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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