rmc phenotypic screening
TRANSCRIPT
Building an in-silico phenotypic screening approach with Reaxys
Olivier BARBERAN
Senior Product Manager
Reaxys Medicinal Chemistry
February 2016
Target-directed and Phenotypic screening: parallel pathways to the
same goal
Phenotypic screening identifies compounds
that produce a biological response in a cell
or animal model
Target screening identifies
compounds that produce a biological
response on an isolated target
Phenotypic screening is the most successful approach
in Drug Discovery Strategy
• Majority of small-molecule first-in-class NMEs
that were discovered between 1999 and 2008
were first discovered using phenotypic assays
• 28 of the first-in-class NMEs came from
phenotypic screening approaches, compared
with 17 from target-based approaches.
• This is despite the current focus of small-
molecule drug discovery on target-based
approaches.
• A possible contributing factor to this trend could
have been a lag time between the introduction
of new technologies and strategies, and their
impact in terms of the number of approved first-
in-class NMEs derived from these approaches.
Bibliographic reference : How were new medecines discovered? D. Swinney
and J. Anthony (Nature Reviews), July 2011
A phenotype-led approach is still very success successful
Bibliographic reference : How were new medecines discovered? D. Swinney
and J. Anthony (Nature Reviews), July 2011
Phenotype - led vs. Target - led
However, a drawback is the need to use time-consuming genetic, chemical and/or
biophysical methods to identify the targets of compounds that are active (Target
deconvolution)
Phenotypic screening can find molecules that have more optimized drug-like
properties (such as cell penetration) than target-based screens.
Why using an in silico Phenotypic screening strategy in drug
discovery
Development of an In Silico Phenotypic screening approach in order to :
2) Building an automated tool in order to establish a target FingerPrint for
disease specific cell lines
1) identify pharmacological targets involved in cell based assay and
understand the molecular mechanisms of action of drugs (MMOA).
7
Scenario Melanoma cells predominantly occur in skin. Melanoma is less common than
other skin cancer. However, it is much more dangerous if it is not found in the
early stages. It causes the majority (75%) of deaths related to skin cancer.
Which are the targets involved in proliferation of melanoma cells lines ? And
which substances are acting on ?
Melanoma Cells
Search In RMC
Which Targets are involved in melanoma cells proliferation ?
Searching Melanoma cells line in Reaxys Medicinal chemistry using cell
taxonomy
Retrieving compounds active on Melanoma cells lines
66666 Substances tested on melanoma cell lines
Including actives and inactives substances Activity < 1µM
17600 Substances inhibiting melanoma cell lines
proliferation (IC50<1µM)
Compounds tested
melanoma cell lines
Melanoma cell lines
On which target active compounds on melanoma cells line are active
on?
Move from
cell lines
dimension
to target
dimension
BRAF, BRAF (V600E),
Ceramide glucosyltransferase
etc….
Targets
Substances
Cell lines
Targets
Affinity
On which target anti proliferative compounds (melanoma cell lines)
are active on?
BRAF (V600E),BRAF,
Ceramide
glucosyltransferase,
Melanocortin 1
Receptor, etc…
IC50<1µM
IC50<10 nM
Melanocortin 1
Receptor, ERK2,
BRAF, Ceramide
glucosyltransferase,
, BRAF (V600E), ,
Melanocortin 4
receptor,
CB1 receptors,
In silico Phenotypic screening Automated Process using
API and Pipeline pilot node
Target Fingerprint on A375 Melanoma cells : Overview
996
molecules
Cell line A375
IC50 <= 1µM
996 molecules +In
vitro Biological
results on targets
In vitro Biological
results on targets
Define activity class of
compounds
active / inactive on target
Target active
ratio calculation
Biological Threshold @ 1µM
Actives
Inactives
For each activity point!
PipelinePilot process to define activity class
Define activity class of compounds
For each compound and its given target:
Compound_Active_Ratio = (#Actives) / (#Actives + #Inactives)
Active if Active_Ratio ≥ 0.8
Inactive if Active_Ratio ≤ 0.2
Target Fingerprint on A375 Melanoma cells : Overview
996
molecules
Cell line A375
IC50 <= 1µM
996 molecules +In
vitro Biological
results on targets
In vitro Biological
results on targets
Define activity class of
compounds
active / inactive on target
Target active
ratio calculation
Target active ratio calculation
For each Target, count the number of Active and Inactive molecules
Target_Active_Ratio = (#Actives - #Inactives) / (#Actives + #Inactives)
Target FingerPrint for A375 cell line
#Molecules >= 20
Target FingerPrint of A375 cell lines
#Molecules >= 20
Average Activity
Rate in RMC
All compounds are
active on the target
Activity rate =1
All compounds are
not active on the
target
Activity rate = -1
Target Fingerprint of A 375 Melanoma cells based on Similar Compounds
996
molecules
Cell line A375
IC50 <= 1µM
3525 molecules
+In vitro Biological
results on targets
In vitro Biological
results on targets
Define activity class of
compounds
active / inactive on target
Target active
ratio calculation
3525
molecules
Chemical Similarity
Search 85%
Target Fingerprint of A375 based on similar Compounds
(85% similarity)
Target Fingerprint of A375 based on similar Compounds
(85% similarity)
#Molecules >= 20
Average Activity
Rate in RMC
A3R and A375 melanoma cells relationship in literature
• On A375 cells, A3R stimulation activated PI3K which induced Akt
phosphorylation resulting in reduced levels of phosphorylated
ERK1/2.
• A3R agonist (Cl-IB-MECA) inhibits cell proliferation
• Agonist effect abolished by A3 receptor antagonist
• No effect of A1, A2a and A2b receptors antagonists
• Merighi et al., 2005 (J. Biol. Chem.)
Conclusion
Using Reaxys API and Pipeline pilot an automated process was set up to
establish a target FingerPrint for disease specific cell lines.
Reaxys Medicinal chemistry provides High Quality data to identify
pharmacological targets involved in phenotypic screening and understand the
molecular mechanisms of action of drugs (MMOA).