雨课堂学堂在线学堂云《Artificial Intelligence Drug Design（复旦大学）》单元测试考核答案

ArtificialIntelligenceDrugDesign第1题Regardingthehistoryof"NewDrug+AI"R&D,whichofthefollowingstatementsiscorrect?AAI-drivendrugdiscoveryisabrand-newconceptthatsuddenlyappearedin2025,withnopriortechnicalfoundation.BTherootsofAI-drivendrugdiscoverycanbetracedbacktoComputer-AidedDrugDesign(CADD)thatemergedinthe20thcentury,suchasearlymolecularmodelingandQuantitativeStructure-ActivityRelationship(QSAR)studies.CBeforethe21stcentury,AItechnologyhadalreadycompletelydominatedtheentirenewdrugR&Dprocess.DThereleaseofproteinstructurepredictiontoolslikeAlphaFoldhashadnosubstantialimpactonthedevelopmentofAI-drivendrugdiscovery.第2题WhichofthefollowingdescriptionsregardingTraditionaldrugdiscovery,Computer-AidedDrugDesign(CADD),andArtificialIntelligenceDrugDiscovery(AIDD)isINCORRECT?ATraditionaldrugdiscoveryoftenreliesheavilyontheexperienceofresearchersandhasahighrateofscreeningfailure.BCADDprimarilyusesphysical-chemicalmethods(e.g.,moleculardocking)toimprovescreeningefficiencythroughcomputationalsimulation.CAIDDfocusesonminingpatternsfromlargedatasetsusingmachinelearning,anditseffectivenesshighlydependsonthequalityofthedataandthereliabilityofthealgorithms.DTheemergenceofAIDDhascompletelyreplacedCADDandtraditional"wetlab"methods,becomingthesolemeansofdrugdevelopment.第3题The"threemajorproblems"or"threemajorchallenges"commonlyfacedinthefieldofnewdrugR&Dusuallyreferto?ALowcost,shortcycle,highsuccessrate.BManypatents,fastapproval,highprofits.CThe"three10"dilemma:R&Dcycleexceeds10years,investmentexceeds$1billion,andsuccessrateislessthan10%.DShortageofrawmaterials,productionpollution,anddifficultiesinpackagingandtransportation.第4题Intheprocessofnewdrugdevelopment,whichofthefollowingisNOTaprimaryapplicationscenarioforArtificialIntelligenceDrugDiscovery(AIDD)?AMiningmassivedatasetsthroughdeeplearningforthediscoveryandvalidationofnewdrugtargets.BUsinggenerativemodelstodesignentirelynewcandidatecompoundmoleculesfromscratch.CDirectlyreplacingallanimalexperimentsandhumanclinicaltrialstoensuredrugsare100%safeandeffective.DPredictingtheAbsorption,Distribution,Metabolism,Excretion,andToxicity(ADMET)propertiesofdrugcandidates.第5题WhichofthefollowingstatementsaccuratelydescribesthedevelopmentstagesofnewdrugR&DinChina?AChina'snewdrugR&DhasalwaysfocusedprimarilyonoriginalFirst-in-class(FIC)drugs.BFromthe"11thFive-YearPlan"tothe"13thFive-YearPlan"period,China'snewdrugR&Dgraduallyachievedatransitionfromtrackingandimitationtoindependentinnovation.CUptonow,themaintaskofChinesepharmaceuticalcompaniesremainsthelarge-scaleimitationofforeigndrugswhosepatentshaveexpired.DChina'snewdrugcreationstillreliesentirelyontraditional"wetlab"methodsandhasnotyetintroducedcomputer-aidedtechnologies.第1题RegardingtheapplicationofGPTmodelsindrugdevelopment(AIDD)andthedevelopmenthistoryofDeepSeek,whichofthefollowingdescriptionsiscorrect?AGPTmodelscannotprocessbiomedicaltextsormolecularstructuredataandarethereforecompletelyunsuitablefordrugdevelopment.BGPTmodelsmaybeusedindrugdevelopmenttoassistinliteraturemining,generatingmoleculardescriptions,orpredictingdruginteractions.CDeepSeekwasfoundedin2010andwasoneoftheearliestcompaniesengagedinlargemodelresearchanddevelopment.DDeepSeekfocusesonhardwarechipmanufacturingandhasnotbeeninvolvedintheresearch,development,oropen-sourcingofAIlargemodels.