm.nih.-gov/Blast.cgi).

2.2. 3D model creation

The aquatic organisms found to possess sufficient sequencesimilarity with the human drug targets COX2 and PR were selected.These homology sequences were submitted to a fully automatedprotein structure homology-modeling server, Swiss Model(http://swissmodel.expasy.org/) (Peitsch, 1995) in the automatedmode for the creation of 3D protein models. The models werebased on a known crystallized molecular structure of sheepCOX2 PDB 1PXX and human PR PDB 3D90 obtained from RCSB Pro-tein Data Bank (http://www.pdb.org). The quality of the modelswas evaluated using the QMean Z score provided by Swiss Model(Benkert et al., 2011). Q-MEAN Z-score is a useful measure forthe description of the absolute quality of theoretical models andis a valuable measure for identifying significant errors. Q-MEANZ-scores less than �4.0 indicate that part of the protein structureis not modelled correctly. The QMEAN Z-score provides an esti-mate of the absolute quality of a model by relating it to referencestructures solved by X-ray crystallography. The QMEAN Z-score isan estimate of the ‘‘degree of nativeness’’ of the structural featuresobserved in a model by describing the likelihood that a model is ofcomparable quality to high-resolution experimental structures.The three plots available for download visualize the quality of a gi-ven model with respect to these reference structures. The referencestructures are a non-redundant subset of the PDB sharing less than30% pairwise sequence identity among each other and are solved ata resolution below 2 Å.

Small molecule models for the drugs levonorgestrel, diclofenacand ibuprofen were created by converting the SMILES code to apdb file using the conversion programme Cactus (http://cac-tus.nci.nih.gov/translate/).

2.3. Molecular docking

Molecular docking experiments were performed using Auto-Dock 4.0 molecular docking software package (www.scripps.edu).The package is used in combination with AutoDock Tools (ADT) –an accessory programme that allows the user to interact withAutoDock from a Graphic User Interface (GUI). AutoDock is a suiteof automated docking tools designed to predict how small mole-cules/ligands such as substrates or drug candidates, bind to areceptor/protein of known 3D structure. Diclofenac and ibuprofenwere docked with the COX2 protein models: human, Daphnia pulex(water flea), Oncorhynchus mykiss (rainbow trout), Danio rerio (ze-bra fish), Salmo salar (Atlantic salmon) and Xenopus tropicalis (Wes-tern clawed frog). Levonorgestrel was docked with the PR proteinmodels for: human, D. rerio and Xenopus laevis (African clawedfrog).

2.3.1. Preparing the ligand and macromolecule files for AutoDockThe PDB files created in Swiss Model were prepared using the

GUI (graphic user interface) of ADT in order to limit imperfectionsin the PDB files e.g. missing hydrogen atoms, multiple moleculesand added water. First all the hydrogen atoms were removed fromthe macromolecule files. Then polar hydrogen’s were restored. ADTthen checked whether the molecule had charges, if not ADTchecked whether the molecule was a peptide and added Gasteigercharges. Finally solvation parameters were added and the filessaved with .pdbqs extension (where ‘q’ and ‘s’ represent chargeand solvation, respectively).

The ligand files for diclofenac and ibuprofen were also read inADT, all the hydrogens and charges were added and the non-polarhydrogens merged and saved with .pdbqs extension. ADT thenautomatically determined the best root, which is defined as thefixed portion of the ligand from which rotatable branches sprout.Next the rotatable bonds in the ligand were defined, making allamide bonds non-rotatable and the number of active torsionswas set to the fewest atoms. The ligand file was then saved withligand out .pdbq extension (q representing charge).

2.3.2. Preparing the grid parameter fileFor the calculation of docking interaction energy, a three-

dimensional box (grid) was created in which the target location(suspected enzyme active binding site) of the protein moleculewas enclosed. The grid volume was large enough to allow the li-gand to rotate freely, even with its most fully extended conforma-tion. The grid box size was set to 64000 total grid points, with 40points in each of the x, y, z directions. The spacing was set to0.375 Å.

