Joe Olechno1, Sean Ekins2, Antony Williams3, Rich Ellson1

Pittcon 2013Session 26703:55 PM, March 21, 2013

Liquid Handling Processes Impact Computational Modeling in Drug Discovery

1. Labcyte Inc.2. Collaboration in Chemistry3. Royal Society of Chemistry

•What is Acoustic Liquid Handling?

•Serial Dilutions vs. Direct Dilutions

•Lead Optimization and Pharmacophores

•The Impact of Serial Dilutions on Drug Discovery

•Conclusions

Agenda

2

3

Acoustic Droplet Ejection (ADE)

Comley J, Nanolitre Dispensing, Drug Discovery World, Summer 2004, 43-54

4

• Extremely precise• Extremely accurate• Rapid• Auto-calibrating• Completely touchless

– No cross-contamination– No leachates– No binding

Acoustic Droplet Ejection (ADE)

Acoustic energy expels droplets without physical contact

0

2.5

5.0

7.5

10.0

12.5

15.0

0.1 1 10 100 1000 10000Volume (nL)

%CV

Comley J, Nanolitre Dispensing, Drug Discovery World, Summer 2004, 43-54

•What is Acoustic Liquid Handling?

•Serial Dilutions vs. Direct Dilutions

•Lead Optimization and Pharmacophores

•The Impact of Serial Dilutions on Drug Discovery

•Conclusions

Agenda

5

Conventional Dose-Response Set-up by Serial Dilution

Assay Plate

Intermediate Buffer Dilution Plate

Source Plate

7

Serial Dilution vs. Direct DilutionSerial with Tips Direct with Acoustics

• Equal volumes of changing concentrations

• Errors are compounded

• Compounds are sequentially diluted. Each new dilution is the source for the next step.

• Many “touches” with tips (or significant potential for carry-over or leachates)

• Touchless—no carry-over, leachates or binding

No solute lost

• Low-volume assays with low solvent concentration

• Maximum of one dilution step

• Changing volumes of equal concentrations

• Reduced errorSerial Dilution

Direct Dilution• Low-volume assays with high solvent concentration (or compound loss)

Direct Dilution Process

Third StepTransfer 75, 25,

7.5 and 2.5 nL of each hit to four consecutivewells

Source Plate Assay Plate

Intermediate Plate

First StepTransfer 252.5and 2.5 nL to two wells in an intermediate plate

Second StepDilute intermediateplate with 25 mL DMSO in each well

Fourth StepTransfer 75, 25, 7.5 and 2.5 nL of each dilutedsample to four consecutive wells of the assay plate(30, 10, 3 and one droplets, respectively)

(30, 10, 3 and one droplets, respectively)

Intermediate Plate

12-point curves

•What is Acoustic Liquid Handling?

•Serial Dilutions vs. Direct Dilutions

•Lead Optimization and Pharmacophores

•The Impact of Serial Dilutions on Drug Discovery

•Conclusions

Agenda

9

Traditional Scaffold Modifications

Fibrinogen Receptor Inhibitor

10

HNH2N

NH

HN

NH

HN

NH2 O

OO

O

OH

OHO

HNH2N

NH

NH

HN

O

OH

OHO

O

O

H2N

NH

NH

N

O

O

O CH3

H2N

NH

HN

NH

O

O

O

O CH3

CH

IC50 = 29 µM

IC50 = 3 µM

IC50 = 0.15 µM

IC50 = 0.067 µM

Poor stability, poor bioavailability, non-patentable

Poor oral availability

Excellent oral availability, good stability

Poor stability, poor bioavailability

But what to do if the structures are dissimilar?

N

H3CO

NCl

N

N

NH

Cl

OBoth compounds bind strongly to the GABAA receptor.

These compounds are extremely different in structure but both have the same effect. Is there a way to reconcile this and generate information to make new drugs?

Diazepam CGS-9896

12

•Describes the optimal binding of a protein to a ligand.

•Shows how different structures bind to same site.

•Designed from screening data.

Pharmacophores

Hydrophobic pocket

GABAA Receptor Pharmacophore

Hydrogen bond acceptor

Hydrogen bond donor

Hydrophobic pocket

GABAA Receptor Pharmacophore

Hydrogen bond acceptor

Hydrogen bond donor

•What is Acoustic Liquid Handling?

•Serial Dilutions vs. Direct Dilutions

•Lead Optimization and Pharmacophores

•The Impact of Serial Dilutions on Drug Discovery

•Conclusions

Agenda

15

Real World Data – EphB4 Receptor

16

Compound #

5 0.002 0.5534 0.003 0.1467 0.003 0.778

W7b 0.004 0.1528 0.004 0.445

W5 0.006 0.0876 0.007 0.973

W3 0.012 0.049W1 0.014 0.1129 0.052 0.17010 0.064 0.817

W12 0.158 0.250W11 0.207 14.40011 0.486 3.030

3.312.8

1.669.6

6.2

8.2

IC50 Acoustic (µM) IC50 Tips (µM) Ratio IC50Tip/IC50ADE

276.548.7

259.342.5

111.313.7

139.04.2

Barlaam et al., WO2009/010794Barlaam et al., US 7,718,653

14 compounds with structures and IC50 data.

