DRUG DISCOVERY AND DEVELOPMENT M. Hanafi Puslit Kimia LIPI Kawasan PUSPIPTEK, Serpong.

DRUG DISCOVERY AND DEVELOPMENT

M. HanafiPuslit Kimia LIPI

Kawasan PUSPIPTEK, Serpong

Target IdentificationAnd Validation

Search of Lead Structure

Optimization of Lead Structure

PreclinicalDevelopment

Research Phases in Drug Development

Idea

Lead Structure

Candidate for Development Product

Development Product

DEVELOPMENT of NOVEL DRUGSDEVELOPMENT of NOVEL DRUGSfrom NATURAL PRODUCTfrom NATURAL PRODUCT

1. Screening of Natural Compounds for Biological Activity :

Soil, plants, fungi, etc

2. Isolation and Purification of Active Principle

3. Determination of Structure : NMR, IR, MS

4. Structure-Activity relationships(SAR) :

Identification of Pharmacophore

5. Synthesis of Analogues :

Increase activity, reduce side effects

6. Receptor Theories : binding site information

7. Design and Synthesis of Novel Drug Structure

NR

N

O

OH

HN

NHO

OO

O

OO

O

Vincristine (R = -CHO) – Vinblastine (R = -CH3)Vinca rosea (Catharanthus roseus) (Apocynaceae)

O

O

O

H O

N

N

Camptothecin

Camptotheca acuminata

O

O

O

H O

N

N

O H

N

Topotecan

Lead compounds from Natural Products

Discovery from Natural Products

H

O

O

HO

H

O

O

Lovastatin Aspergillus tereus Anticholesterol -

O

O

O

OOR

HN

N

OOH

O

UK-3A

Streptomycesp sp. 517-02Cytotoxic to P338, KB

N

N

HO O

Phenazine carbioxylatePseudomonas pycocyaneae

O

O O

O

HO

CalanoneCallophyllum tesmanii

OCOOCH3 OH

HO OCH3

HO

CH3

Sulochrin - AntidiabetesAspergillus terreus

O OH

HO

MeO

O

O

O

N

Gingerol

O O

OMe

OH

MeO

HO

Curcumin

Piperine

Lead Compounds

Rational drug designRational drug design

X-ray crystallography X-ray crystallography has developed so that the has developed so that the determination of the 3-D crystal structures of determination of the 3-D crystal structures of proteins and receptors is coming easier.proteins and receptors is coming easier.

The Protein Data Bank The Protein Data Bank (see (see http://pdb.ccdc.cam.ac.uk/pdb/) has data for http://pdb.ccdc.cam.ac.uk/pdb/) has data for hundreds of published structures which are all hundreds of published structures which are all freely availablefreely available

Coupled with advances in Coupled with advances in computing power and computing power and molecular modellingmolecular modelling the so-called the so-called rational or rational or structure-based drug designstructure-based drug design..

database /genes

protein targets

chemical diversity

identify ‘hit’

optimize ‘hit’ structure

Diagram 1. Natural Product Drug Development from new information to new therapy (Guo et al., 2006)

Influencing Bio-molecular Influencing Bio-molecular ProcessesProcesses

Target = enzyme, receptor, nucleic acid, …Ligand = substrate, hormone, other messenger, ...

Protein BcL-xL -Protein BcL-xL -

Visualisasi enzim α-α-GlukosidaseGlukosidase

Binding site prediction

Positon of ligand in enzym target

Enzym HMG-CoA Reductase

Virtual Screening by Virtual Screening by in Silico in Silico DockingDocking

New Technologies and should Enable Parallel Process and Faster Time to Market at Lower Cost

Drugs Fail Because of two Major Reason

39 % fail due to deficiencies in Absorption, Distribution, Metabolism & Elimination (ADME)

30% fail due to lack of efficacy

11% fail due to animal toxicity

10% fail due to adverse effects in man

5% fail due to commercial reason

5% miscellaneous

H-bonding, electrostatic and hydrophobic interactions can be identified and, hopefully, optimised by “in silico” design.

