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Proseminar der Bioinformatik

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Title: Proseminar der Bioinformatik


1
Proseminar der Bioinformatik
  • Alejandro Pironti
  • Betreuer Thomas Betz
  • Drug Transport Group
  • 31.05.2006

2
Polar Molecular Surface Properties Predict the
Intestinal Absorption of Drugs in Humans
  • By Katrin Palm, Patric Sternberg, Kristina
    Luthman and Per Artursson (1997)

3
Drug Bioavailability
  • Drug bioavailability rate and extent a
    therapeutically active drug reaches systemic
    circulation and is available at site of action

4
Absorbed fraction (FA)
  • Intravenously FA 100
  • Orally FA decreases due to incomplete
    absorption. Bioavailabilty may decrease due to
    presystemic metabolism

5
Orally administrable drugs
  • Preferred by the consumer for their convenience
  • Cost of drug development USD 800 million in
    2001

6
Processes Featuring Gastrointestinal Absorption
  • Passive cell diffusion
  • Cell-membrane and fat solubility of drugs
  • Active drug transport
  • Phagocytosis / Pinocytosis
  • Presystemic Metabolism
  • Disintegration and dissolution of tablets

7
Passive cell diffusion
  • Most drugs are absorbed from the intestine by
    passive cell diffusion
  • Most drugs are absorbed in the small intestine

8
Small intestine
  • Duodenum
  • Jejunum
  • Ileum

http//training.seer.cancer.gov/module_anatomy/uni
t10_3_dige_region4_intestine.html
9
Jejunum
  • Inner wall of jejunum covered with Villi

http//www.vivo.colostate.edu/hbooks/pathphys/dige
stion/smallgut/anatomy.html
10
Passive transport
http//www.vivo.colostate.edu/hbooks/pathphys/dige
stion/smallgut/transport.html
11
Lipinskis Rule of Five
  • Number of hydrogen-bond donors 5
  • Number of hydrogen-bond acceptors 10
  • Molecular weight 500
  • LogP 5

12
Ghoses Extension of Lipinskis Work
  • LogP ? -0.4, 5.6
  • Molar refractivity ? 40, 130
  • Molecular weight ? 160, 480
  • Total number of atoms ? 20,70

13
Hydrogen Bonds
  • The strength of hydrogen bonds depends on donor
    and acceptor
  • OH N 29 kJ/mol
  • OH O 20 kJ/mol
  • NH N 12 kJ/mol
  • NH O 8 kJ/mol

http//www.lbl.gov/MicroWorlds/Kevlar/KevlarClue4.
html
14
Partition Coefficient
Organic solvent 1-octanol
15
Molar Refractivity (MR)
  • Size and polarizability of a molecule

n refractive index, M molecular weight, ?
density
16
Summary of the article
  • Theoretical method for predicting drug absorption
  • Strong sigmoidal relationship between the
    absorbed fraction and dynamic polar molecular
    surface

17
Polar Molecular Surface Area
  • Area occupied by nitrogen and oxygen atoms, and
    hydrogen atoms attached to these heteroatoms
  • Depends on conformation

Sulfasalazine
18
Dynamic Polar Molecular Surface Area (PSAd)
  • Statistical average
  • Each low energy conformation is weighted by its
    probability of existence

19
PSAd Calculation
  • 1) Determination of 3D structures
  • 2) Surface calculation
  • 3) Statistical average of conformations

20
Determination of 3D Structures
  • Conformational analysis with aid of MM2
  • Molecular mechanics force fields

21
Determination of 3D Structures
  • Calculate probability of existence
  • Set of low energy conformers for each drug
    molecule with respective probabilities of
    existence

22
Surface Calculation
  • Free surface area results from fusion of
    van-der-Waals radii
  • Gauß-Bonnet theorem

23
Surface Area Calculation
  • Divide surface area into polar and non-polar
  • Set of low energy conformers for each drug
    molecule with respective probabilities of
    existence
  • Molecular volume, polar and non-polar surface
    area for each conformation of each drug compound

