Challenges in Agrochemicals Design - Semantic Scholar

1

Challenges inChallenges inAgrochemicals DesignAgrochemicals Design

K-J Schleifer

Computational Chemistry & BiologyBASF SE, Ludwigshafen

2

BASFBASF –– TheThe Chemical CompanyChemical Company

104.779 employees worldwide, 33.000 at Ludwigshafen and > 8.000 in R&D

2

3

BASFBASF´́ss PortfolioPortfolio

Oil & GasFunctionalSolutions

PerformanceProducts

AgriculturalSolutions

ConstructionChemicals

Chemicals

Inorganics

Petro-chemicals

Inter-mediates

PaperChemicals

Coatings

Dispersions& Pigments

Plastics

PerformancePolymers

Poly-urethanes

CropProtection

Oil & Gas

CareChemicals

Catalysts

PerformanceChemicals

4

Insecticidesagainst harmful

insect pests

Herbicidesagainst weeds

Fungicidesagainst harmful

diseases

CropCrop protectionprotection

Otherse.g. growthregulators

Agricultural SolutionsAgricultural Solutions

3

5

DrugsDrugs && AgrochemicalsAgrochemicals

Efficacy

&

Bioavailability

6

Mode of Action ofMode of Action of AgrochemicalsAgrochemicals

HerbicidesLipid Synthesis- Acetyl CoA carboxylase

Branched Chain aa Synthase- Acetolactate synthase

Photosynthesis PS I / II

Protoporphyrinogen Oxidase

Pigment Synthesis- PDS- HPPD

EPSP Synthase (Glyphosate)

Microtubule Assembly

Cell Division

Cell Wall (cellulose) Synthesis

Auxin Transport

InsecticidesNervous SystemAcetylcholinesterase

Ion ChannelsGABA-gated Cl-channelsSodium channel modulatorsnAChR agonistsnAChR allosteric modulatorsnAChR channel blockerVGSC blockerRyanodine receptor modulatorsChloride channel activators

Respiration ChainMitochondrial cplx. I-V inhibitors

Growth RegulatorsChitin biosynthesis

Nuclear ReceptorEcdysone receptor agonists

FungicidesNucleic Acid Synthesis- RNA polymerase I- Adenosin-deaminase

Mitosis and Cell Devision- -tubulin assembly

Respiration- Succinate-dehydrogenase- Cytochrome bc1 (Qo & Qi)

AA and Protein Synthesis

Signal Transduction-MAP/Histidine kinase

Lipid and Membrane Synthesis- Methyltransferase

Sterol Biosynthesis- C14 demethylase- 14 reductase

4

7

BioavailabilityBioavailability of Drugsof DrugsAbsorptionAbsorption

8

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsAbsorptionAbsorption –– PlantsPlants

Cuticula

Stomata

Roots

5

9

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsAbsorptionAbsorption –– Plants, Fungi and InsectsPlants, Fungi and Insects

Cell wallMembranes Oral

ChitinousExoskeleton

10

BioavailabilityBioavailability of Drugsof DrugsDistributionDistribution

Blood

6

11

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsDistribution/TranslocationDistribution/Translocation -- PlantsPlants

Xylem

Phloem

12

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsDistributionDistribution -- InsectsInsects

dorsal artery

7

13

BioavailabilityBioavailability of Drugsof DrugsMetabolismMetabolism

Blood

Skin

Phase I ReactionOxidation, Reduction, Hydrolysis

cytochrome P450 oxidases(Cyp P450)

Phase II ReactionConjugation of water-soluble groups

UDP-glucuronosyltransferasesglutathione S-transferases

Humans 57 genesDrosophila ~ 80 genesArabidopsis > 300 genes

14

BioavailabilityBioavailability of Drugsof DrugsExcretionExcretion

Urine & Feces

8

15

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsExcretionExcretion -- PlantsPlants

inclusion of waste products

16

ToxicologyToxicology ofof DrugsDrugs

9

17

ToxicologyToxicology of an Insectizideof an Insectizide

18

Regulatory relevant issuesRegulatory relevant issues ofof AgchemsAgchems

Enviromental Fate

Soil dissipation/accumulationBound residuesGround waterSurface waterAirRelevant metabolites

Residues

Residues levelToxic metabolites

Toxicology

CMR propertiesEndocrine disruptorsImmuno toxicityAcute/Chronic toxicityRisk for consumer, worker, residentSelected formulants

Biology

EfficacyCrop toleranceResistance riskImpact on food qualityImpact on succeeding & adjacent crops

Ecotoxicology

AquaticHoney bee, non-target arthropodsNon-target plantsSoil organismsWildlife (birds, mammals)Buffer zonesRecovery of biocoenoses

