Multi-Residue Multi Ligand Docking

Tuesday September 18th 2012 DEVELOPMENT OF METHODS FOR DOCKING AND DESIGNINGSMALL MOLECULES WITHIN THE ROSETTA CODE FRAMEWORK A doctoral dissertation defense presented byGORDON HOWARD LEMMON

ROSETTADo NOT explain!1Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code22Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code33What is structural biology?Proteins

DNAStructural Biology is the study of structure and function of biological molecules such as DNA, RNA, and proteins4

The meilerlab focuses on proteins

There are 1000s of different proteins that all have a unique role to play these include proteins that form muscle, hair, and skin, to proteins that perform chemical reactions, forming and breaking chemical bonds.4How big are proteins?5

Water1.51 HHOAmprenavir~17 72 atomsHIV-1 Protease (PR)~54 3163 atoms1 Angstrom () = 1 ten millionth of a millimeterExplain here that most drugs that you pick up at the pharmacy work by binding to specific proteins.Proteins are very large. How is a molecule this large constructed?5Proteins consist of amino acid chains6

How are molecules as large as proteins created?6Protein sequence determines structure7

This protein has 198 amino acids it is actually two chains of 99 AA eachHow can the sequence determine something as complex as 3-D structure? It has to do with the way that amino acids interact with each other.7Protein structure determines functionHIV-1 protease cleaves poly-protein precursors to form functional proteins8

Peptide chainHIV-1 proteaseSequence determines structure, which determines function.These mature proteins plays a role in the activity of the HIV virus8Proteins are dynamic9

9Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code1010What is protein modeling?Prediction of protein structure from Sequence alone (de novo folding)

HIV-1 PRAmino Acid SequenceANPCCSNPCQNRGECMSTGFDQYKCDCTRTGFYGENCTTPEFLTRIKLLLKPTPNTVHYILTHFKGVWNIVNNIPFLRSLIMKYVLTSRSYLIDSPPTYNVHYGYKSWEAFSNLSYYTRALPPVADDCPTPMGVKGNKELPDSKEVLEKVLLRREFIPDPQGSNMMFAFF11

Determining sequence is easy, determining structure is hard. If we can predict structure we can understand function.

11What is protein modeling?Prediction of protein structure from 2.Sequence similarity (Comparative modeling)

HIV-1 PR SequencePQITLWKRPLVTIRIGGQLKEALLDTGADDTVLEEMNLPGRWKPKMIGGIGGFIKVRQYDQIPIEICGHKAIGTVLVGPTPTNVIGRNLLTQIGCTLNFHIV-2 PRHIV-1 PR12

+Using EXPERIMENTAL structures as comparison12What is ligand docking?Prediction of structure of protein/ligand interfacePrediction of ligand binding affinity13

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Structure means the position of the small molecule with respect to the ligand.Predicting binding affinity is more difficult.If we can predict ligand binding affinity, then we can make predictions about how tight a potential drug will bind to its target and how specific that binding will be.13Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code1414Rosetta protein modeling consists of sampling and scoring15

Point out that this is 15RosettaLigand docking consists of sampling and scoring16

RosettaLigand docking consists of sampling and scoring17

The lowest scoring model we predict will be closest to the true position that the small molecule will assume.17RosettaLigand docking consists of sampling and scoring18

RosettaLigand score functionKnowledge-based score terms19

Score termDefault weightattractive 0.8repulsive 0.4solvation 0.6dunbrack 0.4pair 0.8hbond_lr_bb 2.0hbond_bb_sc 2.0hbond_sc 2.0

Ive talked about H-bonding but there are many terms and each has a default weight.19Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code2020

21HIV-1 PR is flexible

Simmerling 200522HIV-1 PR becomes rigid upon PI binding23

HIV-1 protease mutations

WHO drug resistance mutations in red

24Mutation leads to conformational diversityMutations lead to drug resistance. WHO keeps track of these mutations24FDA approved protease inhibitors (PIs)

Tipranavir

Darunavir

Atazanavir

Lopinavir25Medicine: As HIV-1 PR mutates, a patient being treated with one of these PRs stops responding to treatment. So they are switched to a different PR.25Previous PR/PI G predictions failedCheng (2009)Score FunctionCorrelation N=112Number of non-hydrogen atoms0.172X-Score (HPScore)0.341SYBYL (ChemScore)0.276DS (PMF04)0.183DrugScore (PairSurf)0.225AutoDock0.38

Jenwitheesuk E Samudrala R. (2003)26Experimental vs Predicted HIV-1 PR GExperimental vs Predicted!26Defining G and G

27dG = Gibbs free energy.ddG = Binding affinity. Relative binding affinity w/respect to mutation.27176 experimental PR/PI Gs171 PR template structures

