molecules

Article The Targeted Pesticides as Acetylcholinesterase Inhibitors: Comprehensive Cross-Organism Molecular Modelling Studies Performed to Anticipate the Pharmacology of Harmfulness to Humans In Vitro

Milan Mladenovi´c 1,*, Biljana B. Arsi´c 2,3 ID , Nevena Stankovi´c 1, Nezrina Mihovi´c 1, Rino Ragno 4,5 ID , Andrew Regan 6, Jelena S. Mili´cevi´c 7 ID , Tatjana M. Trti´c-Petrovi´c 7 and Ružica Mici´c 8

1 Kragujevac Center for Computational Biochemistry, Faculty of Science, University of Kragujevac, Radoja Domanovi´ca12, P.O. Box 60, 34000 Kragujevac, Serbia; [email protected] (N.S.); [email protected] (N.M.) 2 Department of Mathematics, Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18000 Niš, Serbia; [email protected] 3 Division of Pharmacy and Optometry, University of Manchester, Oxford Road, Manchester M13 9PT, UK 4 Rome Center for Molecular Design, Department of Drug Chemistry and Technologies, Faculty of Pharmacy and Medicine, Sapienza Rome University, P.le A. Moro 5, 00185 Rome, Italy; [email protected] 5 Alchemical Dynamics srl, 00125 Rome, Italy 6 School of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, UK; [email protected] 7 VinˇcaInstitute of Nuclear Sciences, University of Belgrade, P.O. Box 522, 11001 Belgrade, Serbia; [email protected] (J.S.M.); [email protected] (T.M.T.-P.) 8 Faculty of Sciences and Mathematics, University of Priština, Lole Ribara 29, 38220 Kosovska Mitrovica, Serbia; [email protected] * Correspondence: [email protected]; Tel.: +381-34-336-223

Academic Editor: Diego Muñoz-Torrero


Received: 6 August 2018; Accepted: 24 August 2018; Published: 30 August 2018


Abstract: Commercially available pesticides were examined as Mus musculus and Homo sapiens acetylcholinesterase (mAChE and hAChE) inhibitors by means of ligand-based (LB) and structure-based (SB) in silico approaches. Initially, the crystal structures of simazine, monocrotophos, dimethoate, and acetamiprid were reproduced using various force fields. Subsequently, LB alignment rules were assessed and applied to determine the inter synaptic conformations of atrazine, propazine, carbofuran, carbaryl, tebufenozide, imidacloprid, diuron, monuron, and linuron. Afterwards, molecular docking and dynamics SB studies were performed on either mAChE or hAChE, to predict the listed pesticides’ binding modes. Calculated energies of global minima (Eglob_min) and free energies of binding (∆Gbinding) were correlated with the pesticides’ acute toxicities (i.e., the LD50 values) against mice, as well to generate the model that could predict the LD50s against humans. Although for most of the pesticides the low Eglob_min correlates with the high acute toxicity, it is the ∆Gbinding that conditions the LD50 values for all the evaluated pesticides. Derived pLD50 = f (∆Gbinding) mAChE model may predict the pLD50 against hAChE, too. The hAChE inhibition by atrazine, propazine, and simazine (the most toxic pesticides) was elucidated by SB quantum mechanics (QM) DFT mechanistic and concentration-dependent kinetic studies, enriching the knowledge for design of less toxic pesticides.

Keywords: pesticides; AChE; conformational analysis; QSAR; molecular docking; molecular dynamics; quantum-chemical studies; concentration-dependent kinetic studies

Molecules 2018, 23, 2192; doi:10.3390/molecules23092192 www.mdpi.com/journal/molecules Molecules 2018, 23, 2192 2 of 37

1. Introduction Pesticides [1] are either chemical or biological agents, widely used in agriculture [2], that deter, incapacitate, kill, or otherwise discourage pests. Their inappropriate administration leads to contaminated food while intentional release pollutes the environment, especially the soil, groundwater and natural waterways [3]. The uptake of contaminated food and water is potentially toxic to humans and other species. Pesticides mostly, exert toxicity by inhibiting the enzyme acetylcholinesterase (AChE) [4] which degrades acetylcholine (ACh), an essential neurotransmitter in the central nervous system (CNS) of insects, rodents, and humans [5]. AChE competitive inhibitors interrupt the physiology of autonomic ganglia, as well as, neuromuscular, parasympathetic and sympathetic effector junctions [6], controlled by ACh. However, little is known about the pharmacology of pesticides acting as AChE inhibitors. This report considers the pharmacology of common agricultural pesticides used in particular in the Western Balkans region [7,8]: atrazine, simazine, propazine, carbofuran, monocrotophos, dimethoate, carbaryl, tebufenozide, imidacloprid, acetamiprid, diuron, monuron, and linuron (Table1). Despite their widespread usage, experimental crystal structures deposited at Cambridge Crystallographic Data Centre (CCDC) are available only for simazine [9], monocrotophos [10], dimethoate [11], and acetamiprid [12], highlighting the poor availability of either ligand-based (CCDC deposition) or structure-based (Protein Data Bank (PDB) deposition) information about these compounds. Triazines, such as atrazine, simazine, and propazine [13], are used as herbicides in crabgrass supression. Carbamates (carbofuran and carbaryl) are used against potato beetle; carbofuran was found extremely toxic for humans [14]. Organophosphate pesticides (monocrotophos and dimethoate) are used as insecticides [15]. Dimethoate is widely used to kill insects and as an insecticide for crops, vegetables, orchards, as well as for residential purposes [16]. Tebufenozide (a dialkylhydrazine pesticide) is used for plant protection [17]. Imidacloprid and acetamiprid, as neonicotinoids, are prescribed for the control of sucking insect pests (aphids, whiteflies, plant-hoppers, and thrips) and a number of coleopteran pests [17,18]. Diuron (a methylurea pesticide) is used to protect fruit, cotton, sugar cane and wheat [13]. Linuron and monuron (phenylurea pesticides) are plant protection agents [19]. Lethal doses for house and field mouse Mus musculus, for all of the above-mentioned pesticides, are known (Table1)[ 20–31]. Lethal doses for Homo sapiens were calculated (Table1) according to the recommendations of Reagan-Shaw et al. [32], using Equation (1):

animal K , HED = animal dose m (1) human Km where HED is human equivalent dose in mg/kg of body weight, animal dose is used dosage for the specific model organism in mg/kg of body weight, animal Km factor is equal to 3, human Km factor is equal to 37. The overexposure to pesticides results in the AChE inhibition at brain and nervous system nerve endings, as well as with other types of AChE found in the blood [33]; as a consequence, the ACh concentration increases its effects. Although, the AChE inhibition by pesticides listed in Table1 is firmly established and the lethal doses are known, their behaviour in the inter-synaptic space and their interaction within the AChE active site, are still poorly investigated. Bearing in mind that different ACh conformations can trigger different receptors (nicotinics and muscarinics, respectively), conformational analysis (CA, ligand-based (LB) approach) could be considered as a computational tool to predict pesticides behaviour before their interaction with AChE [34]. Due to the lack of crystal structures of any pesticides co-crystallized with AChE, CA can be used to gather pesticide conformations that are, upon the interaction with AChE, going to be transformed into the bioactive ones [35]. Molecules 2018, 23, 2192 3 of 37 MoleculesMolecules 2018 2018, 23,, x23 , x 3 of 337 of 37 MoleculesMolecules 2018 20182018, 23,, , x 2323 ,, xx 3 of 3337 ofof 3737 MoleculesMolecules 2018 20182018, 23,, , x 2323 ,, xx 3 of 3337 ofof 3737 MoleculesMoleculesMolecules 2018 20182018,, 23,, , ,x x 2323 ,, xx 3 of 3373 ofof 3737 50 50 TableTable 1. Acetylcholine 1. Acetylcholine and and training training set pesticidesset pesticides structur structures ases well as well as their as their oral or acuteal acute toxicities toxicities (LD (LD50 50 TableTableTable 1. 1.Acetylcholine Acetylcholine 1. Acetylcholine and and training training set set pesticidesset pesticides pesticides structur structures structures ases well as well as their as as their theiroral or acute oralal acute toxicities acute toxicities toxicities (LD (LD50 50 (LD TableTable 1. Acetylcholine 1. Acetylcholine and and training training set pesticidesset pesticides structur structures ases well as well as their as their oral or acuteal acute toxicities toxicities (LD (LD50 50 50 Tablevalues)values)Table 1. against Acetylcholine 1. against Acetylcholine Mus Mus musculus and musculus and training (uppertraining (upper set values); pesticidesset values); pesticides training structurtraining structur setes setpesticides ases pesticideswell as well as calculatedtheir as calculated their oral or acute oralal acuteoral acutetoxicities acutetoxicities toxicities toxicities(LD (LD50 50 Tablevalues)Tablevalues)Table 1. against AcetylcholineAcetylcholine 1.1. against AcetylcholineAcetylcholine Mus Mus musculus andand musculus and andtrainingtraining (uppertrainingtraining (upper setset values); pesticides pesticidessetset values); pesticidespesticides training structurstructur training structurstructur setes pesticidesset aseses wellpesticides asas wellwell as calculatedtheir asas calculatedtheirtheir oral or oracute oralalal acute acuteoral acutetoxicities acutetoxicitiestoxicities toxicities (LDtoxicities (LD50(LD 5050 values)values)values) against against againstMus Mus Mus musculusmusculus musculus (upper(upper (upper values); values); values); training trainingtraining set setpesticides pesticides pesticides calculated calculated calculated oral oral acute oral acute toxicities acute toxicities toxicities (LDvalues)(LDvalues)50 values) 50against values) against against Mus against Mus musculusHomo Homomusculus sapiens sapiens(upper (upper(lower (lowervalues); values,values); values, training bold training bold and set and italic)pesticidesset italic)pesticides [32]. [32]. calculated calculated oral oral acute acute toxicities toxicities values)(LDvalues)(LDvalues)50 values) 50against values) againstagainst against Mus against MusMus musculusHomo musculusmusculusHomo sapiens (uppersapiens (upper(upper(lower values);(lower values,values);values); values, training bold trainingtraining bold and set and italic)pesticidessetset italic)pesticidespesticides [32]. [32]. calculatedcalculated calculatedcalculated oraloral oral oral acuteacute acuteacute toxicitiestoxicities toxicitiestoxicities (LD(LD(LD50values) values)50 values) againstagainst against HomoHomo Homo sapiens sapiens sapiens (lower(lower (lower values, values, values, bold bold and and anditalic) italic) italic) [32]. [32]. [32 ]. (LD50 50 values)50 against Homo sapiens (lower values, bold and italic) [32]. (LD50 50 values) against Homo sapiens (lower values, bold and italic) [32]. (LD(LD(LD50 values)50values) values) against againstagainst Homo HomoHomo sapiens sapienssapiens (lower (lower50(lower 50values, values,values, bold boldbold and and anditalic) italic)italic) [32]. [32].[32]. 50 50 LD50LD 50 LD50LD 50 Pesticide Structure LD50LD 50 Ref. Pesticide Structure LD50LD 50 Ref. PesticidePesticidePesticide StructureStructureStructure LD50LD 50 Ref.Ref.Ref. PesticidePesticidePesticide Structure Structure Structure LD50LD 50 Ref.Ref.Ref. PesticidePesticide StructureStructure (mg/kg)LD(mg/kg)50LD 50 Ref.Ref. PesticidePesticide Structure Structure (mg/kg)LD(mg/kg)50LD 50 Ref.Ref. PesticidePesticide StructureStructure (mg/kg)LDLD(mg/kg)(mg/kg)50LD50LD 5050 Ref.Ref. PesticidePesticide Structure Structure (mg/kg)LD(mg/kg)(mg/kg)50LDLD 5050 Ref.Ref. PesticidePesticidePesticide Structure StructureStructure (mg/kg)(mg/kg)(mg/kg) Ref.Ref.Ref.Ref. Pesticide PesticidePesticidePesticide Structure Structure Structure (mg/kg)(mg/kg)(mg/kg) Ref.Ref.Ref. Ref. (mg/kg)(mg/kg)(mg/kg)(mg/kg) (mg/kg)(mg/kg)(mg/kg) 0.8500.850 50005000 atrazineatrazine 0.8500.8500.850 [20][20] tebufenozide tebufenozide 500050005000 [29][29] atrazineatrazineatrazine 0.06890.8500.06890.850 [20][20][20] tebufenozide tebufenozidetebufenozide 405.405000405.405000 [29][29][29] atrazineatrazine 0.06890.8500.8500.06890.06890.8500.850 [20][20][20] tebufenozide tebufenozidetebufenozide 405.405000405.40405.4050005000 [29][29][29] atrazineatrazineatrazineatrazine 0.06890.0689 [20][20[20] [20]] tebufenozide tebufenozidetebufenozidetebufenozide 405.40405.40 [29][29] [29][29 ] 0.06890.06890.06890.0689 405.40405.40405.40

3.183.18 131131 propazinepropazine 3.183.183.18 [21][21] imidacloprid imidacloprid 131 131131 [30][30] propazinepropazine 0.2583.180.2583.18 [21][21][21] imidacloprid imidaclopridimidacloprid 10.6213110.62 131 [30][30][30] propazinepropazine 0.2583.183.180.2580.2583.18 3.18 [21][21][21] imidacloprid imidaclopridimidacloprid 10.6213110.6210.62 131131 [30][30][30] propazinepropazinepropazine 0.2580.258 [21][21[21] [21]] imidacloprid imidaclopridimidaclopridimidacloprid 10.6210.62 [30][30] [30][30 ] 0.2580.2580.2580.258 10.6210.6210.62

5 55 18 1818 simazinesimazine 5 5 [24][24] acetamipridacetamiprid 18 18 [31][31] simazinesimazinesimazine 0.40555 0.405 5 [24][24][24] acetamiprid acetamipridacetamiprid 14.921814.92 18 [31][31][31] simazinesimazinesimazine 0.4055 0.4050.405 55 [24][24][24] acetamiprid acetamiprid 14.921814.92 14.9218 18 [31][31][31] simazinesimazinesimazinesimazine 0.4050.405 [24][24[24] [24]] acetamiprid acetamipridacetamipridacetamiprid 14.9214.92 [31][31] [31][31 ] 0.4050.4050.4050.405 14.9214.9214.92 0.405 14.92

O O O O O O O O N O NO O 2 2 500500 NH O HON OO O 2 2 500 500 carbofurancarbofuran NH NHO O 2 2 [25][25] diurondiuron 500 500 [22][22] carbofurancarbofuran HN HNO OO O 22 2 [25][25] diurondiuron 500 500 [22][22] carbofurancarbofuran NH HNON OO O 0.1622 0.162 2 [25][25] diurondiuron 40.5450040.54 500 [22][22] carbofurancarbofuran NH HO O O 0.1622 0.1620.162 22 [25][25[25] ] diurondiurondiuron 40.5450040.5440.54 500500 [22][22] [22 ] carbofurancarbofurancarbofuran H HH O O 0.1620.1620.162 [25][25] [25] diurondiurondiuron 40.5440.54 [22][22] [22] O OO 0.1620.162 40.5440.54 0.1620.1620.162 40.5440.5440.54

14 14 17001700 monocrotophosmonocrotophos 1414 1414 [26][26] monuronmonuron 170017001700 [23][23] monocrotophosmonocrotophosmonocrotophos 1.135141.135 14 [26][26[26][26] ] monuronmonuronmonuron 437.841700437.841700 [23][23][23] [23 ] monocrotophosmonocrotophos 1.1351.135141.135 1.13514 14 [26][26][26] monuronmonuron 437.841700437.84437.8417001700 [23][23][23] monocrotophosmonocrotophosmonocrotophos 1.1351.135 [26][26] [26] monuronmonuronmonuron 437.84437.84 [23][23] [23] 1.1351.135 437.84437.84 1.1351.135 437.84437.84

6060 6060 240024002400 dimethoatedimethoatedimethoate 60 60 [27][27[27][27] ] linuronlinuronlinuronlinuron 24002400 [19][19][19] [19 ] dimethoatedimethoate 4.864.8660 4.86 60 [27][27] linuronlinuron 194.592400194.592400 [19][19] dimethoatedimethoate 4.8660 4.864.86 6060 [27][27] linuronlinuron 194.592400194.59194.5924002400 [19][19] dimethoatedimethoatedimethoate 4.864.86 [27][27] [27] linuronlinuronlinuron 194.59194.59 [19][19] [19] 4.864.86 4.86 194.59194.59194.59

100100100 100 carbarylcarbarylcarbaryl 100 100 [28][28[28][28] ] acetylcholine acetylcholineacetylcholineacetylcholine carbarylcarbaryl 8.111008.118.11 100 [28][28] acetylcholine acetylcholine carbarylcarbarylcarbaryl 8.111008.11 8.11100 100 [28][28][28] acetylcholine acetylcholine carbarylcarbarylcarbaryl 8.118.11 [28][28] [28]acetylcholine acetylcholineacetylcholine 8.118.11 8.11

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The AChE [36 AChE]. active The active AChE site site comprises comprises active the site the aromatic comprises aromatic the twoanionicanionictwo independent independentdomain, domain, which units, which units, comprisingaccommodates accommodatescomprising 614 614 theamino the aminoACh AChacids positive acids positive [36]. [3 Thequaternary6]. quaternaryThe AChE AChE active amine, active amine, site and site comprises and the comprises the esterase esterase the thearomatic catalytic aromaticcatalytic aromaticanionictwotwoanionicanionictwo independent independentanionicindependentdomain, domain,domain, domain,which units, whichwhich units,units, accommodatescomprising which accommodatescomprisingaccommodatescomprising accommodates 614 614 614theamino the aminotheAChamino AChacidsACh positive acidsacids the positive positive[36]. ACh[3[3 Thequaternary6].6]. ThequaternaryThequaternary positiveAChE AChEAChE active amine, quaternary activeactive amine,amine, site and site sitecomprises andand the comprisescomprises amine, thetheesterase esteraseesterase the andthethe aromaticcatalytic aromatic aromaticcatalyticcatalytic the esterase anionicdomain,domain,anionic domain, containing domain, containing which whichthe theaccommodates catalytic accommodatescatalytic triad triad Ser203,the Ser203,the ACh ACh His4 positive His4 positive47, 47,and quaternary and Glu334quaternaryquaternary Glu334 with amine, with amine,amine, the andthe purpose andand purposethe the theesterase of esteraseesterase hydrolysingof hydrolysing catalytic catalyticcatalytic anionicdomain,anionicdomain,anionic domain, containing domain,domain, containing which whichwhichthe accommodates thecatalytic accommodates accommodatescatalytic triad triad Ser203,the Ser203, the theACh ACh AChHis4 positive His4 positive47,positive 47,47,and quaternaryquaternary andand Glu334 quaternaryquaternary Glu334Glu334 with amine,amine, withwith amine,amine, the andand thethepurpose and and purposethepurposethe the theesteraseesterase of esteraseesterase hydrolysingofof hydrolysing hydrolysingcatalyticcatalytic catalyticcatalytic catalyticthedomain,thedomain, ACh ACh domain, tocontaining acetatetocontaining acetate containing and the and choline.the catalytic choline. catalyticthe The triad The catalytic estertriad Ser203,ester hydrolysisSer203, hydrolysis triadHis4 His447, Ser203,reaction 47,and reaction and Glu334 leads His447, Glu334 leads towith the towith and the formation the Glu334formationpurpose purpose of withof anof hydrolysingof acetylated-an hydrolysing the acetylated- purpose of domain,the domain,thethedomain,ACh AChACh containingto acetate tocontainingtocontaining acetateacetate and the andand choline. thethecatalytic choline. choline. catalyticcatalytic The triad TheThe estertriadtriad Ser203, esterester hydrolysis Ser203,Ser203, hydrolysishydrolysis His4 His4His447, reaction 47,and47, reactionreaction andand Glu334 leads Glu334Glu334 leadsleads towith the towithtowith thetheformation the the purposeformationformation purposepurpose of of an ofof hydrolysing of of acetylated-anan hydrolysinghydrolysing acetylated-acetylated- hydrolysingenzyme.theenzyme.the theACh AChACh toThen, acetate the toThen,to acetate acetatethe ACh the acetyl-enzymeand toacetyl-enzymeandand choline. acetate choline.choline. 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Given Given that that the the pharmacology pharmacology of theof the majority majority of widelyof widely used used pesticides pesticides (Table (Table 1) is1) still is still poorly poorly (Figure[33].[33].[33]. Given1b) Given [33 that]. that the thepharmacology pharmacology of theof themajority majority of widelyof widely used used pesticides pesticides (Table (Table 1) is1) still is still poorly poorly understood,understood,GivenGiven that the that the thefocus the focuspharmacology ofpharmacology thisof this study study of was theof was tothe majority provideto majority provide of the widelyof the LBwidely LBor used SBor used SBcheminformatics-based pesticides cheminformatics-based pesticides (Table (Table 1) is1) still guidelinesis stillguidelines poorly poorly understood,Givenunderstood,GivenGivenGiven that that the thatthat the thefocus thepharmacologythefocuspharmacology of pharmacologypharmacology thisof this study study of was of the of ofwas the to thethemajority provide majorityto majoritymajority provide of the widely ofof the LB widely widely LBor used SBor usedused usedSBcheminformatics-based pesticides cheminformatics-based pesticidespesticides pesticides (Table (Table(Table (Table1) is 1)1) still guidelinesis1is) still still guidelines ispoorly still poorlypoorly poorly forunderstood, forunderstood,several several important the important the focus focus tasks, of tasks, thisof andthis study and unresolvedstudy unresolved was was to provide toquestions: provide questions: the (1)the LB (1)how LBor how SBor to SBcheminformatics-based defineto cheminformatics-baseddefine the the pesticides’ pesticides’ structures guidelines structures guidelines in in understood,understood,for understood,forforseveralunderstood, severalseveral important the the importantimportant focus thethefocus focusfocus tasks, ofof tasks, tasks,this ofof and thisthis study study andand unresolved studystudy unresolvedunresolvedwas was waswas to to provide toquestions:to provide provide provide questions:questions: the the(1) thetheLB (1)how(1) LB orLB how how SB or orto SBcheminformatics-based defineSB toto cheminformatics-baseddefinecheminformatics-baseddefine cheminformatics-based the thethepesticides’ pesticides’pesticides’ structures guidelines structuresstructures guidelinesguidelines guidelines in inin aqueousfor aqueousforforseveral severalseveral solution important solution importantimportant prior tasks,prior tasks,tasks,to andtointeraction andandinteraction unresolved unresolvedunresolved with with questions: AChE questions:questions: AChE? 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(2)(2)howimportant howimportanthow to definetoto assignmentsdefinedefine assignments the thethepesticides’ pesticides’pesticides’of theof the LBbioactive LBbioactiveorbioactive orSB SB inprotocolsconformations aqueousprotocolsconformations applied solution applied upon hereinupon priorhereinthe thewereinteraction to wereinteraction interactionto provideto providewith with answersAChE? with answersAChE? AChE? Otherto Otherseveralto severalimportant (2) important important how important toassignments defineassignmentsquestions: questions: the of (1) pesticides’theof (1)is the thereLBis thereLBor anyorSB bioactive any SB conformationsprotocolsconformationsprotocolsconformations applied applied upon hereinuponupon hereinthe thethewereinteraction wereinteractioninteraction to provideto providewith withwith answersAChE? answersAChE?AChE? Otherto severalOthertoOther severalimportant important importantimportant important assignments assignmentsassignmentsquestions: questions: of (1) theofof (1)is the the LBthereis thereLBLBor any SBoror any SBSB conformationspossibilityprotocolspossibilityprotocols applied to appliedanticipate uponto anticipate herein the herein interactionthe were the pesticides were pesticides to provideto with provideacute acute AChE? answers toxicity answers toxicity Other fromto fromseveralto importantpre-bound several pre-bound important important assignmentsconformations, conformations, questions: questions: of before (1) the before (1)is LB thethereis or thethere actual SB any actual protocols any protocolspossibilityprotocolspossibilityprotocols applied to appliedanticipate appliedto anticipate herein hereinherein the were thepesticides werewere pesticides to providetoto provideacuteprovide acute answers toxicity answers answerstoxicity fromto from severalfromtoto pre-bound severalseveral pre-boundpre-bound important importantimportant conformations, conformations,conformations, questions: questions:questions: before (1) before before (1)is(1) therethe isis thetherethethereactual any actualactual anyany appliedpossibilityinteractioninteractionpossibility herein towith anticipate weretowith anticipate AChE? toAChE? provide the (2)the pesticides (2) pesticidescan answerscan the acutethe pesticides’ acute topesticides’ toxicity several toxicity fromacute important fromfromacute pre-bound toxicity pre-bound pre-boundtoxicity questions: be conformations, be quantifiedconformations,conformations, quantified (1) is from therebefore from beforebefore the any the the thebound the possibilityactual bound actualactual to possibilityinteractionpossibilityinteractioninteractionpossibility towith anticipate to towithwith anticipate anticipateAChE? AChE?AChE? the (2) thethepesticides (2)(2) pesticidescanpesticides cancan the acute thethepesticides’ acuteacute pesticides’pesticides’toxicity toxicitytoxicity fromfromacute fromacutefromacute pre-boundpre-bound toxicity pre-bound pre-bound toxicitytoxicity be conformations,conformations, be bequantified conformations,conformations, quantifiedquantified from beforebefore fromfrom beforebefore the thethe thethe boundthe theactualactual bound bound actualactual anticipate interaction interactioninteraction the with pesticides withwith AChE? AChE?AChE? acute (2) (2)(2)can toxicity cancan the the thepesticides’ from pesticides’pesticides’ pre-bound acute acute toxicity conformations, toxicity be bequantified quantified before from thefrom actualthe the bound interactionbound interaction interaction interaction with withwith AChE? AChE?AChE? (2) (2)(2)can can canthe thethepesticides’ pesticides’pesticides’ acute acuteacute toxicity toxicitytoxicity be bebequantified quantifiedquantified from fromfrom the thethebound boundbound with AChE? (2) can the pesticides’ acute toxicity be quantified from the bound conformations, upon the actual interaction with AChE? To the best of our knowledge, there are no previous reports on MoleculesMolecules 20182018,, 2323,, 2192x 44 ofof 3737