hydrogen bonding

hydrophobic π-stacking interaction

Design of DHODH Design of DHODH Inhibitors Inhibitors

Properties of orally Properties of orally Available Available

Drug-like CompoundsDrug-like Compounds

The Lipinski : Rule of five criteriaThe Lipinski : Rule of five criteria Molecular weight 500 Da Molecular weight 500 Da Log Log PP ≤ 5 ≤ 5 Hydrogen bond donors (OH and NH) ≤5 Hydrogen bond donors (OH and NH) ≤5 Hydrogen bond acceptors (lone-pairs of hetero-Hydrogen bond acceptors (lone-pairs of hetero-

atoms, like O and N) atoms, like O and N) Number of heavy atoms 10–70 Number of heavy atoms 10–70

O O

H 3 C O O C H 3

O HH O

6 '5 '

4 '

3 '

1 '

2 '

1

23

45

6

7

Curcumin

O

O C H 3

O HH O

H 3 C O

PGV-0

O

O C H 3

O HH O

H 3 C O

H 3 C O O C H 3

H 3 C O O C H 3

H O O H

O

HGV-0

PGV-1

HGV-1

H 3 C O O C H 3

H O O H

O

O C H 3 O C H 3

Compound HeLa T47D Raji MCF-7 Myeloma

Curcumin 15.76 20 14 20* 6

PGV-0 7.60 10 3 10* 3

PGV-1 ND 1.5 ND 2.5* ND

Cytotoxic effect of curcumin, PGV-0 and PGV-1 on some cell’s types (IC50 ,

M)

* Concentrations to induce cell apoptosis as indicated by PARP cleavage

Log P

2.56

3.19

2.94

For “direct analogues”, a new lead must normally promise improvements in properties over an existing drug to be pursued. They are sometimes known as “me-too compounds”. For example ACE inhibitors:

Direct and structural analogues

H S

O

N

C O 2 H

NH

O

N

C O 2 H

E t O 2 C

P h

Captopril

Log P 3.09

EnalaprilLog P 0.24

Since the discovery of captopril many new ACE inhibitors have been Since the discovery of captopril many new ACE inhibitors have been discovered. The active site model of ACE was significantly improved, discovered. The active site model of ACE was significantly improved, and the development of enalaprilat (enalapril) showed that and the development of enalaprilat (enalapril) showed that carboxylates could be used as the zincbinding motif if the structure carboxylates could be used as the zincbinding motif if the structure benefited from additional hydrophobic binding.benefited from additional hydrophobic binding.

Success inspires competition

H O 2 C

O

N

C O 2 H

O

N

CO2H

HO2C

IC50

75

18.33

NH

O

N

C O 2 H

E t O 2 C

P h

IC50

4.08

1

NH

O

N

CO2H

HO2C

Log P -0.92

EnalaprilLog P 3.09

Log P -0.1

Log P -0.52

DEVELOPMENT OF DEVELOPMENT OF LOVASTATIN FoR LOVASTATIN FoR

ANTICHOLESTEROLANTICHOLESTEROL

Find and Optimized a Lead Find and Optimized a Lead Compound: Compound: LovastatinLovastatin

» Minimise energy of structure : Chem3D, Gaussian, Mopac,

» QSAR (hub. Struktur Aktivits) : HyperChemPro

» Direct Ligand Design (HMG-CoA rductase): Arguslab 4.0

» Synthesis» Bioaactivity Test

METHODOLOGY

Sintesis

Activity evaluationIn vivo

Drug DesignHyperchem &Docking

ActiveAnticholesterol

compound

QSAR Parameter Identificatio

n

O

O

O

O

Evaluation Results Total

cholesterol(mg/dl)Evaluation Results: HDL (mg/dl)

HIPOTESIS

“… makin mudahmenembus dinding usus halus”

= makin tinggi aktivitasnya

H

O

O

HO

H

O

O

Lovastatin

H

OH

OH

COOR

HO

H

Ester StatinR = Bu, Hex, Oct, dst.