The location of the suspected enzyme binding sites on thereceptor molecules were obtained by opening the pdb files andlocating the co-ordinates for the amino acid residues thought tobe involved in binding diclofenac (Rowlinson et al., 2003) or levo-norgestrel (Petit-Topin et al., 2009). The parameters required tocreate the grid were stored in the grid parameter file with the mol-ecule .gpf extension.

2.3.3. Preparing the docking parameter fileThe docking parameter file, which instructs AutoDock about the

ligand to move, the map files to use, and other properties definedfor the ligand was created. AutoDock’s Lamarckian genetic algo-rithm (LGA) was the algorithm used for the docking file, whichwas stored with the .dpf extension. Finally, the AutoDock job wasrun from the GUI (graphical user interface) created at the Univer-sity of Westminster. Each docking experiment was run 1000 timesand the results stored in docking log files with the .dlg extension.The best 10 docking log files, i.e. those with the lowest energybinding scores in docked ligand complexes were chosen. These

S.D. Walker, S. McEldowney / Chemosphere 93 (2013) 2568–2577 2571

were then read in the ADT viewer. A conformation instance wascreated for each docked result found in the docking log. A confor-mation represents a specific state of the ligand and has either aparticular set of state variables from which all the ligand atoms’co-ordinates can be computed or the co-ordinates themselves.Conformations also have energies: docked energy, binding energy,and possibly per atom electrostatic and van der waals energies.AutoDock 4 computes the free energy of binding and reports a de-tailed energy breakdown.

The molecular dockings were run from the portal created at theUniversity of Westminster (https://autodock-portal.sztaki.hu/).

2.4. Multiple sequence alignment

The multiple sequence alignment program CLUSTALW(www.genome.jp/tools/clustalw/) was used to locate conservedresidues on the COX2 and PR homologues.

3. Results

3.1. Model validation

The quality of the protein models was assessed using theQmean Z score. The Qmen Z scores for all the protein models aredisplayed in Table 1. All the protein models had Qmean Z scoresof greater than �4 and were assessed as reliable (Table 1).

3.2. Diclofenac and ibuprofen

The results of the initial NCBI protein BLAST homology searchrevealed that O. mykiss, D. rerio, S. salar and X. tropicalis have highgene sequence similarity with human COX2. The percentage se-quence identities, accession numbers and Qmean Z scores (Table 1).D. pulex also produces a COX2 enzyme with 46% sequence similar-ity with the human form. The multiple sequence alignment resultsindicate that the amino acids TYR 385 and SER 530 found to beimportant for binding of diclofenac and other NSAID’s (Rowlinsonet al., 2003) by hydrogen bonding are conserved in O. mykiss, S. sal-ar, D. rerio, D. pulex and X. tropicalis (Fig. 1).

The molecular docking experiments for S. salar, D. rerio, O. my-kiss and X. tropicalis with diclofenac or ibuprofen were successful.Ibuprofen and diclofenac both docked in the same ligand bindingpocket of the X. tropicalis, D. rerio, S. salar and O. mykiss COX2homologues. The results show that in each case the ten best (low-est energy) dockings, diclofenac and ibuprofen molecules werepositioned in the same orientation directly on top of one another.This indicates the high reliability and the reproducibility of the re-sults. Control dockings with the human COX2 receptor protein pro-duced the same results. The free energy of binding for each of theseparate experiments ranged from �7.62 to �5.9 kJ mol�1. The freeenergy of binding for each of the drugs to each COX2 homologuewas similar within each separate experiment. The amino acid res-idues tyrosine and serine formed hydrogen bonds with diclofenacand ibuprofen within the same binding pocket of COX2 homo-logues in human, O. mykiss, D. rerio, S. salar and X. tropicalis.

Diclofenac and ibuprofen failed to bind to the D. pulex COX2homologues. This suggests that although the protein was of highsimilarity to the human form, amino acid residue sequence and3D structure differences must prevent it from binding diclofenacor ibuprofen.