24
Statistical Average of Conformers
  • Dynamic total, polar and non-polar surface areas.
    Dynamic volume.
  • Take data generated by previous two steps and
    calculate statistical average
  • Each low energy conformation weighted by its
    probability of existence

25
Criteria for the Selection of Model Drugs
  • Drug absorption 0.3 .. 100
  • Lipophilicity CLogP -8.09 .. 4.50
  • Charge , -, o, -
  • Number of hydrogen bond donors and acceptors
  • Passive transport

26
Results
27
Results
  • The sigmodial equation

was fitted to the data
28
FA-PSAd Relationship
  • RMSE 9.2 r2 0.94

29
FA-PSAd Relationship
  • PSAd lt 63 Å2 ? FA gt 90
  • PSAd gt 139 Å2 ? FA lt 10

30
Other Relationships
  • PSAd-FA weaker relationship. RMSE 12.7, r2
    0.89
  • NPSAd-FA no correlation observed

31
Comparison with other theoretical methods
  • Ht RMSE 13.9, r2 0.87
  • Ha RMSE 14.1, r2 0.87
  • Hd RMSE 24.4, r2 0.60
  • CLogP RMSE 31.6, r2 0.34

32
Disregards
  • Differences in the strengths of hydrogen bonds
    are not taken into consideration
  • Other parameters are expected to influence
    absorption e.g. charge, molecular size
  • Compound selection not representative for all
    available and theoretically possible molecules

33
Disregards
  • Energy minimizations performed in vacuum.
    Disregard?
  • Gas phase, water, chloroform the simulation
    environment has little influence on PSAd

34
Advantages towards hydrogen- bonds counting
methods
  • PSAd is a better predictor than Ht or Ha since
    intramolecular hydrogen bond formation is taken
    into account

35
Further Research Motivated by this Study
  • David E. Clark
  • 74 compounds with absorption data from a study by
    Wessel et al.
  • 67 were classified correctly by PSAd gt 139 Å2
    criterion

36
Further Research Motivated by this Study
  • David E. Clark
  • 24 compounds with absorption data from a study by
    Kansy et al.
  • 21 compounds classified correctly
  • PSAd gt 139 Å2 criterion is rough!!!

37
Further Research Motivated by this Study
  • P. Ertl et al. methodology to calculate TPSA
    (topological polar surface area)
  • TPSA can be calculated 2-3 orders of magnitude
    faster than PSAd while correlating highly with
    the latter
  • The calculation of TPSA does not require the
    determination of the 3D structure of the
    compounds (input SMILES strings)

38
Bibliography
  • K. Palm, P. Stenberg, K. Luthman, and P.
    Artursson. Pharm. Res. 14.5 (1997).
  • K. Palm, K. Luthman, A.-L. Ungell, G. Strandlund,
    and P. Artursson. J. Pharm. Sci. 8532-39 (1996).
  • Wessel, M.D. et al. J. Chem. Inf. Comput. Sci.
    38726-735 (1998).
  • P. Ertl, B. Rohde, P. Selzer. J. Med. Chem.
    43.20 3714-3717 (2000)
  • D.E. Clark. J. Pharm. Sci. 8.8807-814 (1999)
  • http//www.chemie.uni-konstanz.de/www/fb/prghlp/mm
    ads_13.htmlRef94
  • http//www.iainm.demon.co.uk/spring99/davclark.pdf
  • http//en.wikipedia.org
  • http//www.radcliffe-oxford.com/books/samplechapte
    r/6916/Chap1.pdf
  • http//mathworld.wolfram.com/
  • Slides of the following lectures
  • Computer-Aided Drug Design by Andreas Kämper
    (2005) MPII Saarbrücken
  • Modelling Drug Transport with Bioinformatics
    Methods by Dirk Neumann (2005) University of
    Saarland
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