第2题RegardingthetrainingmodelofChatGPTanditsrelationshipwiththeGPTseriesmodels,whichofthefollowingstatementsisINCORRECT?AChatGPTisaspecificapplicationproductdevelopedbasedontheGPT(GenerativePre-trainedTransformer)architecture.BThetrainingprocessofChatGPTinvolvedpre-trainingonlarge-scaleinternettextdatatolearngrammarandknowledge.CThetrainingofChatGPTalsoincludesaReinforcementLearningfromHumanFeedback(RLHF)phase,whichmakesthemodel'sresponsesmorealignedwithhumanpreferences.DThetrainingofChatGPTwascompletedinonego,andaftertrainingiscomplete,themodel'sknowledgeisautomaticallyupdatedinreal-timeovertimewithouttheneedforretrainingorfine-tuning.第3题Regardingthedevelopmentalstagesofartificialintelligence,thegenerallyrecognizedevolutionarypathis?AStartingfromArtificialGeneralIntelligence(AGI)andthenregressingtonarrowAI(weakAI).BStartingdirectlyfromsuperintelligentAIcapableofself-evolution.CMainlyprogressingthroughstagesfromearlylogicalreasoningandrule-basedengines,tostatisticalmachinelearning,andthentothecurrenteraofdeeplearningandgenerativelargemodels.DThedevelopmentofartificialintelligencehasalwaysstagnatedwithnoclearstagedivision.第4题Whichofthefollowingdescriptionsregardingthehistoryofartificialintelligenceiscorrect?ATheconceptofartificialintelligencewasfirstbornduringtheinternetbubbleperiodintheearly21stcentury.BTheDartmouthConferenceheldin1956iswidelyregardedasthebirthmarkofartificialintelligence.CBythe1960s,artificialintelligencetechnologyhadbecomefullymatureandintegratedintodailylife.DBreakthroughsindeeplearningtechnologyoccurredduringtheAIwinterofthe1970s.第5题WhichofthefollowingdescriptionsisthemostaccuratedefinitionofArtificialIntelligence(AI)?AArtificialIntelligencereferstotechnologythatcompletelyreplacesthehumanbrainwithcomputers,endowingthemwithself-awarenessandemotions.BArtificialIntelligenceisabranchofsciencededicatedtoresearchinganddevelopingtheories,methods,technologies,andapplicationsystemsthatsimulate,extend,andexpandhumanintelligence.CArtificialIntelligencespecificallyreferstorobotichardwaredevicescapableofperformingphysicalactions.DArtificialIntelligenceisanewconceptthatemergedinthe21stcentury,withnopriorrelevantideasinhumanhistory.FundamentalsofDeepLearning第1题WhenusingtheTransformermodelforproteinorgenesequenceprediction,itscoreadvantagecomparedtoRNN/LSTMmodelsisprimarilyreflectedin:ALowercomputationalcomplexityBBetterhandlingoflong-rangedependencieswithinsequencesCBeingspecificallydesignedfor2DimagedataDInherentlynotrequiringpositionalencoding第2题ThetwocorecomponentsinaGenerativeAdversarialNetwork(GAN)are:AEncoderandDecoderBGeneratorandDiscriminatorCConvolutionalLayerandPoolingLayerDAttentionMechanismandFeedforwardNetwork第3题Whenadeeplearningmodelexperiences"overfitting,"themostdirectmanifestationis:AHighaccuracyonthetrainingset,butasignificantdropinaccuracyonthetestsetBExcessivelylongtrainingtimeCAllmodelparametersbecomezeroDPredictionsconsistentlyyieldthesamevalue第4题Duringthetrainingofdeeplearningmodels,the"lossfunction"isusedtomeasure:AThedifferencebetweenthemodel'spredictedvaluesandthetruevaluesBThenumberofmodelparametersCThenoiselevelinthetrainingdataDThecomputationalspeedofthecomputer第5题Theprimaryroleofthe"activationfunction"inaneuralnetworkwithindeeplearningisto:AAcceleratethemodeltrainingprocessBIntroducenonlinearity,enablingthenetworktofitcomplexfunctionsCReducethenumberofparametersDPreventgradientvanishingAIinIdentifyingPotentialDrugTargets第1题InAI-drivendiscoveryofpotentialdrugtargets,knowledgegraphsserveas"knowledgeintegrators."Thisisprimarilybecausetheycan:APerformhigh-precisionmoleculardynamicssimulationstocalculatebindingenergies.BConnectentitiessuchasgenes,diseases,drugs,andsideeffects,whicharescatteredacrossvastamountsofliteratureanddatabases,inarelationalmanner.CAutomatehigh-throughputscreeningexperimentsinthelaboratory.DPrimarilyvisualizethethree-dimensionalstructuresofproteins.第2题WhenusingAItoidentifytargets,whatisthecoreadvantageofthe"networkpharmacology"concept?AItfocusessolelyonasingletarget,makingthemechanismofdrugactionsimplerandclearer.BItviewsdiseasesascomplexnetworkdysfunctions,suggestingthatinterventionstargetingmultiplekeynodes(targets)withinthenetworkmaybemoreeffective.CItprimarilyreliesonnetworkdiagramsofchemicalsynthesispathwaysfordrugdesign.DItcandisregardunimportantgenesindiseasepathways,thussimplifyingthemodel.第3题IfanAImodellearnsfromknowndrug-targetinteractionpairstopredictwhetheranovelsmallmoleculewillbindtoaspecifictarget,thistaskmostlikelybelongstowhichofthefollowingmachinelearningparadigms?AUnsupervisedLearningBReinforcementLearningCSemi-supervisedLearningDSupervisedLearning第4题IntheprocessofusingAItoidentifydrugtargets,whatisthemainpurposeofintegratingmulti-omicsdata,suchasgenomic,transcriptomic,andproteomicdata?ATodirectlypredictthechemicalstructuresofsmall-moleculedrugs.BToscreenforcompoundsthatareeasiesttosynthesize.CToidentifykeygenesorproteinssignificantlyassociatedwithdiseasestates.DTosimulatethemetabolicprocessesofdrugswithinthehumanbody.第5题Intheartificialintelligence-assisteddrugtargetdiscoverypipeline,whichofthefollowingistypicallythestartingpoint?AConductinghigh-throughputvirtualscreeningagainstcandidatetargetsBPredictingthethree-dimensionalstructuresofproteinsusingdeeplearningmodelsCIdentifyingandvalidatingpotentialdisease-associatedtargetsfrommulti-omicsdataDValidatingtheefficacyandsafetyofcandidatedrugsinpreclinicalmodelsProteinStructurePredictionandDesign第1题AkeyenhancementoftheAlphaFold3modelcomparedtoAlphaFold2is:AItcompletelyabandonedattentionmechanismsinfavorofusingpureconvolutionalnetworks.BItexpandedtopredictthestructuresandinteractionsofcomplexesinvolvingproteinswithDNA,RNA,smallmoleculeligands,andmore.CItonlyimprovedtheaccuracyofsecondarystructurepredictionforsingle-chainproteins.DItreducedtheamountoftrainingdatausedwithoutalteringthemodelarchitecture.第2题ThekeyreasonAlphaFold2hassignificantlyimprovedtheaccuracyofproteinstructurepredictionis:AItreliessolelyonconvolutionalneuralnetworkstoprocessaminoacidsequences.BItemploysanend-to-endtrainingarchitecture,integratingtheEvoformermoduletoprocessmultiplesequencealignmentsandpairwisefeatures,andrefinesthepredictedstructureiterativelythroughastructuremoduleinatranslation-androtation-invariantmanner.CItreliesentirelyonphysicalforcefieldsforabinitiofoldingsimulations.DItsolelypredictsaccuratesecondarystructuresandthenassemblesthemintoa3Dmodel.