Welcometothe2018D3Rworkshop!

WorkshoponChallengesinDockingandScreeningUSNationalInstitutesofHealth,2005

Participantsfrompharma,academia,USgovernmentAcademic:MikeGilson,ArtOlson,BrianShoichetGovernment:ChrisAustin,AnneChaka,JayneKapur,JannaWehrlePharma:JeffBlaney,WendyCornell,DebbieLoughney,CathyPeishoff,EmanuelePerola

ConclusionsComputationalpredictionsofposesandaffinitiesneedtoimproveDatasetsfrompharmacouldhelp

Workshopreport:http://bit.ly/2pLpy8C

EvaluationofProtein-LigandModelingMethods

Testshavebeenrunwithknowledgeoftheexperimentalresults

Differentmethodshavebeentestedfordifferentsystems

Valueofblinded,community-wide,predictionchallenges

NIH-fundedinitiativeCSAR2010-2014(Carlson,U.Michigan)D3R2014-present(Amaro&Gilson,UCSanDiego)

Pharmaaspotentialsourceofdatahighlyrelevanthithertounpublished

NIH-U01Resource,UniquePurposeblindedpredictionchallengestodriveadvancesinCADD

CentralGoal:Utilizepreviouslyunpublisheddatasetsasbenchmarksfordevelopersofprotein-ligandmodelingtechnologies

SynergywithPublicDatabases:Publicreleaseofmoreindustrialcrystalstructuresandaffinitydata

BroaderGoals: UtilizeblindeddatasetstodriveimprovementofallCADDtechnologiesandtofostereducationanddisseminationofmethods

MorepredictiveCADDmethodsbenefiteveryone!

DrugDesignDataResource(D3R)

D3RProjectTeam

MikeGilsonRommieAmaro Huanwang Yang

JasmineYoung

StephenBurley

MikeChiu

Conor Parks

JeffWagner JeffGretheChrisChuras

Zied Gaieb

CrystallographyGroup

Chenghua Shao

D3RScientificAdvisoryBoard

Aled EdwardsSGC

DavidMobleyUCIrvine

JohnMoultUMaryland

AdrianRoitbergUFlorida

Torsten SchwedeBiozentrum

CharlesGrimshawTakeda

MartinStahlRoche

UniqueHubforCADDCommunity

CoherentCADDdatasets

Blindedchallenges:Protein-ligand,modelsystems

Evaluationmetrics

Capturinganddisseminatingworkflows

Workshopsandnetworking

ChallengeTypes

GrandChallenges:ligand-proteinposesandaffinities

SAMPL:affinities,physicalpropertiesofsimplersystemswithDavidMobley,JohnChodera,&MichaelShirts

CELPP:automated,weeklyposepredictionchallenge

Stage1:Predictposesandaffinitiesofmultipleligandsforaprotein

Stage1b:Releaseco-crystalstructureswithoutligandstoenableself-docking(Isolatesevaluationofdockingalgorithm)

*Co-crystalstructureswithligandsreleased*

Stage2:Predictaffinitiesagain

Alldatareleased,depositedtoPDB,BindingDB

GrandChallenges

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

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

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

SAMPL6Host-GuestandpKaChallengesHost-Guest:124submissionsfrom6groups

pKas:95submissionsfrom10groups

DeepCavityCavitandHostsBruceGibb,TulaneU.

8guestmoleculeswithbothOAandTEMOAhostvariants

Cucurbit[8]urilHostLyleIsaacs,U.Maryland

10guestmolecules

SmallMoleculepKasJohnChodera,SKMCC

25compounds

NewSAMPLing Challenge

Testsefficiencyofconformationalsamplingmethods

BindingfreeenergyconvergencewithNumberofenergyevaluationsWallclocktimeTotalCPUtime

Host-guestsystemswithspecificsetups

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

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

FromOurGCParticipants…

Ithasmadememoreawareofthechallengesofsampling.I'vebeenworkingonbetterwaystoincludethisintoourprotocolsandmethods.

Iwouldpaymoreattentiontothereceptorconformationsandflexibility.

TheD3Rchallengesallowedustovalidateourdockingprotocol

DockingseemstobeimprovedbymachinelearningandIplantoincorporatesuchapproaches.

...itwilldefinitelychangetheIdodockingtoavoidorminimizefalsepositives.

Ithasmademepleasantlysurprisedwhenascoringfunctionactuallydeliversausefulresultandmakesmeveryskepticalofpeoplewhoblindlytrustthescorethattheyget.

SpecialIssuesinJCAMDthankstoTerryStouch,SeniorEditor-in-Chief

GC201514articles,2016

GC223articles,2017

SAMPL51/212articles,2016

SAMPL52/217articles,2017

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)

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

https://drugdesigndata.org

WebPortalforData,Challenges,CommunityActivities

MealsLightbreakfasts:todayandtomorrowLunchtodayandtomorrowDinnertoday,here;onyourowntomorrow

ShuttlesBothmornings7:30amand7:45amThursdayevening:8:05pmand8:15pmFriday:3:30pm,3:45pmand5:30pm

Posters:Onwalls,pleaseusebluetapeprovided

ContactPeopleMeganMurphyIrisVillanuevaAnyonefromtheD3Rteam

Practicalities

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