conformations, upon the actual interaction with AChE? To the best of our knowledge, there are no eitherprevious LB orreports SB efforts on either to predict LB or the SB bioactive efforts to conformations predict the bioactive of investigated conformations pesticides of (Tableinvestigated1) for bothpesticides mouse (Table and human 1) for both AChEs, mouse as well and ashuman to enumerate AChEs, theiras well acute as to toxicities enumerate by means their acute of free toxicities energy ofby formation means of free (Eglob_min energy) inof theformation aqueous (E solutionglob_min) in and/or the aqueous free energy solution of and/or binding free (∆ Genergybinding )of to binding AChE. All(∆G thebinding cheminformatics) to AChE. All the findings cheminformatics were externally findings validated were externally on the series validated of other on the commonly series of usedother pesticidescommonly (Table used2 pesticides), also known (Table as AChE2), also inhibitors known as (i.e., AChE the inhibitors test set). (i.e., the test set).

FigureFigure 1.1. The crystal structure of hhAChEAChE (PDB (PDB ID: ID: 4EY5) 4EY5) in in complex complex with with huperzine huperzine A A (a ().a ).Subunit Subunit A Ais isdepicted depicted in inpink pink ribbons ribbons wherea whereass the the B Bsubunit subunit is iscoloured coloured in inor orange.ange. Huperzine Huperzine A Ais ispresented presented in inblack black and and its its structure structure is is highlighted highlighted with with dashed dashed lines. lines. The The anionic anionic sub-site is described byby blueblue spheres,spheres, whilewhile thethe esteraseesterase sub-areasub-area isis encircledencircled byby redred spheres.spheres. For thethe sakesake ofof clarity,clarity, hydrogenhydrogen atomsatoms werewere omitted.omitted. The graphic was generatedgenerated using thethe UCSFUCSF ChimeraChimera softwaresoftware (Resource(Resource forfor Biocomputing,Biocomputing, Visualization,Visualization, and InformaticsInformatics (RBVI),(RBVI), UniversityUniversity of California,California, San Francisco,Francisco, CA, USA).USA). BiochemicalBiochemical mechanismmechanism ofof AChACh hydrolysishydrolysis byby AChEAChE ((bb).).

TheThe testtest setset waswas compiledcompiled ofof organophosphates,organophosphates, carbamatescarbamates andand structurallystructurally non-classifiednon-classified pesticides.pesticides. Regarding organophosphates, chlorpyrifos [[37],37], DDVP [14], [14], fenitrothion [[38],38], azinphos- methylmethyl [[39],39], nalednaled (dibrom)(dibrom) [[40],40], TCVPTCVP [[41],41], parathion [[39],39], methyl parathion [[42],42], diazinon [[43],43], phosmetphosmet [[14],14], azamethiphosazamethiphos [[44],44], andand terbufosterbufos [[45],45], respectively, areare usedused asas insecticides.insecticides. Moreover, glyphosateglyphosate isis aa broad-spectrumbroad-spectrum systemicsystemic herbicideherbicide andand cropcrop desiccantdesiccant [[46],46], malathionmalathion isis mostlymostly usedused forfor mosquitomosquito eradicationeradication [[47],47], parathionparathion isis usedused asas anan acaricide.acaricide. PhosmetPhosmet isis mainlymainly usedused onon appleapple treestrees toto controlcontrol codlingcodling mothmoth andand onon aa numerousnumerous fruitfruit crops,crops, ornamentals,ornamentals, andand wineswines forfor thethe controlcontrol ofof aphids,aphids, suckers,suckers, mites,mites, andand fruitfruit flies.flies. TerbufosTerbufos isis aa nematicidenematicide usedused onon corn,corn, sugarsugar beetsbeets andand graingrain sorghum,sorghum, andand it it is extremelyis extremely toxic toxic to birds. to birds. On the On other the hand, other carbamate hand, carbamate pesticides, pesticides, such as methomyl such as andmethomyl methiocarb and methiocarb are used against are used insects; against oxamyl insects; is anoxamyl extremely is an extremely toxic pesticide toxic topesticide humans, to fish,humans, and fish, and birds [48–50], whereas methiocarb is additionally used as a bird repellent, acaricide and

Molecules 2018, 23, 2192 5 of 37 birds [48–50], whereas methiocarb is additionally used as a bird repellent, acaricide and molluscicide. Molecules 2018, 23, x 5 of 37 MoleculesMolecules 2018,, 23 20182018,, xx ,, 2323,, xx 5 of 37 55 ofof 3737 AmongMoleculesMoleculesMolecules the 20182018 structurally,,, 2323 20182018,,, xxx ,,, 2323,,, xxx non-classified pesticides, 2,4-D is widely used as a herbicide, which55 ofofmimics 3737 55 ofof 3737 the actionmolluscicide.molluscicide. ofmolluscicide. the plant Among growth AmongAmong the structurally hormonethethe structurallystructurally auxin,non-classified non-classifiednon-classified resulting pesticides, in thepesticides,pesticides, uncontrolled 2,4-D 2,4-D2,4-Dis widely isis growth widelywidely used usedas andused a herbicide, eventual asas aa herbicide,herbicide, death in molluscicide.molluscicide.molluscicide. Among AmongAmong the structurally thethe structurallystructurally non-classified non-classifiednon-classified pesticides, pesticides,pesticides, 2,4-D 2,4-D2,4-Dis widely isis widelywidely used asusedused a herbicide, asas aa herbicide,herbicide, susceptiblewhichwhichwhich mimics plants mimicsmimics the [ 14action thethe]; DDT actionaction of the is of originallyof plant thethe plantplantgrowth developed growthgrowth horm onehormhorm as auxin, anoneone insecticide, auxin,auxin, resulting resultingresulting usedin the toinin uncontrolled controlthethe uncontrolleduncontrolled malaria growth and growthgrowth typhus, whichwhichwhich mimics mimicsmimics the action thethe actionaction of the ofof plant thethe plantplantgrowth growthgrowth horm onehormhorm auxin,oneone auxin,auxin, resulting resultingresulting in the inin uncontrolled thethe uncontrolleduncontrolled growth growthgrowth andand as eventualandand a contact eventualeventual death poison death deathin susceptible against inin susceptiblesusceptibleseveral plants plantsplants [14]; arthropods DDT [14];[14]; DDTisDDT originally [51 isis]; originallyoriginally DEET developed is developeddeveloped the most as an commonasasinsecticide, anan insecticide,insecticide, active used ingredienttousedused toto andand eventualeventualandand eventualeventual deathdeath death death inin susceptiblesusceptible inin susceptiblesusceptible plantsplants plantsplants [14];[14]; DDT DDT[14];[14]; isDDTisDDT originallyoriginally isis originallyoriginally developeddeveloped developeddeveloped asas anan asasinsecticide,insecticide, anan insecticide,insecticide, usedused tousedtoused toto controlcontrolcontrol malaria malariamalaria and typhus, andand typhus,typhus, and as andand a contact asas aa contactcontact poison poisonpoison against againstagainst several severalseveral arthropods arthropodsarthropods [51]; DEET [51];[51]; DEETDEET is the ismostis thethe mostmost incontrolcontrol insectcontrolcontrol malariamalaria repellents malariamalaria andand typhus, fortyphus, andand protection typhus,typhus, andand asas andand aa against contactcontact asas aa contactcontact poisonpoison mosquitoes, poisonpoison againstagainst againstagainst ticks,severalseveral severalseveral fleas, arthropodsarthropods chiggers, arthropodsarthropods [51];[51]; leeches DEET DEET [51];[51]; DEETDEET isis and thethe ismostismost many thethe mostmost biting commoncommoncommon active activeactive ingredient ingredientingredient in insect inin insectinsect repellents repellentsrepellents for pr forotectionfor prprotectionotection against againstagainst mosquitoes mosquitoesmosquitoes,, ticks,ticks,,,, ticks,ticks,fleas,ticks,fleas, fleas,fleas,chiggers,fleas,chiggers, chiggers,chiggers,chiggers, insectscommoncommoncommoncommon [52 activeactive]. activeactive ingredientingredient ingredientingredient inin insectinsect inin insectinsect repellentsrepellents repellentsrepellents forfor prpr forotectionfor prprotectionotection against againstagainst mosquitoes mosquitoesmosquitoes,, ticks,ticks,,,, ticks,fleas,ticks,ticks,fleas, fleas,chiggers,fleas,fleas,chiggers, chiggers,chiggers,chiggers, leechesleechesleechesleeches andand manymany andand manymany bitingbiting bitingbiting insectsinsects insectsinsects [52].[52]. [52].[52]. leechesleechesleechesleechesleeches andand manymany andandand manymany many bitingbiting bitingbitingbiting insectsinsects insectsinsectsinsects [52].[52]. [52].[52].[52]. Table 2. Test set pesticides structures and their oral acute toxicities (LD50 values) against Mus musculus Table TableTable2. Test 2. 2.set TestTest pesticides setset pesticidespesticides structures structuresstructures and their andand oral theirtheir acute oraloral toxicities acuteacute toxicitiestoxicities (LD50 values) values)(LD(LD5050 values)values)values) againstagainst againstagainstagainst Mus musculus MusMus musculusmusculus Table Table2. Test 2. set Test pesticides set pesticides structures structures and their and oral their acute oral toxicitiesacute toxicities (LD5050 values) values)(LD505050 values)values) againstagainst againstagainst Mus musculus Mus musculus (upperTable Table2.Table values); Test 2. 2.set TestTest pesticides test setset set pesticidespesticides pesticides structures structuresstructures calculatedand their andand oral theirtheir oral acute oraloral acute toxicities acuteacute toxicities toxicitiestoxicities (LD5050 (LDvalues) values)(LD(LD5050 values)values)values)values) againstagainst againstagainstagainst Mus against musculus MusMusHomo musculusmusculus sapiens (upper(upper(upper values); values);values); test set testtest pesticides setset pesticidespesticides calculated calculatedcalculated oral acute oraloral toxicitiesacuteacute toxicitiestoxicities (LD50 values)(LDvalues)(LD5050 values)values)values) againstagainst againstagainstagainst Homo HomosapiensHomo sapienssapiens (upper(upper(upper(upper values);values); values);values); testtest setset testtest pesticidespesticides setset pesticidespesticides calculatedcalculated calculatedcalculated oraloral acuteacute oraloral toxicitiesacutetoxicitiesacute toxicitiestoxicities (LD(LD5050 values)(LDvalues)(LD505050 values)values) againstagainst againstagainst Homo Homosapiens sapiens (lower(upper(upper(upper(upper(upper values, values);values); values);values);values); bold testtest setset and testtesttest pesticidespesticides italic) setsetset pesticidespesticidespesticides [32 calculatedcalculated]. calculatedcalculatedcalculated oraloral acuteacute oraloraloral toxicitiesacutetoxicitiesacuteacute toxicitiestoxicitiestoxicities (LD(LD5050 values)(LDvalues)(LD(LD50 values)values)values) againstagainst againstagainstagainst Homo HomosapiensHomo sapienssapiens (lower(lower(lower(lower values,values, values,values, boldbold andand boldbold italic)italic) andand italic)[32].italic)[32]. [32].[32]. (lower(lower(lower(lower(lower values,values, values,values,values, boldbold andand boldboldbold italic)italic) andandand italic)[32].italic)[32].italic) [32].[32].[32].

LD50 LD5050 LD50 LD5050 LDLD5050 LD5050 LD50 LD5050 Pesticide Structure LD5050 LDLD505050 Ref. Pesticide Structure LD5050 LDLD505050 Ref. PesticidePesticidePesticide Structure Structure LD 50 LD50Ref. Ref. Ref.Pesticide PesticidePesticide Structure Structure LD 50 LD50Ref. Ref.Ref. PesticidePesticidePesticide StructureStructureStructure (mg/kg)(mg/kg)(mg/kg)(mg/kg)(mg/kg) Ref. Ref.Ref.Pesticide PesticidePesticide Structure Structure Structure (mg/kg)(mg/kg)(mg/kg)(mg/kg)(mg/kg) Ref. Ref.Ref. (mg/kg)(mg/kg)(mg/kg)(mg/kg)(mg/kg) (mg/kg)(mg/kg)(mg/kg)(mg/kg)(mg/kg) 1040 1040 113 113 10401040 10401040 113 113113113 azamethiphosazamethiphosazamethiphosazamethiphos 10401040 1040 [44][44][44 ] [44][44]phosmet phosmetphosmetphosmet 113113 113 [53][53] [53][53][53 ] azamethiphosazamethiphosazamethiphosazamethiphos 84.324 84.32484.324 84.324 [44][44] [44][44][44]phosmet phosmetphosmet 9.162 9.1629.1629.162[53] [53] [53][53][53] 84.32484.324 84.324 84.324 9.1629.162 9.1629.162 84.324 84.324 9.162 9.162 azinphos-azinphos- 7 7 465 465 azinphos-azinphos-azinphos- 7 7 7 465 465465 azinphos-methylazinphos-azinphos-azinphos-azinphos- 77 77 [54][54][54 ] [54][54]TCVP TCVPTCVP TCVP 465465 465465 [55][55] [55][55][55 ] methylmethylmethyl 0.5670.567 0.5670.567 [54] [54] [54][54][54]TCVP TCVP TCVP 37.70237.702 37.702 37.702[55][55] [55][55][55] methylmethylmethyl 0.567 0.567 0.5670.567 37.70237.70237.702 37.702 methylmethyl 0.567 0.567 37.70237.702

20002000 20002000 1.6 1.61.61.6 chlorpyrifoschlorpyrifoschlorpyrifoschlorpyrifos 20002000 20002000 [56][56][56 ] [56][56]terbufosterbufos terbufosterbufosterbufos 1.61.6 1.61.6 [57][57] [57][57][57 ] chlorpyrifoschlorpyrifoschlorpyrifoschlorpyrifos 162.162162.162162.162162.162 [56][56] [56][56][56]terbufosterbufos terbufosterbufosterbufos 0.129 0.1290.1290.129[57] [57] [57][57][57] chlorpyrifos 162.162162.162162.162 [56] terbufos 0.129 0.1290.129 [57] 162.162 162.162 162.162 0.1290.129 0.129

1717 1717 350 350350350 DDVPDDVPDDVPDDVP 1717 1717 [58][58 ] [58][58]methiocarb methiocarbmethiocarbmethiocarb 350350 350350 [59] [59][59][59 ] DDVPDDVPDDVP 17 1.378 [58][58] [58][58]methiocarb methiocarbmethiocarb 350 28.378[59][59] [59][59] DDVPDDVP 1.3781.378 1.378[58] [58] [58]methiocarb methiocarb 28.37828.378 28.378[59][59] [59] 1.3781.378 1.3781.378 28.37828.37828.378 28.378

66 6666 12 1212 diazinondiazinon 666666 6666 [60] [60]methomyl methomyl 1212 121212 [61] [61] diazinondiazinondiazinondiazinon 66 66 [60][60][60 ] [60][60][60]methomyl methomylmethomylmethomyl 12 12 [61][61] [61][61][61][61 ] diazinondiazinon 5.3515.351 5.3515.351 [60] [60] [60]methomyl methomyl 0.972 0.9720.9720.972[61] [61] [61] 5.3515.351 5.3515.351 0.9720.972 0.9720.972

50 5050 5.4 5.45.4 fenitrothionfenitrothionfenitrothion 505050 5050 [62] [62][62]oxamyl oxamyloxamyl 5.45.4 5.45.45.4 [63] [63][63] fenitrothionfenitrothionfenitrothionfenitrothionfenitrothion 50 40.540[62][62] [62 ] [62][62]oxamyl oxamyloxamyloxamyl 5.4 0.437 [63][63] [63][63][63 ] fenitrothionfenitrothionfenitrothion 40.54040.54040.540 [62][62] [62]oxamyloxamyl oxamyl 0.437 0.4370.437[63] [63] [63] 40.540 40.540 40.540 40.540 0.4370.437 0.4370.437

5000 50005000 113 113113 glyphosateglyphosateglyphosate 500050005000 50005000 [64][64] [64][64] DDT DDT DDT 113113 113113113 [14][14] [14][14] glyphosateglyphosateglyphosateglyphosate 405.405 405.405405.405 [64][64] [64 ] [64][64][64] DDT DDT DDT DDT 9.162 9.1629.162[14] [14] [14][14][14][14 ] glyphosate 405.405 405.405405.405405.405 [64] DDT 9.162 9.1629.1629.162 [14] 405.405405.405 405.405 9.1629.162 9.162

O OO O O O OO 290 290290 O OO OO O 639 639639 290 290 O OHO OHOH 639 639 malathionmalathion 290290290 290290 [65] [65] 2,4-D 2,4-D OO OHOO OH 639639 639639 [66] [66] malathionmalathion 290 290 [65] [65][65]2,4-D 2,4-D O OHO OHOH 639 639 [66] [66][66] malathionmalathionmalathionmalathion 23.513[65] [65 ] [65][65] 2,4-D 2,4-D 2,4-D2,4-D OHOH OH 51.810[66] [66][66][66 ] malathionmalathion 23.51323.513 [65][65] [65]2,4-D2,4-D 2,4-D Cl ClClCl ClCl 51.81051.810 [66][66] [66] 23.51323.513 23.513 Cl ClCl Cl Cl 51.810 51.810 51.810 23.51323.51323.513 ClCl ClClCl Cl Cl 51.81051.81051.810 23.51323.513 Cl ClCl Cl 51.81051.810

methylmethylmethyl 18 1818 75 7575 methylmethylmethylmethyl 181818 1818 [67] [67][67]dicamba dicambadicamba 7575 757575 [68] [68][68] parathionparathion 1.459 1.459 [67][67][67 ] [67][67]dicamba dicambadicambadicamba 61.37861.378 [68][68] [68][68][68 ] parathionparathionparathion 1.459 1.4591.459 [67] [67]dicamba dicamba 61.37861.378 61.378 [68] [68] parathionparathionparathion 1.4591.4591.459 1.459 61.37861.378 61.378 61.378

160 160160 1.95 1.951.95 nalednaled nalednaled(dibrom) (dibrom)(dibrom) 160160160 160160 [69] [69][69]DEET DEET DEET 1.951.95 1.951.951.95 [70] [70][70] naled naled(dibrom)naled (dibrom)(dibrom) 12.97212.972 12.972[69][69] [69][69][69]DEET DEET DEET 0.158 0.1580.158[70] [70] [70][70][70] naled naled(dibrom) (dibrom) 12.97212.972 12.972 [69] [69 ] [69]DEET DEETDEET 0.158 0.1580.158 [70] [70][70 ] (dibrom) 12.97212.97212.972 12.972 0.1580.158 0.1580.158 2 750 2 2 750 750 parathionparathionparathion 22 2 22 [71][71] [71][71]sulfoxaflor sulfoxaflorsulfoxaflor 750750 750750750 [72][72] [72][72] parathionparathionparathionparathion 0.162 0.1620.162 [71] [71] [71 ] [71][71][71]sulfoxaflorsulfoxaflor sulfoxaflorsulfoxaflorsulfoxaflor 60.81060.810 60.810 [72][72] [72][72][72][72 ] 0.1620.1620.162 0.1620.162 60.81060.810 60.810 60.810 60.810 0.162 0.162 60.810 60.810