第3题Inproteinstructureprediction,deeplearningmodelsoftenincorporateevolutionarycouplinginformation(co-evolution)asinput.Itsprimaryroleisto:AProvidethephysicochemicalpropertiesofaminoacidsBReflectco-evolutionaryrelationshipsbetweenresiduepairsinthesequence,aidinginthedeterminationoflong-rangecontactsCDirectlyindicatesecondarystructuretypesDCalculatethemolecularweightoftheprotein第4题Proteincontactmappredictionbelongstowhichtypeoftask?ASequence-to-sequencegenerationtaskBSequence-to-2Dmatrixpredictiontask(determiningwhetherresiduepairsareincontact)CStructure-to-sequenceinversedesigntaskDImageclassificationtask第5题Inproteindesigntasks,thegoalofthe"inversefolding"problemis:ATopredictthethree-dimensionalstructurebasedonaknownaminoacidsequenceBTodesignpossibleaminoacidsequencesbasedonatargetthree-dimensionalstructureCTocalculatethebindingfreeenergybetweenaproteinandaligandDTopredictthestabilityofaproteininsolutionC6第1题IntheprocessofAImoleculargenerationandmodeltrainingoptimization,whichofthefollowingisNOTtypicallyconsideredachallenge?AThechemicalvalidity(e.g.,compliancewithvalencerules)andsynthesizabilityofgeneratedmolecules.BInsufficientqualityandquantityoftrainingdata,leadingtopoormodelgeneralizationability.CExtremelyslowgenerationspeedofnewmoleculesbythemodel,producinglessthanonemoleculepersecond.DTheproblemofmodeloverfitting,wherethemodelperformswellonthetrainingsetbutpoorlypredictsnewmolecules.第2题MolecularrepresentationmethodsarefundamentaltoAIdrugdesign.Theirmainpurposeisto?ATransformthechemicalstructureofdrugmoleculesintomathematicalforms(suchasfingerprints,graphs,strings,orvectors)thatcomputerscanunderstandandprocess.BDirectlyinjectcomputercodeintochemicalreagentstomakethempharmacologicallyeffective.CDescribethetasteandcolorofdrugsintextsothatpatientscanmakechoices.DOnlyusedtocalculatethemarketpriceandsynthesiscostofmolecules.第3题Regarding"IndirectDrugDesign,"whichofthefollowingstatementsiscorrect?AIndirectdrugdesignreferstotheprocessofconstructingpharmacophoremodelsorquantitativestructure-activityrelationshipmodelsbasedonthestructuresofknownactivesmallmoleculeligandswhenthetargetproteinstructureisunknown,therebyguidingthedesignofnewmolecules.BIndirectdrugdesignisexactlythesameasdirectdrugdesign,bothbasedontargetproteinstructure.CIndirectdrugdesignreliesentirelyonartificialintelligenceanddoesnotrequireanyexistingdrugmoleculedata.DIndirectdrugdesignreferstobypassingtargetsandligandsandproceedingdirectlytotheclinicaltrialstage.第4题InAI-assisteddrugdesign,"DirectDrugDesign"typicallyrefersto?ARandomlysynthesizingalargenumberofcompoundsforscreeningwithoutrelyingonanytargetstructureinformation.BDirectlypurchasingexistingdrugsfromthemarketforefficacytesting.CBasedontheknownthree-dimensionalstructureofatargetprotein,usingcomputationalmethods(suchasmoleculardockingorgenerativemodels)todirectlydesigncandidatemoleculesthatcanfitintoit.DDirectlyhavingAImodelsautomaticallycompleteallwetlaboperationswithouthumanintervention.