10

19

BioavailabilityBioavailability ofof AgrochemicalsAgrochemicalsSpecificity of HerbicidesSpecificity of Herbicides

Crop Weed

ADMET

oo+o--

ADMET

oo--o+

20

DevelopmentCandidate

1

Dossier

0 10

Lead Product

8

ProductDevelopment

Years2 3 4 5 6 7 9

LeadIdentification Registration

Research Development

LeadOptimization

R&D cost per product around $ 250 million (industry average)

R&D ProcessR&D Process

Molecular ModellingSupport

11

21

Compounds

Optimization

Target-basedScreening

Organism-basedScreening

New Lead Identification in Crop ProtectionNew Lead Identification in Crop Protection

Leads

DevelopmentCandidates

Output is complementary!

22

Requirements of a Compound LibraryRequirements of a Compound Library

Compound Library TargetOrganism Compound Library

intrinsic activity at unknown target(s)

& bioavailability (ADME)

intrinsic activity at isolated target

12

23Lemna (Duckweed)

OrganismOrganism--basedbased LeadLead IdentificationIdentification

PreScreen

Hit-validation

PreScreen

Leadfinder

Primary Screening

Greenhouse

Analog Syntheses

GreenhousePhysico-Chemistry

Lead-identification

HIT

TO

LE

AD

HIT

ID

24

Hit-validation

PreScreen

Leadfinder

Primary Screening

Greenhouse

Analog Syntheses


Lead-identification

HIT

TO

LE

AD

HIT

ID


Leadfinder

13

25

control a.i.

(Bleacher)

Hit-validation

PreScreen

Leadfinder

Primary ScreeningGreenhouse

Analog Syntheses


Lead-identification

HIT

TO

LE

AD

HIT

ID


Greenhouse

26

1) Relevant chemical space

remove reactive & toxic fragments

choose only agro-like substances

2) Select a diverse subset for screening

3) Look for similar compounds closeto screening hits hit validation

Compound Selection for Random ScreeningCompound Selection for Random Screening

14

27

1) remove reactive & toxic fragments

Descriptors for FilteringDescriptors for Filtering

substructures defined by chemist‘s knowledge

3) Select a diverse subset for screening

4) Look for similar compounds

MACCS keys and topological descriptors

2) choose only agro-like substances

1-D descriptors and pharmacophore points

28

Molecular Weight

• 200 to 500 range (86%); < 200 (11%); > 500 (3%)

Melting Point (°C)

• 50 - 200 (60%); < 50 (30%); > 200 (10%)

pKa (acid)

• ~10% pKa < 5

pKa (base)

• ~1% pKa > 5

PhysChemPhysChem Properties of AgrochemicalsProperties of Agrochemicals

Pesticide Manual 11th Ed. 1997 (~ 700 cpds)

15

29

LongLong--Distance TransportDistance Transport

Translocation in Xylem and Phloem

HAHA H+ + A-H+ + A-

pH 5 - 6pH 5 - 6

pH ~8pH ~8

“Intermediate Permeability”and “Weak Acid Theories”

“Intermediate Permeability”and “Weak Acid Theories”

Phloem Vessel

Xylem Vessel

modified, from D.A. Kleier et al. (1998)

30

Bioavailability Rules: AgroBioavailability Rules: Agro vs.vs. DrugsDrugs

-< 200° C-< 300° Cmelting point

≤ 100.7 - 22-12 (H)

1-8 (I)

-HB-acceptors

≤ 50 - 1≤ 3 (H)

≤ 2 (I)

≤ 3HB-donors

≤ 51 – 5

7 (I)

≤ 3.5 (H)

0 - 5 (I)

≤ 3

logP < 3)

logPOW

≤ 500200 – 400

500 (I)

150 – 500~ 300molecularweight

LipinskyClarke-Delaney

TiceBriggsAuthors

Properties

“Rule of 5“„Guide of 2“I & post-emergence H

activity more likely

“Rule of 3“

16

31

Screening StrategiesScreening Strategies

Compound Library TargetOrganism Compound Library

intrinsic activity at unknown target(s)

& bioavailability (ADME)

intrinsic activity at isolated target

32

Target-Identification

Antisense Technology

ReduceGenexpression

Target Gen

Rateof Vitality

Target AntisenseAntisense--TechnologyTechnology

17

33

Effect in the Plant (Phenotype)

TargetActivity

34

Plant specific Targets?Plant specific Targets?