AmongAmongAmong all of allallthe ofof listed thethe listed listedpesticides pesticidespesticides (training (training(training and testandand set testtest compounds), setset compounds),compounds), the pharmacology thethe pharmacologypharmacology of ofof AmongAmongAmong all of allallthe ofof listed thethe listedlistedpesticides pesticidespesticides (training (training(training and testandand set testtest compounds), setset compounds),compounds), the pharmacology thethe pharmacologypharmacology of ofof organophosphorusAmongorganophosphorusorganophosphorus all of (OP), the listed(OP),(OP),compounds compoundscompounds pesticides as hAChE asas (training hhAChEAChE inhibitors, inhibitors,inhibitors, and is testby far isis set byby the far compounds),far most thethe investigated;mostmost investigated;investigated; the it pharmacology involves itit involvesinvolves of organophosphorusorganophosphorusorganophosphorus (OP), (OP),compounds(OP), compoundscompounds as hhAChE asas hhAChEAChE inhibitors, inhibitors,inhibitors, is by far isis by bythe farfar most thethe investigated;mostmost investigated;investigated; it involves itit involvesinvolves the phosphorylationthethe phosphorylationphosphorylation of catalytic ofof catalyticcatalytic Ser203 Ser203Ser203 and the andand formation thethe formationformation of stable ofof stablestable inactive inactiveinactive phosphyl-AChE phosphyl-AChEphosphyl-AChE adducts adductsadducts organophosphorusthethe phosphorylationphosphorylationthethethe phosphorylationphosphorylationphosphorylation ofof (OP), catalyticcatalytic ofofof compounds catalyticcatalyticcatalytic Ser203Ser203 Ser203Ser203Ser203 andand as thethe andandandh formationformationAChE thethethe formationformationformation inhibitors, ofof stablestable ofofof stablestable stable inactiveinactive is by inactiveinactiveinactive phosphyl-AChEphosphyl-AChE far the phosphyl-AChEphosphyl-AChEphosphyl-AChE most investigated;adductsadducts adductsadductsadducts it [36]. Moreover,[36].[36]. Moreover,Moreover, methylcarbamate methylcarbamatemethylcarbamate (MC) (MC)(MC)insecticides insecticidesinsecticides likelike carbofurancarbofuran likelike carbofurancarbofuran andand similarsimilar andand similarsimilar compounds,compounds, compounds,compounds, occupyoccupy occupyoccupy involves[36].[36]. Moreover,Moreover,[36].[36].[36]. the Moreover,Moreover,Moreover, phosphorylation methylcarbamatemethylcarbamate methylcarbamatemethylcarbamatemethylcarbamate of (MC)(MC) catalytic (MC)(MC)(MC)insecticidesinsecticides Ser203 insecticidesinsecticidesinsecticides andlikelike carbofurancarbofuran the likelikelike formation carbofurancarbofurancarbofuran andand similarsimilar of andandand stable similarsimilarsimilar compounds,compounds, inactive compounds,compounds,compounds, phosphyl-AChE occupyoccupy occupyoccupyoccupy the catalyticthethe catalyticcatalytic triad triadtriadarea andareaarea actandand as actact reversible asas reversiblereversible competitive competitivecompetitive inhibitors inhibitorsinhibitors of ACh ofof AChACh[73], elucidated[73],[73], elucidatedelucidated by byby adductsthethe catalyticcatalyticthethethe [ 36 catalyticcatalyticcatalytic]. Moreover,triadtriad triadtriadtriadareaarea andareaandareaarea methylcarbamate actactandandand asas actactact reversiblereversible asasas reversiblereversiblereversible (MC) competitivecompetitive insecticides competitivecompetitivecompetitive inhibitorsinhibitors like inhibitorsinhibitorsinhibitors carbofuran ofof AChACh ofofof AChACh[73],ACh[73], and elucidated[73],elucidated[73],[73], similar elucidatedelucidatedelucidated compounds, byby bybyby molecularmolecularmolecular docking dockingdocking (SB) studies (SB)(SB) studiesstudies on Nephotettix onon NephotettixNephotettix cincticeps cincticepscincticeps AChE.AChE. AChE.AChE.AChE. DockingDocking DockingDockingDocking studiesstudies studiesstudiesstudies werewere werealsowerealsowere performedperformed alsoalsoalso performedperformedperformed occupymolecularmolecularmolecular the docking catalytic dockingdocking (SB) triad studies (SB)(SB) area studiesstudies on and Nephotettix on acton NephotettixNephotettix as reversible cincticeps cincticepscincticeps competitiveAChE.AChE. AChE.AChE.AChE. DockingDocking DockingDockingDocking inhibitors studiesstudies studiesstudiesstudies werewere of ACh alsowerewerealsowere [performedperformed 73 alsoalsoalso], elucidatedperformedperformedperformed by for imidaclopridforfor imidaclopridimidacloprid analogues analoguesanalogues [74]. [74].[74]. forfor imidaclopridimidaclopridforforfor imidaclopridimidaclopridimidacloprid analoguesanalogues analoguesanaloguesanalogues [74].[74]. [74].[74].[74].

Molecules 2018, 23, 2192 6 of 37 molecular docking (SB) studies on Nephotettix cincticeps AChE. Docking studies were also performed for imidacloprid analogues [74]. Therefore, to enrich the information related to the pharmacology of commonly used commercial pesticides,MoleculesMoleculesMolecules the 2018 2018 targets 2018, ,23 23, ,23 ,x x , ofx herein study, their mechanisms of action were either confirmed or nominated66 of of6 37of 37 37 Molecules 2018, 23, x 6 of 37 by meansMolecules of reversible 2018, 23, x and reversible-like (for organophosphorus pesticides only, docking performed6 of 37 Therefore,Therefore,Therefore, to to toenrich enrich enrich the the the information information information related related related to to tothe the the pharmacology pharmacology pharmacology of of ofcommonly commonly commonly used used used commercial commercial commercial to obtain non-covalent conformation that is going to be transformed to the covalent one) cross-docking, pesticides,pesticides,pesticides,Therefore,Therefore, thethe the to targetstotargets enrich targetsenrich of the ofthe of herein herein information informationherein study,study, study, related related theirtheir their to mechanismstomechanisms themechanisms the pharmacology pharmacology ofof of actionaction action of of commonly commonlywerewere were eithereither either used used confirmedconfirmed commercialconfirmed commercial oror or Mus musculus Homo sapiens as wellnominatedpesticides,pesticides,nominated asnominated by single thebytheby by step meanstargetsmeans targetsmeans molecular of of of of reversible hereinreversible hereinreversible dynamics study,study, andand and theirreversible-liketheir studiesreversible-like reversible-like mechanismsmechanisms on (for(for (for of oforganophosphorusorganophosphorus actionorganophosphorusactionand werewere eithereither pesticidespesticides pesticidesconfirmedconfirmedAChE only,only, only, or level.or Alongsidedockingnominatednominateddockingdocking with performedperformed the performed byby prediction meansmeans toto to ofobtainofobtain obtain ofreversiblereversible free non-covalentnon-covalent non-covalent energy andand ofreversible-likereversible-like conformabinding,conforma conformation generatedtiontion (for (for thatthat that organophosphorus organophosphorus isis bioactiveis goinggoing going toto to be conformations,be be transformedtransformed transformed pesticidespesticides to wereto only,only, to thethe the the startingcovalentdockingdockingcovalent pointscovalent one)performed forperformedone) one) the cross-docking, cross-docking, cross-docking, definition toto obtainobtain ofas as non-covalent theasnon-covalentwell well well mechanism as as asby by by single single singleconformaconforma ofstep step actionstep molecular tionmoleculartion molecular of thatthat 2-chloro-1,3,5-triazine-based isdynamics isdynamics dynamics goinggoing to tostudies studies bestudiesbe transformedtransformed on on on Mus Mus Mus musculus musculus pesticidesmusculus toto thethe (atrazine,andcovalentcovalentandand simazine,Homo Homo Homo one) one) sapiens sapiens sapiens cross-docking, cross-docking, and AChE AChE AChE propazine, level. level. level. as as Alongside well Alongsidewell respectively),Alongside as as by by with single withsingle with the the as step thestep predicti thepredicti predictimolecular molecular mostononon toxicof of dynamicsofdynamicsfree free free ones. energy energy energy studies DFTstudies of of ofbinding, quantumbinding, binding,on on Mus Mus generated generatedmusculus musculusgenerated mechanics mechanisticbioactiveandandbioactivebioactive HomoHomo studies conformations, conformations, sapiens sapiensconformations, were AChEAChE supposed werelevel. level.were were the AlongsidetotheAlongside the shedstarting starting starting further withpoints withpoints points thelightthe fo fo predictirfopredictir the onrthe the pesticide-AChEdefinition definition definitiononon ofof freefree of of ofthe energyenergythe the mechanism interactionsmechanism mechanism ofof binding,binding, of of for ofaction action generated generatedaction the purposeof of of2- 2- 2- bioactive conformations, were the starting points for the definition of the mechanism of action of 2- of designingchloro-1,3,5-triazine-basedbioactivechloro-1,3,5-triazine-basedchloro-1,3,5-triazine-based pesticides conformations, with lowerwere pesticides pesticides pesticides the acute starting (atrazine, toxicity(atrazine, (atrazine, pointsprofiles. simazine, simazine, fosimazine,r the definition and and and propazine, propazine, propazine, of the mechanismrespectively), respectively), respectively), of as actionas asthe the the most ofmost most 2- toxicchloro-1,3,5-triazine-basedchloro-1,3,5-triazine-basedtoxictoxic ones.ones. ones. DFT DFT DFT quantumquantum quantum mechanics pesticidesmechanicspesticides mechanics (atrazine, mechanistic(atrazine,mechanistic mechanistic simazine,simazine, stst udiesstudiesudies andand werewere were propazine,propazine, supposed supposed supposed respectively), respectively), toto to shedshed shed furtherfurther further asas the lightthelight light mostmost onon on 2. Resultspesticide-AChEtoxictoxicpesticide-AChEpesticide-AChE and ones.ones. Discussion DFTDFT interactions interactionsquantumquantum interactions mechanicsmechanics for for for the the the purpose purpose purpose mechanisticmechanistic of of ofdesigning designing designing ststudiesudies pesticides pesticides pesticides werewere supposedsupposed with with with lower lower lower toto acute shed acuteshed acute toxicityfurther furthertoxicity toxicity profiles. light profiles.light profiles. onon pesticide-AChEpesticide-AChE interactions interactions for for the the purpose purpose of of designing designing pesticides pesticides with with lower lower acute acute toxicity toxicity profiles. profiles. 2.1. The2.2. Conformational2.Results Results Results and and and Discussion Discussion Discussion Analysis of Pesticides in Aqueous Solution 2.2. Results Results and and Discussion Discussion Conformational2.1.2.1.2.1. The The The Conformational Conformational Conformational analysis Analysis Analysis Analysis (CA) of of studies Pesticidesof Pesticides Pesticides are in in herein inAqueous Aqueous Aqueous reported Solution Solution Solution for simazine [9], monocrotophos [10], dimethoate2.1.2.1. The The [11 Conformational Conformational], and acetamiprid Analysis Analysis [of 12of Pesticides ]Pesticides (Table 3in in), Aqueous asAqueous pesticides Solution Solution with known crystal structures, as well ConformationalConformationalConformational analysis analysis analysis (CA) (CA) (CA) studies studies studies are are are herein herein herein reported reported reported for for for simazine simazine simazine [9], [9], [9], monocrotophos monocrotophos monocrotophos [10], [10], [10], as for atrazinedimethoatedimethoatedimethoateConformationalConformational and [11], [11], [11], carbofuran, and and and analysisacetamiprid analysisacetamiprid acetamiprid as (CA) (CA) pesticides [12] [12]studies studies[12] (Table (Table (Table are thatare 3), 3),herein herein3), exertas as aspesticides pesticides pesticidesreported reported the highest with withfor forwith simazine knownsimazine acuteknown known toxicitycrystal crystal[9], [9],crystal monocrotophos monocrotophos structures, structures, (Tablestructures,4). as Toas aswell[10], [10],well avoidwell redundancy,asdimethoatedimethoateas asfor for for atrazine atrazine appliedatrazine [11], [11], and and and studiesand carbofuran, carbofuran, acetamiprid carbofuran,acetamiprid to the as as other as[12] pesticides [12]pesticides pesticides (Table (Table pesticides that 3), that3), that as asexert exert pesticidesexertpesticides are the the reported the highest highest highestwith with acuteknown asknownacute acute Supplementary toxicity toxicity crystaltoxicitycrystal (Table (Tablestructures, structures,(Table 4). Material.4). 4). To To as To asavoid avoidwell wellavoid The crystalredundancy,asasredundancy, structures redundancy,for for atrazine atrazineof applied applied and simazineappliedand carbofuran, carbofuran, studies studies studies [9], monocrotophostoto as toasthe the pesticides thepesticides other other other pesticid pesticid that pesticidthat [10 exert exertes],es es dimethoateare are thearethe reported reported highesthighestreported [acute as11acuteas as],Supplementary Supplementary andSupplementary toxicity toxicity acetamiprid (Table (Table Material. Material. 4). Material.4). [To 12To ]avoid avoid (TableThe The The 3 , Tablescrystalredundancy, S1–S3)redundancy,crystalcrystal structures structures werestructures appliedapplied used of of ofsimazine assimazine studiessimazinestudies starting [9],to to[9], [9], the themonocrotophosconformational monocrotophos monocrotophos otherother pesticidpesticid [10], es[10],es geometries[10], areare dimethoate dimethoate dimethoate reportedreported for as[11], as[11], the[11], SupplementarySupplementary and and CA. and acetamiprid acetamiprid Foracetamiprid pesticides Material.Material. [12] [12] [12] (Table (Tablewithout (Table TheThe experimental3,crystalcrystal3, 3,Tables Tables Tables structures structures data S1–S3) S1–S3) S1–S3) (Table were wereof ofwere 4simazine simazine ,used used Tables used as as asstarting[9], S1–S3),[9],starting starting monocrotophos monocrotophos conformational startingconformational conformational conformations [10], [10], geometries geometriesdimethoate dimethoategeometries were for for[11], [11],for the the builtthe and andCA. CA. CA. fromacetamiprid acetamipridFor For For pesticides pesticides scratch pesticides [12] [12] and without without (Tablewithout(Table energy 3, Tables S1–S3) were used as starting conformational geometries for the CA. For pesticides without minimized.experimental3,experimental experimentalTables For S1–S3) the data datasake data were (Table (Table of(Table used clarity, 4, 4, asTables4, Tables Tablesstarting pesticides S1–S3), S1–S3), S1–S3), conformational starti starti were startingngng divided conformations conformations conformations geometries into four were forwere were groupsthe built built builtCA. from from Forbasedfrom scratch pesticidesscratch scratch on theirand and and without energy energy common energy minimized.experimentalminimized. For For data the the (Tablesake sake of of4, clarity, clarity,Tables pesticides S1–S3),pesticides starti were wereng dividedconformations divided into into four four were groups groups built basedfrom based scratch on on their their and common common energy structuralminimized.experimentalminimized. patterns: For dataFor 2-chloro-1,3,5-triazinethe the(Table sake sake of 4, of clarity,Tables clarity, S1–S3),pesticides pesticides derivatives: starti were ngwere conformationsdivided divided simazine, into into four were four atrazine, groups builtgroups frombased and based scratch propazineon on their their and common energycommon (Tables 3 structuralminimized.structural patterns: patterns: For the 2-chloro-1,3,5-triazine 2-chloro-1,3,5-triazinesake of clarity, pesticides derivatives: derivatives: were divided simazine, simazine, into atrazine, fouratrazine, groups and and basedpropazine propazine on their (Table (Table common 3 3 and and and4, Tablestructuralminimized.structural S1, respectively);patterns: Forpatterns: the 2-chloro-1,3,5-triazinesake 2-chloro-1,3,5-triazine amideof clarity, derivatives: pesticides derivatives: derivatives: monocrotophos,were divided simazine, simazine, into dimethoate,atrazine,four atrazine, groups and and based andpropazine propazine carbofuran on their (Table (Table common (Tables3 and 3 and 3 TablestructuralstructuralTableTable 4,4, 4, Table Tablepatterns: patterns:Table S1,S1, S1, 2-chloro-1,3,5-triazinerespectively); 2-chloro-1,3,5-triazinerespectively); respectively); amideamide amide derivatives: derivatives: derivatives: derivatives:derivatives: monocrotophos,simazine, simazine,monocrotophos, monocrotophos, atrazine, atrazine, dimethoate,dimethoate, and dimethoate,and propazine propazine andand and (Table (Table carbofurancarbofuran carbofuran 3 3 and and and4, Table S2, respectively), carbaryl and tebufenozide (Table S2); 6-chloropyridine-3-yl)methanamine (TableTableTable(Table(Table 4,3 4,3 and 3TableandTable and Table Table Table S1,S1, 4, respectively);4,respectively); 4,Table Table Table S2, S2, S2, respectively), respectively), respectively), amideamide derivatives:derivatives: carbaryl carbaryl carbaryl and monocrotophos,andmonocrotophos, and tebufenozide tebufenozide tebufenozide dimethoate,(Table dimethoate,(Table (Table S2); S2); S2); 6-chloropyridine- 6-chloropyridine- and6-chloropyridine-and carbofurancarbofuran derivates:3-yl)methanamine(Table(Table3-yl)methanamine3-yl)methanamine acetamiprid 3 3 and and Table Table (Table 4, derivates:4,derivates: Table derivates:Table3, TableS2, S2, acetamipridrespectively), acetamiprid respectively),acetamiprid S3) and imidacloprid (Table (Table carbaryl carbaryl(Table 3,3, 3, andTable andTable Table (Table tebufenozide tebufenozide S3)S3) S3) S3); andand and 1-(4-chlorophenyl)-3-methylurea imidaclopridimidacloprid (Tableimidacloprid (Table S2); S2); 6-chloropyridine- 6-chloropyridine-(Table(Table (Table S3);S3); S3); 1-(4-1-(4- 1-(4- condensates:chlorophenyl)-3-methylurea3-yl)methanamine3-yl)methanaminechlorophenyl)-3-methylureachlorophenyl)-3-methylurea diuron, monuron, derivates:derivates: andcondensates: condensates: acetamiprid condensates:acetamiprid linuron (Tabledi di (Table uron,(Tablediuron,uron, S3). monuron, 3,monuron,3, monuron, TableTable S3)and S3)and and andlinuronand linuron linuron imidaclopridimidacloprid (Table (Table (Table S3). S3). S3). (Table(Table S3);S3); 1-(4-1-(4- chlorophenyl)-3-methylureachlorophenyl)-3-methylurea condensates: condensates: di diuron,uron, monuron, monuron, and and linuron linuron (Table (Table S3). S3). Table 3.TableTableTrainingTable 3. 3. 3. Training setTrainingTraining pesticides set setset pesticides withpesticidespesticides the known with withwith the crystalthethe known knownknown structures: crystal crystalcrystal chemical structures: structures:structures: structures, chemical chemicalchemical conformational structures, structures,structures, Table 3. Training set pesticides with the known crystal structures: chemical structures, analysis,conformationalTableconformationalconformational superposition 3. Training analysis,analysis, ofanalysis, theset experimental superpositionpesticidessuperposition superposition with conformation ofof of thethe the exknownex perimentalexperimentalperimental and crystal generated conformationconformation conformationstructures: global andandchemical minimaand generatedgenerated generated usingstructures, globalglobal theglobal best conformational analysis, superposition of the experimental conformation and generated global performingminimaconformationalminimaminima force using using using fields. the the analysis,the best best best performing performing performing superposition force force force fields. fields.of fields. the experimental conformation and generated global minima using the best performing force fields. minima using the best performinga a forceglob_min fields.b b c c d d f f PesticidePesticidePesticide FFFFFF a a EEglob_minEglob_min b b NGMSNGMSNGMS c c NFNFNF d d PesticidePesticidePesticide CAA CAA CAA f f a a bb cc d d e e f f g g PesticidePesticide FFFF a E(kJ/mol)glob_minE(kJ/mol)glob_minb NGMSNGMS c NFNF d AlignmentAlignmentPesticide e e RMSDCAARMSD CAA (Å) (Å)f g g Pesticide FF E(kJ/mol)glob_min(kJ/mol) NGMS NF AlignmentPesticideAlignment RMSDRMSD CAA (Å) (Å) h e g (kJ/mol)h h Alignment e RMSD (Å)g simazinesimazinesimazine MM3MM3MM3 (kJ/mol)(kJ/mol)NANANA h NANA NA NANA NA Alignment Alignment e RMSDRMSDEC/MMFFEC/MMFFEC/MMFF (Å) (Å) g h simazine AMBER94AMBER94AMBER94MM3 NANANAh NANA NA NANANA EC/MMFF 0.667 0.667 0.667 simazine AMBER94MM3MM3 NANA h NANA NA NA EC/MMFFEC/MMFF 0.667 AMBER94MMFFMMFF −−1022.181022.18NA 136 NA136 27822782NA 0.667 AMBER94AMBER94MMFFMMFF −1022.18−NA NA1022.18 NA136 NA136 2782NA NA2782 0.667 0.667 MMFF −1022.18 136 2782 MMFFMMFFMMFFs −1022.181022.18NA 136 NA 136 2782NA 2782 MMFFsMMFFs NANA NA NA NANA MMFFs NA NA NA MMFFs NA NA NA OPLSAAMMFFsOPLSAA −−793.61NA793.61 NA158158 2306NA2306 OPLSAAOPLSAAOPLSAA −793.61793.61−793.61 158 158158 2306 23062306 monocrotophosmonocrotophos OPLSAAMM3MM3 −NA793.61NA NANA158 NA2306NA EC/MMFFEC/MMFF monocrotophosmonocrotophos OPLSAAMM3MM3MM3 −793.61NA NANA NA158 NANA 2306NA NANA EC/MMFFEC/MMFFEC/MMFF monocrotophos AMBER94MM3 NA NA NA EC/MMFF 0.620 monocrotophos AMBER94AMBER94AMBER94MM3 NA NANA NA NA NA NA NANA 0.620EC/MMFF 0.620 0.620 AMBER94MMFF −307.36NA NA241 NA 62 EC/MMFFs 0.620 AMBER94MMFFMMFFMMFF −307.36NA307.36−307.36 NA241 241241 NA 62 62 62 EC/MMFFs EC/MMFFs EC/MMFFs 0.620 MMFF −307.36 241 62 EC/MMFFs MMFFsMMFFsMMFFMMFFsMMFFs −−310.26307.36310.26−310.26 218241218 218218 6162 61 61 61 EC/MMFFs 3.521 3.521 3.521 3.521 OPLSAAMMFFs −310.26 NA 218 NA 61 NA 3.521 OPLSAAMMFFsOPLSAAOPLSAA −310.26NANANA NA218NANA NA 61NANA 3.521 OPLSAA NA NA NA dimethoatedimethoatedimethoate OPLSAAMM3MM3MM3MM3 NA NANANA NANA NANA NANA NANA EC/MMFFEC/MMFFEC/MMFFEC/MMFF dimethoate AMBER94MM3 NA NA NA EC/MMFF 0.148 dimethoate AMBER94AMBER94AMBER94MM3 NA NANA NA NA NA NA NANA 0.148EC/MMFF 0.148 0.148 MMFFAMBER94MMFF −−383.68NA NA340 340 NA 44 44 EC/MMFFs EC/MMFFs 0.148 AMBER94MMFFMMFF −383.68NA−383.68 NA340340 NA 44 44 EC/MMFFs EC/MMFFs 0.148 MMFFsMMFFsMMFF −−386.71383.68 340215 215 4440 40 3.227 EC/MMFFs 3.227 MMFFsMMFFMMFFs −386.71383.68−386.71 215340215 4044 40 EC/MMFFs 3.227 3.227 OPLSAA −228.66 998 15 EC/OPLSAA OPLSAAOPLSAAMMFFsOPLSAA −−228.66386.71228.66−228.66 998215998998 15 4015 15 EC/OPLSAA EC/OPLSAA EC/OPLSAA 3.227 MMFFs −386.71 215 40 2.746 3.227 OPLSAA −228.66 998 15 EC/OPLSAA 2.746 2.746 OPLSAA −228.66 998 15 EC/OPLSAA 2.746 2.746 2.746 acetamipridacetamipridacetamiprid MM3MM3MM3 NANA NA NANA NA NANA NA EC/MMFF EC/MMFF EC/MMFF 2.746 acetamiprid AMBER94MM3 NA NA NA EC/MMFF 0.783 acetamiprid AMBER94AMBER94MM3 NANA NA NA NANA EC/MMFF 0.783 0.783 AMBER94MMFF −31.45NA 1916 NA NA14 EC/MMFFs 0.783 AMBER94MMFFMMFF −31.45NA−31.45 1916 NA1916 NA14 14 EC/MMFFs EC/MMFFs 0.783 MMFF −31.45 1916 14 EC/MMFFs MMFF −31.45 1916 14 EC/MMFFs

Molecules 2018, 23, 2192 7 of 37

Table 3. Cont.