3.3. Levonorgestrel

The BLAST homology search found high sequence similaritywith the human PR receptor in the aquatic organisms D. rerio

and X. laevis (Table 1). The multiple sequence alignment resultsfor the PR homologues indicate that the residues MET909 andASN719 found to be important in the binding of levonrgestrel inthe ligand binding cavity of the PR are conserved in X. laevis andD. rerio (Fig. 2). The molecular docking results for levonorgestrelwith the PR homologues of D. rerio and X. laevis showed that thisligand bound to the same binding pocket as in the human controlmodel (Table 1). The free energy of binding was �7.08 kJ mol�1 forD. rerio and �6.32 kJ mol�1 for X. laevis. The 10 lowest energy doc-kings all had the same positioning and orientation of levonorge-strel in the ligand binding pocket. The hydrogen bonding thatoccurred in the docked molecules occurred between levonorgestreland ASN719 as in the human crystallized model. However, nohydrogen bonding occurred with MET909.

4. Discussion

4.1. Diclofenac and ibuprofen

The molecular docking results indicate that the fish O. mykiss, D.rerio, S. salar and the frog X. tropicalis would react in a similar waywhen exposed to diclofenac and ibuprofen as humans if similarinternal concentrations were reached. The hydrogen bonding thatoccurs was similar for all the experiments indicating a strong pos-sibility that these organisms, in all probability, would all respondto diclofenac and ibuprofen in the same way as humans by inhib-iting prostaglandin production. These results suggest that ibupro-fen and diclofenac might cause a concentration addition effect insurface waters.

4.1.1. FishThere is some disparity in ecotoxicological studies performed

with diclofenac and fish. Some published chronic toxicity dataindicates that diclofenac could cause serious adverse effects invertebrate species at environmentally relevant concentrations.Significant reductions in COX2 expression levels in the liver, gillsand kidney of O. mykiss have been reported for diclofenac expo-sure of 1 lg L�1 (Mehinto et al., 2010). Hoeger et al. (2005)showed that diclofenac inhibits prostaglandin synthesis in browntrout (Salmo trutta) in vitro at 100 nM and Cuklev et al. (2011)found that diclofenac affected the expression of multiple genesin exposed fish at concentrations detected in European surfacewaters. Functional analysis of differentially expressed genes re-vealed effects on biological processes such as inflammation andthe immune response, in agreement with the MoA of diclofenacin mammals. These ecotoxciological studies support the resultsof the molecular docking studies performed with the fish COX2homologues and diclofenac. Although a recent study by Memmertet al. (2013) reported a no effect concentration (NOEC) for diclofe-nac in O. mykiss and D. rerio of 320 lg L�1, far higher than environ-mental concentrations. The ibuprofen molecular dockingexperiments for D. rerio here are supported by a recent study byMorthorst et al. (2013) which found that COX2 levels were signif-icantly reduced in D.rerio after exposure to ibuprofen at concen-trations detected in sewage effluent.

Prostaglandins regulate kidney function (Mutschler, 1996; Mor-thorst et al., 2013), therefore a reduced prostaglandin productionin fish may lead to renal complications. Renal failure is the estab-lished cause of the near extinction of vultures in Asia exposed todiclofenac when used as a veterinary medicine (Oaks et al., 2004;Taggart et al., 2007). Renal complications are also a known side ef-fect of NSAIDs in humans (Banks et al., 1995). It is believed that thebioconcentration (BCF) of diclofenac is the reason for the high sen-sitivity of Gyps vultures to diclofenac. Again there is disagreementin the literature as to the BCF of diclofenac in fish. Schwaiger et al.

Table 1Results of molecular docking experiments between cyclooxygenase (COX2) homologues with ibuprofen or diclofenac and progesterone receptor homologues with levonorgestrel.(The receptor enzyme is shown as a blue ribbon and the drug ligand is shown a green molecule; only the lowest free energy of binding for each docking experiment is shown, thefree energy of binding was similar for each for the 10 lowest energy dockings within each experiment).

