Simone BrogiSimone Brogi and Andrea Tafiand Andrea Tafi

Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di SienaDipartimento Farmaco Chimico Tecnologico, Università degli Studi di SienaVia Aldo Moro, IVia Aldo Moro, I--53100 Siena, Italy53100 Siena, Italy

WeWe havehave appliedapplied aa novelnovel approachapproach toto generategenerate aa ligandligand--basedbased pharmacophorepharmacophore modelmodel.. TheThe pharmacophorepharmacophore waswas builtbuilt fromfrom aa setset ofof 4242 compoundscompounds showingshowing activityactivity againstagainst MCFMCF--77 cellcelllineline derivedderived fromfrom humanhuman mammarymammary adenocarcinoma,adenocarcinoma,11 usingusing thethe programprogram PHASE,PHASE,22 implementedimplemented inin thethe SchrödingerSchrödinger suitesuite softwaresoftware packagepackage.. PHASEPHASE isis aa highlyhighly flexibleflexible systemsystem forforcommoncommon pharmacophorepharmacophore identificationidentification andand assessmentassessment andand 33DD--databasedatabase creationcreation andand searchingsearching.. TheThe bestbest pharmacophorepharmacophore hypothesishypothesis showedshowed fivefive featuresfeatures:: twotwo hydrogenhydrogen--bondbondacceptors,acceptors, oneone hydrogenhydrogen--bondbond donor,donor, andand twotwo aromaticaromatic ringsrings.. TheThe structurestructure––activityactivity relationshiprelationship (SAR)(SAR) soso acquiredacquired waswas appliedapplied withinwithin PHASEPHASE forfor molecularmolecular alignmentalignment inin aacomparativecomparative molecularmolecular fieldfield analysisanalysis (CoMFA)(CoMFA) 33DD--QSARQSAR studystudy..33 TheThe 33DD--QSARQSAR modelmodel yieldedyielded aa internalinternal testtest setset rr22 equalequal toto 00..9797 andand demonstrateddemonstrated toto bebe highlyhighly predictivepredictive withwith respectrespect totoanan externalexternal testtest setset ofof 1818 compoundscompounds (r(r22 ==00..9393)).. InIn summary,summary, inin thisthis studystudy wewe improvedimproved aa previouslypreviously developeddeveloped CatalystCatalyst MCFMCF--77 inhibitoryinhibitory pharmacophore,pharmacophore,44 andand establishedestablished aa predictivepredictive33DD--QSARQSAR modelmodel.. WeWe havehave furtherfurther usedused thisthis modelmodel toto detectdetect novelnovel MCFMCF--77 cellcell lineline inhibitorsinhibitors throughthrough 33DD databasedatabase searchingsearching

Pharmacophore generationPharmacophore generationPHASEPHASE 22..55 implementedimplemented inin thethe MaestroMaestro 88..00modelingmodeling packagepackage (Schr(Schröödinger,dinger, LLC,LLC, NewNewYork,York, NY)NY) waswas usedused toto generategeneratepharmacophorepharmacophore modelsmodels forfor MCFMCF--77 cellcell linelineinhibitorsinhibitorsSomeSome highlyhighly activeactive SERM,SERM, werewere selectedselected forforgeneratinggenerating thethe pharmacophorepharmacophore hypotheseshypotheses(Fig(Fig.. 22))PharmacophorePharmacophore featurefeature sitessites forfor thethe bestbestPHASEPHASE modelmodel werewere:: twotwo hydrogenhydrogen--bondbondacceptorsacceptors (A(A33,, AA55),), oneone hydrogenhydrogen--bondbond donordonor(D(D66)) andand twotwo aromaticaromatic sitessites (R(R99,, RR1010)) (Fig(Fig..11))CommonCommon pharmacophorepharmacophore hypotheseshypotheses werewereidentified,identified, scoredscored andand rankedranked.. TheThe regressionregressionisis performedperformed byby aa partialpartial leastleast squaressquares (PLS)(PLS)methodmethodAllAll thethe moleculesmolecules usedused forfor QSARQSAR studiesstudieswerewere alignedaligned toto thethe pharmacophorepharmacophorehypothesishypothesis obtainedobtained inin PHASEPHASE

FigFig.. 11 SuperpositionSuperposition ofof bestbest PHASEPHASE modelmodel andand thethe mostmost activeactive compoundcompound inin thethe setset ((3838))..PharmacophorePharmacophore featuresfeatures areare colorcolor--codedcoded:: cyancyan forfor hydrogenhydrogen bondbond donordonor (D),(D), pinkpink forfor hydrogenhydrogen bondbondacceptoracceptor (A),(A), brownbrown ringsrings forfor thethe aromaticaromatic featuresfeatures (R)(R)

