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Lecture given in Albin Sandelins course on high throughput biology. Here I talk about RNA directed drugs and how we apply bioinformatics and large data sets to facilitate drug discovery and development. First edition of this talk is from 2011, with a few updates in 2013 and 2014. All data has been published previously elsewhere.
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Drugs directed against RNA
- a bioinformatics perspective
Morten Lindow
Associate director, Informatics
Santaris Pharma A/S
Goals for today Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT
R&D productivity is falling
Sections Introduction to regulatory oligonucleotides
Locked nucleic acids with phosphorothioate backbones
Invention, affinity, PK
Targeting mRNAs
ApoB, PCSK9
Targeting microRNA
miR-122
Deciphering target biology
Clinical trials
Most drugs work on proteins
…GGGCGACACUCCACCAUGAAU……
translation
CGCUGUGAGGUG
GUA
|||||||||||||||
Chemically diverse
3D
Many types of interactions with ligands
Diverse cellular compartments
Hard to develop regulator
Chemically simple
1D
Fewer cellular compartments
Easy to develop regulator
RNAseHRISC
RISC
Enzyme-directing oligonucleotides
ASOs siRNA miRNA
+ Draw on the white board to explain different classes of regulatory oligonucleotides
Designing oligos as RNA regulators
miRNAssiRNAs
Natural selection
ASOs
Intelligent design
(oligoinformatics)
TargetSurveyor.pl
?
Lindow et al.,
PLoS Comput Biol. 2007
Plant genomes have
>2000 genomic pre-miR
structures with
complementarity to
mRNA. Just waiting for
the right niche to show up.
How to bioinformatically find the
best target site on a mRNA? Which attributes would you look for?
How would you implement them?
• Vast compound libraries
• Combinatorial chemistry
• High through put screening on
primary target
• Specificity screen on related
receptors
• Tolerability screen
Lead optimization
Clinical development
CGCUGUGAGGUGGUA
|||||||||||||||
CCCCCUGAUGGGGGCGACACUCCACCAUGAAUCACUCCCCUG
~2 m
onth
s
TargetSurveyor.pl
Automated oligosynthesis
qPCR
23 optimized leads
2 in pre-clinical dev
2 in phase 1
1 in phase 2
~2 y
ears
Both Nature and Business make
use of oligonucleotides
Take 2 minutes to talk to your
neighbour and update your notes Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT
LNA
Invention, structure, PK
Inventor Professor Jesper WengelUniversity of Southern Denmark
Exclusive worldwide rights fortherapeutic use
Owns the rights to everything else
LNA, Locked nucleic acid
In LNA ribose is locked in an RNA-like conformation
High stabilityHigh affinity
Take 2 minutes to talk to your
neighbour and update your notes Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT
Two metabolic targets for gapmers
ApoB-100
PCSK9
Low density lipoprotein
LDL in serumAtherosclerosisIncreases the risk of
apoB-100
is a component of
LDL-receptor
removes
PCSK9
enhances
degradation of
SPC3833
SPC4061downregulates
downregulates
ApoB mRNA reduction leads to lowering of total cholesterol
fat diet, saline treated
normal diet, saline treated
fat diet, anti-apoB-gapmers
Niels Fisker, Marie Lindholm, M. Hedtjärn, C. Rosenbohm and Ellen Marie Straarup
Low density lipoprotein
LDL in serumAtherosclerosisIncreases the risk of
apoB-100
is a component of
LDL-receptor
removes
PCSK9
enhances
degradation of
SPC3833
SPC4061downregulates
downregulates
PCSK9 in mice
PCSK9 mRNA is reduced
Mice were treated with a
single i.v. injection of 20 mg/kg
LDLR protein is reduced
Niels Fisker, Marie Lindholm, M. Hedtjärn, C. Rosenbohm and Ellen Marie Straarup
PCSK9 antagonism leads to lowered
LDL in mice
PCSK9 mRNA is reduced
LDLR protein is reduced
total cholesterol
is reduced
serum LDL is reduced treatment - +
Time for a break
Targeting microRNA
LNA-antimiR – miravirsen
- an oligo to regulate an oligo
RISC
miR-122
miravirsen
Inhibits expression
8 LNA,
7 DNA
Wienholds et al, Science (2005)
Antagonism of miR-122 leads to
reduced plasma cholesterol
Elmen&Lindow et al, Nature 2008
Esau et al, Cell Metab 2006
Kreutzfeldt et al. Nature 2005
Single i.v. injection of
miravirsen in mice
Three i.v. injections of miravirsen
in African green monkeys
miR-122 and hepatitis C virus
HCV is a single stranded RNA virus
HCV genome resembles an mRNA
170 million infected worldwide
Current treatment often ineffective and
with serious side effects
2x miR-122 binding
sites in 5’NTR Viral replication
Jopling et al, Science 2005
Elmen&Lindow et al., Nature 2008
HCV is the target indication for
miravirsen
Discuss (5 minutes):
advantages and disadvantages or targeting a host factor vs direct targeting
of viral molecules
?
