©2009, COSMOlogic GmbH & Co KGCOSMO-RS Symposium 2009 Properties predicted by COSMO-RS-based QSAR...

©2009, COSMOlogic GmbH & Co KGCOSMO-RS Symposium 2009

Properties predicted by Properties predicted by

COSMO-RS-based QSAR COSMO-RS-based QSAR

Dr. Karin Wichmann

COSMOlogic GmbH & Co. KG Burscheider Str. 515D-51381 LeverkusenGermany

Phone: +49-2171-731-683Fax: +49-2171-731-689Email: [email protected]: http://www.cosmologic.de


Property Prediction with the Property Prediction with the -potential-potential

COSMOtherm allows for the prediction of the entire fluid phase equilibrium

thermodynamics of almost arbitrary compounds, e.g:

- Activity coefficients

- Solubility

- Partition coefficients between well characterized liquid phases

The chemical potential and thermodynamic properties of liquids can easily be computed

using the COSMO-RS -potential S():

e.g. activity coefficients XS:

XScombS

XXS dp ,)()(

kTXX

XS

XS /)(exp


Treatment of complex or chemically less well-defined matricesTreatment of complex or chemically less well-defined matrices

Some physiological and thermodynamic equilibria involve phases or matrices which are

- Chemically not well defined or of unknown composition

- Disordered

- Not really liquid / amorphous

E.g. phases like

- Biological tissues, blood, brain, the intestinal resorption system

- Soap, polymers, cotton

- Solid adsorbents like activated carbon

→ -potential cannot be calculated directly by COSMO-RS



Chemically not well defined phases can be treated indirectly with the -moments:

The -potential can be approximated very accurately by a set of functions M iX:

-moments MiX are defined with:

And Hydrogen Bonding moments Mi,HBX

M0X: molecular area

M1X: negative total charge of compound X

M2X: correlated with the screening energy for X

M3X: “skewness” of the profile

M-1/-2X or Mdon/acc

X: hydrogen bond capacity

)dσ(σf(σpM ii

XXi )

0 for )( if ii

m

i

Xi

iS

XS Mcμ

2

~

HB

HB

HBdonacc σσ

σσ

σσ(σf(σf

if

if 0)) /1/2



With the -moments,

- each phase / matrix can be characterized by a set of -coefficients ciS.

- Differences between two phases can be described by the same kind of expansion,

with coefficients ciS,S‘ being the difference of the coefficients of the two phases.

- Partition coefficients between two phases are generally expressed by a linear

combination of the compounds -moments in the form:

m

i

Xi

iSSSS

XSS MccK

2,,,

~~log


QSPR applicationsQSPR applications

-moments can be used as descriptors for linear QSAR/QSPR applications.

Using COSMOtherm -moment descriptors it is possible to predict:

- Partition behaviour between almost arbitrary phases, such as

- CaCo2 cell permeability

- logKBB blood-brain barrier partition

- logKOC soil-water partitioning (environmental fate)

- logKIA intestinal absorption

- . . . and many more

- Solubility of drugs in arbitrary solvents

- Chemical potentials of crystal surfaces in solution

→ morphology of drugs


QSPR applicationsQSPR applications

- Only five -moments MiX are necessary to get a general QSPR description of solvents

or biological matrices:

- This is in correspondence with the general solvation theory of Abraham, which claims

that solvent space is five-dimensional.

- Intercorrelation of the COSMOtherm -moments and the Abraham set of solvent

descriptors is possible*

XXXXXXS McMcMcMcMcP don,35acc,34332201

*Andreas M. Zissimos, Michael H. Abraham, Andreas Klamt, Frank Eckert, John Wood, J. Chem. Inf. Comput. Sci. 42 (2002) 1320


Blood-Brain PartitioningBlood-Brain Partitioning

-2

-1.5

-1

-0.5

0

0.5

1

1.5

-2 -1.5 -1 -0.5 0 0.5 1 1.5

regression

exp

. lo

gB

B

logBB = 0.0043 M0 - 0.017 M2 - 0.0031 M3 + 0.24

N = 103rms = 0.41R2 = 0.691

Exp. Data: Rose, K.; Hall, L. H.; Hall, L. M.; Kier, L. B. Modeling Blood-Brain Barrier Partitioning Using Topological Structure Descriptors, 2003. Elsevier MDL Web Site. http://www.mdl.com/solutions/white_papers/MDLQSARreprint.jsp (accessed Feb 13, 2004).