Receptor Organism Accessionnumber

Percentsequenceidentity (%)

Qmeanz score

Ligand Free energy ofbinding(kJ mol�1)

Picture

COX2 Danio rerio NP_001020675 75 �2.4 Diclofenac �5.13

Ibuprofen �7.62

Salmo salar �3.08 Diclofenac �6.26

Ibuprofen �7.45

Oncorhynchusmykiss

NP_001118139 72 �2.37 Diclofenac �6.62

Ibuprofen �5.9

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Table 1 (continued)

Receptor Organism Accessionnumber

Percentsequenceidentity (%)

Qmeanz score

Ligand Free energy ofbinding(kJ mol�1)

Picture

Xenopustropicalis

NP_001025697 75 �2.48 Diclofenac �6.56

Ibuprofen �5.98

Daphnia pulex EFX85708 46 �2.8 – Failed to bind todiclofenac oribuprofen

PR Danio rerio AAY85275 65 �1.58 Levonorgestrel �7.08

Xenopus laevis NP_001079100 58 0 Levonorgestrel �6.32

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(2004) have reported a BCF of up to 2700 in the liver and kidneys offish and Mehinto et al. (2010) found a BCF of 600 in fish bile. How-ever, recent studies by Memmert et al. (2013) and Cuklev et al.(2011) have reported much lower BCFs of less than 10 in blood,plasma, liver and whole fish samples. Currently standardised eco-toxicity tests which do not incorporate the MoA of the drug orknown mammalian side effects are likely to underestimate the ef-fects of diclofenac. The use of molecular docking information couldprovide direction for ecotoxicity tests based on the likelihood of asimilar MoA occurring. It is still unknown what the effects of re-duced prostaglandin synthesis in fish may have on populationnumbers.

4.1.2. FrogsThe molecular docking experiments show that the X. tropicalis

COX2 also binds diclofenac and ibuprofen in the same bindingpocket by hydrogen bonding to the same amino acid residues as

in the human form. This indicates that the X. tropicalis COX2 en-zyme would be inhibited in a similar way to humans. Currentlyno chronic ecotoxicological studies have been undertaken for X.tropicalis or any frog species, investigating prostaglandin produc-tion with NSAID exposure. This represents a research need in orderto establish the likelihood of ecotoxicological effects of NSAIDs onfrogs. Currently, amphibians are not covered in the ERA guidelinesfor ecotoxicity testing of human pharmaceuticals. Other humanpharmaceuticals entering surface waters may also have effects onfrogs related to the human MoA of the drug. For instance it hasbeen found that the antidepressant sertraline can disrupt the neu-roendocrine system in tadpoles causing developmental toxicity atenvironmentally relevant concentrations (Conners et al., 2009).Over the last 25 years amphibians have declined dramatically inmany areas of the world to the point which amphibians are nowmore threatened than either mammals or birds (Beebee and Grif-fiths, 2005).

Homo sapiens

Oncorhynchus mykiss

Danio rerio

Salmo salar

Xenopus tropicalis

Daphnia pulex

Homo sapiens

Oncorhynchus mykiss

Danio rerio

Salmo salar

Xenopus tropicalis

Daphnia pulex

Homo sapiens

Danio rerio

Salmo salar

Oncorhynchus mykiss

Xenopus tropicalis

Daphnia pulex

Fig. 1. CLUSTAL W multiple sequence alignment of cyclooxygenase (COX2) homologues. (Conserved residues involved in binding of diclofenac and ibuprofen by hydrogenbonding, tyrosine (Y) and serine (S) are highlighted red; Leucine (L) and Isoleucine are highlighted in blue.).

