Ligand Building with ARP/wARP

1. Ligand Building with ARP/wARP

2. Automated Model Building Given the native X-ray diffraction data and a phase-set To rapidly deliver a complete, accurate and error free model

3. Back to about 2000: a side project for a PhD student Building Ligands from Dummy Atoms / Seed Points

4. Nearest Neighbour Distance Distribution Given a coordinate error, the inter-atomic distances in a protein model change:

5. Building a Ligand into a Difference Map imagine: a ligand consisting of N atoms a density map containing M points the only thing to do is to correctly select N out of M ! Fit that into that !

6. A Simple Example: Select 3 out of 4 • The task is to find an equilateral triangle • Prior knowledge: edges should have a length 1.0 Å • Reliability: error on data (distances) is 0.01 Å a d c b

7. A Simple Example: Select 3 out of 4 • The task is to find an equilateral triangle • Prior knowledge: edges should have a length 1.0 Å • Reliability: error on data (distances) is 0.01 Å a d c b

8. A Simple Example: Select 3 out of 4 • The task is to find an equilateral triangle • Prior knowledge: edges should have a length 1.0 Å • Reliability: error on data (distances) is 0.01 Å a d c b

9. A Simple Example: Select 3 out of 4 • The task is to find an equilateral triangle • Prior knowledge: edges should have a length 1.0 Å • Reliability: error on data (distances) is 0.01 Å a d c b

10. M points in a density map W X Y Z Combinatorial Explosion A B C D N atoms in the ligand molecule Ligand Building as a Label Swapping Problem • Sources of possible prior information: • Chemical composition of a ligand • Bonding distances • Angle bonded distances • Chirality • VdW interactions

11. Topological Extension(a branch and bound approach) Label Swapping 22-atoms molecule of retinoic acid Initial map 349 grid points Complexity 1059 Sparse map 58 grid points Complexity 1037

12. Retinoic acid - topological extension Topology of the sparse map Topology of the ligand

13. Real Space Fit for Final Selection of the Model 22 atoms molecule of retinoic acid: among 100 “top” models: 21 are less than 0.5 Å r.m.s.d. from the final model the “best” model is 0.14 Å r.m.s.d. from the final model

14. MTZ file Protein without ligand Ligand Ligand Building Module in ARP/wARP 6.1 Take the largest object in the difference map Build the ligand there (label assignment) Real space refinement of the ligand

15. Ligand Building Module in ARP/wARP 6.1

16. Large-Scale Test • - PDB and MTZ from the EDS • - Ligand PDB from HICUP • Exclude DNA • Exclude ligands covalently bound to the chain • Exclude ligands with partial occupancies • (3821 structures) Working sample Ligand building Run with default parameters Performance Assessment Name-by-name Nearest neighbour Assume the PDB structure to be correct

17. Accuracy of Ligand Building Process Ligand scale (correct site incorrectly built ligand) Protein scale (incorrect site) Atomic scale (correctly built ligand into correct site)

18. Size of the Largest Ligand in the Working Sample 3821 structures 2981 structures with Ligand size  7

19. Dependence on Resolution of the Data

20. Dependence on Ligand DisorderB factors

21. Dependence on Ligand DisorderR.m.s.d (Ligand_Bfactors)

22. Dependence on Ligand Size

23. What is the Ligand Site / Largest Object ? Take the largest object in the difference map Build the ligand there (label assignment) Real space refinement of the ligand Typically it is the largest set (cluster) of connected map points where the density is above a threshold It is however mostly the case that at different thresholds there are different (and even non-overlapping) clusters

25. Density Clusters and a Fragmentation Tree At each density threshold count the number of clusters. A maximum is reached at typically ~1.5 sigma density level.

26. Fragmentation Tree: an Example 1ED5 (nitric oxide synthase), 1.8 Å resolution, Rfactor 21 % (with CNS) Ligands: 2 x HEM and NGR (N-omega-nitro-L-arginine)

27. Fragmentation Tree: an Example 1ED5 (nitric oxide synthase), 1.8 Å resolution, Rfactor 21 % (with CNS) Ligands: 2 x HEM and NGR (N-omega-nitro-L-arginine)

28. Scoring of Density Clusters Looking for HEM, finding HEM Looking for NGR, finding NGR Looking for NGR, finding HEM Looking for HEM, finding NGR

29. Selection of Correct Density Cluster

30. Other Lessons ? Take the largest object in the difference map Build the ligand there (label assignment) Real space refinement of the ligand

31. Ligand Building: ARP/wARP 6.1 and perspectives

32. ARP/wARP - the people Developers EMBL Hamburg: Guillaume Evrard, Johan Hattne, Gerrit Langer, Venkat Parthasarathy, Tilo Strutz, Victor Lamzin and many in-house friends NKI Amsterdam: Serge Cohen, Diederick De Vries, Marouane Jelloul, Krista Joosten, Tassos Perrakis Former members and collaborators Richard Morris, Peter Zwart, Francisco Fernandez, Olga Kirillova, Matheos Kakaris, Gleb Bourenkov, Garib Murshudov, Alexei Vagin, Andrey Lebedev, Peter Briggs, Eleanor Dodson, Keith Wilson, Zbyszek Dauter, Gerard Klejwegt