The Importance of Protein Flexibility in Protein-Ligand Docking Jennifer Metzger October 15th, 2008

2 Introduction Methods Results Discussion Jennifer Metzger Saarland University Talk Outline Introduction  Motivation  My Task Methods  Preparation of molecules  AutoGrid  AutoDock Results  Streptavidin + Biotin  MDM2 + Diz Discussion 1

3 Introduction Methods Results Discussion Jennifer Metzger Saarland University Motivation Why are so many people interested in protein-ligand docking? 2

4 Introduction Methods Results Discussion Jennifer Metzger Saarland University Interactions Protein-ligand interactions have important role in cellular processes: Signal transduction Immune response Energy generation DNA repair Apoptosis hormone-receptors2.jpg

5 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking Definition: Docking tries to find the energetically most feasible three dimensional arrangement of two molecules in close contact with each other. Shortly, answers two questions: What does complex look like? What energy necessary to disrupt complex? 4

6 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking => Plays essential role in: Study of macromolecular structure and interactions Rational drug design 5

7 Introduction Methods Results Discussion Jennifer Metzger Saarland University Induced Fit Model Modification to lock-key model Binding of ligand causes change in shape of protein and ligand Results in proper alignment 6 /Gellmanpg9-12/LockandKey.html

8 Introduction Methods Results Discussion Jennifer Metzger Saarland University My Task Show that accounting for protein flexibility is crucial in protein-ligand docking when the ligand binds to the protein surface instead of a deep binding pocket 7

9 Introduction Methods Results Discussion Jennifer Metzger Saarland University Streptavidin+Biotin Streptavidin: Homotetramer Isolated from bacterium Streptomyces avidinii Each monomer binds one molecule of vitamin biotin non-covalently Complex: Exceptionally high affinity (K a ~ M -1 ) One of strongest known non-covalent interaction Basis for many important biotechnological applications 8

10 Introduction Methods Results Discussion Jennifer Metzger Saarland University MDM2 MDM2 (Mouse double minute protein 2): 491 amino acids Important negative regulator of tumour suppressor p53 Represses transcriptional activity Carries nuclear export signal Accelerates destruction within proteasome Part of p53 auto-regulatory feedback loop Transcription activated by p53 Various mechanisms allow p53 to escape inhibition Increased levels in several human tumour types => Important drug target in anticancer therapy 9

11 Introduction Methods Results Discussion Jennifer Metzger Saarland University MDM2+Diz Diz: Benzodiazepinedione antagonist of HDM2-p53 interaction Increases transcription of p53 target genes Decrease proliferation of tumour cells expressing wild-type p53 10

12 Introduction Methods Results Discussion Jennifer Metzger Saarland University Method My Task: Show importance of protein flexibility in protein-ligand docking by using two test systems Two different approaches: 1.Using AutoDock4 2.Using molecular dynamics (MD) snapshots 11

13 Introduction Methods Results Discussion Jennifer Metzger Saarland University First Example Test system: Streptavidin + Biotin Three different experiments are performed: Docking to bound protein structure without flexibility (Re-docking) Docking to unbound protein structure with(out) flexibility (Apo-docking) 12

14 Introduction Methods Results Discussion Jennifer Metzger Saarland University Second Example Test system: MDM2 + Diz Four different experiments are performed: Re-docking to bound protein structure Apo-docking to unbound protein structure with and without flexibility Docking into molecular dynamics (MD) snapshots 13

15 Introduction Methods Results Discussion Jennifer Metzger Saarland University Scheme One experiment consists of: Preparation of Ligand and Protein Pre-computation of AutoGrid maps Perform docking with AutoDock Analyzing AutoDock results 14

16 Introduction Methods Results Discussion Jennifer Metzger Saarland University PDB Files Following crystal structures from PDB where used: 1swbapo Streptavidin 1mk5Streptavidin + Biotin 1z1mapo MDM2 1t4eMDM2 + Diz 15

17 Introduction Methods Results Discussion Jennifer Metzger Saarland University PDB files are not perfect Missing atoms Added water More than one molecule Chain breaks Alternate locations => Need to be corrected before usage 16

18 Introduction Methods Results Discussion Jennifer Metzger Saarland University Ligand Add all hydrogen atoms Add charges Check whether total charge per residue is integer Detect aromatic carbons Assign ‚AutoDock type‘ to atoms (Only AutoDock4) Choose rotatable bonds 17

19 Introduction Methods Results Discussion Jennifer Metzger Saarland University Protein Add all hydrogen atoms Add charges Check whether total charge per residue is integer Assign ‚AutoDock type‘ to atoms (Only AutoDock4) Choose flexible residues (Only AutoDock4) Assign solvation parameters 18

20 Introduction Methods Results Discussion Jennifer Metzger Saarland University Grid Maps AutoGrid computes grid maps needed by AutoDock One map for each atom type in ligand and moving part of protein + electrostatics map Interactions of atom probe with protein atoms are pre-computed on grids Trilinear interpolation used to compute score of candidate ligand conformation 19 autodocktools/UsingAutoDock4WithADT.ppt.Handouts3pp.v3.pdf

21 Introduction Methods Results Discussion Jennifer Metzger Saarland University Short Repetition A docking algorithm needs: Search method Scoring function 20 algorithms-for-global-optimization-in-fuzzy-models/

