Fighting Cancer: Allostery and Targeting Cancer Cell

to emergence of 4 additional hallmarks ... cancer cells produce energy by primarily ... subsequently metabolized through alternative pathways Allo...
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2017 Drug Design and Delivery Symposium “Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism”

Stefan Gross

Scott Edmondson

Director, Enzymology Agios Pharmaceuticals

Director of Chemistry, AstraZeneca

Slides available now! Recordings are an exclusive ACS member benefit.

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What You Will Learn

• Rationale for Targeting Cancer Cell Metabolism • Drugging Glycolysis: Activators of Pyruvate Kinase • Targeting the TCA Cycle: Inhibitors of Isocitrate Dehydrogenase and Glutaminase

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Altered Cellular Metabolism: An Emerging Hallmark of Cancer • Historically, 6 hallmarks of cancer • Sustained proliferative signaling • Evading growth suppressors • Resisting cell death • Enabling replicative immortality • Inducing angiogenesis • Activating invasion/metastasis • Scientific progress has led to emergence of 4 additional hallmarks • DNA destabilization • Inflammation • Avoiding immune destruction • Deregulation of cellular energetics

Cancer Metabolism is capability to modify cellular 17

metabolism to most effectively support neoplastic proliferation

What is the Warburg Effect? • A) The propensity of cancer cells to migrate from a primary tumor and form distant metastases

• B) The accumulation of genomic deletions in tumor suppressor genes as tumor-initiating events • C) The observation that cancer cells produce energy by primarily by glycolysis and accumulate lactate • D) The secretion of growth factors by newly established metastases to establish a robust nutrient supply • E) The inability for students to retain knowledge of metabolic pathways greater than 24 hours after an examination 18

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Link between Dysregulated Cellular Metabolism and Cancer is a Proven Concept 1920s

1970s

2000s

HALLMARKS OF CANCER: THE NEXT GENERATION Douglas Hanahan and Robert A. Weinberg

Otto Warburg

PET Scans Normal tissue

Hallmarks of Cancer

Warburg Effect

History of Targeting Cancer Metabolism •

1940s: antifolates as efficacious cancer agents



1960s and 1970s: glutamine analogs, acivicin and 6-diazo5-oxo-norleucine, introduced the possibility of therapeutic benefit through inhibition of glutamine pathways in cancer cells



Dihydrofolate reductase

methotrexate

folic acid

acivicin glutamine

6-diazo-5-oxo-norleucine

1970s: asparaginase therapy for the treatment of childhood ALL through starvation of aspargine-dependent leukemic cells

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Obviously, there are key metabolic nodes which are potential drug targets for small molecule therapeutics

Key Central Metabolic Pathways Utilized by Cancer Cells Glycolysis •

• •

Many cancers utilize glucose for ATP production and to provide carbon for biosynthetic pathways Regulated directly by multiple growth factors and tumor microenvironment Key targets include HK2, Eno2, and PKM2

Glutamine Pathway • •

Glutamine dependence described in triple negative breast cancer and RCC Increasing appreciation emerging

Isocitrate Dehydrogenase 1 and 2 • • • • • • 22

First reported gain-of-function mutations in cancer metabolism Heterozygous point mutations confer neoactive biochemical properties Production of first reported oncometabolite, 2hydroxy glutaric acid Prevalent in glioma, AML, lymphoma, chondrosarcoma Likely to be disease initiating mutations First wave of inhibitors recently entered clinical trials

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Challenges of drugging metabolic targets •

Little or no prior history of inhibitor development – These aren’t your parents’ GPCRs or kinases!



