Mudasiretal
CorrespondingauthorTelFax:鮼62ઈ274ઈ545188513339 Emailaddress:mudasir@ugmacid
DESIGN OF NEW POTENT INSECTICIDES OF ORGANOPHOSPHATE DERIVATIVES
BASED ON QSAR ANALYSIS
Mudasir*, Yari Mukti Wibowo, and Harno Dwi Pranowo
Austrian-Indonesian Centre (AIC) for Computational Chemistry, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada,
Sekip Utara P.O. Box Bls. 21, Yogyakarta 55281, Indonesia
Received November 22, 2012; Accepted February 26, 2013
ABSTRACT
Design of new potent insecticide compounds of organophosphate derivatives based on QSAR (Quantitative Structure-Activity Relationship) analytical model has been conducted. Organophosphate derivative compounds and their activities were obtained from the literature. Computational modeling of the structure of organophosphate derivative compounds and calculation of their QSAR descriptors have been done by AM1 (Austin Model 1) method. The best QSAR model was selected from the QSAR models that used only electronic descriptors and from those using both electronic and molecular descriptors. The best QSAR model obtained was:
Log LD50 = 50.872 – 66.457 qC1 – 65.735 qC6 + 83.115 qO7
(n = 30, r = 0.876, adjusted r2 = 0.741, Fcal/Ftab = 9.636, PRESS = 2.414 x 10 -6
)
The best QSAR model was then used to design in silico new compounds of insecticide of organophosphate derivatives with better activity as compared to the existing synthesized organophosphate derivatives. So far, the
most potent insecticide of organophosphate compound that has been successfully synthesized had log LD50 of
-5.20, while the new designed compound based on the best QSAR model, i.e.: 4-(diethoxy phosphoryloxy) benzene
sulfonic acid, had log LD50 prediction of -7.29. Therefore, the new designed insecticide compound is suggested to be
synthesized and tested for its activity in laboratory for further verification.
Keywords:QSAR analysis; insecticides; organophosphate; semi-emphiric AM-1; molecular design
ABSTRAK
Telah dilakukan desain senyawa insektisida baru turunan organofosfat berdasarkan pada model analisis Hubungan Kuantitatif Struktur-Aktivitas (HKSA). Senyawa turunan organofosfat dan aktivitasnya diperoleh dari literatur. Pemodelan komputasi terhadap struktur senyawa turunan organofosfat dan perhitungan deskriptor HKSA-nya telah dilakukan menggunakan metode AM1 (Austin Model 1). Model HKSA terbaik dipilih dari model HKSA yang hanya menggunakan deskriptor elektronik dan dari model yang menggunakan baik deskriptor elektronik maupun molekul. Model HKSA terbaik yang diperoleh adalah:
Log LD50 = 50,872 – 66,457 qC1 – 65,735 qC6 + 83,115 qO7
(n = 30, r = 0,876, adjusted r2 = 0,741, Fcal/Ftab = 9,636, PRESS = 2,414 x 10-6)
Model HKSA terbaik tersebut kemudian digunakan untuk merancang secara in silico senyawa insektisida baru turunan organofosfat yang mempunyai aktivitas lebih baik dibandingkan dengan turunan organofosfat yang sudah
ada. Sejauh ini, insektisida organofosfat paling ampuh yang telah berhasil disintesis mempunyai log LD50 sebesar
-5,20, sedangkan senyawa baru yang telah dirancang berdasarkan model HKSA terbaik, yakni: asam 4-(diethoxy
phosphoryloxy) benzena sulfonat mempunyai log LD50 prediksi sebesar -7,29. Oleh karena itu, senyawa insektisida
baru yang telah dirancang ini disarankan untuk disintesis dan diuji aktivitasnya di laboratorium untuk verifikasi lebih lanjut.