22 Introduction Methods Results Discussion Jennifer Metzger Saarland University Search Methods Four methods are available in AutoDock: Simulated Annealing Genetic Algorithm Local Search Lamarckian Genetic Algorithm 21

23 Introduction Methods Results Discussion Jennifer Metzger Saarland University Genetic Algorithm In our case: Individuals represent ligand conformations Genes correspond to state variables State variables describe translation, orientation, and torsion angles of ligand => Ligand’s state corresponds to genotype atomic coordinates correspond to phenotype 22

24 Introduction Methods Results Discussion Jennifer Metzger Saarland University Genetic Algorithm 1.Start with a random population 23

25 Introduction Methods Results Discussion Jennifer Metzger Saarland University Genetic Algorithm 1.Start with a random population 2.Perform genetic operations i.Mapping and Fitness evaluation ii.Selection iii.Crossover iv.Mutation v.Elitism 24

26 Introduction Methods Results Discussion Jennifer Metzger Saarland University Genetic Algorithm 1.Start with a random population 2.Perform genetic operations i.Mapping and Fitness evaluation ii.Selection iii.Crossover iv.Mutation v.Elitism 3.Until one termination criteria is met i.Maximum number of generations ii.Maximum number of evaluations 25

27 Introduction Methods Results Discussion Jennifer Metzger Saarland University Lamarckian Genetic Algorithm Genetic algorithm that mimic Lamarckian evolution Environmental adaptation of phenotype become heritable traits Additional local search 26 Morris, G. M., Goodsell, D.S. et al. Automated Docking Using a Lamarckian Genetic Algorithm and Empirical Binding Free Energy Function. J. Computational Chemistry (1998)

28 Introduction Methods Results Discussion Jennifer Metzger Saarland University Scoring Functions Empirical Free Energy Function of AutoDock3: 27

29 Introduction Methods Results Discussion Jennifer Metzger Saarland University Scoring Functions Semiempirical Free Energy Force Field of AutoDock4: 28 Huey, R., Morris, G. M., et al. Semiempirical Free Energy Force Field with Charge-Based Desolvation J. Computational Chemistry (2007)

30 Introduction Methods Results Discussion Jennifer Metzger Saarland University Scoring Functions Semiempirical Free Energy Force Field of AutoDock4: 29

31 Introduction Methods Results Discussion Jennifer Metzger Saarland University Streptavidin + Biotin Apo Streptavidin Biotin Bound Streptavidin 30

32 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock3 31 => Complex conformation could be obtained without protein flexibility Only small changes in rmsd Rmsd in all trials below 1

33 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock3 32 Score of re-docking conformations always better than apo-docking Only very small changes in score

34 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock4 33 Outlier in higher ranks Small changes in lower ranks

35 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock4 34 To many flexible residues result in worse rmsd

36 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock4 One flexible residue results in better energy than inflexible apo-docking More flexible residues lead to better energies and to larger changes => In this case flexibility does not help so much 35

37 Introduction Methods Results Discussion Jennifer Metzger Saarland University MDM2 + Diz Bound MDM2 Diz 36

38 Introduction Methods Results Discussion Jennifer Metzger Saarland University MDM2 + Diz Apo MDM2 Diz 37

39 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock3 Very small changes at re-docking Small changes at apo-docking Rmsd of apo-docking considerably worse than of re-docking 38

40 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock4 Similar rmsd as inflexible apo-docking for 3R and 6R A bit better for 1R 39

41 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock3 Best rmsd of snapshots mostly better than best rmsd of apo-docking Gets comparable or better results than with rigid protein => In this case flexibility improve results 40

42 Introduction Methods Results Discussion Jennifer Metzger Saarland University Docking with AutoDock3 Native MDM2-Diz complex 41 Best rmsd docking result of snapshot 25

43 Introduction Methods Results Discussion Jennifer Metzger Saarland University Discussion Protein flexibility is very helpful when binding pocket is not present in apo structure To use AutoDock4 protein flexibility, residues in pocket have to be known Docking to snapshots is better approach Molecular dynamics simulations help to find pocket what results in better rmsd Native complex not necessarily determined after MD snapshot approach => Docking into MD snapshots is a promising approach which builds starting point for further investigations 42

44 Introduction Methods Results Discussion Jennifer Metzger Saarland University Summary Most proteins do not match rigid lock-key model Inclusion of protein flexibility in protein-ligand docking can be crucial Docking into molecular dynamics snapshots detects binding pockets Promising approach for e.g. structure-based drug design 43

45 Jennifer Metzger Saarland University Streptavidin+Biotin –Freitag, S., Trong, I.L., et al. Structural studies of the streptavidin binding loop. Protein Sci. (1997), 6: MDM2 –Uhrinova, S., Uhrin, D., et al. Structure of free MDM2 N-terminal domain reveals conformational adjustments that accompany p53-binding. J Mol. Biol. (2005), 350: AutoDock+AutoGrid – –Morris, G. M., Goodsell, D.S. et al. Automated Docking Using a Lamarckian Genetic Algorithm and Empirical Binding Free Energy Function. J. Computational Chemistry (1998), 19: –Huey, R., Morris, G. M., et al. Semiempirical Free Energy Force Field with Charge-Based Desolvation J. Computational Chemistry (2007), 28: Approach –Eyrisch, S., Helms, V. Transient Pockets on Protein Surfaces Involved in Protein-Protein Interaction. J. Med. Chem. (2007), 50: References