?
?
?
Can miravirsen reduce HCV-load in vivo?
Can HCV mutate to escape miravirsen treatment?
What is the physiological role of miR-122?
Does miravirsen have any off-targets?
miravirsen reduces HCV in
chimpanzees
Lanford et al, Science 2010How would you spot viral escape mutants?
Can HCV mutate to escape
miravirsen treatment?
Cooper et al, J Hepat, 2009
Direct-acting small molecule inhibitor
of viral RNA polymerase
Period of treatment
Rebound during
treatment
Lanford et al, Science 2010
LNA-antimiR targeting the host factor
miR-122
Rebound 2 weeks after
end of treatment
Deep sequencing of virus from
treated animalsHCV specific primers to amplify miR-122 binding region
454 deep sequencing
73,000 to 214,000 reads at 4 time points
Does frequency of variants change?
No evidence of viral escape from
miravirsen!
What is the physiological role of miR-122?
Are miR-122 targets upregulated after miravirsen
treatment? Can this be used as an efficacy
endpoint?
Is there a non-sequence specific effect of treatment
with LNA-oligos?
Is there a sequence specific effect of treatment with
miravirsen? (off-target effect on mRNAs?)
Antagonism of miR-122:
Effects on gene expression
Distance between transcriptomes
Data from Elmen & Lindow et al, Nature 2008
5 fat mice treated with miravirsen
5 fat mice treated with 2 mismatch control
5 fat mice treated with saline
Are miR-122 targets upregulated
after miravirsen treatment?
RISC
miR-122
Inhibits expression
ProblemOn the level of the individual gene only a few targets are
significantly upregulated (n=5) and only with about 25%
How can we get more power, by utilizing the fact that
miR-122 regulates many (several hundred) genes?
Sequence and expression analysis
combined yields a miR-signature
All ~20 000 genes
mRNA changes
antimiR
Control
predicted miR-122 targets
log2(antimiR/control)0 means no change
for each gene:
Expression analysis Sequence analysis
Null-hypothesis:Are the distributions of background and predicted targets identical?
Test: two-sided Kolmogorov-Smirnov
Response to miravirsen treatment
log2(miravirsen/saline)
Density
14503
mRNAs with
no site
879 mRNA
with
miR-122 site
0 0
miR-signature is an efficacy endpoint
p=6.60E-27
Off-target effects?
RISCmiR
antimiR
Yes, the antimiR binds and
derepress targets of the miR
Direct effect on (partially)
complementary targets?
Experimental assessment of specificity
Does potential binding of tiny LNAs to
perfect match sites lead to off-target
effects at the mRNA or protein level?
Oligo Sequence Sites in human transcriptome Sites in mouse
transcriptome
Tiny antimiR-21 GATAAGCT 917 688
Tiny antilet-7 ACTACCTC 737 608
Tiny antimiR-122 CACACTCC 2416 2127
Control oligo TCATACTA 617 356
Assessment of off-target effect - mRNA
Sort according to t-statistics
Analyze all possible 8-mers
- Bin width: 100 genes
- Test for overrepresentation in
leading set
TTTTTTTT
TTTTTTTA
TTTTTTTC
...
