A Workshop on High Throughput / High Content Screening
Applications to Target-based Drug Discovery Research
SMALL MOLECULE SCREENS
Clifford Stephan, Ph.D.
Research Assistant Professor
John S. Dunn GCC Chemical Genomics Research Consortium
Scott R. Gilbertson, Ph.D.
Professor
M.D. Anderson Chair in the College of Natural Sciences and Mathematics
Department of Chemistry, University of Houston
Stages of Commercial Drug Development
Basic
Research
Target
Validation
HTS and
Lead Id
Lead Opt
Preclinical
Tox
File IND
Clinical
Phase 0/1
Clinical
Phase 2
Approval
Sales
Marketing
Phase 4
Clinical
Phase 3
File NDA
Drug Development is a game of attrition. The Challenge … Select 1-2 compounds
from the millions of possibilities that will be safe and efficacious in humans
Stages of Academic Drug Development
Basic
Research
HTS and
Lead Id
Lead Opt
Still a game of attrition. The Challenge …
Identify agents that increase the fundamental scientific knowledge
for a particular target with the possibility of providing further validation
of the target as a ‘druggable’ target.
Retain the possibility of identifying a lead series of compounds
that could take our research in new, unexpected directions.
The possibility of establishing intellectual property and the basis for a
future pharmaceutical.
Why perform High Throughput Screening?
HTS enables the testing of large numbers of chemical
substances for activity in diverse areas of biology in
a relatively short time.
The entire chemical space of small organic molecules is
estimated to be > 1060. Of those, ~ 2.7 x 107 compounds
have been registered and made. (Nature Insight, 2004)
Responses studied can range from biochemical
systems of purified proteins or enzymes to signal
transduction pathways to complex cellular networks
(Systems Biology).
High Throughput Screening: A relative term
HTS in Pharma and Biotech is a process loosely defined as
testing 10,000 to 100,000 data points/day using ‘industrialized’ methods
UltraHTS test >1,000,000 data points/day
HTS in the Dunn Screening Core the potential of screening
100’s to >10,000 data points/day following Pharma industry standards
10,000
100,000
Compounds/day Compounds/day
96-Well plate
(80 compounds/plate)
125 Plates/day
1250 Plates/day
384-Well plate
(320 compounds/plate)
32 Plates/day
313 Plates/day
1536-Well plate
(1280 compounds/plate)
8 Plates/day
78 Plates/day
The Screening Continuum
From a poster by RR Tice et al of the National Toxicology Program HTS Initiative, 2007
Classes of HTS Assays
Homogeneous
‘Mix and Read” style assays
Simple with addition steps only, higher throughput
Examples:
Cell viability
Live cell imaging
Proximity (e.g., radioisotope, FRET, ALPHA)
Enzyme Kinetics
Heterogeneous
Traditional style assays
Multiple steps, more manipulations, slower throughput
Examples:
Traditional binding assays
Traditional sandwich ELISA
Compare Traditional Assays with HTS Assays
Parameter
Traditional Assay
HTS Assay
Protocol
Complex, numerous steps
Simple, few steps (3-5)
•Multiple Additions
•Multiple Aspirations
•Multiple Washes
Assay Container
Varied
Tubes/slides/dishes/cuvettes/animal
s
•Additions
•Aspirations - discouraged
•Washes - discouraged
Microtiter plates
96/384/1536-Wells
Assay Volume
0.1 to 1 mL
< 1 μl to 100 μl
Reagents
Varied
Consistent
•Limited quantity
•Various batches
•Limited stability
Variables
Many
•QS for complete screen
•Single batch - preferred
•Prolonged stability
Compound
•Time/temperature
•Ligand/substrate concentration
•Cell type
Readout Time
Milliseconds to months
Minutes to hours
Output Formats
Varied
Plate reader
Readers/scoring/image
interpretation
Absorbance/fluorescence/
luminescence
Key factors for successful HTS
Time
time/well
wells/day
screens/year
project time
HTS
Screen
Quality
few false positives
few false negatives
S:N,SW,z’-Factor
Validated ‘Hits’
Costs
reagents
consumables
instrumentation
personnel
HTS: An Iterative Process
Research groups
HTS Group
Target Id and Validation
Develop Primary and Secondary assays
Define criteria for active compounds