H

O

O

HO

H

O

O

Simvastatin

“Perubahan Polaritas/Sterik

DESAIN 2:DESAIN 2:Mengisi pusat aktif enzim [docking]Mengisi pusat aktif enzim [docking]

Tabernero et al. J. Biol. Chem., 2003

Lovastatin fit terhadap enzimmelalui 4 buah interaksi:

C H 3

O

H 3 C

H 3 C

O

H O O

O

L o v a s t a t i n ( 1 )

H

C H 3

O

H 3 C

H

H 3 C

O

H

H O O

O

H 3 C C H 3

S im v a s t a t i n ( 2 )

C H 3

O

H 3 C

O

O

O

1 8

Log P 3.77Log P 5.73

Log P 5.68

SIMVASTATIN & LOVASTATIN DERIVATIVES AND LOG P

Log P 4.8

H

OH

H

OH

H

HO O

O

Log P 4.6

H

CH3

O

H3C

H

CH3

H3C

O

H

O O

O

O

10

C30H46O6Exact Mass: 502.33

Interaction Dehydrolovastatin (grey)

and the active site of HMG-CoA reductase (dark)

NONO CompoundsCompounds Interaction Energy (kcal / Interaction Energy (kcal / mol)mol)

Log PLog P

11 Substrat (HMG-CoA)Substrat (HMG-CoA) - 10,5055- 10,5055

22 DehydrolovastinDehydrolovastin - 9.95- 9.95 4.804.80

33 Lovastatin (1)Lovastatin (1) - 9,48- 9,48 3.773.77

44 Simvastatin (2)Simvastatin (2) - 8,86- 8,86 5.735.73

55 Buthyl ester Buthyl ester (Lovastatin)(Lovastatin)

- 9,91- 9,91 4,924,92

INTERACTION ENERGY WITH HMG CoA REDUCTASE AND LOG P

ArgusLab 4.0

HyperChem 7.0

Synthesis Synthesis DehydrolovastatinDehydrolovastatin

CH3

O

H3C

H3C

O

O

O

CH3

O

H3C

H3C

O

O

O

Lovastatin

HO

pTsOH, Cyclohehane

Dehydrolovastaton

88,3 % (EtOH)

Heksan:EtOAC (4:1)

Lovastatin

Parameter Normalcontrol

Hiperlipi-demic

Simvastatin

(7,2 mg/200 g bw)

Lipistatin(7,2 mg/

200 g bw)

Lipistatin(14,4 mg/200 g bw)

Total cholesterol

(mg/dl)(%)

111,79 156,66 112,03 (28,49%)

106,64 (31,93 %)

105,54 (32,55 %)

Trigliseride (mg/dl)

(%)

106,29 172,53 102,28 (40,72%)

103,85 (40,0%)

94,79 (45,06%)

LDL-cholesterol

(mg/dl)(%)

32,34 72,99 30,23 (58,58%)

25,00 (65,75%)

28,77 (60,58%)

HDL-cholesterol

(mg/dl)(%)

58,20 49,16 61,34 (24,77%)

60,87 (23,82%)

57,81 (17,60%)

Evaluation Results of Antihiperlipidemic Activity on Rat for Lipistatin and Simvastatin

Development of UK-3A analog potential for Breast cancer treatment

Lipinski Rule Hyperchem Program MW < 500 g/mol; log P < +5

Virtual Interaction (molecular docking) ArgusLab program

Virtual Interaction (molecular docking) ArgusLab program

Structure Analog Design UK3A in silico

Structure Analog Design UK3A in silico

Sel Normal vs Sel KankerSel Normal vs Sel KankerSel Payudara NormalSel Payudara Normal

Protein-protein anti-apoptosis (a.l. Protein-protein anti-apoptosis (a.l. Bcl-xL) diinhibisi oleh protein-Bcl-xL) diinhibisi oleh protein-protein pro-apoptosis yang sama protein pro-apoptosis yang sama banyaknyabanyaknya

Sel Kanker PayudaraSel Kanker Payudara

Protein-protein anti-apoptosis Protein-protein anti-apoptosis (a.l. Bcl-xL) berlebih, sehingga (a.l. Bcl-xL) berlebih, sehingga ada yang tidak terinhibisiada yang tidak terinhibisi

Akibat:Akibat:Sel payudara rusak tidak alami Sel payudara rusak tidak alami apoptosis; terus tumbuh dan apoptosis; terus tumbuh dan membelah tidak terkendali membelah tidak terkendali (kanker)(kanker)

Simstein Simstein et alet al, 2003., 2003.

