Models for ionic compounds Some high volume pharmaceuticals ...
Transcript of Models for ionic compounds Some high volume pharmaceuticals ...
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Models for ionic compounds
Content
What are ionic compounds?
Ionic compounds and living cells
The Cell Model
Results
The “Standard Model” for ionics
Ibuprofen
pain killer
NHOH O
Cl
Cl
Diclofenac
pain killer
O
O
O
OH
CH3
Aspirin
pain killer
NH
NH
O
O
O
CH3
CH3
Barbital
sleeping pill
S
NH
OO
ONH2
O
Cl
OH
Furosemide
diuretics
N
SNH
O
O
O
OH
CH3
CH3
H H
Penicillin
antibiotics
Some high volume pharmaceuticals
So what have these drugs in common?
This was actually a question to my dear students Ibuprofenz = -1, pKa = 4.41
NHOH O
Cl
Cl
Diclofenacz = -1, pKa = 4.18
O
O
O
OH
CH3
Aspirinz = -1, pKa = 3.48
NH
NH
O
O
O
CH3
CH3
Barbitalz = -1, pKa = 7.95
S
NH
OO
ONH2
O
Cl
OH
Furosemidez = +1 and -1
pKa = 9.79 and 3.04
N
SNH
O
O
O
OH
CH3
CH3
H H
Penicillinz = +1 pKa = 2.45
These pharmaceuticals are acids
The result was obtained using the ACD/I-Lab service
Metforminantidiabetic
Hydrochlorothiazidediuretics
Amitriptylineantipsychotic
Trimethoprimantibiotics
Morphinnarcoticum
More high volume pharmaceuticals
And what have these drugs in common?
NH
NH
N
NH
NH2
CH3
CH3
N
N
NH2
NH2O
O
O
CH3
CH3
CH3
NCH3
CH3
SSNH
O O
NH
O
O
NH2
Cl
N
H
OHOH O
CH3
Metforminz=+2, pKa1 13.86
Hydrochlorothiazidez=+2, pKa 9.57, 8.95
Amitriptylinez=+1, pKa 9.18
Trimethoprimz=+1, pKa 7.2
Morphinz = -1, pKa = 9.50 (acid)
z = +1, pKa = 8.26 (base)
These compounds are bases
NH
NH
N
NH
NH2
CH3
CH3
N
N
NH2
NH2O
O
O
CH3
CH3
CH3
NCH3
CH3
SSNH
O O
NH
O
O
NH2
Cl
N
H
OHOH O
CH3
2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 3 5 7 9 11 13pH
Fra
ctio
ns
neutral ion
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 3 5 7 9 11 13pH
Fra
ctio
ns
neutral ion
Ibuprofen
acid, pKa = 4.41
Trimethorpim
base, pKa = 7.2
Impact of pH on speciation of ionics
(Weak) acids are ionic at high pH and bases at low pH
)(101
1apKpHinf
ni ff 1and
SNH
N
N
N
NHO
O O
O
O
O
CH3
CH3
CH3
2,4-Dsystemic herbicide
pKa 2.98 (acid) metsulfuron-methylsystemic herbicide,
pKa 4.11 (acid)
P
O
NHO
OH
OHOH
glyphosateherbicide, multi-ionic, pKa
6.22 (of acid),
+ strong acids & weak base
Systemic herbicides
PO
O
OH OH
NH2CH3
glufosinateherbicide, multi-ionic,
pKa 3, 2.2 (acids), pKa 9.7 (base)
N
O
CH3
CH3 CH3
tridemorphsystemic fungizide,
pKa 7.90 (base)
N
NH
NH
O
O
CH3
carbendazimsystemic fungizidepKa 6.09 and 11.97
(base)
NNCl
CH2
O
Cl
imazalilsystemic fungizide,
pKa 6.75 (base)
NNH
N
CH3
cyprodinilsystemic fungizide,
pKa 3.09 (base)
Systemic fungicidesSystemic Pesticides
Herbicidal action is best when the chemical is distributed via phloem (to all growing parts of the plants, incl. roots).
The phloem has a high pH (ca. pH 8), and weak acids accumulate in that. That’s why systemic herbicides are typically weak acids.
Fungi often attack via xylem (a dead pipe). Fungicides are good if accumulating and distributing in xylem.
The xylem is acidic (ca. pH 5.5). That’s could be the reason why systemic fungicides are typically weak bases.