Development of a PHASE 3DDevelopment of a PHASE 3D--QSAR modelQSAR modelTheThe PHASEPHASE--generatedgenerated 33DD pharmacophorepharmacophore waswas usedused asas thethealignmentalignment templatetemplate forfor thethe 33DD--QSARQSAR modelmodel (Fig(Fig..44--55))33

PhasePhase determinesdetermines howhow molecularmolecular structurestructure affectsaffects drugdrugactivityactivity byby dividingdividing spacespace intointo aa finefine cubiccubic grid,grid, encodingencoding

AcknowledgmentAcknowledgment:: WeWe areare gratefulgrateful toto ProfProf.. VassiliosVassilios RoussisRoussis andand coco--workersworkers forfor thethe chemicalchemical entitiesentities andand thethe biologicalbiological assaysassays

ReferencesReferences:: ((11)) SouleSoule HH.. DD.. etet alal.. JJ.. NatlNatl CancerCancer InstInst.. 19731973 5151 ((55)) 14091409;; ((22)) PHASEPHASE 22..55 ((SchrSchröödinger,dinger, LLC,LLC, NewNew York,York, NYNY));; ((33)) DixonDixon SS.. LL.. etet alal.. JJ.. ComputComput.. AidedAided MolMol.. DesDes.. 20062006 2020((1010--1111)) 647647;; ((44)) Kladi,Kladi, MM.. etet alal.. JJ.. NatNat.. ProdProd.. 20092009 ASAPASAP DOIDOI:: 1010..10211021/np/np800481800481ww;; ((55)) PHASEPHASE useruser manualmanual;; ((66)) Walters,Walters, WW.. PP.. etet alal.. AdvAdv.. DrugDrug DelivDeliv.. RevRev.. 20022002 5454 255255

FigFig.. 22 SERMSERM derivativesderivatives usedused inin thisthis studystudy

FigFig.. 33 PredictedPredicted versusversus observedobserved valuevalue inhibitoryinhibitory activityactivity pICpIC5050 (M)(M)

3D3D--Database searchingDatabase searching

ConclusionConclusion

activityactivity byby dividingdividing spacespace intointo aa finefine cubiccubic grid,grid, encodingencodingatomatom typetype occupationoccupation asas numericalnumerical information,information, andandperformingperforming aa partialpartial leastleast--squaressquares (PLS)(PLS) regressionregressionTheThe independentindependent variablesvariables inin thethe QSARQSAR modelmodel werewere derivedderivedfromfrom aa regularregular gridgrid ofof cubiccubic volumevolume elementselements thatthat spanspan thethespacespace occupiedoccupied byby thethe trainingtraining setset ligandsligands andand biologicalbiologicalactivitiesactivities (pIC(pIC5050 values)values) werewere usedused asas dependentdependent variablesvariables.. InInadditionaddition toto thethe qq22,, thethe conventionalconventional correlationcorrelation coefficientcoefficient rr22

andand itsits standardstandard errorserrors werewere alsoalso computedcomputed (Table(Table 11))

FigFig.. 44 33DD--QSARQSAR modelmodel aroundaround thethe mostmostactiveactive compoundscompounds inin thethe setset ((3838))

InIn ourour study,study, wewe builtbuilt aa pharmacophorepharmacophore modelmodel bybyapplyingapplying thethe ligandligand--basedbased pharmacophorepharmacophore generationgenerationapproach,approach, usingusing PHASEPHASE.. DifferentDifferent pharmacophorepharmacophorebasedbased QSARQSAR modelsmodels werewere developeddeveloped byby usingusing PLSPLSanalysisanalysisTheThe bestbest resultingresulting hypothesishypothesis consistedconsisted ofof fivefivefeaturesfeatures:: twotwo hydrogenhydrogen bondbond acceptors,acceptors, oneonehydrogenhydrogen--bondbond donordonor andand twotwo aromaticaromatic sitessites.. TheThealignmentalignment rulerule ofof thethe bestbest--fitfit modelmodel waswas usedused totodevelopdevelop ligandligand--basedbased33DD--QSARQSAR modelmodelTheThe establishedestablished computationalcomputational tooltool endowedendowed withwithhighhigh predictivepredictive abilityability andand robustness,robustness, mightmight bebeusefuluseful forfor thethe designdesign andand optimizationoptimization ofof newnew MCFMCF--77cellcell lineline inhibitorsinhibitors