Multiple, highly homologous isoforms – Precision medicine could require targeting of cancer-cell specific enzymes arising through splice-site selection



Small, polar active sites – Substrates and products typically undergo only minor modifications (decarboxylation, oxidation, double-bond formation or movement) – Active-site inhibitors unlikely to be “traditionally drug-like” – Specificity can be a challenge as many metabolic enzymes share substrates and a common set of cofactors; NAD(H) FAD(H), TPP



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Efficient enzymatic activity –

Sustained target engagement requried to shut down pathway



High metabolic flux can cause rapid and high accumulation of substrate which can be subsequently metabolized through alternative pathways

Allosteric modulators, with non-competitive or uncompetitive mechanisms of action, can resolve many of these challenges

Allosteric Modulation of Metabolic Targets Pyruvate Kinase (PKM2) Glutaminase (GAC) with BPTES

24 Mitochondrial Isocitrate Dehydrogenase

(IDH2) with AGI-6780

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Allosteric Inhibitors of Mutant Isocitrate Dehydrogenase Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism Stefan Gross, Ph.D. | Director, Enzymology | Agios Pharmaceuticals | March 2017

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Isocitrate Dehydrogenase (IDH) 1/2 Mutations in Cancer IDH1-R132H R132C R132S R132M

Cytoplasm

IDH2-R172K R172S

R100A

X

   

R140Q R140W

Histone demethylases DNA demethylases Prolyl hydroxylases Collagen hydroxylases

Mitochondria  Parsons et al, Science 2008: Recurrent point mutations at a single residue (R132) in one allele of IDH1 first identified in glioma; low frequency mutations in IDH2 also described (R172) 

IDH1 (R132) and IDH2 (R172 and R140Q) mutations found across multiple tumor types

 WT IDH1 and IDH2 catalyze the NADP+-dependent oxidative decarboxylation of isocitrate 26

IDH1 and IDH2 mutations result in decreased capacity to catalyze isocitrate to αketoglutarate conversion

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IDH1 and IDH2 Mutations: Distinct genetically defined populations Indication

IDH1m Mainly R132H and R132C

IDH2m Mainly R140Q and R172K

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Estimated % IDHm

Low grade glioma & secondary GBM

68-74

Chondrosarcoma

40-52

Acute Myeloid Leukemia (AML)

6-10

MDS/MPN

3

Intrahepatic Cholangiocarcinoma

11-24

Ollier/Maffucci

80

Others* (colon, melanoma, lung, prostate)

1-3

Acute Myeloid Leukemia (AML)

9-13

MDS/MPN

3-6

Angio-immunoblastic NHL

30

Intrahepatic Cholangiocarcinoma

2-6

Giant Cell Tumor of the Bone

80

Others* (melanoma, glioma)

3-5

Based on literature analysis. Estimates will continue to evolve with additional future data. ** Includes “basket” of emerging unconfirmed indications.

A Surprising Biochemical Observation: IDH1 mutant enzyme generates and then consumes NADPH O

O

OH O

HO

O

IDH1 OH

NADP+

NADPH + CO2

IDH1m OH

O

NADPH

NADP+

D-2HG

HTS assay

NADPH Levels

OH

O

HO

NADP+ Isocitrate 28

Dang L et al. Nature 2009

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IDH Mutation as a Gain of Function in Glioma: 2-HG as an “Oncometabolite” NORMAL METABOLISM

isocitrate

IDH

Normal

aKG isocitrate

Tumor suppressor

loss-of-function

aKG

Metabolic Insight

IDH

isocitrate

2-HG

mIDH

Oncogene

gain-of-function

CANCER METABOLISM

mIDH

aKG

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Model of IDHm Tumorigenesis: 2HG Drives Epigenetic Changes isocitrate

Oncogene

DNA and Histone Demethylases

IDH IDH-mt

2-HG

aKG

1. Hypermethylation Me

Me

2. Modulation of gene expression

Me

Blocked Differentiation Leukemic Blasts Cells

Me

Me Me

Me Me Me

Me

Me Me

Me

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Model of IDHm Tumorigenesis: 2HG Drives Epigenetic Changes isocitrate

Oncogene

DNA and Histone Demethylases

IDH IDH-mt

X

2-HG

aKG

IDHm Inhibitor

Active Demethylation

Release of Blocked Differentiation Differentiated Myeloid Cells

X-Ray Co-Complex of AGI-6780/IDH2R140Q

AGI-6780 32

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AGI-6780/IDH2R140Q Co-complex