Pesticide FF a E b NGMS c NF d Pesticide CAA f Molecules 2018, 23, x glob_min 7 of 37 MoleculesMolecules 2018 2018, 23, ,23 x , x 7 of7 37of 37 e g MoleculesMoleculesMolecules 2018 2018 2018, 23,, 23,x 23 , x, x (kJ/mol) Alignment RMSD (Å)7 of7 737of of 37 37 acetamiprid MM3 NA NA NA EC/MMFF AMBER94 NA NA NA 0.783 MMFFs −31.29 1816 6 0.823 MMFFsMMFFsMMFF −31.29−31.29−31.45 18161816 1916 6 6 14 EC/MMFFs0.8230.823 MMFFs −31.29 1816 6 0.823 MMFFsMMFFsMMFFs −31.29−31.2931.29 18161816 1816 6 6 60.823 0.8230.823

OPLSAA NA NA NA OPLSAA NA NA NA a b OPLSAAOPLSAA NANA c NANA NANA Force field;a Energy ofb theOPLSAA global minimum;NA NumberNA ofctimes thatNA a single global minimum structure was found a Force field;b OPLSAAEnergyOPLSAA of the NAglobal NA minimum; NA NAc Number NA NA of times that a single global minimum a ForceForce field; field; b Energy Energy of dofthe the global global minimum; minimum; c Number Number of oftimes times that that a singlea single global global minimum minimum in 10,000a processed structures;b Number of families i.e., differentc conformations found in 10,000 processed structures; a aForce Force field; field;b bEnergy Energy of of the the global global minimum; minimum;c cNumber Numberd of of times times that that a asingle single global global minimum minimum e structureForcestructurestructure field; was was foundwasEnergy found found in in10,000of in 10,000the 10,000 processedglobal processed processed minimum; structures; structures; structures; Number d Number d Number Number of of times offamilies offamilies familiesthat i.e., a i.e., singledifferent i.e., different different global conformations conformations minimumconformations Red—experimental conformation, Violet—MMFF conformation,d Blue—MMFFs conformation, Green—OPLSAA structurestructure was was found found in in 10,000 10,000 processed processed structures; structures;e d Numberd Number of of families families i.e., i.e., different different conformations conformations conformation;foundstructurefoundfound in was in f 10,000 Conformationin found10,000 10,000 processedin processed 10,000processed dependent processed structures; structures; structures; alignment structures; e eRed—experimental accuracy;Red—experimental Red—experimentalNumberg RMSDof families measuredconformation, conformation, i.e.,conformation, different between Violet—MMFF conformationsViolet—MMFF theViolet—MMFF heavy atoms of e foundfound inin 10,00010,000 processedprocessed structures;structures;e e Red—experimentalRed—experimental conformation,conformation, Violet—MMFFfViolet—MMFF pesticidesconformation,foundconformation,conformation, ofin experimental 10,000 Blue—MMFFs Blue—MMFFs processedBlue—MMFFs and best performingconformation,structures; conformation, conformation, force Red—experimentalGreen—OPLSAA field Green—OPLSAA Green—OPLSAA conformations; conformation; hconformation,conformation;Not conformation; available. f Violet—MMFFConformationf ConformationConformation f conformation,conformation, Blue—MMFFsBlue—MMFFs conformation,conformation,g Green—OPLSAAGreen—OPLSAA conformation;conformation;f f ConformationConformation dependentconformation,dependentdependent alignment alignment Blue—MMFFsalignment accuracy; accuracy; accuracy; conformation, g RMSDg RMSDRMSD measured measured measuredGreen—OPLSAA between between between the the conformation;heavythe heavy heavy atoms atoms atoms of Conformationofpesticides ofpesticides pesticides of of of g dependentdependent alignmentalignment accuracy;accuracy;g gRMSD RMSD measuredmeasured betweenbetweenh thethe heavyheavy atomsatoms ofof pesticidespesticides ofof experimentaldependentexperimentalexperimental alignment and and bestand best performibestaccuracy; performi performing ng forceRMSDng force force field fieldmeasured fieldconformations; conformations; conformations; between h Not h Notthe available.Not available.heavy available. atoms of pesticides of CA in explicit solvent may be used to predict the singleh pesticideh stability prior to AChE binding. experimentalexperimentalexperimental and and and best best best performi performi performingng forceng force force field field field conformations; conformations; conformations; h Not NotNot available. available. available. Herein, CAs were tentatively carried out by using five different force fields (FFs): MM3, AMBER94, CACA inCA inexplicit inexplicit explicit solvent solvent solvent may may may be be used be used used to topredict topredict predict the the single the single single pesticide pesticide pesticide stability stability stability prior prior prior to toAChE toAChE AChE binding. binding. binding. CACA in in explicit explicit solvent solvent may may be be used used to to predict predict the the single single pesticide pesticide stability stability prior prior to to AChE AChE binding. binding. MMFF,Herein,Herein,Herein,CA MMFFs, CAs in CAs explicit CAs were were and were tentativelysolvent OPLSAAtentatively tentatively may carried be [carried35 carriedused]. out Either toout byoutpredict by using forby using using the crystallized five singlefi vefidifferentve different pesticidedifferent pesticides force force forcestability fields fields fields or (FFs): prior (FFs): pesticides (FFs): MM3,to MM3, AChE MM3, AMBER94, withAMBER94, binding. AMBER94, unknown Herein,Herein, CAs CAs were were tentatively tentatively carried carried out out by by using using fi fiveve different different force force fields fields (FFs): (FFs): MM3, MM3, AMBER94, AMBER94, experimentalMMFF,Herein,MMFF,MMFF, CAsMMFFs, MMFFs, structures,MMFFs, were and tentatively and andOPLSAA OPLSAA the OPLSAA procedurecarried [35]. [35]. [35]. Eitherout Either Eitherby was forusing for divided crystallizedfor crystallized fi crystallizedve different into pesticides thepesticides forcepesticides following fields or orpesticides or (FFs):pesticides pesticides steps: MM3, with (1)with AMBER94,with conformationalunknown unknown unknown MMFF,MMFF,experimental MMFFs, MMFFs, structures, and and OPLSAA OPLSAA the procedure[35]. [35]. Either Either was for for dividecrystallized crystallizedd into pesticides pesticidesthe following or or pesticides pesticides steps: (1) with withconformational unknown unknown analysis;experimentalMMFF,experimental (2) MMFFs, determination structures, structures, and OPLSAA the of the energyprocedure procedure[35]. ofEither thewas was globalfor divide crystallizeddivide minimumd dinto into thepesticides the (followingE glob_minfollowing or ),pesticidessteps: andsteps: (3)(1) (1) theconformationalwith conformational LB unknown superposition experimentalexperimentalexperimentalanalysis; (2)structures, structures, determinationstructures, the the theprocedure ofprocedure procedure energy was of was thewas divide globaldivide divided dintominimumd into into the the thefollowing (following Efollowingglob_min), steps: and steps: steps: (3) (1) the(1) (1)conformational LBconformational conformational superposition of structuresanalysis;analysis; (2) to(2) determinationdefine determination the alignment of ofenergy energy of accuracy. ofthe the global global All minimum minimum steps were (E glob_min(E performedglob_min), and), and (3) (3) inthe orderthe LB LB superposition tosuperposition obtain the best glob_min analysis;analysis;of structures (2) (2) determination determination to define the of ofalignment energy energy of of accuracy. the the global global All minimum minimum steps were glob_min( E(E performedglob_min),), and and (3)in (3) orderthe the LB LBto superposition obtainsuperposition the best performingofanalysis; ofstructures structures (2) FF, determination to either todefine define by the the means alignment of alignment energy of capability accuracy.of accuracy.the global All to All minimumsteps predict steps were were the ( Eperformed performed free), energy and in (3) inorder order ofthe global toLB toobtain superposition obtain minimum the the best best or to of ofstructuresofperforming structures structures to to define FF,to define define either the the thealignmentby alignment alignmentmeans accuracy.of accuracy. capabilityaccuracy. All All Allstepsto steps predictsteps were were were theperformed performed performedfree energy in inorder in oforder order global to toobtain to obtain minimumobtain the the thebest best orbest to superimposeperformingperforming molecules. FF, FF, either either by The by means highermeans of goalofcapability capability of CA to was topredict predict to answer the the free free the energy question:energy of ofglobal Howglobal minimum to minimum consider or or theto to FF of performingperformingperformingsuperimpose FF, FF, FF,either molecules.either either by by meansby means Themeans higherof of capabilityof capability capability goal of to CA to predictto wapredict predicts to the answer the thefree free free energythe energy energy question: of of globalof global globalHow minimum tominimum minimum consider or or thetoor to toFF choicesuperimposesuperimpose while treating molecules. molecules. pesticides: The The higher higher by predictedgoal goal of ofCA CAE wa was tos toanswer valuesanswer the orthe question: by question: alignment How How to capability? toconsider consider the the FF FF superimposesuperimposeof choice while molecules. molecules. treating The Thepesticides: higher higher goal bygoal predicted of of CA CAglob_min wa wa Esglob_min sto to answer answer values the the or question: byquestion: alignment How How capability? to to consider consider the the FF FF ofsuperimpose ofchoice choice while while molecules. treating treating pesticides: The pesticides: higher by goal by predicted predicted of CA waEglob_min Es glob_minto answer values values orthe orby question: by alignment alignment How capability? capability? to consider the FF glob_min of ofchoiceof choice choice while while while treating treating treating pesticides: pesticides: pesticides: by by predictedby predicted predicted Eglob_min E Eglob_min valuesvalues values or orby or by alignmentby alignment alignment capability? capability? capability? Table 4. Training set pesticides of the highest toxicity with the unknown crystal structures: chemical TableTableTable 4. Training4. 4.Training Training set set pesticides set pesticides pesticides of ofthe ofthe highest the highest highest toxicity toxicity toxicity with with withthe the unknown the unknown unknown crystal crystal crystal structures: structures: structures: chemical chemical chemical TableTable 4. 4. Training Training set set pesticides pesticides of of the the highest highest toxicity toxicity with with the the unknown unknown crystal crystal structures: structures: chemical chemical structures,structures,Tablestructures,structures, 4. Training conformational conformational conformational conformational set pesticides analysis,analysis, analysis, ofanalysis, the superposition superposition highest superposition superposition toxicity of of ofthewith of the experimental the the experimental experimentalunknown conformation crystal conformation conformationconformation structures: and and generatedand chemical and generated generated generated structures,structures, conformational conformational analysis, analysis, superposition superposition of of the the experimental experimental conformation conformation and and generated generated globalglobalstructures,global minimaglobal minima minima conformationalminima using using using using the the the best best the bestanalysis, performingperformingbest performing performing superposition force force force force fields. fields. fields. offields. the experimental conformation and generated globalglobal minima minima using using the the best best performing performing force force fields. fields. global minima using the besta performing forceb fields. c d f Pesticide FFa Eglob_minb NGMSc NFd Pesticide FFDAAf PesticidePesticide FFFF a Eglob_minEglob_min b NGMSNGMS c NFNF d PesticidePesticide FFDAA FFDAA f a a b b c c dd ff PesticidePesticidePesticide FF FFaFF a Eglob_minEEglob_min(kJ/mol)glob_minb b NGMSNGMSNGMSc c NFNFdNF d PesticideAlignmentPesticide e FFDAA FFDAARMSD FFDAAf (Å) f g Pesticide FF (kJ/mol)Eglob_min(kJ/mol) NGMS NF AlignmentPesticideAlignment e e RMSD FFDAARMSD (Å) (Å) g g e g atrazine (kJ/mol)(kJ/mol) AlignmentAlignmente e e RMSDRMSD (Å) (Å)g g g atrazineatrazine MM3MM3 MM3 −(kJ/mol)(kJ/mol)1161.48−1161.48−1161.48 445 445 445 23 23 23 Alignment Alignment MM3/MMFFRMSDRMSDMM3/MMFFMM3/MMFF (Å) (Å) atrazineatrazine MM3MM3 −1161.48−1161.48h 445445 23 23 MM3/MMFFMM3/MMFF atrazine AMBER94AMBER94MM3AMBER94 −1161.48NANA hNA h NA445NA NA NA 23NA NA MM3/MMFF 0.892 0.892 0.892 atrazine MM3 1161.48h 445 23 MM3/MMFF AMBER94AMBER94MMFF NA−NA1007.32h h NANA147 NANA 62 MM3/MMFFs 0.892 0.892 AMBER94AMBER94MMFFMMFF −1007.32NA−1007.32 h NA147NA147 NA 62 NA 62 MM3/MMFFs MM3/MMFFs 0.892 0.892 MMFFMMFF −1007.32−1007.32 147147 62 62 MM3/MMFFs MM3/MMFFs MMFFMMFFsMMFFMMFFsMMFFs −−1007.32992.631007.32−992.63−992.63 509147 147509 509 2062 62 20 20 MM3/MMFFs MM3/MMFFs 0.931 0.931 0.931 MMFFsMMFFs −992.63−992.63 509509 20 20 0.931 0.931 MMFFsMMFFsOPLSAA −992.63992.63−783.57 509 509 364 20 20 19 MMFF/MMFF 0.931 0.931 S OPLSAAOPLSAA −783.57−783.57 364364 19 19 MMFF/MMFF MMFF/MMFFS S OPLSAAOPLSAA −783.57−783.57 364364 19 19 MMFF/MMFF MMFF/MMFFSS S OPLSAAOPLSAA −783.57−783.57 364 364 19 19 MMFF/MMFF MMFF/MMFFS 0.3430.343 0.343 0.343 carbofuran MM3 29.60 3617 2 MMFF/MMFF 0.343 0.343 S carbofuran MM3 29.60 3617 2 MMFF/MMFF 0.343 S S carbofuran MM3MM3 29.60 29.60 3617 3617 2 2 MMFF/MMFFMMFF/MMFF S carbofurancarbofuran AMBER94MM3MM3 29.6029.60NA 36173617 NA 2NA 2 MMFF/MMFFMMFF/MMFF 0.075 S S carbofuran AMBER94AMBER94AMBER94MM3 29.60NA NANA 3617 NA NA NA NA2 NA NA MMFF/MMFF 0.075 0.075 S AMBER94AMBER94 NANA NA NA NANA 0.075 0.075 AMBER94MMFFMMFFMMFFMMFF 20.30 20.30NA20.30 20.30 3307 NA 33073307 3307 NA2 2 2 2 MMFF/OPLSAA MMFF/OPLSAA MMFF/OPLSAA MMFF/OPLSAA 0.075 MMFFMMFF 20.3020.30 33073307 2 2 MMFF/OPLSAA MMFF/OPLSAA MMFFsMMFFsMMFFMMFFsMMFFs 15.9220.30 15.9215.9215.92 33843307 3384 3384 3384 2 2 2 2 MMFF/OPLSAA 0.216 0.216 0.216 OPLSAAMMFFsMMFFsMMFFsOPLSAA 15.92 73.2715.9215.9273.27 3384 5621 3384 3384 5621 2 75 2 2 75 MMFFs/OPLSAA MMFFs/OPLSAA 0.216 0.216 0.216 OPLSAAOPLSAA 73.2773.27 5621 5621 75 75 MMFFs/OPLSAA MMFFs/OPLSAA OPLSAAOPLSAAOPLSAA 73.2773.2773.27 5621 5621 5621 75 75 75 MMFFs/OPLSAA MMFFs/OPLSAA MMFFs/OPLSAA0.239 0.239 0.239 0.239 a a b b c c 0.239 0.239 Forcea Forcea field;ForceForce field; field;Energy field; b Energy b Energy ofEnergy the of global ofthe ofthe global minimum;the global global minimum; minimum; minimum;Number c Number ofc Number timesNumber thatof oftimes a oftimes single times that that global thata singlea minimumsinglea single global global global structure minimum minimum 0.239minimum was found a a b b d c c in 10,000a ForceForce processed field; field;b structures; EnergyEnergy of ofNumber the the global global of families minimum; minimum; i.e.,c different NumberNumberd conformations of of times times that that found a asingle insingle 10,000 global global processed minimum minimum structures; structureForcestructurestructure field; was was foundwasEnergy found found in in10,000of in 10,000the 10,000 processedglobal processed processed minimum; structures; structures; structures; Number d Number d Number Number of of times offamilies offamilies familiesthat i.e., a i.e., singledifferent i.e., different different global conformations conformations minimumconformations e d Red—experimentalstructure was found conformation, in 10,000 Violet—MMFFprocessed structures; conformation,e d Numberd Blue—MMFFs of families i.e., conformation, different conformations Green—OPLSAA structurefound inwas 10,000 found inprocessed 10,000 processed structures; structures;e e Red—experimental Number of families conformation, i.e., different conformationsViolet—MMFF foundstructurefound in was fin10,000 found10,000 processedin processed10,000 processed structures; structures; structures; Red—experimentalRed—experimental Numberg of families conformation, conformation, i.e., different Violet—MMFF conformationsViolet—MMFF conformation; Force field dependent alignment accuracy;e e RMSD measured between the heavy atoms of pesticides foundfoundconformation, inin 10,00010,000 Blue—MMFFs processedprocessed conformation,structures;structures;e Green—OPLSAARed—experimentalRed—experimental conformation; conformation,conformation, f Force Violet—MMFF Violet—MMFFfield dependent conformation,foundconformation, in 10,000 Blue—MMFFs Blue—MMFFs processed conformation, conformation,structures; Green—OPLSAA Green—OPLSAARed—experimentalh conformation; conformation; conformation, f Force f Force fieldViolet—MMFF field dependent dependent experimental and best performing force field conformations; Not available. f conformation,conformation, Blue—MMFFs Blue—MMFFsg conformation, conformation, Green—OPLSAA Green—OPLSAA conformation; conformation;f Forcef Force field field dependent dependent alignmentconformation,alignmentalignment accuracy; accuracy; Blue—MMFFs accuracy; g RMSD g RMSD RMSD measured conformation, measured measured between between betweenGreen—OPLSAA the the heavy the heavy heavy atoms atoms conformation;atoms of ofpesticides ofpesticides pesticides experimentalForce experimental experimental field dependent and and bestand best best g alignmentalignment accuracy; accuracy;g RMSDg RMSD measured measured between hbetween the the heavy heavy atoms atoms of of pesticides pesticides experimental experimental and and best best performingalignmentperformingperforming accuracy; force force force field field RMSD fieldconformations; conformations; conformations; measured h betweenNot h Not available.Not available. theavailable. heavy atoms of pesticides experimental and best h CAperforming resultsperformingperforming for force force simazineforce field field field conformations; conformations; conformations; [9], monocrotophos h Not Noth Not available. available. available. [10 ], dimethoate [11], and acetamiprid [12] are reportedCA inCA CAresults Table results results3 for. MM3for simazinefor simazine simazine and [9], AMBER94 [9], monocrotophos[9], monocrotophos monocrotophos could not[10], [10], be[10], dimethoate applieddimethoate dimethoate to [11], all[11], [11], ofand and the andacetamiprid acetamiprid crystallized acetamiprid [12] [12] pesticides [12]are are are CACA results results for for simazine simazine [9], [9], monocrotophos monocrotophos [10], [10], dimethoate dimethoate [11], [11], and and acetamiprid acetamiprid [12] [12] are are as thereportedreported neededreportedCA resultsin inTable parametersinTable Tablefor 3. 3.MM3simazine 3.MM3 MM3 and for and [9],andAMBE the AMBE monocrotophosAMBE optimizationR94R94 R94could could could not not [10],were benot be applied be dimethoateapplied not applied available.to toall toall of[11], all ofthe of theand crystallized Possiblethe crystallized acetamipridcrystallized workaround pesticides pesticides pesticides[12] are as as could as reportedreportedthe needed in in Table Table parameters 3. 3. MM3 MM3 forand and the AMBE AMBE optimizationR94R94 could could were not not be notbe applied appliedavailable. to to all allPossible of of the the crystallized workaroundcrystallized pesticides pesticides could be as theas be thereportedthe needed utilization needed in Tableparameters parameters of 3. AntechamberMM3 for forand the the AMBEoptimization optimization suiteR94 could [75 were], were not by not be whichnot available.applied available. the to genericPossible all Possible of the AMBERworkaround crystallized workaround parameters couldpesticides could be be the couldas the be thethe needed needed parameters parameters for for the the optimization optimization were were not not available. available. Possible Possible workaround workaround could could be be the the utilizationtheutilization neededutilization of parameters ofAntechamber ofAntechamber Antechamber for suitethe suite optimizationsuite [75], [75], [75], by by which by which werewhich the the not genericthe generic available. generic AMBER AMBER AMBER Possible parameters parameters parameters workaround could could could be could be calculated, be calculated, calculated,be the calculated,utilizationutilization but thenof of Antechamber Antechamber a different suite protocolsuite [75], [75], by wouldby which which have the the generic beengeneric developed AMBER AMBER parameters parameters instead ofcould could the onebe be calculated, calculated, based on the bututilizationbut thenbut then then a differentofa different aAntechamber different protocol protocol protocol suite would would would[75], have haveby have beenwhich been been deve thedeve developed genericlopedloped instead insteadAMBER instead of ofthe parameters ofthe one the one basedone based based could on on the on bethe well-known the calculated, well-known well-known well-knownbutbut then then accrediteda a different different protocol Schrödingerprotocol would would softwarehave have been been [deve76 deve].loped MMFFloped instead instead showed of of the the to one one be based the based only on on the FFthe well-known containingwell-known the accreditedbutaccredited thenaccredited a differentSchrödinger Schrödinger Schrödinger protocol software softwarewould software have[76]. [76]. been[76]. MMFF MMFF deveMMFF lopedshowed showed showed instead to to ofbe to be thethebe onethe theonly basedonly only FF onFF FFthecontaining containing well-knowncontaining the the the accreditedaccreditedaccredited Schrödinger SchrödingerSchrödinger software softwaresoftware [76]. [76].[76]. MMFF MMFFMMFF showed showedshowed to totobe be bethe the theonly onlyonly FF FF FFcontaining containingcontaining the the the

Molecules 2018, 23, 2192 8 of 37 parameterizations for all of the compounds; MMFFs failed in the optimization of simazine whereas OPLSAA was not applicable to monocrotophos and acetamiprid. The absolute values of Eglob_min are not necessarily good measures of FF quality [77]. FFs and are usually parameterized to give good values of relative energies among different conformations of the same molecule [77], so a lower value of energy for a global minimum does not necessarily mean that a given FF would perform better [77]. The energy differences between the conformations are simple reliable indicators of conformational analysis algorithm ability than the absolute energy values [77]. Therefore, the evaluation of conformation reproducibility was achieved by means of calculated minima root mean square deviation (RMSD) values [78] upon conformations’ superimposition (Tables3 and4 , Tables S1–S3). Comparison of the experimentally available crystal structures conformations with those obtained by CA revealed, a high level of performance by MMFF (displaying RMSD values lower than 1 Å for all of the four considered pesticides) [78]. That was somehow expected, given that MMFF-based optimization was applicable to all of the listed pesticides. Regarding the MMFFs and OPLSAA, these FFs only succeeded in reproducing the crystal structure of acetamiprid.