Kata Kunci:analisis HKSA; insektisida, organofosfat; semi-empirik AM-1; perancangan molekul
INTRODUCTION
Insecticidesarechemicalorbiologicaloriginagents thatcontrolinsectsThecontrolisresultedfromkilling theinsectorotherwisepreventingitfromengagingin
Mudasiretal
Fig 1. Chemical structure of organophosphate
insecticidesVariationofsubstituentwasdoneatC3or C4aswellasRAtomicnumberingisusedonlyforthe purposeofmolecularmodel
ranges from cholinesterase inhibition in plasma erythrocytesandbraintissuetotheappearanceof
[4] InsomecasesAChEthatisinhibitedbycertain
types of organophosphorus esters is irreversibly phosphorylatedandspontaneousregenerationdoesnot inmodification of enzymeproperty includingits sensitivitytoinhibitionbyinsecticides
Since 1970s the use of most persistent organochlorine insecticides has been restricted consequentlythelesspersistentbuthighlyeffective organophosphateagentshasbeenthemostwidespread pesticidesusedworldwideandbecometheinsecticides offirstchoiceCurrentlyalleffortsarefocusedon developinginsecticideswithnewandsafermodesof action A rational approachfor developing new insecticidesistomakeuseofQSARQuantitative StructureઈActivityRelationshipmodelsfortherapid prediction andvirtual preઈscreening of insecticide activity
AQSARequationisamathematicalequationthat correlatesthebiologicalactivitytoawidevarietyof physical orchemicalparametersTherearemany examplesavailableintheliteratureinwhichQSAR modelshavebeenusedsuccessfullyforthescreeningof compoundsforbiologicalactivity[6–9]Thepreઈrequisite ofdevelopingQSARequationsistheavailabilityofa wide range of molecular structures and their complementaryactivitiesQSARstudieshavebeen successfully done for the organophosphates and carbamates [10] using only freeઈenergyઈrelated physiochemicalsubstituentparameterssuchaspsand othersFurthermoreNaiketal[11]hasconducted QSARstudyfortheorganophosphatesandcarbamates
using Eઈstate electronic structural topological quantum mechanics and physicochemical based descriptorswhichcanbecalculatedwithoutstructural alignmentsThebehavior ofQSARmodelswas examinedwithavarietyofstatisticalparametersinline withwhathasbeenusedbyDeswalandRoy[12]for thedevelopmentofthrombininhibitors
BasedonthedataofacutetoxicityLD50molL
ઈ1 empirical AM1 calculation of quantumઈchemical descriptorsThebestQSARmodelobtainedfromthe
studywasthenusedtodesignin siliconewcompounds
of insecticideof organophosphatederivativeswith betteractivityascomparedtotheexistingsynthesized organophosphatederivatives
EXPERIMENTAL SECTION LD50molLઈ1ofthesecompoundstohouseflyMusca
nebulo L.weretakenfromHanschetal[13]except
forthecompound24fromGandheandPurnanand [14]Allchemicalsareanaloguestomethylandethyl paraoxonscompounds12and22whicharecapable ofinhibitingAChEdirectly[14]Theselectedchemicals have significant differencesin structureforthe substituentsXatmetaandparapositionsrangingfrom electronઈdonatinggroup–CH3toelectronઈwithdrawing
group–NO2whilethealkylgroupRvariesfrom
methyltobutyl
Computational Validation and Descriptor Calculation
Inordertoobtainthemostsuitablemethodof calculationtheparentcompoundoforganophosphate wasfirstcomputationallymodeledusingeitherAustin ModelAM1orParameterizedmodelPM3available inHyperchem 70softwareprogram tocalculate
chemicalshiftofthecompoundusing1H HyperNMR
Mudasiretal
Table 1. ChemicalstructureandinsecticideactivityoforganophosphatederivativesagainsthouseflyMusca nebulo
