label and label-free technologies in synergy · label and label-free technologies in synergy...

Sponsored by:

Participating Experts:

William P. Janzen

University of North Carolina

Chapel Hill, NC

Brian K. Shoichet, Ph.D.

University of California San Francisco

San Francisco, CA

Charles A. Lunn, Ph.D.

Merck Research Laboratories

Kenilworth, NJ

Brought to you by the Science/AAAS Business Office

2 March, 2011

Label and Label-free Technologies in Synergy

Webinar SeriesScience

Creating a Powerful Approach to Drug Discovery

In Vitro Pharmacology

Label and Label-free Technologies in Synergy:


Charles A. Lunn



Kenilworth, New Jersey 07033

21


Technology advances have NOT increased

new drug approval by FDA

• Development costs increasing exponentially, without corresponding increase in drugs into clinic– Munos B. Lessons from 60 years of

pharmaceutical innovation. (2009) Nat Rev Drug Discov. 8(12): 959-968.

– Kola I. The state of innovation in drug development. (2008) Clin Pharmacol Ther. 83(2): 227-230.

• WASHINGTON (Jan. 6) The Food and Drug Administration approved 26 drugs in 2009, compared with 25 approvals in 2008.

Strategies

to find

BETTER

compounds

&

compounds

for non-

traditional

targets

2010’s

22


New technologies within traditional screening

strategies may bias hits

• Biochemistryo Soluble protein domain may not mimic target biologyo Non-native substrate may not mimic target biology

• Cell biologyo Selecting reporter (cAMP, adenylate cyclase, βarrestin) will determine hitso Selecting host cell may determine hits

Du et al, 2009o Recombinant cells may not contain accessory proteins important for target biology

23


The Unknown

As we know, There are known knowns.

There are things we know we know. We also know

There are known unknowns. That is to say

We know there are some things We do not know.

But there are also unknown unknowns, The ones we don't know

We don't know. D. H. Rumsfeld

12 Feb. 2002 Department of Defense news briefing

Biologically relevant assays guard against

underappreciated characteristics of target

24


Label-free methods allow enzymology with native

substrates: High throughput mass spectrometry

Su

bstr

ate

Pro

du

ct

0 min2.5 min

5 min

10 min

15 min

20 min

30 min

60 min

acetate

Wang, et al. A Fluorescence-Based

Homogeneous Assay for Measuring Activity

of UDP±3-O-(R-3-Hydroxymyristoyl)-

Nacetylglucosamine Deacetylase. Analytical

Biochemistry 290, 338–346 (2001).

Quantitate product by thin

layer chromatigraphy

Quantitate amino group

using fluorescamine

Quantitate radioactive acetate

after charcoal adsorption

Bound ligand stabilizes protein,

increasing denaturation temperature

exposing hydrophobic dye binding sites

Langsdorf et al. Screening for antibacterial inhibitors of the UDP-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC) using a high-throughput mass spectrometry assay. J Biomol Screen. 15(1): 52-61 (2010).

25


26

High throughput mass spectrometry useful

for many biochemical target classes

ACETYL-COENZYME A CARBOXYLASE.

Jonas, et al (2009) Comb Chem High

Throughput Screen. 12(8):752-759.

STEAROYL-COA DESATURASE.

Soulard et al (2008) Analytica

Chimica Acta 627(1): 105-111

ACETYLCHOLINESTERASE.

Ozbal, et al. (2004) Assay Drug

Dev Technol. 2(4): 373-81.

PHOSPHATIDYLSERINE

DECARBOXYLASE.

Forbes et al (2007) J Biomol

Screen. 12(5): 628-634.

.


• How to balance to optimize cmpd. development?

Possible advantage of label-free assays for

screening with biologically relevant cells (?)

E.N. Johnson, Ph.D. Dept. Automated Biotechnology Merck & Co., Inc.

Engineered

Cell system

Surrogate

endpoint

Engineered

Cell system

Physiological

endpoint

Cell Line

Endogenous

Expression

Physiological

endpoint

Primary Cell

Endogenous

Expression

Surrogate

endpoint

Primary Cell

Endogenous

Expression

Physiological

endpoint

Category 5 Category 4 Category 3 Category 2 Category 1

(2007) Amer. Drug Discovery, 3 (2): 12-22.

BIOLOGICAL RELEVANCE

TARGET SELECTIVITY

27


• Genzyme’s CXCR4 partial agonistPlerixafor approved for hematopoeiticstem cell mobilization non-Hodgkin's

lymphoma and multiple myeloma.

Elizabeth “Lisa” Smith

UAS-bla plus GP160

CXCR4 plus Hybrid Transactivator

Cell Fusion Assay12k cells plated 3/15/10

0 10 20 301000

2000

3000

4000

5000

Hela

Hela + AMD

U2Os

U2Os+AMD

Hela+U2Os

Hela+U2Os+AMD

Time (hours)

Ref

Imp

ed

an

ce

0 2 4 61000

2000

3000

4000

5000

Hela

Hela + AMD

U2Os

U2Os+AMD

Hela+U2Os

Hela+U2Os+AMD

Time (hours)

Ref

Imp

ed

an

ce

28

CellKey technology may offer

label-free path to biorelevant cells

Seeking unique CXCR4 antagonists blocking HIV-induced cell fusion

Asra Malikzay

NH

NH

N

NH

NH

NH

N

NH

Plerixafor

(AMD 3100;

Tocris Biosci.)