第5题Whichofthefollowingdescriptionsiscorrectregardingthebasictheoryofdrugdesign?ADrugdesignreliesentirelyonaccidentaldiscoveryandhasnotheoreticalfoundationwhatsoever.BThecoreofdrugdesignisbasedonunderstandingthestructureofdisease-relatedbiologicaltargets(suchasproteins)tofindorconstructmoleculesthatcanspecificallyinteractwiththem.CDrugdesignonlyneedstoconsiderthecolorandodorofcompounds,withoutconsideringtheirthree-dimensionalstructure.DDrugdesigntheoryonlybegantoemergeaftertheriseoftheinternetinthe1990s.dosageform第1题Whichbrain-targeteddrugdeliverystrategycancircumventtheblood-brainbarrier?ANasaladministrationBCarrier-mediatedtransportCReceptor-mediatedtransportDIncreasingthelipophilicityofdrugmolecules第2题Whichofthefollowingtypesdoesnotbelongtothedesigntypesofsustained-releaseformulations?ADiffusion-controlledBErosion-controlledCOsmotic-controlledDPulsatilerelease第3题AccordingtoLipinski'sRuleofFive,whichofthefollowingisnotacriterionforpredictingpoorabsorptionorpermeabilityofamolecule?AMorethan5hydrogenbonddonors(sumofOHandNHgroups).BMolecularweightgreaterthan500.CCalculatedLogP(partitioncoefficient)lessthan5.DMorethan10hydrogenbondacceptors(sumofNandOatoms).第4题TheauthorofTreatiseonColdDamageandMiscellaneousDiseases(ShangHanZaBingLun)is:ABianQueBHuaTuoCCaiLunDZhangZhongjing第5题BCSClassIIdrugsare:AHighsolubility–highpermeabilitydrugs.BHighsolubility–lowpermeabilitydrugs.CLowsolubility–highpermeabilitydrugs.DLowsolubility–lowpermeabilitydrugs.AIApplicationsinMolecularGenerationandSynthesis第1题Fortasksrequiringmulti-stepretrosynthesisdesigninindustrialsynthesisplanning,themostsuitableAIapproachis:ATemplate-basedrulematchingBSequence-basedend-to-endTransformerCSemi-templatemethodsorhybridmodelscombinedwithreinforcementlearningDFrequencystatisticsbasedsolelyonliteraturedata第2题Whichofthefollowingmethodsistypicallyusedtoquantifythesimilaritybetweenmolecularstructures?AMolecularDockingBMolecularDynamicsSimulationCMolecularFingerprintComparisonDQuantumChemicalCalculation第3题Inmolecularrepresentationmethods,themaincharacteristicofSMILES(SimplifiedMolecularInputLineEntrySystem)is:AAcontinuousnumericalrepresentationbasedonthethree-dimensionalconformationofamoleculeBRepresentingmolecularstructureusingalinearstringnotationCApplicableonlytoproteinsandpeptidemoleculesDDependentonexperimentallydeterminedinfraredspectroscopydata第4题Regarding"molecularrepresentation,"whichofthefollowingstatementsiscorrect?AMolecularrepresentationislimitedtotwo-dimensionaltopologicalstructures.BMolecularrepresentationdoesnotincludedescriptionsofphysicochemicalproperties.CMolecularrepresentationcantakevariousforms,suchasgraphstructures,fingerprints,orvectors.DMolecularrepresentationisunrelatedtomoleculargeneration.第5题Themainconceptofgenerativemoleculardesignis:AUtilizingreactiondatabasestopredictreactionmechanismsBGeneratingnovelmoleculeswithdesiredpropertiesfromchemicalspaceusingdeeplearningmodelsCScreeningknowndrugssolelybasedonmoleculardockingresultsDAnalyzingclinicalpharmacokineticsdatausingstatisticalmodelsAIinPredictingDrugProperties第1题Torapidlyscreenavirtuallibrarycontainingmillionsofcompoundsinordertoidentifypotentialhitcompoundswithhighaffinityforanewtarget,whichAIstrategyshouldbeprioritized?APerformlong,all-atommoleculardynamicssimulationsforeachcompound.BUsecomputationallyinexpensiveligand-basedmodels(s