Pharmacophore-based Molecular Docking

1. Pharmacophore-based Molecular Docking Bert E. Thomas, Diane Joseph-McCarthy, Juan C.Avarez

2. Introduction • Pharmacophore Concept • Conformational Expansion Approach • Docking Pre-Computed Conformers • DOCK framework • Conformational Ensembles Docking • Pharmacophore-Based Docking • Pros. & Cons. • Implementation Details • Latest Improvements

3. Pharmacophore • The term, traced to Emil Fischer (1894) and Paul Ehrlich (1909). • The term, introduced by Ehrlich, refers to the molecular framework that carries (phoros) the essential features responsible for a drug's biological activity (pharmacon) • Presently, the term has been expanded to refer to the 3D arrangement of functional groups that enable a compound to exert a particular biological effect • Many pharmacophores are defined simply in terms of three atoms and three distances

4. Pyridinyl imidazole P38 Inhibitors H-bond to Met109 NH Hydrophobic pocket

5. Virtual Screening Rapid computational mining of 3D molecular databases is central to generating new drug leads. The algorithms must be able to handle hundreds of thousands of molecules.

6. Conformational Expansion Approach • Conformational flexibility of the ligand molecule must be considered. • One of the approaches is to address conformational flexibility at database generation step, and not during the docking procedure. • Allows rapid screening.

7. Conformational Expansion Disadvantages • The total number of conformers must be kept manageable. • The torsional increment must give a good coverage of conformational space. • If the appropriate conformation for the ligand is not explicitly represented in the database, the “best” orientation will not be found, and the ligand may be missed entirely!

8. Conformational Expansion Methods Two approaches for docking of pre-computed conformers from a conformationaly extended database will be compared: • Conformational ensembles dockingLorber DM & Shoichet BK. Flexible ligand docking using conformational ensembles. • Pharmacophore-based docking Bert E. Thomas, Diane Joseph-McCarthy, Juan C.Avarez

9. The DOCK Suite

10. The DOCK Algorithm Two steps in rigid ligand mode: Orienting the putative ligand in the site Guided by matching distances, between pre-defined site points on the target to interatomic distances of the ligand.The RT matrix is used for the transform of the ligand. Scoring the resulting orientation Each orientation is scored for each quality fit. The process is repeated a user-defined number of orientations or maximum orientations

11. Define the target binding site points. • Match the distances. • Calculate the transformation matrix for the orientation. • Dock the molecule. • Score the fit.

12. Site Points Generationin DOCK • Program SPHGEN identifies the active site, and other sites of interest. • Each invagination is characterized by a set of overlapping spheres. • For receptors, a negative image of the surface invaginations is created; • For a ligand, the program creates a positive image of the entire molecule.

13. The Matching Can be directed by 2 additional features: • Chemical matching - labeling the site points such that only particular atom types are allowed to be matched to them. • Critical cluster - subsets of interest can be defined as critical clusters, so that at least one member of them will be part of any accepted ligand “match”. Increase in efficiency and speed due to elimination of potentially less promising orientations!

14. Conformational Ensembles Docking

15. Conformational Ensembles Docking Observations: • Generating an orientation of a ligand in a binding site may be separated from calculating a conformation of the ligand in that particular orientation. • Multiple conformations of a given ligand usually have some portion in common (internally rigid atoms such as ring systems), and therefore, contain redundancies.

16. Conformational Ensemble Docking • Conformational ensembles are generated by overlaying all conformations of a given molecule onto its largest rigid fragment. • Only atoms within this largest rigid fragment are used during the distance matching step. The RT matrix is defined. • Each of the conformers is oriented into the site and scored. The score measures steric and electrostatic complementarity. • One matching steps - all the conformers are docked and scored in the selected orientation.

17. Overview of the Ligand Ensemble Method

18. Advantages of Conformational Ensemble Docking Speed increase due to: • One matching step for all the conformers. • The largest rigid fragment usually has fewer atoms (less potential matches are examined).

19. Disadvantages of Conformational Ensemble Docking • Loss of information when the orientations are guided only by a subset of the atoms in molecule. Orientations may be missed because potential distance matches from non-rigid portions of the molecule are not considered. • The ensemble method will fail for ligands that lack internally rigid atoms. • The use of chemical matching and critical clusters is limited.

20. Pharmacophore-Based Docking

21. Pharmacophore-based Docking Basic idea: • Appropriate spatial disposition of a small number of functional groups in a molecule is sufficient for achieving a desired biological effect. • The ensemble formation will be guided by these functional groups.

22. 6.7 4.2-4.7 4.8 5.2 5.1-7.1 3-D Representation of a Protein Binding Site Distances between binding groups in Angstroms and the type of interaction is searchable

23. Pharmacophore Fingerprint • Pharmacophore fingerprint- a set of pharmacophore features and their relative position. • Typical pharmacophore features: • Hydrogen-bond donors and acceptors • Positive and negative ionizable • Hydrophobes and ring centroids • Implemented in DOCK 4.0.1 • Hydrogen-bond donors • Hydrogen-bond acceptors • Dual hydrogen-bond donor and acceptor • 5 or 6 membered ring centroids

24. Notes on Pharmacophore Fingerprint • Each conformer has pharmacophore fingerprint. • Different conformers of the same molecule can have identical pharmacophore fingerprints.