12,000 total cells / well (individual or 1:1 mixture)

1 μM AMD 3100 added (Final volume = 50 μl)

At specified times, plates evaluated for “reference impedance”


Pharmacology of therapeutic target

sometimes hard to predict

• Pharmacology required to exploit anti-inflammatory potential of

cannabinoid CB2 receptor complex

– CB2-specific agonists inhibit1 and induce2 chemotaxis• Montecucco et al, 2008 ; McHugh et al, 2007; Mukhopadhyay et al, 2007; Coopman et al, 2007; Nilsson et

al, 2006; Ghosh et al, 2006; Sacerdote et al, 2000

• Gonsiorek et al, 2007; Tanikawa et al, 2007; Jiang et al, 2007; Kishimoto et al, 2006; Berghuis et al, 2005;

Oka et al, 2004; Jorda et al, 2002

– Cannabinoid agonists inhibit & induce bone growth• Idris et al.(2005); Idris et al (2008); Ofek et al (2006); Karsak et al (2005).

– Cannabinoid CB2 receptor inhibits and exacerbates EAE• Ni et al (2004); Maresz et al (2007); Sipe et al (2005); A.Zimmer and N.Stella, personal communication

• CB2 receptor-specific triaryl bis sulfone inverse agonists function as anti-inflammatory modulators in selected animal models– Inhibit ovalbumin-induced eosinophilia in hypersensitized

mouse (Lunn, et al, 2006a)

– Inhibit methylated BSA-induced monoarticular arthritis (Lunn, et al; 2008)

– Inhibits MOG peptide-induced EAE (Lunn, et al, 2006b)

S

S O O

OO

Cl

F

NH

S

OO

F

F

F

30


PerkinElmer EnSpire Label-Free Analysis:2 Agonists & 1 Inverse Agonist in CHO-hCB2 Cells

-12 -10 -8 -6 -4-20

0

20

40

60

80

100

CP 55,940

WIN 55,212-2

Sch.414319

Conc. (log [M])

Resp

on

se (

pm

)

EnSpire characterization of

cannabinoid CB2 pharmacology

Hill Slope = 0.92

z’ factor = 0.53

Hill Slope = 1.55

z’ factor = 0.46

15,000 cells/well

S

S O O

OO

Cl

F

NS

OO

F

F

F

O

OH

OH

N

O

O

N

O

CP55,940

WIN

Sch.319

31


Another technology-specific hit :

Fenofibrate as CB2 agonist biased for β-arrestin

Characterizing Cannabinoid CB2 Receptor Ligands Using DiscoveRx PathHunter™ β-Arrestin Assay

DEBRA MCGUINNESS, ASRA MALIKZAY, RICHARD VISCONTI, KAREN LIN, MARVIN BAYNE, FREDERICK MONSMA, and CHARLES A. LUNN

(2009) Journal of Biomolecular Screening 14(1): 49-58.

Cl

O

O

O O

● SERENDIPITY: the faculty or phenomenon of

finding valuable or agreeable things not sought for

32

PPARα receptor

agonist activates CB2

with EC50 = 55 nM

CHO vs CHO/CB2+ Fenofibrate

-4 -3 -2 -1 0 1 2 3 40

20

40

60

80

log [nM] Fenofibrate

Zie

C (

ch

an

ge in

oh

ms)

CH

O/C

B2 -

CH

O


Dodgson et al. A 100K well screen for a muscarinic

receptor using the Epic label-free system--a reflection

on the benefits of the label-free approach to screening

seven-transmembrane receptors. (2009) J Recept

Signal Transduct Res. 29 (3-4):163-72.

• A number of compounds were identified which were not found using

a FLIPR-based calcium mobilization assay. May represent

• Off-target false positives … OR …

• Unique opportunities enhancing success for 7TM targets

Successful application of label-free technology

in an HTS environment.

Poor

confirmation

Good

confirmation

33


A.

C.

B.

Traditional biased screening strategy.

Flag unique biology after biased screen.

Confirm target after unbiased screen.

34

Targeting hits from cell-based label-free screen: strategies


Better solution - find better drugs

• Compound libraries reflect the known chemical characteristics of successful therapeutics– Unique resource that must be better utilized

• Better choices for screening assays– Ensure initial compound screen models biology of interest

• Impact choice host cell / assay method

• Better choices of compounds for development– Increase available data on hit compounds, to ensure biology of all

chemotypes tested

• Diminish potency as primary driver for hit selection

• Better choices for Med Chem development

• Label-free technologies offer strategy for unbiased interrogation of compound libraries for best cmpnds

35

Sponsored by:

Participating Experts:

William P. Janzen

University of North Carolina

Chapel Hill, NC

Brian K. Shoichet, Ph.D.

University of California San Francisco

San Francisco, CA

Charles A. Lunn, Ph.D.


Kenilworth, NJ


2 March, 2011




Look out for more webinars in the series at:

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For related information on this webinar topic, go to:

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To provide feedback on this webinar, please e-mail

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Sponsored by:


2 March, 2011




label and label-free technologies in synergy · label and label-free technologies in synergy...

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