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4.1.3. DaphniaDaphnia is a common invertebrate model organism for fresh-

water systems and plays a central role as an algal grazer andimportant food source for fish (Dietrich et al., 2010). High se-quence similarity (46%) with the human COX2 was found in D.pulex. The multiple alignment shows a high sequence similarityin the regions where the amino acid residues, Ser530 andTyr385, important for binding of NSAIDs are present (Fig. 1). A se-quence similarity of greater than 30% is thought to be a reliablethreshold for homology when sequence alignments contain atleast 150 residues (Brenner et al., 1998), which COX2 does. How-ever, according to homology prediction tools such as Homologene(http://www.ncbi.nlm.nih.gov/homologene), COX2 is only con-served in Euteleostomi. Molecular docking experiments with theD. pulex COX2 homologue were unsuccessful and the ligand failedto bind to the receptor molecule. This could be due to the pres-ence of mutations or differences in the amino acid sequence inthe homologue protein leading to a different secondary and ter-tiary protein structure preventing binding. The Daphnia homo-logue has a different amino acid at position 525. In Daphnia thisresidue is an isoleucine but in the human, O. mykiss and X. trop-icalis homologues, this residue is a leucine. Pouplana et al. (2002)found that an isoleucine in this position could severely restrict ac-cess to the active site of cyclooxygenase. Alternatively the COX2homologue in Daphnia may not serve the same function as in ver-tebrates. Molecular docking may then provide further informationon drug–protein binding interactions and than ortholog/sequencesimilarity predictions. The molecular docking results then suggestthat diclofenac and ibuprofen would not have an impact throughtheir MoA on Daphnia. This is supported by ecotoxicological stud-ies. Chronic multigenerational toxicity of diclofenac on D. magnawas not observed until concentrations reached 40 mgL�1 anddid not appear to be due to any obvious MoA related cause (Die-trich et al., 2010). Ecotoxicological assessment of ibuprofen hasalso revealed a lack of chronic toxicity for Daphnia species (Cleu-vers, 2003; Heckmann et al., 2007).

4.2. Levonorgestrel

The molecular docking experiments indicate that fish and frogPR receptor homologues would bind levonorgestrel in the same

way as humans suggesting similar effects based on the MoA. Lev-onorgestrel binds to the PR receptor and affects the human uterineendometrium and decreases fertility (Runnalls et al., 2013). Eco-toxciological data is scarce for levonorgestrel although adverse ef-fects of levonorgestrel have been reported at environmentallyrelevant concentrations. Severe reduced fertility in the fatheadminnow has been reported at 0.8 ng L�1 (Zeilinger et al., 2009)and in the frog Xenopus (Kvarnryd et al., 2011). It is not possibleto elucidate which effects on fecundity such as egg laying andegg maturation are due to the action of which receptor (androgen,estrogen, PR, glucocorticoid, and mineralocorticoid). However, it isknown that the effect of levonorgestrel on the expression of pro-gesterone is significant at 2 and 200 ng L�1 in zebrafish embryos(Zucchi et al., 2012) and that levonorgestrel has high in vitro andin vivo progestogenic activity (Runnalls et al., 2013). Furthermolecular docking experiments with levonorgestrel and the andro-gen, estrogen, glucocorticoid, and mineralocorticoid receptorswould be beneficial.

4.3. Selection of test organisms

In an ERA the predicted no effect concentration (PNEC) for themost sensitive species tested is the figure used to decide if thereis an environmental risk. Sensitivity to toxicants can vary substan-tially between species (Cleuvers, 2004), making the selection oftest organisms paramount in ensuring a protective PNEC. Daphniais regularly used in ecotoxicity tests but the molecular dockingexperiments suggest that this organism does not have a functionaldrug target receptor for ibuprofen or diclofenac. This sort of infor-mation is highly relevant as Daphnia is less likely to exhibit chronicMoA related effects in this case, although may be appropriate forstandardized toxicity testing.

Molecular docking provides a means of increasing the numberof trophic levels and quantity of species tested without doingany actual testing on animals. AutoDock or other molecular dock-ing software could guide the ecotoxicity tests performed by select-ing organisms which could be exposed and identifying organismswith conserved proteins that would probably be affected throughthe MoA of the drug. These in-silico studies would effectively ex-tend the range of test organisms with no ‘wet’ laboratory workand no need to sacrifice organisms.