L.[11]
No Compounds R X LogLD50
1 Dimethylphenylphosphate CH3 H ઈ275
2 Dimethylmઈtolylphosphate CH3 3ઈCH3 ઈ200
3 Dimethylpઈtolylphosphate CH3 4ઈCH3 ઈ199
4 4ઈmethoxyphenyldimethylphosphate CH3 4ઈOCH3 ઈ200
5 3ઈchlorophenyldimethylphosphate CH3 3ઈCl ઈ210
6 4ઈchlorophenyldimethylphosphate CH3 4ઈCl ઈ260
7 3ઈbromophenyldimethylphosphate CH3 3ઈBr ઈ400
8 4ઈbromophenyldimethylphosphate CH3 4ઈBr ઈ353
9 3ઈcianophenyldimethylphosphate CH3 3ઈCN ઈ499
10 4ઈcianofenildimethylphosphate CH3 4ઈCN ઈ484
11 Dimethyl3ઈnitrophenylphosphate CH3 3ઈNO2 ઈ490
12 Dimethyl4ઈnitrophenylphosphate CH3 4ઈNO2 ઈ510
13 Diethylphenylphosphate C2H5 H ઈ320
14 Diethylpઈtolylphosphate C2H5 4ઈCH3 ઈ300
15 3ઈchlorophenyldiethylphosphate C2H5 3ઈCl ઈ380
16 4ઈchlorophenyldiethylphosphate C2H5 4ઈCl ઈ372
17 3ઈbromophenyldiethylphosphate C2H5 3ઈBr ઈ411
18 4ઈbromophenyldiethylphosphate C2H5 4ઈBr ઈ406
19 3ઈcianophenyldiethylphosphate C2H5 3ઈCN ઈ500
20 4ઈcianophenyldiethylphosphate C2H5 4ઈCN ઈ510
21 Diethyl3ઈnitrophenylphosphate C2H5 3ઈNO2 ઈ510
22 Diethyl4ઈnitrophenylphosphate C2H5 4ઈNO2 ઈ520
23 24ઈdichlorophenyldiethylphosphate C2H5 24ઈCl ઈ430
24 25ઈdichlorophenyldiethylphosphate C2H5 25ઈCl ઈ410
25 Dibuthylphenylphosphate C4H9 H ઈ250
26 Dibuthylmઈtolylphosphate C4H9 3ઈCH3 ઈ200
27 Dibuthylpઈtolylphosphate C4H9 4ઈCH3 ઈ210
28 Dibuthyl4ઈmethoxyiphenylphosphate C4H9 4ઈOCH3 ઈ210
29 Dibuthyl3ઈchlorophenylphosphate C4H9 3ઈCl ઈ280
30 Dibuthyl4ઈchlorophenylphosphate C4H9 4ઈCl ઈ250
31 4ઈbromophenyldibuthylphosphate C4H9 4ઈBr ઈ295
32 Dibuthyl3ઈcianophenylphosphate C4H9 3ઈCN ઈ400
33 Dibuthyl4ઈcianophenylphosphate C4H9 4ઈCN ઈ401
34 Dibuthyl3ઈcianophenylphosphate C4H9 3ઈNO2 ઈ421
35 Dibuthyl4ઈnitrophenylphosphate C4H9 4ઈNO2 ઈ438
forfurthercalculationinthisstudy
Basedontheresultofmethodvalidationthe descriptorsofQSARanalysisthatusedformultiple linearregressionanalysisconsistingofatomicnetઈ
chargeqdipolemomentmwerecalculatedbysemiઈ
empiricalAMઈ1MOSCFmethodusingHyperChem
Version70SurfaceareaSAandpartitioncoefficient
logPdescriptorswereobtainedfromQSARproperties availableinthepackageprogramBeforecalculationof predictorswasdonethegeometriesoftheinsecticide moleculeswereoptimizedonthebasisofconjugate gradientmethodusingPolakઈRibierealgorithm with convergencelimitof0001kcalmolઈ1Aઈ1
Generation of QSAR Model Using Regression
Analysis
Thecorrelationmodelsbetweendescriptorsand insecticideactivitywereevaluatedbymultiplelinear
regressionanalysisusingsoftwareSPSS13for
WindowsTMBackwardmethod wasusedforall
regressionanalysisonthebasisofthetwofollowing generallinearequations:
50
LogLD= åPqiqi +Pmm+D 1
0
5
LogLD= åPqiqi +Pmm+PSASA+Plog Plog P+D 2
Theequation1isthegeneralQSARmodelinvolving electronic descriptors only while equation 2 representsthegeneralQSARequationmodelusing combinationofelectronicandmolecularparameters ThesymbolPintheequationsstandsforafitting coefficientofcorrespondingdescriptorsandDisa constant
Design of New Compounds
Mudasiretal
O P O
O O H3C
CH3
H H
H
H H
1
2 3
4
5 6 7 8 9
10
11
newmoleculeswerefertothesynthesizedmolecules withhighestactivitythathasbeenreportedietheones withR=ઈC2H5andXsubstituentswerevariedsothatit consistedofelectronwithdrawingordonatinggroupsTo evaluatetheeffectofXsubstituentsoninsecticide activitytheRgroupswerekeptconstantusingethyl groupcompound36–450whileXwasvariedSimilarly toexaminetheinfluenceofRontheactivitytheX substituentswerekeptconstantcompounds46–49 whilethelengthofRwasvariedfromonetofourC atoms Detailed new designed organophosphate derivativesaregiveninTable2