2.2. The Prediction of Pesticides Structures in Aqueous Solution The above assessed CA procedure was further applied to the training set pesticides with an unknown crystal structures. The results of optimization for the pesticides with the highest acute toxicity (i.e., the lowest LD50 values), atrazine and carbofuran, using the best performing FFs, are reported in Table4, while the comparison of all utilized FFs for atrazine, carbofuran, and the remaining compounds are presented in Tables S1–S3. As expected, AMBER94 FF, as implemented in Schrödinger suite [76] was not applicable at all, MM3, MMFF and MMFFs FFs gave similar global minima for the majority of the listed pesticides, while OPLSAA was not applicable for all compounds. A significant conformational alignment accuracy (RMSD < 1 Å) was achieved for atrazine (MM3/MMFF, MM3/MMFFs, and MMFF/MMFFs combinations, Table2, Table S1) and carbofuran, (MMFF/MMFFs, MMFF/OPLSAA, and MMFFs/OPLSAA combinations, Table3, Table S2). Summarizing the CA results, conclusion can be made, despite the limited number of training set compounds, MMFF is universally applicable FF for either Eglob_min calculation or RMSD-based alignment accuracy assessment and can be used in any further study, describing the pesticides conformational analysis.

2.3. The Prediction of Externally Evaluated Pesticides Structures in Aqueous Solution MMFF was thereafter used to predict the global minimum conformation of test set pesticides (Table2) as well. The results of the optimisation are presented as Supplementary Materials (Table S4). Global minimum conformations were generated for by the means of the identical CA setup. Generated conformations were then used for the purposes of training set results external validation.

2.4. The Pesticides Acute Toxicity Anticipation through the Pre-Bound Conformations The lowest energy conformers of the 2-chloro-1,3,5-triazine group were of high stability in the aquous solution, according to the values obtained by MMFF (Tables3 and4, Table S1). Being chemically stable, pesticides may in perspective saturate the AChE active site and low values of global minimum (Eglob_min) represent the indicators of high acute toxicity (i.e., the low LD50 values) against Mus musculus. For either atrazine, propazine, or simazine, low Eglob_min values are indeed the precondition of high acute toxicity (Table1: LD 50 values equal to 0.85, 3.18, and 5 mg/kg of body weight, respectively, Tables3 and4, Table S1: Eglob_min values equal to −1007.32, −1022.18, and −992.47 kJ/mol, respectively). For much of the lasting pesticides (monocrotophos and dimethoate: Table1 vs. Table3 and Table S2; carbaryl and tebufenozide: Table1 vs. Table S2; imidacloprid: Table1 vs. Table3 and Table S3, and acetamiprid: Table1 vs. Table S3), it appeared that high to medium acute toxicities mostly correlate with low to medium Eglob_min values. The above paradigm was confirmed for carbaryl and tebufenozide, where the high Eglob_min values are a precondition for low acute toxicity (Table1: LD 50 values equal to 100 and 5000 mg/kg of Molecules 2018, 23, 2192 9 of 37

body weight, respectively, Table S2: Eglob_min values equal to 20.43 and 467.38 kJ/mol, respectively), as well as for monocrotophos and dimethoate, whose medium LD50 values (Table1: LD 50 equal to 14 and 60 mg/kg of body weight, respectively) are associated with medium Eglob_min values (Table3: Eglob_min values equal to −307.36 and −383.68 kJ/mol, respectively). On the other hand, the high acute toxicity of carbofuran against Mus musculus (Table1: LD 50 = 2 mg/kg of body weight) disagreed with calculated high Eglob_min values (Table4: Eglob_min value equal to 20.30 kJ/mol). Interestingly, a thermodynamic parameter calculated for carbofuran suggests some instability in aqueous solution; according to the previous observations, a high dosage of pesticide would be required to induce mortality in Mus musculus. Therefore, other parameters need to be considered, to explain why carbofuran acts as an outlier. Among the last group of pesticides, acetamiprid (Table1 vs. Table3 and Table S3) and imidacloprid (Table1 vs. Table S3) also follow the archetype that relatively low Eglob_min values are a precondition for medium LD50 dosages. Linuron, however, behaves oppositely to 2-chloro-1,3,5-triazines group inasmuch as with its low Eglob_min values there is a high LD50 value (Table1: LD 50 = 2400 mg/kg of body weight, Table S3: Eglob_min value equal to −992.47 kJ/mol). Linuron’s structural analogues diuron and monuron, despite the fact they are slightly less stable (higher Eglob_min values, Table S3: Eglob_min values equal to −142.96 and −197.63 kJ/mol, respectively) need to be administered at high dosages to induce mice mortality (Table1, LD 50 = 500 and 1700 mg/kg of body weight, respectively). In order to enumerate the Mus musculus LD50/Eglob_min interconnection, simple linear regression (as implemented in LibreOffice Calc) was analysed considering pLD50 (calculated by converting LD50 from mg/kg of body weight to −log(mol/kg of body weight)), as dependent variable, and Eglob_min values as calculated by MMFF (Table S5), as descriptive independent variables. The use of all the data (model 0) did not lead to a significant statistical regression. However, the exclusion of carbofuran and linuron as highlighted outliers (those with the worse pLD50 fitted values), led to a monoparametric QSAR model 1 (Equation (2)):

2 pLD50 = −0.0021Eglob_min − 2.82 (r = 0.78), (2)

Additional exclusion of diuron and monuron further increased the statistical robustness leading to a QSAR model 2 (Tables S5 and S6, Figure2) with more than 90% of explained variance (90.5%) (Equation (3)): 2 pLD50 = −0.0019Eglob_min − 3.05 (r = 0.905), (3)

The obtained model 2 estimated the pLD50 values of carbofuran, linuron, diuron, and monuron, as in situ generated test set, with good accuracy (Figure2a). On the other hand, model 2 was also used to predict the Mus musculus pLD50 values of the test set pesticides (Tables 2 and S6, Figure2b). However, despite the good statistical potential of model 2 (i.e., the explained variance value), the Eglob_min values cannot be considered as valuable indicators to anticipate the Mus musculus pLD50 values and for the acute toxicity prediction. Molecules 2018, 23, 2192 10 of 37 Molecules 2018, 23, x 10 of 37

Figure 2. The plot of experimental vs. fitted pLD50 values calculated with QSAR model 2 for the Figure 2. The plot of experimental vs. fitted pLD50 values calculated with QSAR model 2 for the training set pesticides (training set values are depicted by blue circles; internal test set values are training set pesticides (training set values are depicted by blue circles; internal test set values are indicated by orange squares) (a); test set pesticides (green circles) (b) against Mus musculus. The plot indicated by orange squares) (a); test set pesticides (green circles) (b) against Mus musculus. The plot of calculated vs. fitted pLD50 values calculated with the QSAR model 4 for the training set pesticides of calculated vs. fitted pLD50 values calculated with the QSAR model 4 for the training set pesticides (training set values are are depicted depicted by blue blue circles; circles; inte internalrnal test test set set values values are are indicated indicated by by orange orange squares squares (c); test set pesticides (green circles) (d) against Homo sapiens..

Moreover, models 1 and 2 cannot be universally applied for the prediction of the Homo sapiens Moreover, models 1 and 2 cannot be universally applied for the prediction of the Homo sapiens pLD50 as the Eglob_min values are common to both model organisms. Therefore, different models are pLD as the E values are common to both model organisms. Therefore, different models are required50 for Homoglob_min sapiens as model organism. In that sense, additional models were developed from required for Homo sapiens as model organism. In that sense, additional models were developed from calculated Homo sapiens pLD50 values (Equation (1)). As expected, the incorporation of all the training calculated Homo sapiens pLD values (Equation (1)). As expected, the incorporation of all the training set, pesticides did not lead to50 any statistically significant model. As above, exclusion of carbofuran set, pesticides did not lead to any statistically significant model. As above, exclusion of carbofuran and linuron led to the model 3 (Equation (4)): and linuron led to the model 3 (Equation (4)): = −0.0021_ + 3.01 = 0.783, (4) pLD = −0.0021E + 3.01 (r2 = 0.783), (4) and further exclusion of diuron 50and monuron ledglob_min to model 4 (Equation (5), Tables S7 and S8, Figure 2c,d): and further exclusion of diuron and monuron led to model 4 (Equation (5), Tables S7 and S8, Figure2c,d): = −0.0019_ + 4.15 = 0.91, (5) 2 pLD50 = −0.0019Eglob_min + 4.15 (r = 0.91), (5) Like for Mus musculus and Homo sapiens, the pLD50 values were not fully satisfactory correlated to theLike global for Mus minima musculus energies,and Homo leading sapiens to, thethe pLDconclusion50 values that were E notglob_min fully values satisfactory are not correlated adequate to indicatorsthe global minimato anticipate energies, the pLD leading50 against to the any conclusion model organism, that Eglob_min the levelvalues was are changed not adequate from indicatorsLB to SB, directingto anticipate that the thepLD free50 against energies any of model binding organism, could thebe levelconsidered was changed as appr fromopriate LB toacute SB, directingtoxicity indicators.that the free Free energies energies of binding of binding could can be consideredbe calculated as appropriateseparately for acute each toxicity pesticide indicators. and model Free organism,energies of by binding performing can be molecular calculated docking separately studies, for each either pesticide for Mus and musculus model organism, AChE or by Homo performing sapiens AChE.molecular docking studies, either for Mus musculus AChE or Homo sapiens AChE.

2.5. The Structure-Based Studies To get more insights into the mechanistic profile of understudied pesticides, their interactions with either mAChE and hAChE, as molecular targets, were also considered. Sequence similarity value between mAChE and hAChE was found to be 88.44% (Figure S1), rising to the 100% identity between

Molecules 2018, 23, 2192 11 of 37

2.5. The Structure-Based Studies To get more insights into the mechanistic profile of understudied pesticides, their interactions with either mAChE and hAChE, as molecular targets, were also considered. Sequence similarity value between mAChE and hAChE was found to be 88.44% (Figure S1), rising to the 100% identity between [the active sites, indicating that similar pharmacodynamics profile should be expected with either mAChE or hAChE by the same molecule. Therefore, the application of SB tools could represent the computational approach to predict the biochemical mechanism and hence the level of acute toxicity. Two SB methodologies were chosen: molecular docking and molecular dynamics. Docking and dynamics studies were initially performed to anticipate the bioactive conformations of pesticides with known acute toxicity and unknown binding mode into the AChE, after which the obtained free energies of binding were correlated to the acute toxicities. Despite the fact there are no co-crystalized AChEs in complex with pesticides as either non-covalent or covalent inhibitors, it was arbitrarily decided to simulate reversible docking, for pure reversible AChE inhibitors, and reversible-like docking, for covalent AChE inhibitors, followed by the appropriate, one step molecular dynamics simulations. Reversible-like docking, was supposed to obtain the pre-covalent conformation that will lead to the AChE covalent modification by literature-claimed [73] covalent inhibitors. The ultimate task of SB studies was to reveal the free energies of binding and to correlate them to the pesticides acute toxicities.

2.5.1. The Alignment Rules Assessment In order to learn how to perform the SB alignment of targeted pesticides within the AChE active sites of either mouse or human molecular target, the 3-D coordinates of reversible AChE inhibitors were taken from their corresponding minimized complexes and used to gain the knowledge how to reproduce their co-crystallized conformations by means of the SB alignment assessment, as well as to determine the best SB molecular docking methodology. Within the SB alignment assessment, AutoDock [79], AutoDock Vina [80] (in the future text just Vina) and DOCK [81] were evaluated to select the best docking algorithm/scoring function and to perform the SB positioning of pesticides. The SB alignment assessment procedure was performed with the standard four step protocol [78]: Experimental Conformation Re-Docking (ECRD), Randomized Conformation Re-Docking (RCRD), Experimental Conformation Cross-Docking (ECCD), and Randomized Conformation Cross-Docking (RCCD). Thus, within the ECRD stage, Vina and DOCK possessed the highest ability to reproduce the experimental conformations of Mus musculus and Homo sapiens AChE inhibitors. Even 75% of the available inhibitors were correctly reproduced by Vina, whereas DOCK was slightly less potent, reproducing the 50% of structures in either rigid or flexible manner, respectively (Tables S9 and S10). Similarly, Vina was of the highest potency in the initial reproduction of Mus musculus AChE inhibitors with the docking accuracy (DA) of 55.55% (Table S9). DOCK, however, completely failed in the reproduction the experimental poses of Mus musculus AChE inhibitors (Table S9). In the initial process, as well as in all other difficulty levels, AutoDock algorithm failed in the experimental conformations reposition. Similar potency for Vina and DOCK was observed within the RCRD stage in the process of human inhibitors reproduction (Table S10, Vina DA equal to 68.75%, DOCK DA equal to 56.25%, respectively). While processing mouse inhibitors (Table S9), Vina re-positioned the modelled inhibitors structures with the high efficiency (DAs equal to 57.78%), while DOCK’s potency dropped below 30%. The level of difficulty was increased during the ECCD stage where either Vina or DOCK retained the high level of accuracy while cross-aligning of human inhibitors (Table S10). As for the other model organism, either Vina or DOCK were inaccurate while matching the co-crystallized inhibitors with diverse mouse enzymes (Table S9). The decisive difference in favour of Vina, by means of the general docking accuracy, was noticed within the RCCD stage, as the most difficult one. The cross-alignment of randomized conformations is considered as the most important validation stage for any docking program as it represents the Molecules 2018, 23, 2192 12 of 37 ability of a program to position a random ligand conformation in a non-native environment, i.e., into its molecular target whose active site amino acids suffered induced fit conformational change due toMolecules the presence 2018, 23, x of structurally different inhibitors. Within the RCCD stage, Vina was far superior12 of 37 in comparison with other programs, by means of The SB alignment accuracy, and, therefore, can be considered as aa valuablevaluable tooltool forfor thethe predictionprediction ofof bioactivebioactive conformationsconformations ofof acetylcholineacetylcholine esteraseesterase inhibitorsinhibitors withwith thethe unknownunknown bindingbinding mode.mode.

2.5.2. The Cross-Docking and MolecularMolecular DynamicsDynamics StudiesStudies ofof AChACh Both the training set or the test set pesticides were submitted to the herein Vina-based proposed SB alignment protocols, protocols, that that have have been been validated validated by reproducing by reproducing the bioactive the bioactive conformations conformations of PDB- of PDB-availableavailable inhibitors inhibitors in complex in complex with AChE with AChE(Supplem (Supplementaryentary Materials Materials Tables TablesS9 and S9 S10, and and S10, Figure and FigureS2) and S2) applied and applied in situ in situpredicting in predicting the bioactive the bioactive conformations conformations of ACh of (Figure ACh (Figure 3). 3). As nono experimentalexperimental structures of AChACh inin complexcomplex withwith eithereither wild-typewild-type mAChE or hAChE are available in the Protein Data Bank, its bioactive conformation within both enzymes was predicted by means of Vina, asas the best performingperforming SB alignment assessmentassessment tool (Figure3 3a,b,a,b, seesee SupplementarySupplementary Materials AlignmentAlignment Rules Rules Assessment Assessment section, section, Tables Tables S9 and S9 S10).and S10). The stability The stability of either of ACh-eitherm AChEACh- ormAChE ACh- orhAChE ACh-h complexAChE complex was confirmed was confirmed using using one one step step molecular molecular dynamics dynamics (MD) (MD) runs, runs, uponupon thethe inspectioninspection ofof CCαα RMSDRMSD valuesvalues (1.2(1.2 nsns simulationsimulation length,length, FiguresFigures S7aS7a andand S8a),S8a), RMSFRMSF valuesvalues ((FiguresFigures S7bS7b andand S8bS8b),), andand trajectoriestrajectories energyenergy termsterms (data(data notnot shownshown butbut availableavailable fromfrom thethe authorsauthors upon request).request). The short-termed MD protocol was sufficientsufficient toto produceproduce stablestable complexes.complexes. TheThe twotwo AChACh posesposes (in(in mmAChEAChE oror hhAChE)AChE) werewere conformationallyconformationally veryvery close,close, displayingdisplaying a RMSDRMSD valuevalue ofof 0.043 Å.

Figure 3.3. The SB alignmentalignment ofof acetylcholineacetylcholine intointo mmAChEAChE activeactive sitesite ((aa);); hhAChEAChE activeactive sitesite ((bb).). TheThe enzyme ribbons are presented in blue and gold, respectively,respectively, activeactive sitesite aminoamino acidsacids areare depicteddepicted inin white.white. For For the the purpose purpose of of clarity, clarity, hydrogen hydrogen atoms atoms are are om omitteditted from from thethe presentation. presentation. The Thegraphic graphic was wasgenerated generated using using the theUCSF UCSF Chimera Chimera software software (R (Resourceesource for for Biocomputing, Biocomputing, Visualization, andand InformaticsInformatics (RBVI),(RBVI), UniversityUniversity ofof California,California, SanSan Francisco,Francisco, CA,CA, USA).USA).

As expected,expected, the positive quaternary ACh amineamine group was located in the anionic sub-site, wherewhere thethe orientationorientation ofof particularparticular groupgroup isis supportedsupported byby strongstrong hydrophobichydrophobic interactionsinteractions with a m((h)Trp86)Trp86 methylmethyl group,group, asas wellwell asas withwith m(h)Tyr124, m((h)Tyr337,)Tyr337, andand mm((hh)Tyr341)Tyr341 aromaticaromatic moietiesmoieties (Figures(Figures S7cS7c andand S8c).S8c). TheThe positivelypositively chargedcharged amineamine waswas electrostaticallyelectrostatically attracted by thethe electronicelectronic cloud of the m((h)Trp86)Trp86 aromaticaromatic group.group. TheThe acetylacetyl groupgroup occupiedoccupied thethe esteraseesterase sub-site:sub-site: the carbonyl oxygen was involved involved in in the the electrostatic electrostatic interactions interactions with with m(hm)Tyr337(h)Tyr337 side side chain chain hydroxyl hydroxyl group group and andm(h)His447m(h)His447 imidazole imidazole ring, ring, while while the thecarbonyl carbonyl ox oxygenygen was was oriented oriented towards towards the the side side chain ofof m((h)Tyr133. Regarding the the mouse mouse enzyme, enzyme, during during the the MD MD run, run, the the carbonyl carbonyl moiety moiety was was observed observed to be involved in the hydrogen bonding with mTyr133 for 29% of simulation time (Figure S8c, dHB = 1.943–2.337 Å) whilst for human enzyme the carbonyl group was mainly involved in the electrostatic interactions with hSer203 and hHis447 (Figure S8c). The analysis of docking and MD results agreed with the hydrolysis reaction pathway of ACh (Figure 1a) that was also externally confirmed by QM/MM studies elsewhere [82]. In fact, the ACh molecule had been approaching m(h)Ser203 during

Molecules 2018, 23, 2192 13 of 37 to be involved in the hydrogen bonding with mTyr133 for 29% of simulation time (Figure S8c, dHB = 1.943–2.337 Å) whilst for human enzyme the carbonyl group was mainly involved in the electrostatic interactions with hSer203 and hHis447 (Figure S8c). The analysis of docking and MD results agreed with the hydrolysis reaction pathway of ACh (Figure1a) that was also externally confirmed by QM/MM studies elsewhere [82]. In fact, the ACh molecule had been approaching m(h)Ser203 during the simulation for the 57% of the time, where the range of distances between the acetyl group and the catalytic residue was 1.473–1.894 Å (Figures S7c and S8c).