Xenopus laevis

Danio rerio

Human

Xenopus laevis

Danio rerio

Human

Fig. 2. CLUSTAL W multiple sequence alignment of the progesterone receptor (PR) homologues. (Conserved residues involved in binding of levonorgestrel by hydrogenbonding, Methionine (M) and Asparagine (N) are highlighted red.).

S.D. Walker, S. McEldowney / Chemosphere 93 (2013) 2568–2577 2575

4.4. Mixture effects

Accurate prediction of mixture toxicity is indispensible for ERA(Cleuvers, 2004). The current ERA does not include additive, syner-gistic or antagonistic effects of mixtures of pharmaceuticals whencalculating exposure concentrations or toxic effect concentrations.Research has repeatedly demonstrated that the additive effects ofmixtures are considerably more pronounced than the effect of eachof its individual components (Kortenkamp, 2009). There is clearlypotential for synergistic and additive effects for ibuprofen and dic-lofenac on aquatic species as they commonly occur as a mixture insurface waters (Ellis, 2006), act on the same drug target and havebeen shown to exhibit combined toxicity following a concentrationaddition concept in toxicity studies (Christensen et al., 2007). It hasalso been suggested that there is substantial potential for additiveand synergistic effects between synthetic progestins (Runnallset al., 2013). Molecular docking experiments such as those de-scribed here could help identify drugs that would bind to the activesite of the same protein or enzyme thereby potentially producingan additive effect that should be investigated in ERAs. In May2012 the European Commission reported engagement in a newprocess to ensure that risks associated with chemical mixturesare properly understood and assessed (European Commission,2012).

4.5. MoA, chronic test end points and molecular docking

Bioinformatics and molecular docking might be a valuable aidin directing the choice of suitable endpoints in chronic ecotoxicitytesting. The molecular docking experiments clearly showed thatthe drugs ibuprofen and diclofenac bound to COX2 proteins in O.mykiss and X. tropicalis suggesting the inhibition of the enzyme.Ecotoxicity tests using COX enzyme inhibition and prostaglandinproduction as test end points have shown that MoA toxicity fordiclofenac occurs in fish species and that a reduction of prostaglan-din synthesis occurs (Mehinto et al., 2010). Although there is stilldisagreement in the literature on the chronic effects of diclofenacon fish. There is no data available on X. tropicalis or ibuprofen, how-ever. It appears from the O. mykiss data that chronic test end pointscould be selected on the basis of the function of target proteins andthe known MoA of the drug, supported by molecular dockingexperiments.

5. Conclusion

There is still little focus on targeted test strategies includingchronic MoA ecotoxicity of mixtures of pharmaceuticals (Gunnars-son et al., 2008; Dietrich et al., 2010). This is because tests are timeconsuming and expensive. There can also be difficulties in selectingappropriate and informative end points based on known pharma-cological properties of the pharmaceutical (Ankley et al., 2007).

Choice of organisms is difficult because it is largely unknownwhich species would be most sensitive to a particular drug. It isunfeasible and unethical to extensively test large numbers oforganisms. As a result protecting the aquatic environment requiresknowledge about conserved drug targets in exposed organisms.This is critical for assessing possible ecotoxicological effects, iden-tification of potentially sensitive species and development of moreefficient ecotoxicity test strategies (Seiler, 2002; Kostich and Lazor-chak, 2008). Bioinformatics databases and analysis tools couldpotentially be useful in this regard, also helping to make chronicecotoxicology tests more appropriate by improving the selectionof test species used and choosing more realistic end points betterfitted to the drug being tested. This work describes a tool whichmay be beneficial for ecotoxicity tests of pharmaceuticasls as a firstscreen to provide indicators for selection of test organisms andMoA related test endpoints.

Acknowledgements

We acknowledge the support of Tamas Kiss and the rest of theinformatics team at the University of Westminster. We thank theUniversity of Westminster for scholarship funding for thisresearch.

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