Biased Ligand Quantification

in Drug Discovery: From

Theory to HTS to Identify

New Biased µ Opioid

Receptor Agonists

Opioids are the most effective analgesics

available clinically

• Opioids remain the most

efficacious analgesic

• Commonly prescribed:

• WW market $12.2Bn

US analgesic prescriptions

by class

Opioids

US sales: $7.3Bn. WW market $12.2Bn

Biased Agonism at GPCRs/7TMs

DESIRED UNWANTED

Stabilisation of different

active conformations of

the receptor

The origins of bias we measure

Christopoulos Reciprocal Relationships: The Ying & Yang of GPCR Allostery

NO

SAR

NO

SAR

The use of a common

reference can overcome

observational and system

bias

Calculating ligand bias

• A key requirement for all methods of biased ligand quantification is a scale which

accounts for both potency and maximal response of the agonist and the use of a

common reference compound to overcome observational and systemic bias.

• The “gold standard” method for describing agonist activity is the operational

model of Black and Leff (1983).

• This furnishes a parameter log(τ/KA) which when combined with common

reference gives Δ log(τ/KA). (Kenakin and Christopoulos 2013) a measure of

relative agonist activity.

Δlog(τ/KA) = log(τ/KA)test - log(τ/KA)ref

• and finally ΔΔlog(τ/KA) – which is a measure of pathway bias for a given

compound.

• ΔΔlog(τ/KA) = Δlog(τ/KA)pathway1 - Δlog(τ/KA)pathway2

• This is great, BUT it is not practical on an industrial scale where 200-300 curves

are fitted in a single experiment, is there a simpler alternative ?

ΔΔlog(Emax/EC50) – A simple alternative ?

• When the slope =1 then (τ/KA) = (Emax/EC50) (Ehlert et al 1999,

Kenakin and Christopoulos 2013).

• This can be calculated from the Emax and EC50 estimated from

the concentration response curves for the compound and

reference as shown below.

∆log(Emax/EC50) = log(𝐸𝑚𝑎𝑥

𝐵

𝐸𝐶50𝐵) − log(

𝐸𝑚𝑎𝑥

𝐴

𝐸𝐶50𝐴) where A is the reference and B the test compound

• But can we use it if slope ≠ 1 ?

Assay technologies

DiscoveRx PathHunter βarrestin

Cisbio HTRF cAMP

35S GTPγS binding

Optimising assays to support HTS - cAMP

The GTPγS assay is not suitable for HTS so an alternative cAMP assay was

developed.

Standards gave similar values of agonist activity in both assays analysed by

either Δlog(τ/KA) or Δlog(Emax/EC50).

U20S β-arrestin DiscoveRx assay

• Difficult to resolve compounds with

Emax less than morphine – which are

potentially interesting compounds.

• We knew U2OS cells have low

expression of GRKs. Which are

involved in the recruitment of βarrestin.

Nickolls et al 2013

-1 0 -9 -8 -7 -6 -5

-2 0

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

[D A M G O ] lo g [M ]

% m

ax

eff

ec

t o

f P

fiz

er S

tan

da

rd

1

U n tra n s d u c e d

M O I 2

M O I 5

M O I 1 0

M O I 5 0

Untransduced

MOI 2

MOI 5

MOI 10

MOI 50

Emax (%)

95.0

92.9

103.1

108.5

109.7

Slope

1.39

1.01

1.05

1.21

1.37

EC50 (M)

1.6e-007

3.8e-008

2.1e-008

9.5e-009

6.8e-009

A

-1 0 -9 -8 -7 -6 -5

-2 0

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

[m o rp h in e ] lo g [M ]

% m

ax

eff

ec

t o

f P

fiz

er S

tan

da

rd

1 U n tra n s d u c e d

M O I 2

M O I 5

M O I 1 0

M O I 5 0

Untransduced

MOI 2

MOI 5

MOI 10

MOI 50

Emax (%)

27.0

46.3

70.5

92.9

96.2

Slope

1.10

0.94

0.91

0.88

0.99

EC50 (M)

2.4e-007

6.2e-008

4.0e-008

3.0e-008

1.7e-008

B

The effect of increasing GRK2 expression on the pharmacology of DAMGO (A) and

morphine (B) in the PathHunter ß-arrestin2 assay.

morphine DAMGO

Effect of GRK2 co-expression

Agonist activity of a set of 10 standard compounds in the PathHunter ß-

arrestin2 assay +/- GRK2, calculated using Δlog(τ/KA) and

Δlog(Emax/EC50).

Co-expression of GRK2 increased the

dynamic range of the assay without a

large effect on the relative agonist

activity as measured by either

Δlog(τ/KA) or Δlog(Emax/EC50).

Pathway bias calculation

Pathway bias values for standard compounds determined using ΔΔlog(τ/KA)

or ΔΔlog(Emax/EC50)

Biased towards cAMP

Biased towards βarrestin

Pathway bias values and the

associated 95% confidence

intervals. A paired t test showed no

significant difference (p=0.52) and a

correlation coefficient of r = 0.863.

HTS output

Diversity of pathway bias across hit compounds.

(τ/KA) vs. (Emax/EC50)

Correlation of pathway bias values determined using either

ΔΔlog(τ/KA) or ΔΔlog(Emax/EC50).

Pathway bias values and the associated 95% confidence

intervals. A paired t test showed no significant difference

(p=0.52) and a correlation coefficient of r = 0.863.

Conclusions

• Ligand bias has the potential to give us new and improved

therapeutics to treat disease.

• Drug discovery has a wealth of in vitro assays with which to

screen for activity and bias. However, making sense of the

results to drive forward SAR can be confounded by both

observational and systemic bias.

• The use of the log(τ/KA) and a common reference overcomes

these issues, but it is practically impossible to perform this

analyses on an industrial scale where 200-300 curve fits are

performed per experiment.

• Our data has confirmed that log(Emax/EC50)* can be used as a

simple to apply alternative which allowed us to rapidly calculate

activity and bias in a consistent manner and triage the output

from an HTS for further screening and analysis.

* If slope ~1ish

Acknowledgements

• Pfizer Neuroscience and Pain UK

Darren Cawkill, Mellissa Clark, Sarah Nickolls, Sian Humphreys,

Gordon McMurray & Nigel Swain.

• University of North Carolina - Terry Kenakin

Pfizer Confidential │ 17