2.5.3. The Cross-Docking and Molecular Dynamics Studies of Pesticides 2-chloro-1,3,5-triazine Group Atrazine’s, simazine’s and propazine’s acute toxicity (Table1) can be explained by means of their docked conformations, within either mAChE or hAChE (Figures4 and5, respectively). The graphical interpretation of the results of the SB and MD studies are herein shown for atrazine (Figures4a and5a, Figure S9 and Figure S10, respectively) and simazine (Figures4b and5b, Figure S13 and Figure S14, respectively), whereas the corresponding illustrations considering the molecular modelling studies of propazine are reported as Supplementary Materials (Figure S3a, Figure S5a, Figure S11, Figure S12, respectively). The best-docked poses of the triazine-based pesticides were found to occupy the ACh binding cavities of both the mAChE and hAChE. The main differences were not related to the predicted pesticides bioactive conformations, but were mainly ascribed to enzymes active site residue Thr83: the side chain methyl group of mAChE Thr83 pointed toward the anionic sub-site, whereas in the human enzyme the corresponding group is flipped out vertically from the active site. The latter caused the differences in the stabilization period during the MD runs: atrazine-mAChE, propazine-mAChE, and simazine-mAChE complexes were respectively of high stability after 0.100 ns, 0.120 and 0.610 ns (Figures S9a, S11a and S13a), whereas the complexes of human analogues equilibrated approximately 20 ps afterwards (Figures S10a, S12a and S14a). Molecules 2018, 23, 2192 14 of 37 Molecules 2018, 23, x 14 of 37

FigureFigure 4.4.The The SB SB alignment alignment of atrazineof atrazine (a); simazine(a); simazine (b); carbofuran (b); carbofuran (c); monocrotophos (c); monocrotophos (d); dimethoate (d); (edimethoate); imidacloprid (e); imidacloprid (f) into the m (fAChE) into activethe mAChE site. The active enzyme site. The ribbons enzyme are presentedribbons are in presented blue, the in active siteblue, amino the active acids site are amino depicted acids in ar white.e depicted For the in purposewhite. For to the clarify, purpos thee hydrogento clarify, the atoms hydrogen are omitted. atoms The graphicare omitted. was generated The graphic using was the UCSFgenerated Chimera usin softwareg the UCSF (Resource Chimera for Biocomputing,software (Resource Visualization, for andBiocomputing, Informatics Visualization, (RBVI), University and Informatics of California, (RBVI), San Francisco,University CA,of California, USA). San Francisco, CA, USA).

Molecules 2018, 23, 2192 15 of 37 Molecules 2018, 23, x 15 of 37

FigureFigure 5. The5. The SB alignmentSB alignment of atrazine of atrazine (a); simazine (a); simazine (b); carbofuran (b); carbofuran (c); monocrotophos (c); monocrotophos (d); dimethoate (d); (e);dimethoate imidacloprid (e); ( fimidacloprid) into the hAChE (f) into active the h site.AChE The active enzyme site. ribbonsThe enzyme are presented ribbons are in presented gold; the activein gold; site aminothe active acids aresite depictedamino acids in white. are depicted For the in purpose white. For to clarify,the purpose the hydrogen to clarify, atoms the hydrogen are omitted atoms from are the presentation.omitted from The the graphic presentation. was generated The graphic using the wa UCSFs generated Chimera using software the (ResourceUCSF Chimera for Biocomputing, software Visualization,(Resource for and Biocomputing, Informatics (RBVI), Visualization, University and of In California,formatics (RBVI), San Francisco, University CA, of USA). California, San Francisco, CA, USA). Nevertheless, within either mice or human bioactive conformations, the 2-chloro-1,3,5-triazines were parallelNevertheless, to m(h)Trp86 within and eitherm(h mice)Tyr337, or human trapped bioactive in the hydrophobic conformations, cage the between 2-chloro-1,3,5-triazines two residues. The individualwere parallel contribution to m(h)Trp86 of these and interactionsm(h)Tyr337, wastrapped respectively in the hydrophobic−37.34 and cage−19.9 between kcal/mol, two residues. according The individual contribution of these interactions was respectively −37.34 and −19.9 kcal/mol, to the Free-Energy Decomposition Analysis, FEDA (Table S11). Atrazine bioactive conformations according to the Free-Energy Decomposition Analysis, FEDA (Table S11). Atrazine bioactive were nearly identical in both enzymes. On the other hand, comparing simazine docked structures ◦ (Figures 4b and5b), the one found in hAChE (Figure5b) was in-plane rotated for about 30 . The Molecules 2018, 23, 2192 16 of 37 triazine nitrogen atom, p-positioned in relation to chlorine, was electrostatically stabilized by both the hydroxyl group of m(h)Tyr337 and the indole nitrogen of m(h)Trp86. The individual contribution of these interactions was respectively −34.26 and −15.56 kcal/mol, according to FEDA (Table S11). Within the mAChE, the m-N’ atoms, holding the isopropyl function of atrazine (Figure4a), and one of the ethyl groups within simazine (Figure4b), were oriented toward the mThr83 methyl group and mTyr341 phenolic moiety. All the described interactions were confirmed during the MD simulation (Figure S9c and Figure S13c, respectively). The atrazine m-N’ atom was involved in a strong hydrogen bonding (HB) (dHB = 2.253–2.976 Å) with the hThr83 hydroxyl group (Figure S10c) in 56% of MD run time. A similar interaction was not detected during the atrazine-mAChE complex MD run (Figure S9c), suggesting that the hThr83 conformational flip and the existence of hThr86-m-N0 HB may even increase the acute toxicity of atrazine to humans. Regarding the simazine, as a consequence of the in-plane rotation, its m-N’ atom created HB with hTyr341 (dHB = 2.341–3.127 Å, 76% of the time of simulation, Figure S14c). Furthermore, the functional groups that substitute the remaining m-N” atoms were directed towards the hTyr133, hSer203, and hHis447, and HB-attracted by hHis447 (simazine established the strongest HB, dHB = 2.379–3.242 Å, 94% of MD time, Figure S14c). Since the precise hydrogen bonds were not observed during the MD simulation within the mAChE, they may represent some indicators that the atrazine and simazine could exert even higher acute toxicity against humans than against mice. Moreover, the described docking/MD interactions were all confirmed by the FEDA application (Table S11). Regarding propazine, the m-N0 atoms, holding the isopropyl units or propazin (Figure S5a) were oriented within the mAChE towards the side chain methyl group of mThr83 and a phenolic moiety of mTyr341. Similarly to atrazine and simazine, propazine may be even more toxic to humans than to mice, as it exerts the toxicity against humans by establishing the hydrogen bonds with hTyr341 (dHB = 2.286–3.114 Å) and hHis447 (dHB = 2.121–3.331 Å) in the 45% and the 95% of time, respectively (Figure S12c). Attracted to mThr83, propazine was limited with the ability to make hydrogen bonds with mTyr341 or mHis447, as confirmed by MD studies (Figure S11c).

2.5.4. The Cross-Docking and Molecular Dynamics Studies of Pesticides Amide Group Among the amide-based pesticides, carbofuran and monocrotophos were of the highest acute toxicity (Table1). Therefore, the results of carbofuran (Figures4c and5c, Figure S15 and Figure S16, respectively) and monocrotophos (Figures4d and5d, Figures S17 and Figure S18, respectively) docking and MD studies are herein reported and discussed, whereas the corresponding graphical interpretations for lower toxic dimethoate (Figure4e, Figure5e, Figure S19, Figure S20, respectively), carbaryl and tebufenozide are reported as a Supplementary Materials (Figure S4, Figure S5, Figures S21–S24, respectively). Carbofuran was the most toxic against Mus musculus (Table1). According to the literature, this particular pesticide is, as a carbamate derivative, proclaimed to be the reversible AChE inhibitor [73]. The results of herein conducted SB studies are in full agreement with the proposed/confirmed reversible inhibition of AChE by carbofuran. Hence, within either mAChE or hAChE active site, the compound’s methyl methylcarbamate scaffold contributed as follows: the N-methyl group was positioned between the methyl group of m(h)Thr83 and m(h)Trp86 (Figures4c and5c), a carbonyl group interfered with m(h)Tyr341 while the ether link was electrostatically stabilized by hydroxyl groups of m(h)Tyr124, m(h)Tyr337, and m(h)Tyr341, respectively. However, during the MD simulations, methylcarbamate displayed rotation towards the m(h)Tyr124 (Figures S15c and S16c) upon which the amide carbonyl group was involved in strong HB with m(h)Tyr124 for the 40% of time (dHB = 2.478−2.783 Å, Figure S15c and Figure S16c, respectively), indicating a possible reason for carbofuran acute toxicity. The other HB was formed between the secondary amine and m(h)Trp86 (dHB = 2.784−3.226 Å, Figure S15c and Figure S16c, respectively). Furthermore, the 2,2-dimethyl-2,3-dihydrobenzofuran part of carbofuran was located beneath the m(h)Trp86 and established hydrophobic interactions with m(h)Tyr337 due to the π-π stacking, as well as the Molecules 2018, 23, 2192 17 of 37 electrostatic interactions with m(h)Tyr124 via 2,2-dimethyltetrahydrofuran oxygen atom. Moreover, all the described docking/MD interactions were confirmed upon conducting the FEDA procedure (Table S11). The covalent mode of inhibition [73] and the high acute toxicity of organophosphorus-based pesticides monocrotophos and dimethoate against Mus musculus and Homo sapiens were primarily conditioned by the interactions of their amide groups with AChE. Hence, in the best docking pose of monocrotophos within mAChE, the amide carbonyl was oriented toward the hydroxyl group of mTyr341 (Figure4d). Such interaction was a result of hydrophobic stabilization between the pesticide’s allyl methyl group and the mTyr341 phenyl ring, as well of the N-methyl group and mThr83. Still, within the human enzyme (Figure5d), corresponding amide carbonyl group approached the hThr83 hydroxyl group, confirming that the orientation of hThr83 makes a difference in SB alignment in hAChE. The consequent important monocrotophos interactions were those generated by the dimethylated phosphoric acid. Thus, the phosphoric acid P=O group established electrostatic interferences with mAChE Tyr124 (Figure4d); the precise oxygen atom served as an HB-acceptor to mTyr124 during the MD simulation (dHB = 2.227–2.946 Å, Figure S17c). For the purpose of hAChE inhibition, the corresponding monocrotophos carbonyl group was, due to the strong hydrophobic attraction between the phosphoric acid methoxy groups and hTrp86, only partially directed towards the hTyr124 (Figure5d). However, monocrotophos adapted its conformation/binding upon 0.718 ns of MD simulations with hAChE (Figure S18a), and, contrarily to mAChE, hTyr124 was involved in 96% of the time in HB with the amide carbonyl (dHB = 1.984–2.117 Å, Figure S18c). Moreover, one of the phosphoric acid oxygen atoms made HB with hTyr337 (35% of simulation time, dHB = 2.449–2.688 Å, Figure S18c). Still, inhibiting mAChE or hAChE, the monocrotophos phosphoric acid moiety remained situated in the proximity of m(h)Ser203 and m(h)His447 (the average distances: 1.25–1.783 Å for mAChE, 1.375–1.651 Å for hAChE, Figure S17c and Figure S18c, respectively), suggesting that the covalent modification of mSer203 or hSer203 will occur in vivo [74]. Moreover, all the described docking/MD interactions were confirmed upon conducting the FEDA (Table S11). The monocrotophos structural analogue, dimethoate, is, as Mus musculus and Homo sapiens AChE inhibitor, limited with the capacity to interfere with m(h)Tyr341 by means of steric interactions, inasmuch as it does not contain the allyl methyl group (Figures4e and5e, respectively). Hence, although dimethoate is in both active sites superimposed to monocrotophos, by means of backbone orientation (Figures4d and5d, respectively), its amide carbonyl is oriented towards m(h)Tyr124 and m(h)Tyr337. The bioisosteric replacement of the phosphoric acid carbonyl group with the thione one influenced that the sulfur atom is within the mouse enzyme directed to the hydroxyl group of m(h)Tyr337, while within the human one the thione moiety is in reach of the m(h)Ser203 and m(h)His447. However, surprisingly, there was a little consistency between the best-docked structure of dimethoate within the mouse active site (Figure4e) and the molecular dynamics solutions (Figure S19). Thus, pesticide’s amide carbonyl established no interactions, while the amide nitrogen was periodically involved in hydrogen bonding with mTyr341 time (dHB = 2.971–3.557 Å, Figure S19c). Thione functional group was HB-acceptor to mHis447 (25% of the time, dHB = 2.894–3.431 Å), while one of the methoxy functions was in the HB-vicinity to mGly121 (27% of the time, dHB = 2.723–3.338 Å). Those interactions allegedly provide the opportunity for mSer203 to perform the electrophilic attack on pesticide (Figure6f). On the other side, there was a high level of agreement between the dimethoate rigid docking (Figure5e) and molecular dynamics within the human enzyme, by means of the amide carbonyl group interactions, given that this pharmacophore was for the 95% of time included in hydrogen bonding with hTyr124 (dHB = 1.643–2.128 Å, Figure S20c). Moreover, one of the phosphoric acid oxygens was, as for monocrotophos, used to make a hydrogen bond with hTyr337 (35% of simulation time, dHB = 2.449–2.688 Å, Figure S20c). In general, considering the overall orientation of the molecule, dimethoate would most likely behave as a covalent inhibitor of human AChE (Figure6f), as well. Molecules 2018, 23, 2192 18 of 37 Molecules 2018, 23, x 21 of 37

Figure 6. Schematic view of pesticides binding interactions within the hAChE active site: atrazine, simazineFigure 6. orSchematic propazine view (a); carbofuranof pesticides or binding carbaryl interactions (b); monocrotophos within the or dimethoatehAChE active (c) site: imidacloprid atrazine, orsimazine acetamiprid or propazine (d); diuron, (a); carbofuran monuron, or or carbaryl linuron (eb).); monocrotophos The hydrogen bonds or dimethoate are presented (c) imidacloprid with pink dashedor acetamiprid half arrows, (d); diuron, the hydrophobic monuron, interactions or linuron ( withe). The a blue hydrogen dot-line bonds marker, are thepresented ionic interactions with pink withdashed the half red dashedarrows, lines.the hydrophobi The proposedc interactions mechanism with of monocrotophosa blue dot-line marker, or dimethoate the ionic acute interactions toxicity againstwith theh AChEred dashed (f). lines. The proposed mechanism of monocrotophos or dimethoate acute toxicity against hAChE (f). Carbaryl reached the comparable bioactive conformation to carbofuran (Figures S3b and S5b), The results of molecular docking are presented as a Supplementary Materials (Figures S35–S42). within both species AChE active sites, with the difference that the 2,2-dimethyltetrahydrofuran scaffold The generated conformations were used further on for the external validation of the training set is in the structure of particular pesticide replaced with another benzene ring. Such replacement has a results.

Molecules 2018, 23, 2192 19 of 37 direct consequence in a diminished toxicity of carbaryl in comparison with carbofuran, against either mice or humans, since carbaryl cannot establish additional electrostatic interactions with m(h)Tyr124. Regarding carbaryl, it is proclaimed (Table1) that this pesticide is more than fifty times less toxic than carbofuran when administered orally to Mus musculus, and MD revealed the reason. Hence, within the mAChE, carbaryl’s amide carbonyl group forms a hydrogen bond, not with the mTyr124, but with the HB-network made of ordered water molecules and mAsn87 (Figure S21c). The precise function also establishes the pure HB with mSer125 (75% of simulation time, dHB = 2.335–2.412 Å, Figure S21c). However, according to the MD study performed on the carbaryl-hAChE complex, there is a 36% of probability that particular carbonyl group is oriented towards HB with hTyr124 (dHB = 2.374–2.894 Å, Figure S22c), thus anticipating the high toxicity of this pesticide to humans. The lowest active amide-based pesticide is tebufenozide (Table1). Almost symmetrical as a compound, this pesticide can be divided in two scaffolds by which it establishes the interactions within the active site of either mAChE or hAChE: the 4-ethylbenzamide and the N-tert-butyl-3,5-dimethylbenzamide (Figure S3c and Figure S5c, respectively). The RMDS value between the mouse and human docked conformations amounts 0.472 Å, implying the high similarity between the obtained conformations. Thus, the ethylbenzene scaffold of 4-ethylbenzamide was oriented parallel to benzene core of m(h)Tyr337, establishing hydrophobic interactions. The carbonyl group that completes the 4-ethylbenzamide was electrostatically attracted by three active site residues: m(h)Tyr124, m(h)Tyr337 and m(h)Tyr341. The hydrophobic part of m(h)Tyr124 additionally stabilized the tert-butyl group, incorporated in the second part of pesticide. The carbonyl group belonging to the tert-butyl-3,5-dimethylbenzamide moiety was geared towards the amide group of m(h)Gln71 and the hydroxyl group of m(h)Tyr124, for the purpose of forming the electrostatic interactions. The remaining part of the distinct subsection, in the form of 3,5-dimethylbenzene, is stabilized with the hydrophobic parts of m(h)Trp86 and m(h)Phe295. Similarly to other amide-based pesticides, this pesticide exerts the toxicity after creating the strong hydrogen bond in-between the tert-butyl-3,5-dimethylbenzamide moiety and either mTyr124 or hTyr124 (95% of simulation time, dHB = 1.273–1.588 Å, Figure S23c; 94% of simulation time, dHB = 1.268–1.575 Å, Figure S24c). Beside those beneficial interferences, the pesticide owns its stability and consequent toxicity to numerous hydrophobic interactions (Figure S23c and Figure S24c, respectively).

2.5.5. The Cross-Docking and Molecular Dynamics Studies of Pesticides (6-Chloropyridin-3- Yl)Methanamine and 1-(4-Chlorophenyl)-3-methylurea Groups The pesticides comprising the two remaining groups exerted the lowest acute toxicities to Mus musculus (Table1). The results of SB and MD studies are herein shown for imidacloprid (Figures4f and 5f, Figure S25 and Figure S26, respectively), while the corresponding exemplifications considering the molecular modelling studies for lower toxic acetamiprid, diuron, monuron, and linuron are available as Supplementary Material (Figures S3–S6 and Figures S27–S34, respectively). Regarding the best docking poses of imidacloprid within either mAChE or hAChE, these indicated that the 2-chloro-5-methylpyridine moiety was sterically stabilized by m(h)Trp86 and m(h)Tyr337 (Figures4f and5f, respectively). The difference in the alignment occurred with the N-(imidazolidine-2-ylidene)nitramide scaffold, whose nitro group was oriented towards mSer203, while the same function in human enzyme was in the proximity of hTyr124. Even though the imidacloprid-mAChE complex was more stable in comparison to the human one (Figure S25a), interactions generated within the complex were inconsistent to those that imidacloprid established with hAChE. Thus, while interacting with mAChE (Figure S25c), the nitro group was involved in the hydrogen bonding with mGly122 (64% of MD time, dHB = 2.483–2.788 Å) and mAla204 (59% of MD time, dHB = 2.771–3.132 Å). The corresponding functional group in hAChE (Figure S26c) was a HB acceptor for hTyr124 (82% of MD time, dHB = 1.664–1.738 Å) and hTyr337 (68% of MD time, dHB = 1.825–1.931 Å), and further confirmed those residues as essential for pesticides acute toxicity in humans. Moreover, all the described docking/MD interactions were confirmed by FEDA (Table S11). Molecules 2018, 23, 2192 20 of 37

The important interactions anticipated by the molecular docking and molecular dynamics (Figure6), provided the basis for the understanding of the general mechanism of acute toxicity on the reversible and reversible-like inhibitors level. Even though the covalent AChE inhibitors are highly efficient as pesticides, the future pesticides production must be based on the reversible-like interactions, avoiding the pesticide-AChE complex regeneration or ageing [73]. The obtained reversible-like docking and MD poses for covalent AChE inhibitors clearly confirmed the potency of selected computational tools (Vina/Desmond programmes pair) to predict the covalent binding mode of any compound in future considered as covalent AChE inhibitor (i.e., the covalent pesticide). Therefore, there was no point to conduct the covalent docking that would be reduced just to a conformational search of the bonded molecules. Hereby applied docking/MD application was also aimed to assess the docking/MD software real utility to investigate the covalent AChE inhibitors. It must be emphasized that any inhibitor, even covalent, must undergo equilibrium between the free and the bonded stage. Therefore, the reversible-like (pre-covalent) pose is of extreme utility to predict the ligand conformation that will proceed to make a covalent bond. This information could be used in future works to design new reversible inhibitors (pesticide). Considering the docking poses of acetamiprid (Figure S3d and Figure S4d, respectively), pesticide’s 2-chloro-5-methylpyridine moieties were aligned to each other in both enzymes and located in-between the m(h)Trp86 and m(h)Tyr337. The toxicity of particular pesticide may be additionally seen through the interactions of (E)-N-ethyl-N0-ethynyl-N-methylacetimidamide function, linked directly to the 2-chloropyridine ring and located in the spatial pocket made of m(h)Trp86, m(h)Gly121, m(h)Tyr133, m(h)Ser203, and m(h)His 447. However, according to the molecular dynamics results (Figure S27c and Figure S28c, respectively), this part of the pesticide has not achieved significant interactions with the specified site of amino acids, and the low toxicity of acetamiprid may be attributed only to the hydrophobic interactions established between the 2-chloro-5-methylpyridine and m(h)Trp86 and m(h)Tyr337. Concerning the remaining compounds, diuron, linuron, and monuron, the basic scaffold they share is the 1-(4-chlorophenyl)-3-methylurea. In the structure of diuron, the terminal amine is dimethyl substituted while the aromatic moiety bears additional m-Cl substituent. Matching the conformations of diuron generated in Mus musculus and Homo sapiens AChE (Figure S4a and Figure S6a, respectively), conclusion can be made that the structures were almost perpendicular to each other, by means of aromatic rings positioning: the aromatic scaffold in mouse enzyme active site was perpendicular to mTrp86 and mTyr337, while in the human environment this scaffold adopted parallel orientation related to hTrp86 and hTyr337 (analogously to previous compounds). Considering the mAChE, the only reasonable explanation for such alignment of diuron is the interaction of mThr83 methyl group with the pesticide aromatic scaffold; the mThr83 side chain was positioned inside the enzyme active site and not out of it, like in humans (Figure S4a). Because of the different alignment, the carbonyl group of diuron0s 1,1-dimethylurea scaffold was oriented towards the mTyr124, mSer203, mTyr337, and mHis447 (Figure S4a). In the human environment (Figure S6a), the exact carbonyl group was directed towards the hTrp86 and hTyr133. The MD simulation of mouse complex confirmed the weak hydrogen bonding between the urea carbonyl group and mTyr124 (31% of simulation time, dHB = 2.872–3.132 Å, Figure S29c), while the corresponding interaction could not be established in human surroundings (Figure S30c). The low intensity of precise hydrogen bond may be the reason of low toxicity of diuron, latter on concluded for linuron, and monuron, too. Speaking of the remaining derivatives, the aromatic scaffolds of monuron (Figure S4b and Figure S6b, respectively), and linuron (Figure S4c and Figure S6c, respectively) were in a sandwich between the m(h)Trp86 and m(h)Tyr337, in either mouse or human enzyme active site. The monuron carbonyl group was oriented towards the m(h)Tyr133 and m(h)Ser203, whereas the particular group in linuron is headed to m(h)Tyr 124, m(h)Tyr133 and m(h)Ser203. The nature of monuron and linuron carbonyl groups interactions with specified amino acid had been revealed after the MD studies. Thus, for either mouse or human AChE-based bioactive conformations, the carbonyl group of monuron Molecules 2018, 23, 2192 21 of 37 interfered with m(h)Tyr124 in a manner of moderate strength hydrogen bonding (within the mouse enzyme active site during the 62% of simulation time, dHB = 2.548–3.012 Å, Figure S31c; within the human enzyme active site during the 56% of simulation time via the ordered water molecule, dHB = 2.936–3.326 Å, Figure S32c). Similar interactions were observed for linuron as well (within the mouse enzyme active site during the 56% of simulation time via the ordered water molecule, dHB = 2.985–3.455 Å, Figure S33c; within the human enzyme active site during the 90% of simulation time, dHB = 2.847–3.278 Å, Figure S34c).