Human Serum Albumin BindingHuman Serum Albumin Binding

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

regression

ex

p. l

og

BB

logKHSA = 0.0084 M0 - 0.017 M2 - 0.0014 M3 + 0.17 M3,acc + 0.24

N = 94rms = 0.33R2 = 0.671

Exp. Data: Kier, L. B.; Hall, L. H.; Hall, L. M. QSAR Modeling of Drug Binding to Protein. -Lactam Serum Binding and Albumin Binding Affinity, 2002. Elsevier MDL Web Site. http://www.mdl.com/solutions/white_papers/ML233QM3_white_paper.jsp (accessed Oct 7, 2004).


Intestinal AbsorptionIntestinal Absorption

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

PIA calculated by COSMO-KIA

PIA

ex

p.

training set: n=38, rms=12.5%

high quality test set: n=107,rms=12.8%

questionable test set: n=24,rms=22%

logKHSA = 0.0040 M0 - 0.0053 M2 - 0.0024 M3 - 0.11 M3,acc - 0.11 M3,don + 1.37


Soil SorptionSoil Sorption

-1

0

1

2

3

4

5

6

7

-1 0 1 2 3 4 5 6 7

regression

ex

p. l

og

KO

C

logKOC = 0.016 M0 - 0.017 M2 - 0.046 M3 + 0.23 M3,acc – 0.33 M3,don + 0.41

N = 386rms = 0.61R2 = 0.72


Adsorption to Activated CarbonAdsorption to Activated Carbon

y = 0.9277x + 0.1379

R2 = 0.9281

-10

-5

0

5

10

15

-10 -5 0 5 10 15

ln[He(exp.)]

ln[H

e(t

he

or.

)]

Fluid Phase (23 Adsorptives)

Gasphase (15 Adsorptives)

Linear (Fluid Phase (23Adsorptives))

[Mehler, Peukert (TU München), Klamt; AICHE Journal. 48, 1093-1099 (2002)]


Model of Cytochrome P450 2D6 and Cytochrome P450 3A4Model of Cytochrome P450 2D6 and Cytochrome P450 3A4

R2 = 0.60rms = 0.66

n = 45

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

-1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4

calc

log

(IC5

0)

R2 = 0.75rms = 0.47

n = 33

0

0.5

1

1.5

2

2.5

3

3.5

0 0.5 1 1.5 2 2.5 3 3.5

calc

log

(IC5

0)

Dataset from J. Med. Chem 2004, 47, 5340.

Modelling inhibition of Cytochrome P450 2D6 using -moment descriptors for a diverse set of 33 compounds from the NCI database.

Log(IC50) = 2.96(0.56) – 0.0097(0.0018)*Area + 0.010(0.0067)*sig2 + 0.050(0.012)*sig3 - 0.42(0.089)*HBacc3

+ 0.39(0.14)*HBdon3

Modelling inhibition of Cytochrome P450 3A4 using -moment descriptors for 45 structurally diverse drugs. (2 outliers deleted.)

Log(IC50) = 4.46(0.50) – 0.0093(0.0017)*Area - 0.0068(0.0078)*sig2 + 0.025(0.010)*sig3 + 0.033(0.128)*HBacc3

+ 0.24(0.14)*HBdon3

Dataset from Pharm. Res. 2003, 20, 1401.

©2009, COSMOlogic GmbH & Co KGCOSMO-RS Symposium 2009 Properties predicted by COSMO-RS-based QSAR...

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