Key Features: - Packing between helixes - Very hydrophobic pocket - H-bonds to Gln316

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AGI-6780/IDH2R140Q Co-complex Folded loops cap binding site

Key Features: - Packing between helixes - Very hydrophobic site - H-bonds to Gln316

Binding site floor “dehydron”

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AGI-6780/IDH2R140Q Co-complex Encapsulation of inhibitor No solvent exposure

Folded loops cap binding site

Key Features: - Packing between helixes - Very hydrophobic site - H-bonds to Gln316

Binding site floor “dehydron”

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Continuous biochemical assay allows direct and high precision measurement of association rate constants

First-order association

Inhibitor added here

Kon = 5.8 x 104 M-1 min-1 Koff = 8.3 x 10-3 min-1 36

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Cell potency driven by extremely long Koff AGI-0007574 0.06

Kobs

0.04

0.02

Koff slow Biochem IC50 (µM) 0.33 Cell IC50 (µM) 0.053

0.00 0.0

Koff Rapid Biochem IC50 (µM) 0.65 Cell IC50 (µM) 0.66

0.2

0.08

0.08

0.06

0.06

Kobs

Kobs

0.10

0.04

Koff slower Biochem IC50 (µM) 0.35 Cell IC50 (µM) 0.011 0.5

1.0

0.8

1.0

AGI-0006780 b2

AGI-0007468

0.00 0.0

0.6

I (uM)

0.10

0.02

0.4

1.5

0.04

Koff wicked slow Biochem IC50 (µM) 0.33 Cell IC50 (µM) 0.053

0.02 0.00 0.0

2.0

0.5

1.0

1.5

2.0

I (uM)

I (uM) 37

AGI-6780: A molecule with nanomolar potency for 2HG inhibition and long residence time against IDH2 R140Q C for aKG

U/C for NADPH

25 20

1 /V

100

15 10

50

1 /V

n o in h ib ito r 5

100 nM 6780

n o in h ib ito r 3 0 n M A G I- 6 7 8 0

200 nM 6780 0 .0 0

0 .0 1

0 .0 2

-4

-2

2

4

6

1 /S

1 /S -5 0

Kon = 5.8 x 104 M-1 min-1 Koff = 8.3 x 10-3 min-1

NADPH

38

aKG

2HG

NADP

6780

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IDH inhibitor lowers 2-HG by ~96% in IDH1-R132H Primary Neurospheres Following Three Doses

Tumor 2-HG Concentration following BID dosing (3 doses)

150 mpk 39

Drugging Glutaminase Targeting the Glutaminase C Variant

Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism Stefan Gross, Ph.D. | Director, Enzymology | Agios Pharmaceuticals | March 2017

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Drugging Glutaminase: Targeting the Glutaminase C Variant

Glutaminase provides an additional pathway for entry of carbons into the TCA cycle 41

Drugging Glutaminase: Targeting the Glutaminase C Variant • Multiple isoforms described transcribed by two different genes – GLS1 (kidney type) • Splice form 1: KGA/GLS1 • Splice form 2: GAC

– GLS2 (liver-type)

Primary sequence alignment of human GAC, human GLS2, and E. coli GLSA2 with structural elements from GAC . Mutation sites for creation of BPTES resistant GAC are denoted with arrows.

• Glutaminase catalyzes the conversion of glutamine to glutamate, which can then be oxidized to aKG to anaplerotically feed the TCA cycle to provide biosynthetic intermediates and ATP

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• Used as a substrate for the generation of glutathione, which helps protect cells from redox stress

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GLS1 in cancer cell metabolism • GLS1 expression has been shown to be positively regulated by c-myc • GLS2 is positively regulated by p53 • GLS1 expression predominates over GLS2 in most cancers • Inhibition of glutaminase activity has been shown to delay tumor growth in several models 43

BPTES, an allosteric inhibitor of glutaminase with isoform specificity

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GAC tetramer with BPTES in allosteric pocket

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BPTES binding pocket interactions. The BPTES molecule is rendered as a stick and colored by atom type, with cyan carbons, yellow sulfurs, blue nitrogens, and red oxygens. The short dimer interface helices and BPTES binding loops are shown with monomers colored green and maroon. Key hydrogen bond interactions to peptide backbone atoms are represented as dashed lines, and the residues contributing to the hydrophobic π-basket (Y394 and F322) are shown.