2.5.6. The Cross-Docking of Externally Evaluated Pesticides The structure-based studies by means of reversible and reversible-like bioactive conformations generation, recommended Vina as a tool for pesticides cheminformatics treating. Therefore, Vina was used to predict the global minimum conformation of test set pesticides (Table2) as well. The results of molecular docking are presented as a Supplementary Materials (Figures S35–S42). The generated conformations were used further on for the external validation of the training set results.

2.6. The Pesticides Acute Toxicity Anticipation through the Bioactive Conformations Upon conducting the reversible and reversible-like molecular docking and molecular dynamics studies, for either training or test set pesticides, the acute toxicity was considered with regard to the established bioactive conformations. Therefore, similarly as above reported for global minima energies, monoparametric QSAR model was derived to initially describe the acute toxicity against Mus musculus by enumerating the acute toxicities through the free energies of formation of reversible and reversible-like binding for all the training set pesticides (model 5, Equation (6), Table S12):

2 pLD50 = −0.7885∆Gbinding − 2.44 (r = 0.95), (6)

A satisfactory model was obtained by means of the whole training set and was used to recalculate the pLD50 values for acute toxicity against Mus musculus, for both the training and test sets (Figure7a,b, Tables S12 and S13). Afterwards, the model was used to predict the pLD50 values for acute toxicity against humans on the basis of ∆Gbinding values for Homo sapiens AChE (Figure7c,d, Tables S14 and S15). Thus, the QSAR model 5 described the acute toxicities against Mus musculus, by means of the free energies of binding of reversible and reversible-like bioactive conformations for either non-covalent or covalent pesticides, respectively. The model is also proven to be a tool for the anticipation of acute toxicities against humans. In the end, the conduced structure-based studies unequivocally supported pLD50/∆Gbinding interrelation obtained by QSAR model 5. In that sense, the SB approach, conducted through Vina as the cheminformatics engine, was proven to be the correct one for the anticipation of acute toxicities of targeted pesticides. Consequently, the Vina-based ∆Gbinding values can be considered in future design as valuable indicators to anticipate the pesticides LD50 values against any model organism. Molecules 2018, 23, x 22 of 37

2.6. The Pesticides Acute Toxicity Anticipation through the Bioactive Conformations Upon conducting the reversible and reversible-like molecular docking and molecular dynamics studies, for either training or test set pesticides, the acute toxicity was considered with regard to the established bioactive conformations. Therefore, similarly as above reported for global minima energies, monoparametric QSAR model was derived to initially describe the acute toxicity against Mus musculus by enumerating the acute toxicities through the free energies of formation of reversible and reversible-like binding for all the training set pesticides (model 5, Equation (6), Table S12): = −0.7885binding − 2.44 = 0.95, (6) A satisfactory model was obtained by means of the whole training set and was used to recalculate the pLD50 values for acute toxicity against Mus musculus, for both the training and test sets (Figure 7a,b, Tables S12 and S13). Afterwards, the model was used to predict the pLD50 values for acuteMolecules toxicity2018, 23 ,against 2192 humans on the basis of ∆Gbinding values for Homo sapiens AChE (Figure22 7c,d, of 37 Tables S14 and S15).

Figure 7. The plot of experimental vs. fitted pLD50 values calculated with QSAR model 5 for training Figure 7. The plot of experimental vs. fitted pLD50 values calculated with QSAR model 5 for training set pesticides (a); test set pesticides (b) against Mus musculus. The plot of calculated vs. fitted pLD50 set pesticides (a); test set pesticides (b) against Mus musculus. The plot of calculated vs. fitted pLD50 values calculated with QSAR model 5 for training set pesticides (c); test set pesticides (d) against Homo values calculated with QSAR model 5 for training set pesticides (c); test set pesticides (d) against Homo sapiens. sapiens. Thus, the QSAR model 5 described the acute toxicities against Mus musculus, by means of the 2.7. The Quantum Mechanical Studies of Acetylcholinesterase Inhibition by 2-Chloro-1,3,5-triazine-based free energies of binding of reversible and reversible-like bioactive conformations for either non- Pesticides covalent or covalent pesticides, respectively. The model is also proven to be a tool for the anticipation of acuteThe toxicities performed against molecular humans. docking In the end, and the molecular conduced structure-based dynamics studies studies agreed unequivocally with the supportedpreviously pLD reported50/∆Gbinding mode interrelation of action ofobtained amide-based, by QSAR 6-chloropyridine-3-yl)methanamine-based, model 5. In that sense, the SB approach, conductedand 1-(4-chlorophenyl)-3-methylurea-based through Vina as the cheminformatics pesticides engine, [was73]. proven The quantumto be the correct mechanical one for (QM) the anticipationcalculations of were acute only toxicities performed of target onedh AChE,pesticides. with Consequently, the aim to the reveal Vina-based the pharmacology ∆Gbinding values of can2-chloro-1,3,5-triazine-based be considered in future design pesticides as valuab and thele indicators origin for to theanticipate acute the toxicity, pesticides given LD that50 values their againstpharmacology any model is the organism. least understood. As molecular docking and molecular dynamics studies indicated the formation of hydrogen bonds network between the atrazine, propazine, and simazine and hAChE, the HB-bearing pesticides-hAChE MD poses were extracted from pesticides-hAChE complexes and subjected to quantum mechanical (QM) DFT mechanistic studies. Thus, the DFT-based calculations were performed on two different levels. The first level included the extraction of MD geometries where favourable hydrogen bonds between the 2-chloro-1,3,5-triazine-based pesticides and hThr83, hTyr341, hTyr124, and hHis447, respectively, were found. Subsequently, the extracted pesticide-hThr83, pesticide-hTyr124, pesticide-hTyr341, and pesticide-hHis447 HB forming geometries were QM optimized in order to locate the transition states (TSs) and/or the intermediary states (ISs) by which the protons transfers occur in the particular segment of biochemical reaction. The second level of calculation attempted to find the identical TSs and/or ISs upon the manual adjustment of starting pesticide-hThr83, pesticide-hTyr124, pesticide-hTyr341, and pesticide-hHis447 geometries, by means of the TS-generating hydrogen atom position between the pesticide and the regarded AChE residue, in a kind of validation process. Each of the reaction pathways assumed the contemplation by means of Intrinsic Reaction Coordinate (IRC) Molecules 2018, 23, 2192 23 of 37 analysis. Remarkably, the independent calculations gave similar/identical results, confirming that each of the obtained TSs and/or ISs is not formed by chance. Thus, the optimization of atrazine-hThr83, atrazine-hTyr124, atrazine-hTyr341, and atrazine-hHis447 HB geometries confirmed that the proton transfer, within each of the geometries, occurs via the adequate transition states. Hence, the inhibition of hAChE starts with the nucleophilic attack of atrazine’s m-N0 atom hydrogen towards hThr83 (Figure8a). The distance between the hThr83 hydroxyl group oxygen atom as a HB acceptor and m-N0 atom as a HB donor amounts 3.758 Å, characterizing particular HB as weak, almost electrostatic by character. This is, certainly, the expected increase in atrazine-hThr83 HB distance, arisen following the QM optimization, in comparison to the one recorded during the MD simulations (dHB = 2.253−2.976 Å). Nevertheless, even the weak HB is enough to increase the acute toxicity of atrazine to humans, in comparison to the propazine and simazine, inasmuch as the latter pesticides are, according to the QM studies, unable to donate proton for the formation of described TS1. Instead, the propazine-hThr83 and simazine-hThr83 interactions (Figure S43a and Figure S44a, respectively) were characterized by the IS1; the optimized QM distance between the hThr83 hydroxyl group oxygen atom and propazine and simazine m-N0 atom was 4.259 Å and 4.281 Å, respectively, suggesting the electrostatic nature of the established bond instead of the HB one. Back to the atrazine, upon the formation of atrazine-hThr83 TS1 (Figure8a and Scheme1), the deprotonation of hThr83 side chain hydroxyl group occurs, yielding the negatively charged oxygen atom, whereas at the same time m-N0 atom becomes positively charged. Identical TS1 conformation and reaction pathway was obtained upon the manual setup and the optimization of the transition state geometry. The calculated activation energy barrier for the generated TS1 is 11.2 kcal/mol and this initial reaction is the rate-limiting step for the hAChE inhibition by atrazine (Figures8a and9). The Free energy profile of all of the described reaction pathways was presented similarly to the study describing the catalytic reaction mechanism of AChE on the ACh level [82]. The manual setup of TS1 coordinates and its optimization resulted in the fact that the 47% of IRC described the proton transfer from TS1 to hThr83, whereas the 53% or IRC quantified the proton transfer from TS1 to atrazine m-N0 atom. This result further supported the proposed nucleophilic attack; the proton transfer is concerted, and the characterized transition state is meaningful. The precise atrazine-hThr83 TS1/hydrogen bond is formed and is stable at all transition and intermediate states during the inhibition process. Molecules 2018, 23, 2192 24 of 37 Molecules 2018, 23, x 24 of 37

Figure 8. The quantum chemical mechanism of Homo sapiens AChE inhibition by atrazine. The Figure 8. The quantum chemical mechanism of Homo sapiens AChE inhibition by atrazine. The extracted extracted geometry of TS1 (a); TS2 (b); TS3 (c); TS4 (d). geometry of TS1 (a); TS2 (b); TS3 (c); TS4 (d). 0 The atrazine-based hAChE inhibition further further flows flows towards the deprotonation of of m--N′ atom (Figure8 8bb andand SchemeScheme1 1)) where where hTyr341 phenoxy anion serves as a HB-acceptor. The deprotonation concerted via via the the TS2, TS2, in in which which the the distance distance betw betweeneen the theelectronegative electronegative atoms atoms amounts amounts 3.211 3.211 Å. The Å. similarThe similar transition transition states states (this time (this the time TS1s) the were TS1s) also were observed also observed for propazine for propazine and simazine and simazine (Figure S43b(Figure and S43b Figure and FigureS44b, S44b,respectively), respectively), and andfor peculiar for peculiar pesticides pesticides this this was was the the rate-limited rate-limited reaction reaction (Figure S45a,b). The calculated activation activation ener energygy barriers for the generation of propazine-hThr83 and simazine-hThr83 TS1 complexes were 8.5 and 8.9 kcal/mol, respectively respectively (Figure (Figure S45a S45a and and Figure Figure S45b, S45b, respectively). ToTo adopt adopt the the atrazine- atrazine-hTyr341hTyr341 TS2 TS2 geometry geometry (Figure (Figure8b and 8b Scheme and Scheme1), atrazine 1), atrazine is slightly is slightlyin-plane in-plane rotated towardsrotated htowardsTyr341, whereashTyr341, propazine whereas propazine and simazine and suffered simazine more suffered severe more longitudinal severe longitudinalmovement (Figure movement S43b and (Figure Figure S43b S44b, and respectively). Figure S44b, Considering respectively). that theConsidering energy difference that the between energy differencethe atrazine- betweenhTyr341 the reactant atrazine- statehTyr341 and TS2 reactant is only state 1.6 kcal/mol and TS2 is (Figure only 1.69), kcal/mol an extra stabilization(Figure 9), an comes extra stabilizationwith the formation comes ofwith atrazine- the formationhTyr341 of TS2. atrazine- The lengthhTyr341 of atrazine- TS2. Theh Tyr124length of HB atrazine- characterizeshTyr124 it asHB a characterizesmoderate one. it The as seconda moderate level ofone. QM The optimization second level also of confirmed QM optimization the meaningfulness also confirmed of TS2. the As meaningfulnessprevious, the meaningfulness of TS2. As previous, of TS2 isthe confirmed meaningfulness since the of 56% TS2 of is IRCconfirmed described since the the proton 56% glidingof IRC 0 describedfrom TS3 tothehTyr341, proton whereas gliding thefrom 44% TS3 or IRCto hTyr341, illustrated whereas the proton the 44% transfer or IRC form illustrated TS2 for atrazine the protonm-N transferatom. Similar form trendsTS2 for were atrazine noticed m-N for′ atom. propazine- SimilarhTyr341 trends and were simazine- noticedhTyr341 for propazine- TS1 (FigurehTyr341 S43b and simazine-Figure S44b,hTyr341 respectively). TS1 (Figure Nevertheless, S43b and Figure during S44b, the rotationrespectively). of atrazine Nevertheless, (the movement during of the propazine rotation ofor simazine),atrazine (the the movement TS1 (IS1) is of sustained propazine (Figure or simazine), S43b and the Figure TS1 S44b,(IS1) respectively).is sustained (Figure S43b and Figure S44b, respectively).

Molecules 2018, 23, 2192 25 of 37

Molecules 2018, 23, x 25 of 37

Scheme 1. The mechanism of Homo sapiens AChE inhibition by atrazine, propazine, and simazine, Schemeverified 1. The by QM mechanism studies. of Homo sapiens AChE inhibition by atrazine, propazine, and simazine, verified by QM studies. In theIn third the third step step of theof the reaction reaction pathway, pathway, the the electrophilicelectrophilic nature nature of ofthe the re-established re-established secondary secondary m-N′ amine is expressed by the release of proton towards the hTyr124 hydroxyl group anion. The m-N0 amine is expressed by the release of proton towards the hTyr124 hydroxyl group anion. The proton proton transfer takes place via the TS3, in which the distance between the electronegative atoms transfer takes place via the TS3, in which the distance between the electronegative atoms amounts amounts 3.522 Å (Figure 8c and Scheme 1). For the purpose of TS3 generation, atrazine is forced to 3.522move Å (Figure longitudinally8c and Scheme in order1). to For form the the purpose tetrahedral of TS3 structure generation, with the atrazine HB-involved is forced residues. to move longitudinallyTherefore, inthis order step tois formslightly the energetically tetrahedral structuremore expensive, with the with HB-involved the free energy residues. difference Therefore, of 4.8 this step iskcal/mol slightly (Figure energetically 9). The characteristic more expensive, of the with tetrah theedral free TS3 energy structure difference is that ofit holds 4.8 kcal/mol the negatively (Figure 9). The characteristiccharged secondary of the m tetrahedral-N′ nitrogen TS3 atom. structure The distinct is that state it holds is supported the negatively by the aromatic charged nature secondary of them -N0 nitrogen atom. The distinct state is supported by the aromatic nature of the atrazine’s 1,3,5-triazine ring, which can accept the m-N0 amine negative charge by the intramolecular resonance stabilization. As mentioned above, the meaningfulness of the TS3 is confirmed since 57% of IRC described the proton Molecules 2018, 23, x 26 of 37 atrazine’sMolecules 2018 1,3,5-triazine, 23, 2192 ring, which can accept the m-N′ amine negative charge by the intramolecular26 of 37 resonance stabilization. As mentioned above, the meaningfulness of the TS3 is confirmed since 57% of IRC described the proton gliding from TS3 to hTyr124, whereas the 43% or the IRC illustrated the protongliding transfer from TS3 from to hTS3Tyr124, to atrazine’s whereas m the-N′ 43% atom. or On the the IRC other illustrated hand, the propazine- proton transferhTyr124 from and TS3 the to 0 simazine-atrazine’shmTyr124-N atom. interactions On the other are hand, characterized the propazine- by hTyr124the IS2 and (Figure the simazine- S43c handTyr124 Figure interactions S44c, respectively),are characterized in which by the the IS2 QM (Figure optimized S43c and distances Figure S44c,between respectively), the hTyr124 in whichand the the propazine QM optimized and simazinedistances were between 4.882 the andhTyr124 3.862 Å, and respectively. the propazine and simazine were 4.882 and 3.862 Å, respectively. Moreover,Moreover, the the formation formation of ofthe the atrazine- atrazine-hAChEhAChE tetrahedral tetrahedral TS3 TS3 struct structureure appears appears to be to the be pre- the conditionpre-condition for hHis447 for hHis447 to be tojointly be jointly arranged arranged with withthe atrazine the atrazine (Figure (Figure 8d and8d andScheme Scheme 1). In1). this In thislast steplast of step the of reaction the reaction pathway, pathway, the atrazine’s the atrazine’s m-N″ aminem-N” suffersamine the suffers nucleophilic the nucleophilic attack from attack hHis447 from imidazolehHis447 imidazole ring, in which ring, the in whichprotonthe transfer proton is carried transfer out is carriedfrom the out pesticide from the towards pesticide the towardsamino acid the viaamino the TS4 acid (the via HB the distance TS4 (the was HB 2.699 distance Å). Consequently, was 2.699 Å). there Consequently, is a localization there isof athe localization negative charge of the aroundnegative the charge m-N″ amine around as thewell,m -whichN” amine can be as once well, again which efficiently can be delocalized once again by efficiently the atrazine delocalized′s 1,3,5- 0 triazineby the atrazinering. Thes 1,3,5-triazinesimilar pathway ring. is Theobserved similar for pathway the propazine- is observedhHis447 for and the propazine-simazine-hhTyr447His447 interaction,and simazine- withhTyr447 the transition interaction, state with labelled the transition as TS2 (the state HB labelled distances as TS2 were (the 2.583, HBdistances and 2.540 were Å, respectively).2.583, and 2.540 In comparison Å, respectively). with the In TS4 comparison (TS2) optimized with the MD TS4 snapshot, (TS2) optimized the orientation MD snapshot, of hHis447 the needsorientation to be of adjustedhHis447 needsvery toslightly, be adjusted following very slightly, which followingthere is whicha proton there transfer is a proton from transfer the atrazine/propazine/simazinefrom the atrazine/propazine/simazine m-N″ aminem- toN” theamine residue to the accompanied residue accompanied with the spontaneous with the spontaneous break of thebreak scissile of the m-N scissile″-H bondm-N” (Figure-H bond 8d, (FigureFigure S43d8d, Figure and Figure S43d S44d, and Figure respectively). S44d, respectively). As a result, a short As a andresult, low-barrier a short and hydrogen low-barrier bond hydrogen (LBHB) bond is (LBHB) formed is formedbetween between the thehHis447hHis447 and and the the atrazine’s/propazine’s/simazine’satrazine’s/propazine’s/simazine’s mm--N”N″ amineamine (Figure (Figure8d, Figure8d, S43dFigure and S43d Figure and S44d, Figure respectively), S44d, respectively),and the willing and proton the willing transfer proton is thus observed.transfer is Energetically,thus observed. this Energetically, is the most favourable this is the reaction most favourablesince the freereaction energy since differences the free energy between differences the reactant between and the transition reactant states and transition were 0.70, states 0.68, were and 0.70,0.62 0.68, kcal/mol, and 0.62 respectively. kcal/mol, respectively. Alongside with Alongside the TS1, with the the TS4 TS1, (TS2) the isTS4 by (TS2) far the is by most far importantthe most importanttransition transition state as it state interrupts as it interrupts the hHis447 the hHis447 to serve to asserve a base as a forbaseh AChEfor hAChE catalytic catalytic triad. triad. By By all allmeans, means, the the meaningfulness meaningfulness of of TS4 TS4 is is confirmed confirmed since since thethe 51%51% ofof IRC described the proton proton gliding gliding fromfrom TS3 TS3 for for hhHis447,His447, whereas whereas the the 49% 49% or or IRC IRC illustrated illustrated th thee proton proton transfer transfer form form TS4 TS4 for for atrazine atrazine 0 mm--NN′ atomatom (Figure (Figure 88dd and SchemeScheme1 1).). SimilarSimilar trendstrends werewere alsoalso noticednoticed forfor propazine-propazine-hhTyr341Tyr341 and and simazine-simazine-hhTyr341Tyr341 TS2TS2 (Figure (Figure S43d S43d and and Figure Figure S44d, S44d, respectively). respectively). Nevertheless, Nevertheless, during theduring formation the formationof the atrazine- of theh atrazine-His447 TS4hHis447 (propazine- TS4 (propazine-hHis447 andhHis447 simazine- and simazine-hTyr447 TS2),hTyr447 the TS1TS2), (IS1), the TS1 TS2 (IS1), (TS1), TS2and (TS1), TS3 (IS2) and wereTS3 (IS2) sustained. were sustained.

FigureFigure 9. 9. FreeFree energy energy profile profile for for HomoHomo sapiens sapiens AChEAChE inhibition inhibition by atrazi by atrazinene determined determined by B3LYP by B3LYP (6- 31G*)(6-31G*) QM QM simulations. simulations.