4444

Inhibisi Bcl-xL dengan ObatInhibisi Bcl-xL dengan Obat

4545

OBATOBAT

Bila kelebihan Bcl-xL diinhibisi, sel rusak akan alami apoptosis secara spesifik >> tidak jadi kanker

Ricci, et al, 2006.Ghobrial, et al, 2005.Ferreira, et al, 2002.

Optimum Conformation(EOptimum Conformation(Eminmin)- )- Chem3D Ultra 10Chem3D Ultra 10

4646

Konformasi PDBGE Konformasi PDOGE

Chem3D

HyperChem Pro (QSAR Parameter) & ArgusLab 4.0 (Ebinding)

47

HyperChem Pro 7.0ArgusLab 4.0

Interaction of Protein BcL-xL & Analog UK-3

N

OH

NH

O

OO

O

A

B C

O

Analog UK-3A : PSMOE

N

OH

NH

O

O

O

O

O

O

OUK-3A

UK-3A Ring opening (Analog UK-3A)

DEVELOPMENT OF ANALOG UK-3A POTENTIAL FOR BREAST CANCER TREATMENT

DEVELOPMENT OF ANALOG UK-3A POTENTIAL FOR BREAST CANCER TREATMENT

PSMOEPSMOE

HN

O

O O

N

OOH

O

BcL-xL Protein

QSAR Parameter & Cytotoxic Test Results

N

OH

HN

O

OH

O OCH3

O

O

O

OOR

HN

N

OOH

O

UK-3A

Log P -1.18Ebinding = -7.1 kcal/molIC50 = >100 g/ml

Log P 1.61Ebinding = -11.65 kcal/molP388 : IC50 = 38 g/ml

O

O

O OH

OO

O

OOHO

O

O

OH

NH

OTaxol

Log P 1.67Ebinding = -10.39 kcal/mol

O

OHN

OOH

HN

O

O

OH O

OAntimycin A3

Log P 1.30, Ebinding = -10.24 kcal/molKB :IC50 = 0.23 mg/mlYMB-1:IC50 = 0.015 mg/ml

HClg/MeOH

Cytotoxic Test Results to P388, KB and YMB-1

NHN

O

O

OH

O

OO

PDBGE : R = Butyl

N

HN

O

O

O

OO

OH

NDBGE : R = Butyl

IC50 34 g/ml (P388)IC50 2.28 g/ml (KB)IC50 1.83 g/ml (YMB-1)

IC50 38 g/ml (P388)

IC50 1.92 g/ml (KB)IC50 5.46 g/ml (YMB-1)

Ebinding=-9.66 kcal/mol), Log P 1.5

Ebinding=-10.29 kcal/mol);

Log P 1.62

NHN

O

O

OH

O

OO

PDOGE : R = Octryl

IC50 9.8 g/ml (P388)IC50 9.84 g/ml (KB)IC50 147.0 g/ml (YMB-1)

Log P 3.32Ebinding -13.538

SAR Parameter & Cytotoxic Test Results P388, KB and YMB-1

O H

HN

O

P388 :IC50 = 7.75 g/mlKB :IC50 = 0.6 g/mlYMB-1:IC50 =2.97 g/ml

Log P 3.29Ebinding = -10.21 kcal/mol

Calanone derivatives and Its Cytotoxic Activity

O

O O

HO

HO

O

O O

O

HO

Calanone Ester Calanol

Log P 2.32Against colon cancer cells HCT116: IC50 = 1.29 µg/mL P388 : IC50 = 7,5 µg/mL

Log P 0.43Against colon cancer cells HCT116: IC50 > 20 µg/mL L1210 : 59.4 µg/mL P388 : IC50 = 15