Example: HPPD InhibitorsExample: HPPD Inhibitors

Humans Plants

NH3

+

O

ONH

3

+

O

OH

O

O

O

OH

O

OH

OH

O

O

-Tocopherol

Co-factors forCarotenoid Biosynthesis

Maleylacetoacetate

Fumarylacetoacetate

Fumarate + Acetoacetate

Succinylacetoacetate

Succinylacetone

Plastoquinone-9

Phe Tyr HPP

Homogentisate

HPPD / Fe(II)

Tyrosinemia I Plant Death

Bleaching

FAAH

O2

CO2

heme biosynthesis

X

O

CF3

O

O

NO2

Nitisone (Orfadin®)

O

S

O

O

NO2

O

O

Mesotrione (Callisto®)

18

35

Basis for Screening StrategyBasis for Screening Strategy

validated target

clear in vitro – in vivo correlation

biochemical assay

lots of active compounds

several X-ray co-crystallized structures

36

StructureStructure--basedbased ScreeningScreening

H N

Fe

DOCKING

H N

Fe

O

S

Cl

O

O

N

N

O

Cl

Cl

O

S

Cl

O

O

N

N

O

Cl

Cl

1TG5.pdb

19

37

StructureStructure--basedbased ScreeningScreening

H N

Fe

O

S

Cl

O

O

N

N

O

Cl

Cl

SCORING

Estimation of

• H-bonds

• Salt-bridges

• vdW-contacts

• electrostatic interactions

• etc.

relative binding affinities

38

Activity

O

S

Cl

O

O

N

N

O

Cl

Cl

O

S

Cl

O

O

N

N

O

Cl

COOH

O

S

Cl

O

O

N

N

O

N

O

S

Cl

OH

O

O

N

N

O

O

SH

Cl

N

N

O

Cl

Cl

O

S

O

O

O

N

Cl

Cl

O

CF3

Cl

N

N

O

Br

O

S

O

O

N

N

O

ClA B C D

E F G H

Affinity/Activity

A B C D

E F G H

A B C D

E F G H

A B C D

E F G H

H N

Fe

O

S

Cl

O

O

N

N

O

Cl

Cl

Compound library

StructureStructure--basedbased virtualvirtual screeningscreening

O

S

Cl

O

O

N

N

O

Cl

Cl

O

S

F

O

O

N

N

O

Cl

Br

O

S

Cl

O

O

N

N

O

N

O

S

Cl

NH2

O

O

N

N

O

O

SH

Cl

N

N

O

Cl

Cl

O

S

O

O

O

N

Cl

Cl

O

CF3

Cl

N

N

O

Br

O

S

O

O

N

N

O

Cl

20

39

StructureStructure--based Virtual Screeningbased Virtual Screening

Scoring with default ParametersScoring with default Parameters

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Anzahl gedockter Verbindungen (sortiert nach ComplOpt-Score)

An

zah

lX

XX

X-I

nh

ibit

ore

n

Default parameters

100 HPPD Inhibitors and 900 Chemicals from ACD

3.1375

500

VSbytested

chancebytestedEF %50

40


0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000Anzahl gedockter Verbindungen (sortiert nach ComplOpt-Score)

AnzahlXXXX-Inhib

itore

n Optimized parameters(e.g. clash factors)

5100

500

VSbytested

chancebytestedEF %50


Scoring with optimized ParametersScoring with optimized Parameters

21

41


CrucialCrucial LigandLigand--Protein Interaction PatternProtein Interaction Pattern

Fe2+

42

Default parametersEF50%= 1.3

Optimized parametersEF50%= 5

Optimized parameters +Binding modeEF50%= 6.3

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Anzahl gedockter Verbindungen (sortiert nach ComplOpt-Score)

An

zah

lak

tiver

Verb

ind

un

gen

You only have to test 8% of the library to find 50% of the actives!



Scoring withScoring with PharmacophorePharmacophore ConstraintsConstraints

22

43


Test: 41 Actives and > 6.000 HTS nonTest: 41 Actives and > 6.000 HTS non--ActivesActives

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 20% 40% 60% 80% 100%

Gedockte Verbindungen (sortiert nach "ComplOpt-Score")

Akti

ve

XX

XX

-In

hib

ito

ren

Enrichment Factor (EF50%) = 5.0

50%

100%

Score/sqrt(molwgt) Enrichment Factor = 7.1

44

Kiefernzapfenrübling(Strobilurus tenacellus)

Buchenschleimrübling(Oudemansiella mucida)

OO

O

O

O

O

O

Strobilurin A

Oudemansin A

Defensive chemicals isolated from fungi (mid 70th):

Profs. Anke and Steglich

UniversityUniversity cooperationcooperation showedshowed thethe way toway to newnew leadlead structuresstructures

StrobilurinsStrobilurins --FungicidesFungicides fromfrom FungiFungi

23

45

Biochemical site of action:respiratory chain

spore mitochondria

I

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

III

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

III

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

II

respiratory chain

46

Mode of ActionMode of Action

I

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

III

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

III

NADH

NAD+

Succinate

Fumarate

H+ H+

Cyt b *

III

Cyt c12e-

IV

H2O

1/2 O2

H+

UQpool

Cyt cATP

Synthase

H+ADP

ATP

II

Strobilurins block the fungal energy production by inhibition of thecomplex III of the respiratory chain.