BPTES inhibitor locks GAC into non-productive conformation

In the BPTES-GAC structure, the glutamate product is bound in the active site. BPTES may function as a product-trapping inhibitor. While it is clear that the inhibitory mechanism is allosteric in nature, the exact mechanism of inhibition is unknown other than the complex is locked into a nonproductive conformation.

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Mutation of 𝜋 – basket residues confers BPTES resistance by converting GLS1 binding site to GLS2 sequence

Ka (PO42-) BPTES IC50 (mM) (µM)

kcat (s-1)

KM (Gln) mM

kcat/KM (M-1s-1)

GAC

22 ± 2

1.4 ± 0.4

1.6 ± 0.5 * 104

80 ± 8

GLS1

10 ± 1

1.9 ± 0.4

5.3 ± 1.2 * 103

76 ± 7

4.0 ± 0.2

6.3 ± 0.8 *

102

8±1

88 ± 17

2.5 ± 0.1

1.6 ± 0.1 * 104

4±2

>100

Enzyme

0.08 ± 0.02 0.06 ± 0.06

GAC F318Y/F322S

2.5 ± 0.3 40 ± 1.5

GAC Y394L

20 ± 1

0.4 ± 0.1

4.7 ± 1.2 * 104

59 ± 19

>100

GAC Y394A

0.01

-

-

-

-

GAC L321F

0.3

-

-

-

-

GAC L321W

0.06

-

-

-

-

GLS2

47

It’s very easy to design an enzyme inhibitor

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Allosteric Activators of PKM2

Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism Stefan Gross, Ph.D. | Director, Enzymology | Agios Pharmaceuticals | March 2017

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Pyruvate Kinase • PK catalyzes the last step of glycolysis, converting phosphoenol pyruvate to pyruvate, with the concomittant production of ATP • PKM2 is a splice variant of PK – Expressed in fetal tissue, rapidly proliferating cells – Capable of switching between a low and high activity state • Allosterically activated by FBP • Allosterically inhibited by phosphotyrosine marked proteins activated by extracellular growth signals

• Unique regulatory properties believed to provide transformed cells with novel metabolic flexibility 50

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Pyruvate kinase is a key metabolic node

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PKM2 “on” directs carbon flow into TCA cycle for energy production

PKM2 - ON

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PKM2 “off” directs carbon flow into pentose phosphate shunt for nucleotide production

PKM2 - OFF

53

PKM2 is allosterically activated by FBP

Two consequences of activation: • Increase in affinity for PEP but not ATP substrate • Decrease in subunit co-operativity 54

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PKM2 contains at least three different allosteric activation sites Synthetic allosteric modulator (AGI-902) Physiological allosteric modulator (Serine) Chaneton et al, Nature 2012 (PDB 4B2D) Physiological allosteric modulator (fructose bisphosphate)

A G I-9 0 2 m im ic s F B P a c ti v a ti o n o f PKM2 0 .8

A p o -P K M 2

u m o l/s e c /m g

A G I -9 0 2 + P K M 2 0 .6

0 .4

0 .2

0 .0 0 .0

0 .5

1 .0

1 .5

2 .0

P E P (m M )

55

Treatment with PKM2 activatiors could potentially force transformed cells into fatal metabolic imbalance PKM2 OFF: generate nucleotides

Rapidly proliferating cell cycles PKM2 activity to satisfy metabolic program

PKM2 ON: generate energy

PKM2 activator-treated cell locked into energy generation and is starved for nucleotide precursors