Real World Data – EphB4 Receptor

17

-3 -2 -1 0 1 2

-3

-2

-1

0

1

2

Log IC50-acoustic

Lo

g IC

50-t

ips

The acoustic technique always provided a more potent IC50 value.

The greater the distance from the red line, the greater the difference in IC50 values.

18

Experimental Process Flow

14 Structures with Data

Acoustic Model

Tip-based Model

Generate pharmacophore models

for EphB4 receptor

Initial data set of 14 WO2009/010794, US 7,718,653

AZ Pharmacophores

Pharmacophore Hydrophobic features

Hydrogen bond

acceptors

Hydrogen bond donors

Observed vs predicted

IC50

Tip-based 0 2 1 0.80

Acoustic based 2 1 1 0.92

Tip-based pharmacophore Acoustic-based pharmacophore

20

Experimental Process Flow

14 Structures with Data

Acoustic Model

Tip-based Model

Generate pharmacophore models

for EphB4 receptor

Acoustic Model

Tip-based Model

Test models against new

data

Results

Results

Independent data set of 12 WO2008/132505

Initial data set of 14 WO2009/010794, US 7,718,653

Compounds Tested with Tip-based Pharmacophore

22

W084.1 0.3488 0.297

W084.2 0.3806 0.456

W084.4 0.6994 0.374

W082.2 0.8392 0.808

W082.4 1.4989 6.270

W083 2.8229 0.198

W084.3 2.9119 0.473

W082.1 3.3829 1.120

WO81 NOT RETRIEVED 38.300

WO82.3 NOT RETRIEVED 1.780

NameTip-based IC50

Prediction (mM)Tip-based IC50

Actual (mM)

Barlaam wo2008/132505

Tip-Based Pharmacophore – Predicted vs. Measured

23

0.1 1 100.100

1.000

10.000

R² = 0.000181499868866175

Predicted Tip-based IC50

Me

as

ure

d T

ip-b

as

ed

IC5

0

1 2 3 4 5 6 7 81

2

3

4

5

6

7

8

R² = 0.183673469387755

Predicted Rank OrderM

ea

su

red

Ra

nk

Ord

er

The pharmacophore developed from tip-based data is an extremely poor predictor of measured activity.

Results of Testing Pharmacophores

Acoustic Pharmacophore Tip-based Pharmacophore

Correctly predicted rank of the most potent compounds

Poor correlation (R2<0.0002) between predicted and measured

The model was inadequate to predict activity of 20% of compounds

Compound with highest measured activity was predicted to have poor binding

Compound predicted to be most active actually had poor activity

24

25

Experimental Process Flow

14 Structures with Data

Acoustic Model

Tip-based Model

Generate pharmacophore models

for EphB4 receptor

Acoustic Model

Tip-based Model

Test models against new

data

Acoustic Model

Tip-based Model

Test models against X-ray crystal structure

pharmacophores

Results

Results

Independent crystallography data Bioorg Med Chem Lett 18:2776; 18:5717; 20:6242; 21:2207

Independent data set of 12 WO2008/132505

Initial data set of 14 WO2009/010794, US 7,718,653

Final Nail in the Coffin – X-Ray Crystallography

•All pharmacophores created from X-ray structures had both hydrophobic and hydrogen bonding features.

•The EphB4-ligand crystal pharmacophore most closely reflects the acoustic pharmacophore.

Pharmacophore Hydrophobic features

Hydrogen bond acceptors

Hydrogen bond donors

Tip-based 0 2 1

Acoustic based 2 1 1

Crystal based (consensus)

2 1 1

•What is Acoustic Liquid Handling?

•Serial Dilutions vs. Direct Dilutions

•Lead Optimization and Pharmacophores

•The Impact of Serial Dilutions on Drug Discovery

•Conclusions

Agenda

27

Reasons to Worry

•This case strongly suggests that aqueous, serial dilutions transferred with tip-based techniques lead researchers away from the most potent drugs.

• How universal is this phenomenon?

28

Acoustic vs. Tip-based TransfersAdapted from Spicer et al., Presentation at Drug Discovery Technology, Boston, MA, August 2005

Adapted from Wingfield. Presentation at ELRIG2012, Manchester, UK

Adapted from Wingfield et al., Amer. Drug Disco. 2007, 3(3):24

Aqueous % Inhibition

Ac

ou

sti

c %

In

hib

itio

n

0 20 40

0

-20

-40

60 80

10

06

08

0

100

-20

-40

20

40

0 10 20 30 40 50

01

02

03

04

05

0S

eri

al

dil

uti

on

IC

50 μ

M

Acoustic IC50 μM

104

104

103

102

10

1

10-1

10-2

10-3

Se

ria

l d

ilu

tio

n I

C50

μM

Acoustic IC50 μM10310210110-110-210-3

Log IC50 acousticL

og

IC

50 ti

ps

Data in this presentation

Reasons to Worry

•This case strongly suggests that aqueous, serial dilutions transferred with tip-based techniques lead researchers away from the most potent drugs.

• How universal is this phenomenon?

• Sticky surfaces– Many solutes stick to walls and tips at low concentrations– Dose-response experiments require precision solute-handling over

many logs.

30

Conclusions

•Tip-based aqueous serial dilutions

•Databases, public and private, should annotate this meta-data along with biological data.

•We encourage researchers to make their data available to expand this study.