24

47

3D3D--QSAR ModelQSAR Model forfor StrobilurinsStrobilurins

Input:Chemically diverse ligandswith different activity levels

3D-conformationgeneration

structural alignment

very high activity (IC50 < 10-9)high activity (IC50 < 10-8)120 strobilurin analoguesbroad activity range ( 10-10 < IC50 < 10-5)

48





calculateproperty fields

property field: steric demand

25

49

......E2

9.8120

...

E1Sn...

5.33

8.52

7.21

EnS2S1pIC50Cpd





correlate propertyfields with activity

.........log 212150 nn EzEmEkShSbSayIC


50






3D-QSAR model

Training set (120 cpds):reproduction of experimental data r2 = 0.95leave-one-out cross-validation q2 = 0.79

3D-QSAR Model for Strobilurins

26

51






3D-QSAR modelPrediction of independent test set: r2pred = 0.78

(32 compounds)

3D-QSAR Model for Strobilurins

52

PDB code: 1SQB & 1SQP (2004)

XX--rayray StructureStructure solvedsolved!!TheThe keykey findsfinds itsits locklock……....

27

53

StrobilurinStrobilurin History at BASFHistory at BASFFrom a Natural Product to Tailor-made Fungicides

Strobilurin A

O

O

O

1996 Kresoxim-methyl

O

O

ON

O Cereals

FVV

Dimoxystrobin

O

NH

ON

O

(invented by Shionogi)

Cereals

2004

2002

Pyraclostrobin

O

N

O

OO

NNCl

Cereals

FVV

Others

Target CropsTarget Crops

FVV

OthersCereals

Rice

Need for a rice fungicide to complete BASF’s strobilurin portfolio

!

from Strobilurus tenacellusAnke et al., 1977

54

92 3 4 5 6 7 8logPow

Target test with isolatedyeast mitochondria

2

3

4

5

6

7

8

9

pl50

Targ

etA

ctivity

Lipophilicity

Biological Activity versus Lipophilicity

Optimum logPOW for in fungus activity = 3.5 ± 1

3.5

5.5

Fungal spore germinationtest with Botrytis cinerea

28

55

log POW

2

3

4

5

6

1 2 3 4 5

pT50

Strong correlation betweendaphnia and fish

pI 5

0A

quatic

To

xicity

atD

aphnia

Lipophilicity

Aquatic Toxicity versus Lipophilicity

Optimum logPOW for acceptable aquatic tox profile = 0 ~ 3

logPOW correlates strongly

with daphnia toxicity

Strong regulatoryrestrictions for fish toxicityin Japan

Kresoxim-methyl (3,4)Dimoxystrobin (3,6)Pyraclostrobin (4,0)

56

Lipophilicity Optimum

Preferred characteristic for a new rice fungicide: logPOW = 2 ~ 3

Lipophilicity OptimaLipophilicity Optima logPOW

Activity on Target Level 4.5 ~ 6.5

Activity in Whole Fungus 2.5 ~ 4.5

Low Aquatic Toxicity 0 ~ 3

29

57

Optimisation ResultsOptimisation ResultsFour Potential Candidates Identified

N

O

NH

O O

NN

N

O

O

logPlogPOWOW

2.4

2.9

Orysastrobin

N

O

NH

O O

NN

O

N

O

O

N

O

NO

NH

O2.6

O

NO

N

NH

O

NO

2.7

IPIPRightsRights

Patent Restrictio

ns

(Ciba-Geigy)

+++

Biological ActivityBiological Activity

PYRIORPYRIOR RHIZSORHIZSO

+++

+++ +++

+++ +++

ResidualResidualEfficacyEfficacy

+++

Residual Efficacy

+

+++

Aquatic ToxicologyAquatic Toxicology

FishFish DaphniaDaphnia AlgaeAlgae

+++ +++ +++

AquaticToxicity

+ + +

58

OrysastrobinLaunched as Arashi® in 2007

(E,E,E,E)-isomer

Successfully introduced in the Japanese and Korean markets

N

O

NH

O O

NN

N

O

O

30

59

Acknowledgment

Thomas MietznerGerhard en-NaserKlaus Kreuz

Thomas GroteHubert SauterEgon HadenSiegfried StrathmannAkihide Watanabe

PhysChem

Orysastrobin

60

Thank you !

Challenges in Agrochemicals Design - Semantic Scholar

Documents