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176 PR/PI Gs sequence but not structure34 sequences10 distinct protease inhibitors171 PR structures represent PR flexibility28RosettaLigand PR/PI Gs predictions290.1 5 PI movementsSide chain and ligand rotamer samplingMinimization of PR side chain and PI torsion anglesMC AcceptMinimize Backbone torsion anglesEnergy filterRandom 5 Translation complete rotation of PI171 PR template structures176 Sequence/PI pairs10 Rosetta relaxed models per input (300,960 models)30,096 Rosetta inputs 1000 RosettaLigand docked models per relaxed model(300,960,000 docked models)Top 10% of models by total score for each Sequence/PI pairTop models by interface score for each Sequence/PI pairRosettaLigand DockingPR/PI Gs prediction workflowx6Reweighting score terms improves HIV-1 PR/PI G predictions Score termDefault weightOptimized weightsGGattractive 0.80.710.31repulsive 0.4-0.010.17solvation 0.60.680.15dunbrack 0.40.290.43pair 0.80.800.80hbond_lr_bb 2.00.850.11hbond_bb_sc 2.00.09-0.20hbond_sc 2.0-0.351.71CORRELATIONS (R)0.160.380.5130

Assuming constant unbound G improves PR/PI G predictionsStandard approachConstant unbound approach31Explain the hypothesis about effect of mutation on flexible vs. rigid structure.31Correlation plotsExperimental on X Predicted on Y Default weights: R=0.1632

Previous PR/PI G predictions failedScore FunctionCorrelation N=112Number of non-hydrogen atoms0.172X-Score::HPScore0.341SYBYL::ChemScore0.276DS::PMF040.183DrugScorePDB::PairSurf0.225AutoDock0.38RosettaLigand0.71

33Experimental vs Predicted HIV-1 PR GExperimental vs Predicted!33Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code3434

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Fragment the Ligand

Search database for fragmentsAssemble rotamer librariesSample from libraries during docking

Flexibility through fragments36Ligand fragment rotamers allow efficient flexibility

37Ligand rotamer docking

38How they were created.38Ligand docking with interface design

A54RL50YC9R DHTDHT: DihydrotestosteroneHisF: imidazole glycerol phosphate synthase

HisFDHTEnlarged prostate glandprostate cancerRosettaLigand prediction39Explain that the ligand moves as well. This is very important!39Fragment based screening can greatly expand sampling spaceCongreve, M. et al. Drug Discov.Today 2003,8, 876-877Traditional ScreeningFragment based screening40The idea is that instead of screening libraries of millions of larger compounds, one could screen libraries of several hundred fragments for several independent fragments, then link these together.40Common drug based FragmentsHartshorn M.J. Murray C.W.et.al. J. Med. Chem. 2005 48 403-413

4141RosettaLigandDesignLibrary of small molecule fragmentsPlace fragments in protein binding site-10-123-7-5Select low energy models for refinementDock ligand with flexible protein side-chains and backbone42RosettaLigandDesignLibrary of small molecule fragmentsPlace fragments in protein binding site-8-15-18-10-12Select low energy models for refinementDock ligand with flexible protein side-chains and backbone43Examples of fragments

Carbon

Oxygen

Nitrogen1 connection

2 connectionsCH2 connections

Ntrp connectionsCore fragment4444Random assembly of fragments

45Rosetta ligand design in action46

Low-res search for starting fragment Refine (dock) starting fragmentGrow small-molecule using fragment libraryRefine (dock) 2-fragment complexGrow small-molecule using fragment libraryRefine (dock) 3-fragment complexAdd Hydrogens to unsatisfied connection pointsProtein binding sites are complex

Dethiobiotin (DTB)Inorganic phosphateMg IonsADP47for example a protein binding pocket can have

47Multiple Ligand docking may capture induced fit effectsSerial Docking

Simultaneous Docking 48Induced-fit means that the protein changes its shape as it interacts with the small molecule.

Enzymes that catalyze chemical reactions, either creating or breaking bonds are good examples.48Rosetta multiple ligand docking

49Outline of presentationWhat is structural biology?Protein modeling and ligand dockingIntroduction to Rosetta softwareHIV-1 PR/PI binding affinity predictionRosetta software developmentLigand docking with waters using improved Rosetta ligand docking code5050

Binding of HIV-1 protease inhibitors involves H2O51Translation of water and PI

52Rotation of water and PI

53RMSD measures accuracy of docked models54

6 Angstrom () RMSD

2 Angstrom () RMSD

6 Angstrom () RMSD

2 Angstrom () RMSD Root mean square deviation

RMSD is an average distance over all pairs of atoms.54Protein-centric waters improve HIV-1 protease placement55

Talk about how important these results are for PI development55Ligand-centric waters improve CSAR inhibitor placementCommunity Structure-Activity Resource299 protein/ligand structures with interface waters56

RMSDs vs Rosetta scores57

RMSD on X axis and Rosetta Interface Score on Y axisWith water we are consistently producing low scoring models below 2 A RMSD57Waters improve docking in non-crowded interfaces58

Interface crowdedness correlates with helpfulness of water docking 59

ConclusionsBinding affinity predictions can be improved byOptimizing Rosetta score term weights Ignoring the unbound stateNew RosettaLigand code allowsMultiple ligand dockingFragment based rotamers for greater flexibilityFragment based design of ligandsDocking with waters helps in spacious binding cavities, hurts in crowded binding cavities

60Professional acknowledgementsMeiler LabJens MeilerKristian Kaufmann Sam DelucaSteven Combs

CommitteeDavid TabbRichard DAquilaBrian BachmannJarrod Smith

Molecular Biophysics Training Grant (NIH)

RosettaCommons

61Personal acknowledgments

Church Friends62Personal acknowledgements

63Personal acknowledgements

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