welcome to the 2018 d3r workshop!...sampl blinded prediction challenges started 2008 small molecule...
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Welcometothe2018D3Rworkshop!
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WorkshoponChallengesinDockingandScreeningUSNationalInstitutesofHealth,2005
Participantsfrompharma,academia,USgovernmentAcademic:MikeGilson,ArtOlson,BrianShoichetGovernment:ChrisAustin,AnneChaka,JayneKapur,JannaWehrlePharma:JeffBlaney,WendyCornell,DebbieLoughney,CathyPeishoff,EmanuelePerola
ConclusionsComputationalpredictionsofposesandaffinitiesneedtoimproveDatasetsfrompharmacouldhelp
Workshopreport:http://bit.ly/2pLpy8C
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EvaluationofProtein-LigandModelingMethods
Testshavebeenrunwithknowledgeoftheexperimentalresults
Differentmethodshavebeentestedfordifferentsystems
Valueofblinded,community-wide,predictionchallenges
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NIH-fundedinitiativeCSAR2010-2014(Carlson,U.Michigan)D3R2014-present(Amaro&Gilson,UCSanDiego)
Pharmaaspotentialsourceofdatahighlyrelevanthithertounpublished
NIH-U01Resource,UniquePurposeblindedpredictionchallengestodriveadvancesinCADD
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CentralGoal:Utilizepreviouslyunpublisheddatasetsasbenchmarksfordevelopersofprotein-ligandmodelingtechnologies
SynergywithPublicDatabases:Publicreleaseofmoreindustrialcrystalstructuresandaffinitydata
BroaderGoals: UtilizeblindeddatasetstodriveimprovementofallCADDtechnologiesandtofostereducationanddisseminationofmethods
MorepredictiveCADDmethodsbenefiteveryone!
DrugDesignDataResource(D3R)
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D3RProjectTeam
MikeGilsonRommieAmaro Huanwang Yang
JasmineYoung
StephenBurley
MikeChiu
Conor Parks
JeffWagner JeffGretheChrisChuras
Zied Gaieb
CrystallographyGroup
Chenghua Shao
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D3RScientificAdvisoryBoard
Aled EdwardsSGC
DavidMobleyUCIrvine
JohnMoultUMaryland
AdrianRoitbergUFlorida
Torsten SchwedeBiozentrum
CharlesGrimshawTakeda
MartinStahlRoche
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UniqueHubforCADDCommunity
CoherentCADDdatasets
Blindedchallenges:Protein-ligand,modelsystems
Evaluationmetrics
Capturinganddisseminatingworkflows
Workshopsandnetworking
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ChallengeTypes
GrandChallenges:ligand-proteinposesandaffinities
SAMPL:affinities,physicalpropertiesofsimplersystemswithDavidMobley,JohnChodera,&MichaelShirts
CELPP:automated,weeklyposepredictionchallenge
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Stage1:Predictposesandaffinitiesofmultipleligandsforaprotein
Stage1b:Releaseco-crystalstructureswithoutligandstoenableself-docking(Isolatesevaluationofdockingalgorithm)
*Co-crystalstructureswithligandsreleased*
Stage2:Predictaffinitiesagain
Alldatareleased,depositedtoPDB,BindingDB
GrandChallenges
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GrandChallenge201535participants,355submissions
HSP90:focusonpotencypredictionsDatafromAbbvieandCarlson’sCSARproject8cocrystalstructures(.6-2.0Åresolution)180IC50s(5nM-20µM)Threeseries:benzimidazolones,aminopyrimidines,benzophenone-likeVariedwater-mediatedinteractions;open/closedconformations
MAP4K4:focusonposepredictionsDatafromGenentech30cocrystalstructures(1.6– 2.5Åresolution)18IC50data(3.1nM - 10µM)DiversechemotypesbindinginATPsiteOpen/closedP-loopstructures
GrandChallenge249participants,262submissions
Farnesoid XReceptor(FXR):posesandpotenciesDatafromRoche36cocrystalstructures(resolutions<2.6Å)102IC50s(0.3nM-260µM)Threeseries+misc:sulfonamides,benzimidazoles,spirosHelixshiftsandvariedwater-bridges
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GrandChallenge3
CathepsinSposes&IC50sJanssenPharmaceuticals
24cocrystalstructures,3.0Å136IC50s,3– 8500nM
27participants303submissions
KinaseKdsSGC-UNC/DiscoverX
Selectivity
VEGFR285(0.62to>104 nM)
JAK289(0.66to>104 nM)
p38-⍺72(0.28to>104nM)
ActivityCliffs
JAK217(53to>104 nM)
ActivityCliffs
TIE218(3.4to>104 nM)
Mutations
ABL112(49to>104nM)
11participants94submissions
6participants25submissions
6participants32submissions
6participants11submissions
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SAMPLBlindedPredictionChallengesStarted2008
SmallmoleculehydrationfreeenergiesNicholls,Mobley,Guthrie,Chodera,Bayly,Cooper,Pande
Simplemodelsystems,e.g.,Host-guestbindingaffinitiesWater-organicphasepartitioncoefficientsSmallmoleculepKavaluesSmallmoleculehydrationfreeenergies
Advantagesvs.protein-ligandchallengesCalculationsfareasiertoconvergeTroubleshootingbyisolationofspecificissuesReducedambiguity(protonationstates,missingresidues…)
https://en.wikipedia.org/wiki/SAMPL_Challenge
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SAMPL6Host-GuestandpKaChallengesHost-Guest:124submissionsfrom6groups
pKas:95submissionsfrom10groups
DeepCavityCavitandHostsBruceGibb,TulaneU.