The REACH chemicals
149 000 chemicals pre-registered at the European Chemical Agency ECHA for REACH. Hereof:
Source: Based on a random sample of 431 chemicals analyzed by Antonio Franco et alii
Ionic compounds
and living cells
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dead living waste
The Electrical Field E
H+ e-
pH 3-9 pH 7.5pH 5-6
- 0.1 V
Separation of charges at the membranes
Comes a molecule
K+
e.g., a base
- 0.1 V K+
K+K+
K+K+
Positive charges accumulate in the symplast
1889 Example Potassium K+
Ci / Co = exp(- z E F / R T)
Z = +1 E = - 0.1 VF / (R T) = 39.6 (constant)
Ci / Co = exp(4) = 55
Chemical equilibrium = 1Electrical equilibrium = 55
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describes the movement of ions in electrical fields
Test: Did my audience understand me?
It will move into the
A) Vacuole (waste) B) Apoplast (dead)
C) Symplast (living) D) Lipids (fat)
DDT is a neutral, lipophilic chemical
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Fick’s 1st Law of Diffusion
Nernst-Planck Equation
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Fractions neutral and ionic
1 fn =
1 + 10(pH - pKa)
Henderson-Hasselbalch
0
0.25
0.5
0.75
1
1 3 5 7pH
Fra
ctio
n
neutral ionic
A weak acid in the cell (pKa = 3)
1 RH 1 RH 1 RH
100 RH
neutral
ionic 100 R- 10 000 R- 100 R-
Complex R-X R-X R-X
pH 5
Symplast pH 7 Vacuole
pH 5apoplast
Summary of Processes
Ions are attracted by electrical fields
Lipophilic compounds sorb to lipids
Weak electrolytes are trapped
“Complexes” behave like neutrals
Transport inside vascular plants
Cuticle
Phloem symplast
Xylem apoplast
Cuticlewaxy layer
pH 5.5
pH 8Daniel Kleier developed a dynamic model to predict phloem transport of chemicals
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Kleier’s model considers the flow in xylem (apoplast, pH 5.5) and phloem (symplast pH 8).
Phloem transport is due to the “ion trap”
Kleier’s model explains phloem mobility
1988 to 1996 - Kleier didn’t consider electricity
Satchivi’s model (2000) calculates uptake and movement of weak electrolytes (pesticides) after spray application
Peticide Biochemistry and Physiology 68, 67-84 (2000)
Satchivi’smodel is for the complete plant.
It is therefore quite complex and needs a lot of parameters
That makes it hard to apply
StartThe exchange terms consider the
ion trap, but no electrics
The Basics of Satchivi’s Model
J = Pn (Co - Ci * fn) + Pd (Co - Ci * fd)
f = fraction, n = neutral, d = dissociated
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Summary
The modern models used in pesticide design (Kleier, Satchivi) do not use the Nernst-Planck equation
The dominant effect considered is the ion trap for weak acids
2000
A very first version of our new approach – dynamic model for root uptake with Nernst-Planck equation behind.
The Cell Model
The typical structure of a cell
(sketch)
cytosol
biomembrane
lipids
nucleus
lysosomes
(cell wall)
mitochondrium
The typical structure of a cell
(seen from the perspective of a neutral compound)
Lipids
The neutral compound “sees” aqueous phase and lipid phases
Water
BCF regressions for neutral compounds
Process:
The neutral chemical partitions into the aqueous and lipid phase (described by Kow).
Example: Briggs RCF
Basic equation:
BCF = W + L x Kow
equivalent to RCF = 0.82 + 0.03 KOW0.77
52.1log77.0)82.0log( KowRCF
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The typical structure of an animal cell
(seen from the perspective of an ionic compound)
cytosol
membrane
lipids
nucleus
lysosomes
(cell wall)
pH 8
pH 7 to 7.4
pH 5
pH 6.5
+20
-70 mV
-160 mV
mitochondrium
Processes for ionic compounds
Ionic compounds undergo extra effects:
► Ionizable compounds occur in (at least) two species,namely the neutral and the ionic molecule.
► Concentration ratios of the species change with pH.
► Ions are attracted or repelled by electrical fields.
► Ions are much more polar than the neutral molecules.
►Membrane permeabilities of ions are small.
BCF regressions for ionic compounds
Application of existing regressions (for neutrals) with apparent log Kow (= log D) as predictor
For ionics: log D instead of log Kow in BCF regressions
iOWinOWn KfKfD ,,
fn: fraction neutral at given pH
fi: fraction ionic at given pH
52.1log77.0)82.0log( DRCF
Measured BCF in roots and water plants at variable pH
At pH ≠ 7 accumulation also for low log D due to ion trap
-1
0
1
2
3
4
-4 -2 0 2 4 6
log D
log B
CF
plants acids plants bases plants
The ion trap
The chemical diffuses into the cell as neutral compound, dissociates and … gets trapped !
