1. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local properties on molecular surfaces Tim Clark Computer-Chemie-Centrum Friedrich-Alexander-Universität Erlangen-Nürnberg

2. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Descriptions of Molecules

3. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Intermolecular Interactions Physical components are well known Coulomb Donor/acceptor Dispersion (and repulsion) We are accustomed to atom-atom approaches Force fields QSAR and QSPR Are there alternatives?

4. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg QM-Based Descriptors “Electronic“ Molecular Electrostatic Potential (MEP) Polarizability Donor/Acceptor Properties Multipole Moments Molecular surface Local properties at a surface Isodensity (DFT, Murray and Politzer) SES (fast) Statistics of the local property as descriptors MEP (Murray and Politzer)

5. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Surface Descriptors MEP at the surface has a physical basis. We should be able to describe intermolecular interactions using only surface properties. Scaffold-Hopping is more likely if we use only surface- based descriptors. Surface integral-models provide an interesting alternative to statistical QSPR...... BUTAtom-based simulation methods scale badly (because they treat atoms)...... BUT Surface-based descriptors are expensive to calculate... and difficult to interpret.

6. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg How Many Descriptors do we need for Physical Properties? (and what are they?) Choose 26 descriptors that appear again and again in our QSPR-models Calculate them for the entire Maybridge database Calculate the principal components (factors) What is the dimensionality of physical property space, what are the descriptors?

7. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg PC-Eigenvalues: Scree Plot

8. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Prinvipal Components PC #Main descriptorsInterpretation 1Polarizability, molecular weight, volume, surface area, globularity Size, shape 2Maximum MEP, mean positive and negative MEPs, total variance Complementary electrostatic surface descriptors 3Minimum MEP, mean negative MEP, balance parameter

9. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Physical property Space PC #Main descriptorsInterpretation 4Total MEP-derived charges on nitrogens, # H-bond donors Complementary Hydrogen-bonding descriptors 5Total MEP-derived charges on H and O, minimum MEP, # aromatic rings 6Dipole moment, dipolar densityDipolar polarity 7-9Total MEP charges on different types of atom Chemical diversity

10. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg What is Missing? Purely electrostatic interactions are described well Donor/Acceptor, Electronegativity and Hardness are described by the atom-specific descriptors Sums of potential-derived charges Counts of H-bond donors and acceptors Number of aromatic rings...... etc. Can we design suitable local properties ?

11. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Ionization Energy Sjoberg, P.; Murray, J. S.; Brinck, T.; Politzer, P. A., Can. J. Chem. 1990, 68, 1440; Murray, J. S.; Abu-Awwad, F.; Politzer, P., THEOCHEM 2000, 501-502, 241; Hussein, W.; Walker, C. G.; Peralta-Inga, Z.; Murray, J. S., Int. J. Quant. Chem. 2001, 82, 160; Politzer, P.; Murray, J. S.; Concha, M. C., Int. J. Quant. Chem. 2002, 88,19.

12. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Ionization Energy MEP IE L

13. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Ionization Energy

14. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Other Local Properties Local Electron affinity: Local Hardness:

15. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Electron Affinity

16. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Electron Affinity Fukui Function

17. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Hardness

18. Computer-Chemie-CentrumUniversität Erlangen-NürnbergPolarizabilty Variational method (Rinaldi and Rivail 1974) Fast (no need for excited states) Comparable to a population analysis

19. Variational Method (AM1) Std. dev. = 2.99 Å 3 PM3 : 4.44 Å 3 MNDO : 1.94 Å 3 Computer-Chemie-CentrumUniversität Erlangen-Nürnberg

20. Parametrized Method (AM1) Test Set Std. dev. = 0.70 Å 3 PM3 : 0.74 Å 3 MNDO : 0.78 Å 3 Computer-Chemie-CentrumUniversität Erlangen-Nürnberg G. Schürer, P. Gedeck, M. Gottschalk, T. Clark, Int. J.Quant. Chem., 1999, 75, 17-31.

21. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Atomic and “Orbital-“ Polarizabilities Additivity: Partitioning:

22. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg One-Center Terms

23. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Two-Center Terms B. Martin, P. Gedeck, T. Clark, Int. J. Quant. Chem., 2000, 77, 473.

24. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg The Additive Molecular Polarizability (AM1) Std. dev. = 0.59 PM3 : 0.65 MNDO : 0.60

25. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Atomic Polarizability Tensors: p-Bromotoluene

26. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Polarizability Density due to a singly occupied atomic orbital j Coulson population of atomic orbital j Mean polarizability calculated for atomic orbital j

27. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Local Polarizability

28. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Correlations Between Local Properties on Molecular Surfaces MEPIE L EA L LL LL MEP1 IE L 0.151 EA L -.120.181 LL 0.210.81-.441 LL 0.290.190.51-.141

29. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg PC-Eigenvalues (Maybridge)

30. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Principal Components Nr.Descriptors% Variance 1 Electrostatic descriptors, local donor/acceptor descriptors. 23.2 2 Local electron affinity descriptors, local polarizability descriptors 15.9 3 Molecular weight, volume, area, globularity 13.7 (23% before) 4 MEP-derived descriptors 8.2 5 Acceptor properties 7.5 6 Polarizability 4.8

31. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Boiling Points (N = 5453): Leave 10% out Cross-validation “old“ and “new“ descriptors 18 Descriptors (18:10:1 = 239 weights) MSE = 0.02 MUE = 17.3 RMSD = 24.9 10 Descriptors (10:9:1 = 128 weights) MSE = 0.3 MUE = 14.6 RMSD = 21.0

32. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Surface-integral models P = target property A i = area of triangle i ntri = number of triangles

33. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Surface-integral models MolFESD: Pixner, P.; Heiden, W.; Merx, H.; Möller, A.; Moeckel, G.; Brickmann, J. J. Chem. Inf. Comput. Sci. 1994, 34, 1309-1319. Jäger, T.; Schmidt, F.; Schilling, B.; Brickmann, J. J. Comput.-Aided Mol. Des. 2000, 14, 631-646 Jäger, R.; Kast, S. M.; Brickmann,. J. Chem. Inf. Comput. Sci. 2003, 43, 237-247. GB/PSA: Best, S. A.; Merz, K. M., Jr.; Reynolds, C. H.. J. Phys. Chem. B 1997, 101, 10479-10487.

34. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Free energies of hydration

35. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Free energies of hydration

36. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Free energies of solvation: n-octanol

37. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Free energies of solvation: chloroform

38. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Enthalpies of hydration

39. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Partial solvation Ligand Water Receptor

40. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Sources of data The available data are limited in Number Quality Use alternative sources e.g. for solvation free energies Gas phase proton affinites (G3) pK a s

41. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Physical-Property Mapping Maybridge used as the “chemistry“ dataset Use the top six principal components to train a 100  100 Kohonen net (unsupervised training) 2,105 compounds selected from the World Drug Index as real drugs used as the drug dataset

42. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Physical Property Map “chemistry“ Train Kohonen Net “Drugs“

43. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Physical Property Map: Drugs

44. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Physical Property Map: Hormones

45. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Model Applicabilty, Maps as Models? Aqueous solubility 550 (ompounds)

46. Computer-Chemie-CentrumUniversität Erlangen-Nürnberg Acknowledgments Dr. Bernd Beck Dr. Andrew Chalk Dr. Peter GedeckDr. Bill King Dr. Harry Lanig Dr. Torsten Schindler Dr. Cenk Selçuki Dr. Paul Winget Matthias Brüstle Bernd Ehresmann Matthias Hennemann Anselm Horn Bodo Martin Gudrun Schürer Kendall BylerJr-Hung Lin Dr. Tim F. Mitchell (Cambridge Combinatorial) Prof. Johnny Gasteiger Pfizer (Dr. Alexander Alex, Dr. Marcel de Groot) Bayer Pharma (Dr. Andreas Göller, Dr. Jörg Kenderich) 4SC Scientific (Dr. Thomas Herz) Alexander-von-Humboldt Foundation Hewlett-Packard