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Tim Clark

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A Non-Atom-Based Paradigm for Modeling, QSAR and QSPR ... J. Quant. Chem. 2002, 88,19. Computer-Chemie-Centrum. Universit t Erlangen-N rnberg ... – PowerPoint PPT presentation

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Title: Tim Clark


1
Tim Clark Computer-Chemie-Centrum Friedrich-Alexan
der-Universität Erlangen-Nürnberg
2
A Non-Atom-Based Paradigm for Modeling, QSAR and
QSPR
A Non-Atom-Based Paradigm for Modeling, QSAR and
QSPR
Tim Clark Computer-Chemie-Centrum Friedrich-Alexan
der-Universität Erlangen-Nürnberg
3
Descriptions of Molecules
4
Intermolecular Interactions are Everywhere
  • Molecule-molecule
  • Boiling point/vapor pressure
  • Solubility/free energies of solvation
  • Partition coefficients
  • Transport properties
  • Molecule-Receptor
  • Binding free energies
  • Scoring functions

5
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?

6
What is Missing from MEP-Based Descriptions?
  • 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 ?

7
Electron-Density-Based Descriptors
  • Electronic
  • Molecular Electrostatic Potential (MEP)
  • Polarizability
  • Donor/Acceptor Properties
  • Electron density ? Molecular surface
  • Local (? position dependent) properties
  • On a grid (ComFA, GRID etc.)
  • On a surface
  • Isodensity (DFT, Murray and Politzer)
  • SES (fast)
  • Statistics of the local property on a surface as
    descriptors
  • MEP (Murray and Politzer)

8
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.
9
Local Ionization Energy
MEP
IEL
10
Local Ionization Energy
11
Other Local Properties
  • Local Electron affinity
  • Local Hardness

12
Local Electron Affinity
13
Local Electron Affinity
14
Local Hardness
15
Polarizabilty
  • Variational method (Rinaldi and Rivail 1974)
  • Fast (no need for excited states)
  • Comparable to a population analysis

16
Variational Method (AM1)
Std. dev. 2.99 Ã…3 PM3 4.44 Ã…3 MNDO 1.94 Ã…3
17
Parametrized Method (AM1)Test Set
G. Schürer, P. Gedeck, M. Gottschalk, T. Clark,
Int. J.Quant. Chem., 1999, 75, 17-31.
Std. dev. 0.70 Ã…3 PM3 0.74 Ã…3 MNDO 0.78 Ã…3
18
Atomic and Orbital- Polarizabilities
Partitioning
Additivity
B. Martin, P. Gedeck, T. Clark, Int. J. Quant.
Chem., 2000, 77, 473.
19
The Additive Molecular Polarizability (AM1)
Std. dev. 0.59 PM3 0.65 MNDO 0.60
20
Atomic Polarizability Tensors p-Bromotoluene
21
Benzene dimer
-2.3 kcal mol-1 a MNDO -3.6 kcal mol-1
-1.2 kcal mol-1 a MNDO -1.0 kcal mol-1
a S. Tsuzuki, H.-P. Lüthi, J. Chem. Phys. 114,
2001, 3949.
22
C2H4CH4 and C2H6CH4
-0.54 kcal mol-1 a MNDO -0.46 kcal mol-1
-0.73 kcal mol-1 a MNDO -0.50 kcal mol-1
S. Tsuzuki, K. Honda, T. Uchimura, K. Tanabe, J.
Phys. Chem. A, 103, 1999, 8265
23
CO-Dimer
Ab initio MNDO
24
Dispersion Energies (kcal mol-1)
Ab initio
MNDO
25
Local Polarizability
Density due to a singly occupied atomic orbital j
Coulson population of atomic orbital j
Mean polarizability calculated for atomic orbital
j
26
Local Polarizability
27
Correlations Between Local Properties on
Molecular Surfaces
28
How do we Describe Physical Properties?
  • Old Descriptors
  • 66 descriptors that appear again and again in our
    earlier QSPR-models
  • Includes atom counts etc.
  • New Descriptors
  • 34 descriptors derived from the four local
    properties
  • No 2D-based descriptors

29
How do we Describe Physical Properties?
  • Calculate descriptors for the entire Maybridge
    database
  • Calculate the principal components (factors)
  • What is the dimensionality of physical property
    space?

30
PC-Eigenvalues (New)
31
Variance Explained
32
Variance Explained
Size, shape
33
Boiling Points (N 5453)Leave 10 out
Cross-validation old and new descriptors
18 Descriptors (18101 239 weights) MSE
0.02 MUE 17.3 RMSD 24.9
10 Descriptors (1091 128 weights) MSE
0.3 MUE 14.6 RMSD 21.0
34
Surface-integral models
  • P target property
  • Ai area of triangle i
  • ntri number of triangles

35
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.

36
Partial solvation
Ligand
Receptor
Water
37
Free energies of hydration
  • N 413
  • MUE 1.39 kcal mol-1
  • RMSD 1.82 kcal mol-1
  • r2 0.99
  • q2 0.95

38
Free energies of hydration
  • N 386
  • MUE 1.33 kcal mol-1
  • RMSD 1.71 kcal mol-1
  • r2 0.70

39
Enthalpies of hydration
  • N 95
  • MUE 1.74 kcal mol-1
  • RMSD 2.10 kcal mol-1
  • r2 0.99
  • q2 0.97

40
Local Solvation Free Energy (H2O)
Salmeterol ?Gsolv(H2O) -5.0 kcal mol-1
?Gsolv(n-Octanol) -24.9 kcal
mol-1 ?Gsolv(CHCl3) -25.6 kcal mol-1
41
Local Solvation Free Energy (H2O)
42
Free Energies of Solvation n-Octanol
  • N 179
  • MUE 0.82 kcal mol-1
  • RMSD 1.09 kcal mol-1
  • r2 0.79
  • q2 0.73c

43
Free Energies of Solvation CHCl3
  • N 87
  • MUE 0.60 kcal mol-1
  • RMSD 0.82 kcal mol-1
  • r2 0.82
  • q2 0.50

44
Local Solvation Free Energy
n-Octanol
Chloroform
45
logP as DGsolv Difference
  • N 105
  • MUE 2.2 kcal mol-1
  • r2 0.667
  • Slope 2.29

46
Sources of data
  • The available data are limited in
  • Number
  • Quality
  • Use alternative sources
  • e.g. for solvation free energies
  • Gas phase proton affinities (G3)
  • pKas (Equilibrium constants are always better
    than energies)

47
Outlook
  • Modelling using molecular surface properties is
    possible
  • We need much higher quality data for models of
    the necessary quality
  • the models are better than the data
  • Local solvation energies are the key to docking,
    pKa calculation, scoring functions,
    amphiphilicity etc.
  • biology happens in dirty water
  • We can now use definitive gas-phase ab initio
    data to derive accurate parameterization data.
  • Local solvation energies point to binding
    features

48
Acknowledgments
  • Erlangen
  • Bernd Ehresmann (local properties, SIMs)
  • Jr-Hung Lin (surfaces, multipole electrostatics)
  • Anselm Horn (multipole electrostatics)
  • Dr. Peter Gedeck (polarizability)
  • Dr. Gudrun Schürer (polarizability)
  • Bodo Martin (polarizabilities, dispersion)
  • Pfizer, Sandwich
  • Dr. Alexander Alex
  • Dr. Marcel de Groot
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