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青蒿素衍生物的定量构效关系(QSAR)研究 Title:QuantitativeStructure-ActivityRelationship(QSAR)StudyofArtemisininDerivatives Abstract: QuantitativeStructure-ActivityRelationship(QSAR)modelinghasbeenwidelyusedindrugdesignanddevelopmenttopredicttheactivityofcompoundsbasedontheirmolecularproperties.Inthisstudy,weinvestigatedtheQSARofartemisininderivatives,whichareknownfortheirantimalarialactivity.Theaimofthisresearchwastoestablishareliableandaccuratemodelthatcanpredictthebioactivityofartemisininderivatives,whichwillaidinthedesignofpotentantimalarialdrugs. Introduction: Malariacontinuestobeamajorglobalhealthconcern,withmillionsofpeopleaffectedeachyear.Artemisinin,anaturalproductisolatedfromtheplantArtemisiaannua,isconsideredoneofthemosteffectiveandcommonlyuseddrugsforthetreatmentofmalaria.However,theemergenceofdrugresistancehashighlightedtheneedfornewandmorepotentantimalarialdrugs.Thesynthesisofartemisininderivativeshasshownpromisingresultsinimprovingdrugefficacyandreducingdrugresistance.QSARmodelingcanprovidevaluableinsightsintothestructure-activityrelationshipsofthesederivatives,thusguidingtherationaldesignofnovelantimalarialagents. Methods: Adatasetofartemisininderivativeswithknownbiologicalactivitieswascollectedfromtheliterature.Moleculardescriptors,suchasphysicochemicalpropertiesandstructuralparameters,werecalculatedforeachcompoundusingappropriatesoftwaretools.ThesedescriptorswerethenusedasindependentvariablestobuildtheQSARmodel.Thedependentvariablewasthebiologicalactivity,expressedintermsofIC50valuesorotherrelevantmeasures.Variousregressionanalysistechniques,suchasmultiplelinearregressionorsupportvectormachineregression,wereemployedtoestablishtheQSARequations. ResultsandDiscussion: TheQSARmodeldevelopedinthisstudyexhibitedgoodstatisticalreliability,asdemonstratedbythecorrelationcoefficient(R^2),cross-validatedcorrelationcoefficient(Q^2),androot-mean-squareerror(RMSE)values.Themodelrevealedthatspecificphysicochemicalandstructuralpropertiesoftheartemisininderivativessignificantlyinflu