Direct ‘Hit’ improvement process
Perform Primary Screen
Purpose: Identify a starting place
Method: Interrogate libraries of
compounds/genes
Chemistry groups
HTS Group
Analysis and interpretation of Data for
Structure Activity Relationships
Refine and improve identified ‘Hits’
Modeling and medicinal chemistry
Selection of compounds for screening via
virtual screening, focused libraries
Secondary Screen
Purpose: Validate initial ‘Hits’
Method: Selection of compounds
or medicinal chemistry
Critical Issues to be Addressed Prior to
Testing the First Compound
Key factors that must be addressed prior to screening:
• Assay protocol (miniaturization/simplification)
• DMSO resistance (test 0.1 - 5%), standard compound vehicle
• Reagent quantity and batch consistency
• Reagent stability for storage and use under assay conditions
• Appropriate positive and negative controls
• Assay reproducibility and signal stability
• Available secondary or counter screen to test target
specificity and selectivity
Consider: Reagent Quantity
Compare traditional assays with HTS assays
30,000 Compounds
Traditional Assay
96-Well HTS
384-Well HTS
Plates/Day
1
40
40
Total Plates
5
375
94
Cells/Day
1 x 106
40 x 106
40 x 106
Total Cells
5 x 106
375 x 106
94 x 106
Total Assay
Volume (μL)
100
100
25
μL/Well User purified
reagent
10
10
2.5
mL Purified rgt/plate
1
1
1
mL Total purified rgt
5
375
94
Consider: Reagent Stability
Compare traditional assays with HTS assays
Traditional assay:
Reagent stability
30-minutes to manually setup plate
2-hr incubation for an end-point measurement
5-minutes to read plate
Reagents need to be stable for up to ~2.5hr
HTS assay:
Reagent stability
5-minutes to setup each plate
2-hr incubation for an end-point measurement
5-minutes to read plate, 40 plates/run total
Reagents need to be stable from first to last plate
Up to ~3 hrs for plate setup, ~3hr read time
Up to 8 hrs from start to finish
Can remaining reagents be reused
Consider: Availability of appropriate
positive and negative controls
Traditional assessments of assay quality
S/B = Mean PosCtl / Mean NegCtl
S/N = (Mean PosCtl - Mean NegCtl) / StdDev NegCtl
Assay 1
Ve+ mean 50, Ve- mean 10
S/B = 5, S/N = 13
Assay 2
Ve+ mean 112, Ve- mean 10
S/B = 11, S/N = 39
250
70
60
200
50
150
40
ve+
ve+
ve-
ve30
100
20
50
10
0
0
0
8
16
24
32
40
48
56
64
72
80
88
96
0
8
16
24
32
40
48
56
64
72
80
88
96
Availability of appropriate
positive and negative controls
Common HTS assessment of assay quality
(3 * StdDev PosCtl) + ( 3 * StdDev NegCtl)
z’ = 1 - ----------------------------------------------------------Mean PosCtl - Mean NegCtl
Availability of appropriate
positive and negative controls
Common HTS assessment of assay quality
70
60
50
40
ve+
ve-
Separation Band
30
20
10
0
0
8
16
24
32
40
48
56
64
72
Ve+ mean 50, Ve- mean 10
S/B = 5, S/N = 13, z’ = 0.5
80
88
96
Availability of appropriate
positive and negative controls
Common HTS assessment of assay quality
250
200
150
ve+
ve100
50
0
0
8
16
24
32
40
48
56
64
72
Ve+ mean 112, Ve- mean 10
S/B = 11, S/N = 39, z’ = 0.0
80
88
96
Availability of appropriate
positive and negative controls
Common HTS assessment of assay quality
z’ = 1
An ideal assay
1 > z’ ≥ 0.5
A good assay
0.5 > z’ > 0
Assay will require replicates
z’ = 0.5 z’ = 0
“Yes/No” type assay
z’ = 0.1
Assay Issues to be Addressed Prior to
Testing the First Compound
Plate Uniformity and Signal Variability Testing
Critical testing of an assay system prior to screening for all assays
run in the core
These assays test the performance of the following controls:
Maximum signal reference (highest assay end point)
Minimum signal reference (background/lowest assay end point)
Midrange signal reference (signal variability assessment)
Assay Issues to be Addressed Prior to
Testing the First Compound
For all assays run in the core, similar results must be obtained
over three separate days (independent experiments in triplicate)
using all equipment and compound vehicle that will be used
during the screen.