For weak acids: at low external pHFor weak bases: at high external pH
The ion trap
measured data from Briggs, Rigitano, De Carvalho et al.Cell model calibrated with E 0
Example: Accumulation of 2,4-D (pKa ~ 3) in water plants
-1.0
0.0
1.0
2.0
3 4 5 6 7 8 9
external pH
log
BC
F
cell model
regression
water weed 2,4-D
ricinus 3,5-D
barley 2,4-D
barley 3,5-D
cell model
regression
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BCFeNePfPf
eNPfPf
J
J
C
CNN
didnin
Ndodnon
out
in
o
i
)1/(
)1/(
,,
,,
)(1 ,,
NidodNdd eaa
e
NPJ
)( ,, inonnn aaPJ
Equations for ionisable compounds
neutral molecules 1st Fick’s Law
Ions Nernst-Planck-equation
J = flux, P = Permeability, a = activity, N = z E F / RT
Equilibrium: Flux in = flux out
f = a / Ct = dissolved fractionn = neutral, d = dissociated (ionic)
Activity as state variable
Driving force for exchange is the activity gradient.
The ratio between activity and total (measurable) concentration is
where W is water content, is activity coefficient (n neutral, d ionic), K is partition coefficient (L x Kow)
Finding
Feasible
ZfC FaC
Z = fugacity capacity
MAMI 2009Mackay 1979
F = activity capacity
Fugacity ActivityDynamic solution
Change of conc. in cytosol is flux in – flux out – flux to organelle + flux from organelle
Analytical solution (2 x 2 matrix)
Change of conc. in organelle is flux from cyt – flux to cyt
Cell model in excelData Cell Model
Table. Parameters of typical animal and plant cells.
mol L-10.30.30.3IIonic strength
V+0.01-0.10-0.07 EMembrane potential
L L-10.030.030.06LLipid content
L L-10.950.950.95WWater content
-5.577pHpH cell sap
UnitPlant
vacuole(90%)
Plantcytosol(10%)
Fishcytosol(100%)
SymbolParameter
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Test predicted BCF versus measured
Acids Bases
The cell model can – to some extend – predict the ion trap
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
-4 -2 0 2 4
log D
log
BC
F
Cell RCF measured
-1.0
0.0
1.0
2.0
3.0
-4 -2 0 2 4
log D
log
BC
F
Cell RCF measured
Summary of Findings
● Many pesticides and most pharmaceuticals are ionizablecompounds
● Acids ionize at high pH, bases at low pH
● Ions are more polar and have a lower BCF than neutrals
● Lipophilic sorption is a dominant process for ionic compounds (as for neutral compounds) and is well predicted with log D
● Weak acids have the highest BCF at low pH (< 7)
● Weak bases have the highest BCF at high pH (> 7)
● The ion trap (for acids: at low pH, for bases: at high pH) may lead to unexpected accumulation
Results of the cell model - Acids
Acids external pH 5
- ion trap -
Acids external pH 7
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
Chemical Equilibrium to water – log BCF plants
Results of the cell model - Bases
Bases external pH 5
- opposite ion trap -
Bases external pH 7
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
Chemical Equilibrium to water – log BCF plants
Results of the cell model - Bases
Bases external pH 9
- ion trap -
Bases external pH 7
Chemical Equilibrium to water – log BCF plants
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
2 3 4 5 6 7 8 9 10
0
2
4-1.0
0.0
1.0
2.0
3.0
log BCF
pKa
log Kow
0
1
2
3
4
Adsorption in soil
Koc of ionic compounds
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Solid-water sorption of ionics
B BH+
B BH+
pHBULK
pHOPT
• lipophilic + electricalinteractions
• cations attracted, anions repulsed from colloids
• pH, pKa, KOW,n
Regression equations for the Koc of ionics
Franco & Trapp 2008, Env Tox Chem
PCPpKa 4.74
TCP pKa 6.1 – 6.9
TeCP pKa 5.4 nitrophenol pKa 7.2
“Standard Model” for ionic compounds
“Standard Model” for ionics
RRRRWR
SWSR
R CkCKM
QCK
M
Q
dt
dC
LLLLLA
LLA
L
LR
RWL
L CkCMK
mLgAC
M
gAC
KM
Q
dt
dC
31000
FFFFAF
FAir
F
FR
RWF
FF CkCKM
gAC
M
gAC
KM
Q
dt
dC
1000
from Cell Model into Standard Model
Modifications for Ionics
Standard Model Cell Model
Fluxes and Processes as before – partition coefficients from cell model
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Some Results
Predicted uptake of acids from soil into plants
Uptake of acids from soil into plants depends on soil pH.
Strong acids are expected to move into leaves (via xylem), weak acids more into fruits (via phloem, at low soil pH).
Predicted uptake of bases from soil into plants
Uptake of bases from soil into plants depends on soil pH.
Moderate to weak bases are expected to move into leaves (via xylem), but only at high soil pH.
Questions?
Ende