The quantum mechanical studies do not provide the basis for the hSer203 covalent modification The quantum mechanical studies do not provide the basis for the hSer203 covalent modification by atrazine’s, propazine’s or simazine’s m-N″ atom substituent, despite the fact that in metabolic by atrazine’s, propazine’s or simazine’s m-N” atom substituent, despite the fact that in metabolic pathways pesticides may release the particular functional group. The literature survey supports pathways pesticides may release the particular functional group. The literature survey supports particular findings since the metabolites from atrazine, simazine and propazines are not able to particular findings since the metabolites from atrazine, simazine and propazines are not able to

Molecules 2018, 23, 2192 27 of 37 Molecules 2018, 23, x 27 of 37 establishestablish thethe interactionsinteractions withwith acetylcholinesteraseacetylcholinesterase [[83].83]. ThisThis statementstatement waswas furtherfurther confirmedconfirmed inin thethe concentrationconcentration dependentdependent kinetickinetic studies.studies. 2.8. The Concentration-Dependent Kinetics of Human Acetylcholinesterase Inhibition by 2-Chloro-1,3,5-triazine-based2.8. The Concentration-Dependent Pesticides Kinetics of Human Acetylcholinesterase Inhibition by 2-Chloro-1,3,5-triazine-based Pesticides There are numerous evidences that organophosphates are irreversible AChE inhibitors whereas There are numerous evidences that organophosphates are irreversible AChE inhibitors whereas the carbamates acts as reversible AChE inhibitors [73]. However, studies show that atrazine decreases the carbamates acts as reversible AChE inhibitors [73]. However, studies show that atrazine decreases the AChE catalytic activity in Chironomus tentans [84] and Carassius auratus, applied synergistically the AChE catalytic activity in Chironomus tentans [84] and Carassius auratus, applied synergistically with organophosphate insecticides, [80]. Nevertheless, the data describing the atrazine’s and the with organophosphate insecticides, [80]. Nevertheless, the data describing the atrazine’s and the related compounds individually influence the hAChE catalytic activity is limited. Therefore, the related compounds individually influence the hAChE catalytic activity is limited. Therefore, the 2- 2-chloro-1,3,5-triazine-based pesticides are herein evaluated as hAChE inhibitors, in the concentrations chloro-1,3,5-triazine-based pesticides are herein evaluated as hAChE inhibitors, in the concentrations comparable to the calculated LD50 values for Homo sapiens (Figure 10). comparable to the calculated LD50 values for Homo sapiens (Figure 10). The results show that all of the examined 2-chloro-1,3,5-triazine-based pesticides inhibit Homo The results show that all of the examined 2-chloro-1,3,5-triazine-based pesticides inhibit Homo sapiens AChE activity in a concentration-dependent manner (Figure 10). The inhibition curves analysis sapiens AChE activity in a concentration-dependent manner (Figure 10). The inhibition curves implies that the aging reaction, in which the hAChE releases itself from covalently bound pesticide, analysis implies that the aging reaction, in which the hAChE releases itself from covalently bound occurs in the presence of atrazine, propazine, and simazine at a high rate, and that the regarded pesticide, occurs in the presence of atrazine, propazine, and simazine at a high rate, and that the pesticides most likely do no inhibit the hAChE covalently [85]. Therefore, the protocol by which the regarded pesticides most likely do no inhibit the hAChE covalently [85]. Therefore, the protocol by Homo sapiens LD50 values were calculated, as well as all the performed molecular modelling studies of which the Homo sapiens LD50 values were calculated, as well as all the performed molecular modelling 2-chloro-1,3,5-triazine-based pesticides, were experimentally validated. studies of 2-chloro-1,3,5-triazine-based pesticides, were experimentally validated.

FigureFigure 10.10. Human AChE inhibition byby 2-chloro-1,3,5-triazine-based2-chloro-1,3,5-triazine-based pesticides.pesticides.

3. Materials and Methods 3. Materials and Methods

3.1.3.1. Materials AcetylcholineAcetylcholine chloridechloride (CAS:(CAS: 60-31-1),60-31-1), acetylcholinesteraseacetylcholinesterase from human erythrocytes (CAS: 9000-81-1),9000-81-1), andand DTNBDTNB (5,5(5,50′-dithiobis(2-nitrobenzoic-dithiobis(2-nitrobenzoic acid)) (CAS: 69-78-3), atrazine (CAS: 1912-24-9), propazinepropazine (CAS:(CAS: 139-40-2), 139-40-2), simazine simazine (CAS: (CAS: 122-34-9), 122-34-9), and PBS and (MDL: PBS MFCD00131855) (MDL: MFCD00131855) were purchased were frompurchased Sigma from Aldrich Sigma (St. Aldric Louis,h Mo., (St. Louis, USA). Mo., USA).

3.2.3.2. TheThe GenerationGeneration ofof PesticidesPesticides StructuresStructures TheThe crystalcrystal structuresstructures of of simazine simazine [9 ],[9], monocrotophos monocrotophos [10 ],[10], dimethoate dimethoate [11], [11], and and acetamiprid acetamiprid [12] were[12] were retrieved retrieved from from The The Cambridge Cambridge Crystallographic Crystallographic Data Data Centre Centre (CCDC) (CCDC) (CSD (CSD IDs: IDs: KUYXIM, ULEJIF,ULEJIF, IPCPYB,IPCPYB, HANBAA).HANBAA). TheThe remainingremaining pesticidespesticides structuresstructures werewere generatedgenerated byby drawingdrawing usingusing thethe MacroModelMacroModel versionversion 88 softwaresoftware (Schrodinger,(Schrodinger, Cambridge, Cambridge, MA, MA, USA) USA) [ 75[75].].

3.3.3.3. The Conformational AnalysisAnalysis TheThe conformationalconformational analysesanalyses werewere performedperformed byby usingusing thethe MacroModelMacroModel versionversion 88 softwaresoftware [[75]75] viavia thethe MonteMonte Carlo/multipleCarlo/multiple minimumminimum (MC/MM)(MC/MM) a approachpproach [76]. [76]. The solute waswas describeddescribed usingusing five different potentials (MM3, AMBER94, MMFF, MMFFs, OPLSAA) [77,85–88]. The effect of solvent was incorporated into the MC/MM calculations using the generalized Born/surface area (GB/SA)

Molecules 2018, 23, 2192 28 of 37

five different potentials (MM3, AMBER94, MMFF, MMFFs, OPLSAA) [77,85–88]. The effect of solvent was incorporated into the MC/MM calculations using the generalized Born/surface area (GB/SA) continuum solvent model [89]. Cut-offs of 12.0 Å and 7.0 Å were employed for electrostatic and van der Waals non-bonded interactions, respectively [90]. The MC simulation involved 104 steps at 310.15 K, applied to all the rotatable bonds, with random torsional rotations of up to ±180◦. This was combined with 103 steps of energy minimization. All the conformational calculations were performed using the MacroModel 8.0 and BatchMin suite of programs [91].

3.4. The Mus musculus and Homo sapiens AChE Sequences Alignment The alignment of mAChE and hAChE sequences retrieved from the UniProt database (entries P221836 and P22303, respectively, Figure S1) was performed by means of ClustalW module [92] using the standard setup.

3.5. The Mus musculus and Homo sapiens AChE Complexes Preparation To the best of our knowledge, there are no crystal structures containing co-crystallized structures of pesticides listed in Table1, in complex with either Mus musculus or Homo sapiens AChE. Therefore, for the purpose of targeted pesticides binding mode definition into the active sites of Mus musculus and Homo sapiens AChEs, respectively, 59 acetylcholine esterase-inhibitor complexes (51 containing mice inhibitors and 8 saturated with human inhibitors) were collected from Protein Data Bank and submitted to structure-based alignment assessment protocols (see Tables S9 and S10). Initially, complexes were prepared for molecular modelling after being loaded into the UCSF Chimera v1.10.1 software [93] for Linux 64 bit architecture and visually inspected. The downloaded complexes were homodimers. For the experimental purposes preparation, complexes were initially arbitrarily superimposed using human crystal under the code name 4EY5 [94] as a template (the best-resolved complex with the resolution of 2.3 Å) using the Matchmaker module and then separated in chains using the command line implementation of the Chimera split command. Upon the thorough examination, the B chain of each complex was retained for further manipulation. Compared to chains A containing complexes, those with chains B were more complete by means of inhibitors presence. Inhibitors were extracted from each chain B complexes after which either proteins or ligands were improved by assigning the hydrogen atoms at pH of 7.4 and Amber parameters [95] using Antechamber semi-empirical QM method. Complexes were the regenerated and energy minimized as follows: through the leap module they were solvated with water molecules (TIP3P model, SOLVATEOCT Leap command) in a box extending 10 Å in all directions, neutralized with either Na+ or Cl− ions, and refined by a single point minimization using the Sander module with maximum 1000 steps of the steepest-descent energy minimization followed by maximum 4000 steps of conjugate-gradient energy minimization, with a non-bonded cutoff of 5 Å. Minimized complexes were re-aligned (4EY5 as a template), after which all of the ligands were extracted to compose the SB aligned training set ready to be utilized for the subsequent structure-based alignment assessment.

3.6. The Structure-Based Alignment Assessment The SB alignment assessment for either Mus musculus or Homo sapiens AChE inhibitors was performed by means of the four step standard protocol [78,96], by means of either AutoDock [79], AutoDock Vina [80], and DOCK [81] docking algorithms/scoring functions. Experimental conformation re-docking (ECRD): a procedure in which the experimental conformations (EC) are flexibly docked back into the corresponding protein, evaluating the program for its ability to reproduce the observed bound conformations. Randomized conformation re-docking (RCRD): similar assessment to ECRD with a difference that the active site of the protein is virtually occupied by conformations initially obtained from computational random optimization of corresponding co-crystallized molecules coordinates and Molecules 2018, 23, 2192 29 of 37 positions. Here the programs are evaluated for their ability to find the experimental pose starting by a randomized minimized conformation. Experimental conformation cross-docking (ECCD): comparable to ECRD, but the molecular docking was performed on all the training set proteins except for the corresponding natives. Here the programs are evaluated to find the binding mode of ligand in a similar but different from the native complex active site at the same time mimicking discrete protein flexibility. Randomized conformation cross-docking (RCCD): same as the ECCD but using RCs as starting docking conformations. This is the highest level of difficulty since the program is demanded to dock any given molecule into an ensemble of protein conformations not containing the native one. The outcome is considered as the most important ability of docking program as the most accurate scoring function is applied to any test set molecules of which the experimental binding mode is unknown. The related docking accuracy (DA) [97] is a direct function of the program’s probability to find a correct binding mode for an active molecule.

3.6.1. The AutoDock Settings The prepared protein structures were imported into AutoDockTools graphical user interface. Nonpolar hydrogen atoms were removed while Gasteiger charges and solvent parameters were added. All of the tested compounds were used as ligands for docking. The rigid root and rotatable bonds were defined using AutoDockTools. The docking was performed with AutoDock 4.2. The xyz coordinates (in Ångströms) of the cuboid grid box used for the computation were: for mouse inhibitors Xmin/Xmax = 1.420/31.800, Ymin/Ymax = 108.000/152.500, Zmin/Zmax = 8.200/43.200; for human inhibitors Xmin/Xmax = 3.200/29.500, Ymin/Ymax = 109.200/153.800, Zmin/Zmax = 8.800/42.100, with a purpose to embrace all the minimized inhibitors spanning 10 Å in all three dimensions. The Lamarckian Genetic Algorithm was used to generate orientations or conformations of ligands within the binding site. The procedure of the global optimization started with a sample of 200 randomly positioned individuals, a maximum of 1.0 × 106 energy evaluations and a maximum of 27,000 generations. A total of 100 runs were performed with RMS Cluster Tolerance of 0.5 Å.

3.6.2. The Autodock Vina Settings The docking simulations were carried out in the same grid space with an energy range of 10 kcal/mol and exhaustiveness of 100 with RMS Cluster Tolerance of 0.5 Å. The output comprised 20 different conformations for every receptor considered.

3.6.3. The DOCK6 Settings During the docking simulations with DOCK program, the proteins were rigid while the inhibitors flexible and subjected to an energy minimization process. The solvent accessible surface of each enzyme without hydrogen atoms was calculated using the DMS program [98], using a probe radius of 1.4 Å. The orientation of ligands was described using the SPHGEN module and by sphere selector. A box around the binding site is constructed with the accessory program SHOWBOX. The steric and electrostatic environment of the pocket was evaluated with the program Grid using a 0.3 Å of grid spacing. Selected spheres were within 8 Å from ligand heavy atoms of the crystal structure and for computing the energy grids an 8 Å box margin and 6–9 VDW exponents were used.

3.7. The Ligand-Based and Structure-Based Alignment Accuracy The alignment fitness for LB or SB approach was quantified by evaluating the RMSD values. The alignment accuracy was initially quantified after reproducing the known crystal structures of simazine [9], monocrotophos [10], dimethoate [11], and acetamiprid [12], with the available force fields, to obtain the conformational alignment accuracy (CAA). Following, the superposition of pesticides structures obtained after the conformational analysis was performed with the purpose to compare the force fields performances, i.e., the force filed-dependent alignment accuracy, FFDAA. Finally, Molecules 2018, 23, 2192 30 of 37 superimposition of docking poses provided the docking accuracy, DA. CAA, FFDAA or DA can be used to test how the conformational alignment can predict the ligand pose as close as possible to the experimentally observed one [97]. The alignment accuracy values can be calculated by the following Equation (7): xA = frmsd, ≤ a + 0.5( frmsd ≤ b − frmsd ≤ a) (7) In particular: xA = CAA or FFDAA, in the case of LB alignment accuracy, whereas the xA = DA, in the case of SB accuracy. The frmsd ≤ a and frmsd ≤ b are fractions of aligned ligands showing an RMSD value less than or equal to 2 Å (a coefficient) and 3 Å (b coefficient), respectively. The widely accepted standard is that the correctly aligned conformations are those with RMSD less than 2 Å on all the heavy atoms between the generated and crystallographic structure, when considering the CAA and FFDAA, while the correctly docked structures are those with RMSD less than 2 Å on all the heavy atoms between docked and co-crystallized ligand, when considering the DA. Structures with the RMSD values larger than 4 Å were considered incorrectly aligned/docked. Structures with RMSD between 2 and 3 were considered partially aligned/docked, whereas those with RMSD higher than 3 and were misaligned/mis-docked and thus not considered in the FFDAA/DA calculation.

3.8. The Structure-Based Alignment of Pesticides The molecular docking of pesticides within either mAChE and hAChE was conducted by the AutoDock Vina [80]. The molecular docking studies were carried out in the cuboid grid box with the following xyz coordinates (in Ångströms): for mAChE Xmin/Xmax = 1.420/31.800, Ymin/Ymax = 108.000/152.500, Zmin/Zmax = 8.200/43.200; hAChE Xmin/Xmax = 3.200/29.500, Ymin/Ymax = 109.200/153.800, Zmin/Zmax = 8.800/42.100, with the energy range of 10 kcal/mol and exhaustiveness of 100 with RMS Cluster Tolerance of 0.5 Å. The output comprised 20 different conformations for every receptor considered.

3.9. The Pesticide-AChE Complexes Molecular Dynamics Simulations The pesticide-AChE complexes formed after molecular docking were used to perform the explicit solvent molecular dynamics (MD) simulations. The parallelized Desmond Molecular Dynamics System [99] and the associated analysis tools, available within the Schrödinger suite 2009 [75] were used for this purpose. The models were prepared using the ‘system builder’ utility. The MMFF force field parameters were assigned to all the simulation systems. Each inhibitors-enzyme complex was placed in the centre of an orthorhombic box ensuring 10 Å solvent buffers between the solute and the boundary of the simulation box in each direction. The TIP3P model was used to describe the water molecules. Moreover, Na+ and Cl− ions were added at a physiological concentration of 0.15 M. The model systems were relaxed to 0.5 Å using the single step minimization protocol and were subjected to the production phase, with the NPT ensemble and the periodic boundary conditions for 1.2 ns. The pressure control was used to maintain the pressure of the cell (1.013 bars) with the isotropic coupling method. The Nose-Hoover thermostat method was used to control the temperature at 310.15 K. The Heavy atom-hydrogen covalent bonds were constrained using the SHAKE algorithm which allowed 2 fs integration step to be used. The integration of the motion equation using the RESPA multiple time step scheme was used in the calculation. The Long-range electrostatic forces were obtained using the smooth Particle-Mesh Ewald (PME) method. In order to calculate the short-range electrostatics and the Lennard-Jones interaction, the cut-off distance was set to 9.0 Å, and the trajectories and the energies were recorded at every 4.8 ps. The simulation quality analysis tool was used to analyse the trajectories; RMSD and RMSF values, the hydrogen bond distances, the angles, and the van der Waals interactions were obtained over the simulation trajectories. Molecules 2018, 23, 2192 31 of 37

3.10. The MM-GBSA Calculations and Free Energy Decomposition The binding free energy [100] of each system was calculated using the MM-GBSA calculations according to the following Equation (8):

∆Gbind = ∆Eele + ∆EvdW + ∆Gsolv + T∆S, (8) where ∆Eele corresponds to the electrostatic energy difference between the receptor-ligand bound and the calculated unbound states using the OPLS_2005 force field, ∆EvdW corresponds to the van der Waals contribution, while ∆Gsolv is the corresponding solvation free energy contribution of the binding which was calculated using the GB/SA continuum model. The Embrace package implemented in MacroModel was used for the ∆Eele, ∆EvdW, and ∆Gsolv calculations. The entropy change ∆S was calculated using the Rigid Rotor Harmonic Oscillator (RRHO) calculations. Having used this algorithm, the change in vibrational, rotational, and translational (VRT) entropy of the ligands on binding was estimated. For the RRHO calculations, the representative complexes were pre-minimized using the Desmond with the explicit solvent retained; a 2000 steps LBFGS minimization (first 10 steps steepest descent) with the residues beyond 15 Å of ligands restrained and a convergence criterion of 0.05 kcal mol−1 Å−1 was used.

3.11. The Quantum Mechanical Mechanistic Studies The DFT-based calculations were performed on the MD-generated pesticide-hAChE complexes on three different levels. The first level included the extraction of hydrogen bond-forming geometries of MD equilibrated pesticide-hThr83, pesticide-hTyr124, pesticide-hTyr341, and pesticide-hHis447 sub-complexes; subsequently, the extracted geometries were QM optimized to locate the transition states (TSs) and/or intermediary states (ISs), by which the protons transfers occur on a particular segment of a biochemical reaction. The second level of the calculation attempted to find the identical TSs and/or ISs following the manual adjustment of the TS-generating hydrogen atom position, between the pesticide and the regarded AChE residue, within the pesticide-hThr83, pesticide-hTyr124, pesticide-hTyr341, and pesticide-hHis447 geometries. Each of the reaction pathways assumed the contemplation by means of Intrinsic Reaction Coordinate (IRC) analysis. As water molecules are not involved in HBs generation, they were all discarded from the system. The initiation or the manual setup of geometries was performed by means of GaussView6 package [101] following which the B3LYP method, as implemented in Gaussian 09 (Gaussian Inc., Wallingford, CT, USA) [102] was used to explore the geometry of the reactants, transition states, intermediary states and products. The single point calculations were carried out on all the geometries at the B3LYP/6-31G* level of theory [82]. The saddle points and transition states were quantified by means of frequency calculations.

3.12. The Assay of the AChE Activity The AChE catalytic activity was measured at 22 ◦C by the Ellman method [103]. The assay mixture contained the 0.25 mM ACh, 0.25 mM DTNB, and 50 mM sodium phosphate buffer. The remaining assay conditions have been reported previously. For the selection of a suitable concentration of AChE, at which the relationship between the initial velocity and the total enzyme concentration should be linear, 0.20–3.20 mg/mL of AChE was assayed in vitro from 2 to 20 min under the same conditions of the temperature and the pH. The rate of change of the substrate cleavage, determined by measuring the absorbance of the reaction product at a wavelength of 412 nm, was performed at different time intervals. The product was calculated for each [AChE] at 4-min incubation time intervals. To study the effect of atrazine, simazine, or propazine on AChE substrate cleavage, the enzyme was preincubated with each pesticide at different concentrations ranging 0–6 µg/mL (concentrations corresponding to the LD50 values) for 10 min prior to the addition of the substrate. Molecules 2018, 23, 2192 32 of 37

4. Conclusions The present report describes the application of the molecular modelling techniques to shed light on the pharmacology of the commonly used pesticides atrazine, simazine, propazine, carbofuran, monocrotophos, dimethoate, carbaryl, tebufenozide, imidacloprid, acetamiprid, diuron, monuron, and linuron as AChE inhibitors The pesticides’ putative pre-binding conformations in the inter-synaptic environment were predicted by means of the conformational analysis where the determined global minima values and the ability to reproduce the pesticides experimental conformations indicated MMFF as the best performing FF. Having known the pesticides pre-bound conformations, their acute toxicities were interrelated to the Eglob_min values through the QSAR studies: for the majority of pesticides, a clear inverse correlation could be observed between the Eglob_min values and the high acute toxicities. However, the chemometric analysis indicated that the Eglob_min values could not be used as proper indicators for high or low LD50 values against Mus musculus or Homo sapiens. Therefore, the pesticides acute toxicity was further on regarded trough the pesticides bound conformations, upon the molecular docking and molecular dynamics-driven interactions with either Mus musculus or Homo sapiens AChE. The conducted studies confirmed the binding modes and the pharmacology of evaluated pesticides as reversible and reversible-like (i.e., future covalent) AChE inhibitors and the determined pesticides pharmacodynamics origin of acute toxicity. The superposed chemometric investigation revealed that for all the pesticides, a clear interrelationship could be observed between the ∆Gbinding values and high acute toxicity, indicating that the ∆Gbinding values can be used as indexes for high or low LD50 values against Mus musculus. Moreover, the obtained chemometric guideline, in the form of the QSAR model pLD50 = −0.7885∆Gbinding − 2.44, is, by all means, suitable for the prognosis of LD50 values against Homo sapiens and can be further used as a universal tool for the acute toxicities administration of novel pesticides. Further studies which consider the inclusion of additional parameters and machine learning algorithm application are in due course in order to generate quantitative structure-activity relationships models able to include all considered pesticides in a comprehensive mathematical model. Nevertheless, it is interesting that the global minima or free energy of formation values may indicate the level of acute toxicity; the calculations may discard the potential new pesticides even before the actual application in agriculture. Therefore, the correlations between the pLD50 and Eglob_min or ∆Gbinding are hereby presented for the very first time as an unprecedented way to study pesticides and to predict their acute toxicity. Moreover, the subsequent structure-based quantum mechanical mechanistic studies for 2-chloro-1,3,5-triazine-based pesticides, as the least understood group by means of pharmacology, revealed pathways by which considered pesticides poison Homo sapiens AChE in a reversible fashion manner. To summarize, all the noticed interactions could further be used in the discovery of novel pesticides with the desirable lower acute toxicity against humans. It is important to emphasize that the conducted QM studies were performed to provide the structural basis for the pesticides’ human AChE toxicity, not the general toxicity. The pesticide toxicity is mainly carried out by means of mechanism; general toxicity is normally due to off target interactions or to active metabolites.

Supplementary Materials: The Supplementary Materials are available online. Author Contributions: B.B.A. and M.M. designed the study; B.B.A., A.R., J.S.M., T.M.T.-P. and R.M. performed conformational analyses. M.M., N.S., N.M., and R.R. performed statistical studies, molecular docking, molecular dynamics studies and QM DFT studies. Funding: This research was funded by the Ministry of Education and Science of Republic of Serbia (Grant Nos. III45006, 174007, and III43004) and Progetti di Ricerca di Università 2015, Sapienza Università di Roma (Grant Nos. C26A15RT82 and C26A15J3BB). Acknowledgments: Gratitude is expressed to Goran Bogdanovic, Institute of Nuclear Sciences Vinˇca,Belgrade, Republic of Serbia, for providing pesticides crystal structures. Special thanks are due to Jill Barber, Division of Pharmacy and Optometry, University of Manchester, Manchester, UK for providing computational facilities and all comments and suggestions which improved the quality of the manuscript. Molecules 2018, 23, 2192 33 of 37

Conflicts of Interest: The authors declare no conflict of interest.

References

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Sample Availability: Samples of the compounds are not available from the authors.

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