TTTTTTGA...
GGGGGGGG
8-mer sequence wordsACACTCCA
AACACTCC
Assessment of off-target effect – mRNA from mouse livers
Sylamer, Enright lab, 2009
Strong evidence for miRNA-
antagonism
No evidence of direct regulation of
mRNAs by LNA-antimiRs!
Take 2 minutes to talk to your
neighbour and update your notes Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT
Time for a break?
Understanding miR-122 biology
through transcriptomics
Microarray data from four different experiments
Model Liver Northern Serum cholesterol levels
Monkey
Normal diet
Monkey
High-fat diet
Mouse
Normal diet
Mouse
High-fat diet
On gene level: only little consistency
between mice and primates
Pathway level changesUnbiased pathway analysis
!"#$%&
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!"#$%&
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!"#$%&'()%#%(*"+,(-./#)%0(1#'"(2/'.3/4(!50-"&%0
-.$/0.1)2
3+(&45%&6
-.$/0.1)7
3*+'/$*1)#%-#%,,%&6
&"0(#%'4*.$+"()))))))))))))))))))))))))))))))))))))4-#%'4*.$+"(
#%-#%,,+"()))))))))))))))))+(&45$+"(
61$%&('&/#0-&12'(2&"*1+1#)(
.($+8+9)$#%.$%&
,.*+(%)$#%.$%&
.($+8+9):,),.*+(%
;"*&)5/.('%,
5"8-.#%)%<-#%,,+"()*%:%*,
!"#$%&
'%(%)*+,$
monkey mouse
high fat mRNA changes mRNA changes
normal mRNA changes mRNA changesHagedorn et al, unpublished
Pathways responding consistently
across diets and species
Cholesterol synthesis enzymes are
downregulated across diets and species
Hagedorn, et. al, unpublished
Systems biology successfully
explains pharmacology!
Take 2 minutes to talk to your
neighbour and update your notes Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT
★Preclinical tox: “SPC3649 (miravirsen) was tolerated at doses that far
exceed those intended for human clinical use”
★Phase Ia study completed: Single dose, dose-escalationin healthy
volunteers
★Phase Ib completed: Multiple ascending doses in healthy volunteers
★Phase II completed: Hepatitis C patients
miravirsen is in clinical trials
Phase 1a. Dose dependent reduction of plasma
cholesterol in humans
Phase 2 trials showed dose
dependent reduction of viremia
Variable response -> possibilities for stratification of patients
Acknowledgements
Santaris microRNA research group
Sakari Kauppinen
Susanna Obad
Joacim Elmen
Santaris Informatics group
Andreas Petri
Peter Hagedorn
Lena Hansson (now Intomics)
Elfar Torarinson (sysadm consult)
Center for biological sequence analysis, DTU
Henrik Bjørn Nielsen
RNA.dk
35M DKK strategic center to “enable RNA therapy”
State of the art proteomics, RNA-seq and other HTP-methods to:
Determine RNA accessibility
Find factors that influence:
RNA drug potency
RNA drug toxicity
Basic research translated to improve RNA drug design
Looking for a thesis-project?
Contact
Morten Lindow – [email protected] or
Jeppe Vinther [email protected]
Wrap up Have a general idea about bioinformatics and high-through-put data can be used in the
industry for drug development
Explain the rationale for RNA directed drugs Differences to traditional small molecule drugs
Roles of bioinformatic sequence analysis
Outline principles about how to detect the best target site on an mRNA
Describe what LNA is and how it improves properties of oligonucleotide drugs
The describe the differences between different RNA directed drugs: siRNA, gapmers, mixmers
Describe the pros and cons of a direct acting vs an indirect acting antiviral
Describe how in global expression analysis, statistical power can be increased by analysing groups of genes instead of single genes Combine expression data with microRNA target prediction
Combine expression data with pathway-information and pharmacological observations
Know about rna.dk and COAT