RESULT AND DISCUSSION
Computational Validation
Insearchingthemostsuitablecalculationmethod formodelingseriesofinsecticidederivativestwosemiઈ empiricalmethodsAM1andPM3hasbeentestedfor
thecalculationofchemicalshiftd dimethyl phenyl phosphateFig2usingHyperNMRavailableinthe Hyperchem 70program withthetorsionangleof
C1ઈO7ઈP8ઈO9keptat180° The results of the
calculationwerethencomparedtothoseobtainedfrom
experimentalmeasurements1HઈNMR 400MHz[15]
aslistedinTable2
Table2showsclearlythatchemicalshiftdata obtainedfrom1HHyperNMRcalculationusingAM1have
Fig 2. Chemicalstructureofdimethylphenylphosphate
anditsatomicnumbers
Fig 3. 3Dઈstructureofdimethylphenylphosphateanditsatomicnetઈchargesaftergeometricaloptimizationusing
AM1method
Table 2.ComparisonofcalculatedandexperimentalNMRchemicalshiftdataδppmforhydrogenatomsinphenyl
ringupperandintwomethylgroupslowerofdimethylphenylphosphate
Methods H12 H13 H14 H15 H16
CalculatedAM1 6388 7187 6983 7316 7731
CalculatedPM3 6336 7204 6951 7143 6712
Experimental[15] 731 718 714 718 731
Methods H19 H20 H21 H22 H23 H24
CalculatedAM1 3551 3197 2955 3554 2951 3193
CalculatedPM3 2853 1164 3182 2846 3171 1158
Mudasiretal
Table 3.Statisticalparametersof5selectedQSARmodelsoforganophosphatederivatives
Model Descriptors r r2 Adjustedr2 SD FcalcFtab PRESS
1 qC1qC2qC4qC5qC6
qO7qP8qO9qO11 0936 0876 0820 0474 6539 2600x10
ઈ7
2 qC1qC2qC4qC6qO7qO9 0932 0869 0834 0455 10028 4404x10ઈ4
3 qC1qC2qC4qC6qO7 0918 0843 0810 0486 9847 1583x10ઈ6
4 qC1qC2qC6qO7 0905 0820 0791 0511 10299 4057x10ઈ4
5 qC1qC6qO7 0876 0768 0741 0568 9636 2414x10ઈ6
a better agreement with those resulted from experimental measurement ascompared to those calculatedbyPM3methodsuggestingthatAM1method describethechemicalconformationoforganophosphate derivativesmoreaccuratelythandoesPM3methods Therefore AM1 method has been selectedas calculationmethodforfurthermodelingofinsecticide compoundsinthisstudyusingC1ઈO7ઈP8ઈO9torsion angleof180°becausethisanglegivethelowest potentialenergy
Geometrical Optimization of Insecticide Structure
towards the oxygen atom due to the high electronegativityofO7OntheotherhandC2C3C4
Generation and Selection of QSAR Model
InsearchingforbestmodelsaccordingtoEq1 and2therelativeimportanceofdescriptorsie: atomic netઈcharge and other propertiescan be
recognizedfromthevariablecoefficientsizeP and
fromtheresultofintervariablecorrelationanalysisby bivariatemethodThisallowstheexclusionofless relevant descriptorandgradual evaluationof the structureoftheactivecenteroftheinsecticides
To obtain the best model that correlates independencevariablesdescriptorsanddependence compounds Fifteen 15 independent variables consistingof11atomicnetઈchargesqofC1C2C3 C4C5C6O7P8O9O10andO11aswellasother
propertiessuchasdipolemomentm surfacearea
SAandpartitioncoefficientLogPwereincludedin themodelsetઈupAtthefirststepallvariablesare includedinthemodelandthelessrelevantvariables weretheneliminatedgraduallyfromthemodelbyenter
andbackwardmethodThisprocedurefinallygives5
QSARmodelsaslistedinTable3FromTable3itis immediatelyemergedthatallselectedmodelsshowa goodcorrelationr ≈09betweenbiologicalactivity anddescriptorsselectedforfittingThissuggeststhat justificationofthebestmodelamong5modelsselected