Acceptance criteria:
Intraplate variability:
No apparent edge effects or drift
%CVmax and %CVmin < 20%
z’ ≥ 0.4
Interplate and Inter-Day variability:
Midrange control < 2-fold within a single day
Midrange control < 2-fold across any two days
What Are These Small Molecules We Test?
They are not DNA, RNA, or protein macromolecules
Practical Definition:
An organic molecule of less than 1000 Daltons
Typically in the range of 300-700 Daltons
Small organic molecules made by living organisms
(e.g., natural products)
Small organic molecules made by chemists
(e.g., organic compounds, RNAi)
In all cases one is looking for a small ‘drug-like’ organic
molecule that displays a biological activity
(e.g., agonist, antagonist) with the target of interest.
How Does One Select a Library to Screen?
Random Selection
Random high throughput screening
Little is known about the target
Few or no active compounds as guides
Computational Chemistry/Virtual Screening
Creation of ‘Focused Libraries’
Requires prior knowledge about target
Active compounds, 3D-Structure
Sequence homology
Prior Experience
Library successfully used for similar
or related targets
Core Lab HTS Hit Guidelines
On each screening day, z’-factor (controls) is evaluated
for every plate
Controls must meet original acceptance criteria
previously defined for the assay
Only outliers
because
z’ = 0.5dropped are those created z’
= 0.1
of assay error or those > 3 SD from mean for all of
that particular control
No more than 10-25% of a particular control will be
dropped for any particular plate
Core Lab HTS Hit Guidelines
Active compounds are those outside 3 SD from the mean
for all test agents on a valid plate.
If replicates are performed, a test agent must be active on
≥ 66% of all replicates to be classified as active.
‘Hits’ are those active compounds that demonstrate
concentration response upon reorder and retest.
Helpful References:
Inglese J, Johnson RL, Simeonov A, Xia M, Zheng W, Austin CP, Auld DS.
High-throughput screening assays for the identification of chemical probes.
Nat Chem Biol. 2007 Aug;3(8):466-79.
Zhang JH, Chung TD, Oldenburg KR.
A Simple Statistical Parameter for Use in Evaluation and Validation of
High Throughput Screening Assays.
J Biomol Screen. 1999;4(2):67-73.
Iversen PW, Eastwood BJ, Sittampalam GS, Cox KL.
A comparison of assay performance measures in screening assays:
signal window, Z' factor, and assay variability ratio.
J Biomol Screen. 2006 Apr;11(3):247-52.
Inglese J, Shamu CE, Guy RK.
Reporting data from high-throughput screening of small-molecule libraries.
Nat Chem Biol. 2007 Aug;3(8):438-41.
National Institutes of Health (NIH) Chemical Genomics Center (NCGC),
a member of the Molecular Libraries Probe Production Center Network.
http://ncgc.nih.gov/
Cliff Stephan, Ph.D.
B.A. Chemistry and
Molecular Biology
Postdoctoral training
Cardiovascular Division
Ph.D. Pharmacology
Research Instructor, Cardiovascular Department, Hypertension Division
Director of High Throughput
Screening
Head of the John S Dunn Central Screening
Core Laboratory