PKM2 ON: generate energy

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Cancer cells do NOT make the following adaptations to thrive in a transformed state? • A) Rewire existing metabolic pathways by reactivating exotic enzyme isoforms • B) Generate novel metabolites with tumor-promoting properties • C) Augment anapleurotic pathways using multiple entry points • D) Reduce their number of ribosomes to divert nucleotides to DNA replication • E) Increase their reliance on specific nutrient pathways fed by abundant metabolites 57

Conclusions •

Cancer Metabolism is capability to modify cellular metabolism to most effectively support neoplastic proliferation



Metabolic adaptations include production of oncometabolites and rewiring metabolic pathways using cancer-specific enzyme isoforms



These adaptations also create unique vulnerabilities through reliance on specific nutrient pathways or exotic enzymes, potentially providing many novel targets for discovery and development



Targeting metabolic enzymes presents unique challenges which may be solved through allosteric regulators



Selective and highly potent molecules can be developed by taking advantage of native allosteric modulator sites and interdomain pockets which are intrinsic properties of many metabolic enzymes



Cancer metabolism has now arrived at an exciting stage that is full of promise for transforming patient outcomes

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“Drug discovery is the most complicated team sport ever”

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Founder’s Day Retreat 2016

2017 Drug Design and Delivery Symposium “Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism”

Stefan Gross

Scott Edmondson

Director, Enzymology Agios Pharmaceuticals

Director of Chemistry, AstraZeneca

Slides available now! Recordings are an exclusive ACS member benefit.

www.acs.org/acswebinars The 2017 DDDS is co-produced with ACS Division of Medicinal Chemistry and the AAPS

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2017 Drug Design and Delivery Symposium Save the Date for the next webinar!

“Cystic Fibrosis: Treatment and Discovery of CFTR Modulators” Peter Grootenhuis, Senior Director Chemistry, Vertex

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Upcoming ACS Webinars www.acs.org/acswebinars Thursday, March 30, 2017

Sustainability Challenges of the Textiles, Dyeing and Finishing Industries: Opportunities for Innovation Co-produced with the ACS Green Chemistry Institute Richard Blackburn, Associate Professor, University of Leeds Joe Fortunak , Professor of Chemistry, Howard University

Thursday, April 13, 2017

The Good, The Bad and the Uncertain: Public Perception of the Chemical Enterprise Session 3 of the Industrial Science Series Mark Jones, Executive External Strategy and Communications Fellow, Dow Chemical William Carroll, Former Chair of the Board, American Chemical Society

Contact ACS Webinars ® at [email protected]

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2017 Drug Design and Delivery Symposium “Fighting Cancer: Allostery and Targeting Cancer Cell Metabolism”

Stefan Gross

Scott Edmondson

Director, Enzymology Agios Pharmaceuticals

Director of Chemistry, AstraZeneca

Slides available now! Recordings are an exclusive ACS member benefit.

www.acs.org/acswebinars The 2017 DDDS is co-produced with ACS Division of Medicinal Chemistry and the AAPS

63

AAPS Annual Meeting San Diego, CA Nov. 12-15, 2017 Learn about the unique challenges and opportunities in oncology R&D: • • • • •

novel targets and data mining PK/PD translation modality diversity and drug design drug delivery & formulation regulatory requirements for CMC & safety Find more information on this and other themes at:

www.aaps.org/annualmeeting

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Upcoming ACS Webinars www.acs.org/acswebinars Thursday, March 30, 2017

Sustainability Challenges of the Textiles, Dyeing and Finishing Industries: Opportunities for Innovation Co-produced with the ACS Green Chemistry Institute Richard Blackburn, Associate Professor, University of Leeds Joe Fortunak , Professor of Chemistry, Howard University

Thursday, April 13, 2017

The Good, The Bad and the Uncertain: Public Perception of the Chemical Enterprise Session 3 of the Industrial Science Series Mark Jones, Executive External Strategy and Communications Fellow, Dow Chemical William Carroll, Former Chair of the Board, American Chemical Society

Contact ACS Webinars ® at [email protected]

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