inTable3isnotadequateonlybycomparingthersize
becauseitsvalueisalmostsimilarThereforeother
statisticalparameterssuchasFcalcFtab model
significanceSDstandarddeviationandPRESS search and design of new organophosphate insecticideswhichisnecessaryduetotherapid resistancedevelopmentofmanyinsectsespeciallyin tropicalcountriesThecompleteequationofthebest modelispresentedinEquation3
LogLD50=50872–66457qC1–65735qC6鮼83115qO7 3
n=30r=0876adjusted r2=0741SD=0568FcalcFtab=9636
PRESS=2414x10ઈ6
Model validation
Mudasiretal
Table 4.Comparisonbetweenpredictedandexperimentalvaluesofinsecticideactivitycalculatedbyselectedmodel
for5compoundsoftestset
PredictedLogLD50
Compoundsof testset
Experimental
LogLD50 Model1 Model2 Model3 Model4 Model5
Compound3 ઈ199 ઈ2746 ઈ2740 ઈ2562 ઈ2420 ઈ2212
Compound4 ઈ200 ઈ2266 ઈ2270 ઈ2003 ઈ1614 ઈ1800
Compound16 ઈ372 ઈ3903 ઈ3881 ઈ3693 ઈ3602 ઈ3732
Compound32 ઈ400 ઈ3523 ઈ3653 ઈ3875 ઈ3942 ઈ3772
Compound34 ઈ421 ઈ4268 ઈ4665 ઈ4784 ઈ4837 ઈ4648
Fig 4.Plotofpredictedversusexperimentalactivity
valuesfor5compoundsoftestsetoforganophosphate insecticidescalculatedbymodel5
Fig 5. Chemicalstructureof4ઈdiethoxyphosphoriloxy
benzenesulfonicacid logLD50isplottedbylinearregressionmethodagainst
thoseobtainedbyexperimentsobservedlogLD50 to
seehowwellthesetwovaluescorrelateeachotherFig 4onlymodel5isshownItisobservedfromthisfigure thatmodel5predictsverywelltheactivityof5 compoundsoftestsetascanbeseenfromthevaluesof theslopeandcorrelationcoefficientroftheplotwhich isclosetounityie:1050and0945respectively
Design of New Insecticides
In designing new insecticide molecules of organophosphatederivativesthebestQSARmodel obtainedisusedasaguidancetopredicttheiractivity TheselectionofRsubstituentsforthenewmolecules isbasedonthepreviouslysynthesizedmolecules havinghighinsecticideactivityieR=C2H5 while X substituentsarevariedsothatthemoleculesbear eitherwithdrawingordonatingsubstituentsDetailed newinsecticidesthathavebeendesignedarelistedin Table 5 together with their predicted activities calculatedusingthebestQSARmodel
Based on LFER Linear Free Energy Relationship in designing new molecules X substituentsareattachedtothephenylringatparaઈ
designedcompoundshavepredictedactivityofLD50
lowerthansynthesizedinsecticideswhichhasbeen reportedinmanyliteraturesThesmallestreported
valueofLD50 for synthesized organophosphate
insecticidesisઈ520usingR=C2H5andX=4ઈNO2as
substituentsAscanbeseenfromTable5compound
464748and49whereX=4ઈSO3H anelectron
withdrawinggrouphavepredictedLD50lower than
thosehasbeenreportedFormthelowestpredicted
LD50valueithasbeenfoundthatcompoundwithR=
C2H5andX=4ઈSO3Hatpositionparagivesthebest
activitywhilethoseusinglongerchainofRtendto decreaseThereforeitisconcludedthatindesigning thenewcompounditisbettertouseXofwithdrawing
electronandR=C2H5AccordingtoHassall[16]the
stabilityofthebindingofphosphatetoOઈserineofthe enzymeisinfluencedbythetypeofRandithasbeen
Mudasiretal
Table 5. NewdesignedorganophosphateinsecticidemoleculesanditspredictedlogLD50calculatedusingthebest
QSARmodel
No Compounds R X Predicted
LogLD50
36 Diethyl4ઈethylphenylphosphate C2H5 4ઈCH2CH3 ઈ1957
37 Diethyl4ઈmethoxyphenylphosphate C2H5 4ઈOCH3 ઈ2562
38 4ઈEthoxyphenyldiethylphosphate C2H54ઈOCH2CH3 ઈ2461
39 4ઈAminophenyldiethylphosphate C2H5 4ઈNH2 ઈ0945
40 Diethyl4ઈmethylaminophenylphosphate C2H5 4ઈNHCH3 ઈ0865
41 4ઈMethylaminophenyldiethylphosphate C2H5 4ઈNCH32 ઈ1704