25. Pharmacophore DOCK

26. Advantages of Pharmacophore-based Docking • Rapid elimination of ligands containing functional groups which would interfere with binding. • Speed increase over docking of individual molecules. • More information pertaining to the entire molecule is retained (no rigid portions). • Chemical matching and critical clusters are encouraged.

27. Speed Comparison Between Ensemble and Pharmacophore-based Docking. Pharmacophore-based advantage: • Reduced number of ligand points considered during distance matching. Ensemble docking advantage: • The average number of conformers per molecule is higher than the average number of conformers per fingerprint. The one step matching speed reduction is slightly higher.

28. Speed Reduction Cont. • Ensemble docking:the average number of conformers per molecule is 297. • Pharmacophore-based:50-100 conformers per pharmacophore

29. Database Preparation • Generating molecular conformations • Systematic search method with SYBYL. • Overlaying molecular conformers onto pharmacophores • Extract 3D pharmacophore from the first molecule of a cluster • Use it to perform a rigid 3D UNITY search of the rest of that cluster to find matches • Save the pharmacophore querywith the associated molecules • Process until all molecules are associated with a pharmacophore

30. Site Points Generation • Chemically labeled site point are generated in an automated fashion using the script MCSS2SPTS . • The script runs a series of MCSS (Multiple Copy Simultaneous Searches) calculations. • MCSS – methodology for finding energetically favorable positions and orientations of small functional group in a binding site. • Uses CHARMM potential energy function to determine the preferred locations or potential energy minima simultaneously for thousands of copies of a given chemical group.

31. Improvements Underway ...

32. MCSS Extension to Include the Target Flexibility • Standard MCSS methodology was lately extended to include the flexibility of the target. • Reference:Collin M Stultz, Martin Karplus “MCSS functionality maps for flexible protein”.

33. Expansion of Conformational Ensembles Docking Su AI, Lorber DM, Weston GS, Baase WA, Matthew BW, Shoichet BK. Docking molecules by families to increase the diversity of hits in database screens: computational strategy and experimental evaluation. Proteins 42, 279-93 (2001).The problem: When one compound fits the site well, close analogs typically do the same. The Solution: The database is grouped into families based on the common rigid fragment. Only the best scoring molecule of a high-ranking family was allowed to hit the list.

34. Improvements toPharmacophore-based Docking • Optimization of database processing. • Additional scoring functions (currently only contact scoring). • Addition of solvation correction (electristatic and non-polar solvation free energy). Proteins 34:4-16 (1999), Shoichet et al. • Pharmacophore fingerprint enrichment.

35. Closing Remarks... • The Pharmacophore is a useful concept, which has assisted in the discovery of many biologically active compounds. • There is still much to develop • Pharmacophore identification • Pharmacophore-based docking methods

36. Happy New Year!

37. Limitations of Pharmacophore-based Searching • A limited subset of key interactions (typically 4-6) which must be extracted from the target site with dozens of potential interactions. • Complex queries are extremely slow. • The majority of the information contained in the target structure is not considered during the search. There is no scoring function beyond the binary (match/no match). Any steric or electronic constraints imposed by the target, but not defined by the target are ignored.

38. Validation Implemented in DOCK 4.0.1. • The test case • methotrexate (MTX) bound to dihydrofolate reductase (DHFR) • Database preparation • MTX translated away and conformationally expanded (500 pharmacophore 1 conformer each). • DOCK's chemical matching and contact scoring set to manual. • Max orientations = 5000.

39. Validation Results • Site points = all pharmacophore points. • Score range: -111 to –3. • RMSD between X-ray and docked conformations was 0.38A. • The best scoring conformer = X-ray complex • Site points = MCSS2SPTS script generated. • Score range: -121 to –60. • RMSD between X-ray and docked conformations was 0.78A. • The best scoring conformer = X-ray complex.

40. Search Methods • Database searches fall in to two major classes: • ligand-based (pharmacophore) • Target-based (molecular docking) • Pharmacophore searches consist of finding molecules that match a set of distances between specific types of atoms or functional groups which interact favorably with the target • Docking methods search for electronic and steric complementary between putative ligands and macromolecule target

41. Molecular-docking Challenges • Aim to predict the conformations and the orientations of a ligand bound to a macromolecule target. A 3D structure is required. • Ligand and target conformational flexibility must be taken into account. • For being used for virtual screening of large compound databases the algorithms must be really fast

42. MCSS Methodology • Determines energetically favorable positions for various functional group types in the binding site of a target macromolecule structure. • Uses CHARMM potential energy function to determine the preferred locations or potential energy minima simultaneously for thousands of copies of a given chemical group.

45. Improvements toPharmacophore-based Docking • Optimization of database processing • Additional scoring functions (currently only contact scoring). • Addition of solvation correction and energy minimization. • Shoichet et al. Have calculated electrostatic and non-polar solvation free energies for molecules in ACD database. Correcting for ligand solvation improved the ranking of known ligands and discriminated against molecules with inappropriate charge states and sizes.