8guestmoleculeswithbothOAandTEMOAhostvariants
Cucurbit[8]urilHostLyleIsaacs,U.Maryland
10guestmolecules
SmallMoleculepKasJohnChodera,SKMCC
25compounds
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NewSAMPLing Challenge
Testsefficiencyofconformationalsamplingmethods
BindingfreeenergyconvergencewithNumberofenergyevaluationsWallclocktimeTotalCPUtime
Host-guestsystemswithspecificsetups
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PosepredictionvariationsSoftwarepackages;.e.g.AutoDockVina,Glide,rDOCK,Gold,RosettaLigand,SurflexLigandoverlayoftenused;e.g.ROCS,PoPSSRelaxationandrescoring;e.g.Moleculardynamics,MMPB/SACombinations;e.g.Gold-PlantsPLP-rDock,RosettaLigand-Omega-ROCS,Surflex-Grim
AffinitypredictionandrankingLigand-basedStructure-based
“Lowresolution”dockingandscoring“Highresolution”freeenergymethods
Machine-learning
WideRangeofProtein-LigandMethods
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Whatwehavelearned…
Accuracyofdockingandscoringcorrelatespoorlywithsoftware choice,andsuccessfulposepredictiondependsonothermethodologicalfactors; e.g.,
ligandandproteinpreparationchoiceofproteinconformationtreatmentofxtal waters.
Posepredictionbenefitsfromuseof known ligand-proteincocrystalstructures;e.g.,byligandoverlay
Humaninspectionandintervention donotconsistentlyimproveresults
Accuracyofposesusedcorrelatespoorlywithscoringaccuracy
Applicationoffreeenergymethodstohost-guestsystemspointstoneedforbetterforcefields
Explicitsolventfreeenergymethodshavenotyetoutperformedfasterscoringmethods
Rigorousevaluationofpredictionsisnon-trivialandcanbecontroversial
https://drugdesigndata.org/about/what-we-have-learned
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FromOurGCParticipants…
Ithasmadememoreawareofthechallengesofsampling.I'vebeenworkingonbetterwaystoincludethisintoourprotocolsandmethods.
Iwouldpaymoreattentiontothereceptorconformationsandflexibility.
TheD3Rchallengesallowedustovalidateourdockingprotocol
DockingseemstobeimprovedbymachinelearningandIplantoincorporatesuchapproaches.
...itwilldefinitelychangetheIdodockingtoavoidorminimizefalsepositives.
Ithasmademepleasantlysurprisedwhenascoringfunctionactuallydeliversausefulresultandmakesmeveryskepticalofpeoplewhoblindlytrustthescorethattheyget.
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SpecialIssuesinJCAMDthankstoTerryStouch,SeniorEditor-in-Chief
GC201514articles,2016
GC223articles,2017
SAMPL51/212articles,2016
SAMPL52/217articles,2017
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Saturday
Sunday
Tuesday
Wednesday
PDB pre-releaseInChIsProtein sequencesForthcoming IDs
D3R releases InChIs and protein structures for docking
D3R opens for submissions
D3R submission window closesPDB releases structures
D3R evaluates predictions against released structures
D3R scriptsEliminate trivial ligandsPick protein structures
TowardGreaterStatisticalPowerContinuousEvaluationofLigandPosePredictions(CELPP)
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CapturingComplexWorkflows
Full description of methods
Reproducibility
Evaluation on new datasets
Application to drug design projects
Method1OMEGA,SHAFTS,Amber11
Method2GLIDE-CCDC-GOLD,Amber14,MMGBSa
Method3WaterMap,SHAPEScreening,StructuralInteractionFingerprint,DFT/B3LYP/6-31G*,GLIDE-SP-XP,Induced-fit-docking,Emodel/GlideScore-SP,BindingPoseMetadynamics
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https://drugdesigndata.org
WebPortalforData,Challenges,CommunityActivities
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MealsLightbreakfasts:todayandtomorrowLunchtodayandtomorrowDinnertoday,here;onyourowntomorrow
ShuttlesBothmornings7:30amand7:45amThursdayevening:8:05pmand8:15pmFriday:3:30pm,3:45pmand5:30pm
Posters:Onwalls,pleaseusebluetapeprovided
ContactPeopleMeganMurphyIrisVillanuevaAnyonefromtheD3Rteam
Practicalities
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D3RTeamatUCSDandRutgersD3RScientificAdvisoryBoardSAMPLco-organizers:Profs.D.Mobley,J.Chodera,M.ShirtsDr.TerryStouch andtheJCAMDteamDrs.PeterLyster,PeterPreusch,andJannaWehrle,NationalInstitutesofHealthDataContributors:JanssenPharma,SGC-UNC,ChoderaLab,GibbLab,IsaacsLab,othersExternalevaluators:Drs.Neysa Nevins,MillLambert,PatWaltersAllchallengeparticipants
Acknowledgements