42 Diethyl4ઈmethylthiophenylphosphate C2H5 4ઈSCH3 ઈ3317
43 Diethyl4ઈethylthiophenylphosphate C2H54ઈSCH2CH3 ઈ3258
44 Diethyl4ઈformylphenylphosphate C2H5 4ઈCHO ઈ4649
45 3ઈDiethoxyphosphoriloxybenzenesulfonicacid C2H5 3ઈSO3H ઈ4659
46 4ઈDiethoxyphosphoriloxybenzenesulfonicacid C2H5 4ઈSO3H ઈ7293
47 4ઈDimethoxyphosphoriloxybenzenesulfonicacid CH3 4ઈSO3H ઈ6598
48 4ઈDipropoxyphosphoriloxybenzenesulfonicacid C3H7 4ઈSO3H ઈ7119
49 4ઈDibuthoxyphosphoriloxybenzenesulfonicacid C4H9 4ઈSO3H ઈ7070
strongestinteractionwithOઈserineoftheenzymehence thiscompoundgivesthehighesttoxicityamongthe others Among new designed organophosphate molecules4ઈdiethoxyphosphoriloxybenzenesulfonic
acidisthemostpotentinsecticidesR=C2H5 X = 4ઈ
SO3HpredictedlogLD50 = ઈ7293 The chemical
structureofthiscompoundisgiveninFig5
Fromtheviewpointofsubstituentsattachedto phenylgroupsitisobservedthatthemostactive synthesized organophosphate derivatives have X substituent=4ઈNO2electrondonatinggroupSimilarly thenewdesignedorganophosphatederivativeswiththe lowestlogLD50valuealsopossesseselectrondonating
groupieX=4ઈSO3HInthisstudythepositionofઈ
SO3Hhasbeenvariedeitherinthemetaઈorparaઈ
positiontoevaluatetheeffectofelectronresonanceby
comparingthepredictedlogLD50 values of the
correspondingcompoundsResultsofthestudyshow thatthereisasignificantdifferenceinthevalueof
predictedlogLD50betweenparaX=4ઈSO3Hpredicted
logLD50=ઈ7293andmetaX=3ઈSO3Hpredictedlog
LD50=ઈ4659substituentsindicatingthatsubstituentat parapositioninducesmorepronounceof electron resonanceeffect onphenyl ringcausingelectron
attractionchargeflowfromO7toઈSO3Hsubstituent
ConsequentlythebindingbetweenP8andO7becomes looserandthephosphategroupiseasilyboundtoOઈ serineoftheenzymeresultinginhigherinsecticide activityofthecorrespondingcompound
CONCLUSION
Wehaveusedasemiઈempiricalmolecularorbital calculationAMઈ1tostudythecorrelationbetween structureandtheactivityofaseriesoforganophosphate insecticidesagainsthouseflyMusca nebulo L. The bestoverallcorrelationisgivenbythecomputed molecularpropertiesofatomicnetchargesofcarbonઈ1
carbonઈ7aswellasOxygenઈ7asanactivecenterof theinsecticidesItisgratifyingtoobservethatthe hypothetical active center of the insecticides corroboratenicelyintermsofpossiblemodeof irreversiblebindingoftheinsectidestocholinesterase ThebestQSARmodelhasbeenabletobeusedto
design in silico newcompoundsof insecticideof
organophosphatederivativeswithbetteractivityas comparedtotheexistingsynthesizedorganophosphate derivativesFromthemoleculardesignithasbeen foundthat4ઈdiethoxyphosphoryloxybenzenesulfonic acidisagoodcandidateasanewmorepotent insectideofthisserieswithlogLD50predictionofઈ729 Thenewdesignedinsecticidecompoundissuggested tobesynthesizedandtestedforitsactivityinlaboratory forfurtherverificationIthasalsobeendemonstrated fromthisresultthatsemiઈempirical AM1method althoughinducespossibleerrorsourcesstillseemto beanecessaryandacceptablecompromisefor quantum pharmacologicalcalculationsonseriesof insecticidemoleculesofthissizeincludingthesearch foractivedrugcenter
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![Table 1. Chemicalstructureandinsecticideactivityoforganophosphatederivativesagainsthousefly L.Musca nebulo [11]](https://thumb-ap.123doks.com/thumbv2/123dok/872639.820977/3.595.92.497.136.512/chemical-structure-insecticide-activity-organophosphate-derivatives-against-housefly.webp)