Cisplatin IC50 = 1.02 µg/ml

O

O O

R

HO

Log P -0.42

Against colon cancer cells HCT116: IC50 > 20 µg/mL L1210 : 70.0 µg/mL P388 : IC50 = 15

Molegro Virtual Docking (MVD)

Alignment of analog compound to ligand

Determination of binding site “pocket” in

the enzyme

Calculation of docking energy value of

compound candidate to fill the “pocket”

Compound candidate synthesis

O

HO

OH

H3C

O

O

HO

OH

OH

O

HO

OH

OH

OH

O

HO

HO

OH

OH

HN

N

HO

HO

OH

OH

O

HO

OCH3

OH

H3C

HO

HO

NH

OH

OH

1-deoksi-nojirimicin

akarbose

nojirimisin

S

HO

HO

CH2OH

CH2 C

H

OH

C

H

CH2OH

OSO3

Salacinol

Inhibitor α-Inhibitor α-GlukosidaseGlukosidase

OCOOCH3 OCOCH3

H3CO OCH3

H3COCO

CH3

OCOOCH3 OH

H3CO OCH3

HO

CH3

OCOOCH3 OH

H3CO O CH3

OCOOCH3 OH

H3CO OCH3

H3CO

CH3

OCOOCH3 OH

HO O CH3

OCOOCH3 OH

H3CO OH

HO

CH3

OCOOCH3 OH

HO OCH3

HO

CH3

7

3

21

6

4

5 (sulochrin)

OH O COOCH3

OH

H3CO

H3C

OH

Br

Br

OH O COOCH3

OCH3

H3CO

H3C

OCH3

O

OCH3

OH3COOC

OOH

Br

H3C

Br

O

OCH3

OH3COOC

OOH

I

H3C

I

O

OCH3

OH3COOC

OOH

Cl

H3C

Cl

D

C

E

BA

OH

O OH

OCH3

OH

O OH

OCH3

H3CO

O OH

OH

dioxybenzene

benzophenone-6

oxybenzone

Sulochrine Derivatives

Ligan Similarity Score

IC50 Ligan Similarity Score

Salacinol -494.341 4 -377.17

B -420.861 22.4 5 -357.712

C -420.769 2 -370.041

E -420.347 7 -369.389

S3 -407.934 6 -366.136

1 -399.824 Benzophenone-6

-362.692

Sulochrin -385.956 80.4 dioxybenzene -359.89

Similarity Calculation Score of the ligan to MVD

KESIMPULAN1. Tanaman Obat dapat dijadukan sumber Ide (Lead Compound)2. Protein/Enzim tertentu dapat digunakan untuk stimulasi interaksi dengan ligan3. Drug design sangat membantu dalam mempercepat dalam pengembangan obat4. Parameter QSAR (Log P) dan Energi dcking dapat dijadikan indikator Optimasi lead Compound

QSAR PARAMETERQSAR PARAMETERPARAMETERPARAMETER CalanonCalanon CalanolCalanol C.OctanoatC.Octanoat

eeC. 2,2-di-C. 2,2-di-

Me-butirat Me-butirat C.Phe-C.Phe-

propionatpropionatTaxol Taxol

Log P Log P 0.430.43 -0.42-0.42 2.322.32 1.961.96 1.21.2 2.252.25Refractivity Refractivity (A(Aoo) )

133.1133.1 133.7133.7 170.5170.5 161.2161.2 176.4176.4 233.6233.6

Polarizability Polarizability (A(Aoo) )

45.445.4 49.749.7 61.761.7 58.0758.07 62.262.2 87.887.8

Surface area Surface area (approx) (approx)

312.1312.1 432.9432.9 576.1576.1 393.1393.1 437.8437.8 122.2122.2

Surface area Surface area (grid) (grid)

477.5477.5 603.5603.5 634.8634.8 574.8574.8 646.9646.9 819.4819.4

Volume Volume 861.8861.8 1068.1068.44

1163.61163.6 1056.81056.8 1172.51172.5 1532.1532.11

Geometry Geometry OptimazatioOptimazation(kcal/mpl)n(kcal/mpl) 146.2146.2 31.231.2