Validation of PHASE 3DValidation of PHASE 3D--QSAR modelQSAR model1818 newnew potentialpotential SERMsSERMs werewere testedtested againstagainst MCFMCF--77 cellscellsandand thenthen usedused asas anan externalexternal testtest setset forfor PHASEPHASE 33DD--QSARQSARmodelmodel validationsvalidations forfor predictivepredictive abilityability.. TheThe predictionprediction resultsresultsofof thisthis externalexternal testtest setset areare showshow inin FigureFigure 33TheThe largelarge valuevalue ofof variancevariance ratioratio (F)(F) indicatesindicates aa statisticallystatisticallysignificantsignificant regressionregression model,model, whichwhich isis supportedsupported byby thethe smallsmallvaluevalue ofof thethe significancesignificance levellevel ofof variancevariance ratioratio (P),(P), ananindicationindication ofof aa highhigh degreedegree ofof confidenceconfidence.. TheThe qq22 valuevaluesuggestingsuggesting thethe modelmodel isis robustrobust (Table(Table 11))55

Therefore,Therefore, thethe correlationcorrelation betweenbetween thethe actualactual andand predictedpredictedvaluesvalues ofof activitiesactivities suggestedsuggested thatthat thethe PHASEPHASE 33DD--QSARQSARmodelmodel waswas reliablereliable.. TheThe steric,steric, electrostatic,electrostatic, andand hydrogenhydrogenbondbond acceptoracceptor andand donordonor fieldfield effectseffects werewere nicelynicely relatedrelated withwithvariationvariation ofof activityactivity

33DD--DatabaseDatabase searchingsearching isis aa powerfulpowerful tooltool toto discoverdiscover newnewstructuresstructures andand designdesign newnew ligandsligands ofof aa biologicalbiological targettarget InIn ourour study,study, thethe computationalcomputational 33DD--QSARQSAR modelmodel developeddevelopedbyby PHASEPHASE waswas usedused toto searchsearch AsinexAsinex chemicalchemical databasesdatabases(about(about 250250,,000000 structurallystructurally diversifieddiversified smallsmall molecules)molecules) forfornewnew chemicalchemical structuresstructures activeactive againstagainst MCFMCF--77 cellcell lineline CompoundsCompounds withwith aa predictedpredicted activityactivity cutoffcutoff valuevalue ofof 00..55(pIC(pIC5050 µµM)M) werewere selectedselected.. OtherOther filtersfilters werewere appliedapplied toto identifyidentifyentriesentries againstagainst MCFMCF--77 cellcell lineline:: thethe compoundscompounds mustmust satisfysatisfythethe Lipiniski'sLipiniski's rulerule ofof fivefiveTheThe queryquery identifiedidentified 1919 toptop--rankingranking compoundscompounds withwith highhighpredictedpredicted activityactivity againstagainst MCFMCF--77 cellcell lineline.. TheseThese moleculesmoleculeswerewere consideredconsidered likelylikely toto bebe wellwell--absorbedabsorbed becausebecause theytheysatisfiedsatisfied Lipiniski'sLipiniski's rulerule ofof fivefive66

TheseThese 1919 toptop--rankingranking compoundscompounds willwill bebe submittedsubmitted totobiologicalbiological evaluationevaluation

Statistical Statistical parameterparameter

valuevalue

SD 0.327

r2 0,97

F 261.4

P 6.731 e-16

RMSE 1.384

Q2 0.74

R 0.81

Table 1 Statistical parameter of PHASE 3D-QSARmodels.Descriptor of the QSAR results: SDStandard deviation of the regression. r2: Value of r2

for the regression. F Variance ratio. P Significancelevel of variance ratio. RMSE Root-mean-squareerror. Q2 value of Q2 for the predicted activities. Rr-Pearson value

FigFig.. 55 33DD--QSARQSAR modelmodel forfor anan activeactive ligandligand (left)(left) andand anan inactiveinactive ligandligand (right)(right);; coloredcolored accordingaccording toto thethe signsignofof theirtheir coefficientcoefficient valuesvalues:: blueblue forfor positivepositive coefficientscoefficients andand redred forfor negativenegative coefficientscoefficients.. PositivePositive coefficientscoefficientsindicateindicate anan increaseincrease inin activity,activity, negativenegative coefficientscoefficients aa decreasedecrease