146.0146.0 149.2149.2 148.4148.4 287.9287.9

Molecular Molecular dynamic(kcadynamic(kcal)l)

200.5200.5 80.580.5 224.3224.3 219.0219.0 219.9219.9 400.5400.5

Citra Interaksi Substrat (bola)dengan Pusat Aktif HMG-CoA reduktase

(kawat)

Citra Interaksi Lovastatin terdehidrasi (kawat abu-abu)

dengan pusat aktif HMG-CoA reduktase (kawat gelap)

Drug targetsDrug targetsDrug targets are most often proteins, but nucleic acids, may Drug targets are most often proteins, but nucleic acids, may

also be attractive targets for some diseases.also be attractive targets for some diseases.

TARGET MECHANISMTARGET MECHANISM

Enzyme Inhibitor : reversible or irreversibleEnzyme Inhibitor : reversible or irreversible Receptor* : Agonist or antagonistReceptor* : Agonist or antagonist Nucleic acid : Intercalator (binder), modifierNucleic acid : Intercalator (binder), modifier

(alkylating agent) or substrate mimic.(alkylating agent) or substrate mimic. Ion channels* : Blockers or openersIon channels* : Blockers or openers Transporters* :Uptake inhibitorsTransporters* :Uptake inhibitors

*present in the cell membranes*present in the cell membranes

Rational Drug DesignPhysiological target where drugs act.

1. Enzymes : where new molecules are made in tissue2. Receptors where circulating messengers, eg. Biogenic amines and

peptides, act to alter cellular activity3. Transport systems the selectivity permit access through membranes into and out of cells, eg. ion channels, transporter moleculed4. Cell replication and protein synthesis controlled by DNA and RNA5. Storage sites where molecules are kept in an inactive form for subsequent release and re-uptake, eg. Blood platelets, neurons

1. The antibiotic chloramphenicol is very bitter, but the palmitate ester does notget absorbed by the tongue so much when taken orally and so is more palatable. The succinate ester on the other hand makes it more soluble making intravenous formulation more effective. Once absorbed the esters are quickly hydrolysed.

2. The ACE inhibitor enalaprilat is potent in vitro, but is poorly absorbed and sonot very effective in vivo. The ethyl ester enalapril, however, is absorbed muchbetter but is a weak ACE inhibitor. It is hydrolyzed to the carboxylic acid byesterase enzymes in the blood, which is where ACE is found.

Prodrugs - examples

Drug developmentDrug development Structure-based drug designStructure-based drug design 6565

Drug candidatesDrug candidates

Bind to specific protein, usually Bind to specific protein, usually receptors or enzymesreceptors or enzymes

Ease of absorption, distribution, Ease of absorption, distribution, metabolism, and excretion (ADME)metabolism, and excretion (ADME)

The Contribution of IT to The Contribution of IT to Drug Discovery is Drug Discovery is IncreasingIncreasing

6767

Drug designing based on Drug designing based on 3D structural information3D structural information

Binding model: Lock and keyBinding model: Lock and key Small molecule: complement in Small molecule: complement in

shape and electronic structureshape and electronic structure Molecule features obey Lipinski’s Molecule features obey Lipinski’s

rulerule– Mw < 500 Mw < 500 – ΣΣ hydrogen bond donors < 5 hydrogen bond donors < 5– ΣΣ hydrogen bond donor acceptors <10 hydrogen bond donor acceptors <10– Partition coefficient (log P) < 5Partition coefficient (log P) < 5

Candidate drugs

Apoptosis:

P53

Bax

Bcl-2

Akt/PKA

NFB

Caspase-3

Cell cycle:

CyclinD1

NFB

COX-2

Kinase

Transcription factors

Metastasis and

Angiogenesis

Tumor Promotion

α-Amilase structureα-Amilase structure Structure-based drug designStructure-based drug design 6969

A domain

C domain

B domain

Binding pocketCa2+

αα-Amilase structure-Amilase structure

PDB 7TAA

HIV protease structureHIV protease structure Structure-based drug designStructure-based drug design 7070

Binding pocket

D25 D25

Catalytic residues

HIV protease structure

PDB 1HSH