Download The importance of residence and recognition time of drug

GE Healthcare
Life Sciences
The importance of residence and
recognition time of drug-target
interactions in understanding efficacy and
SAR
Markku Hämäläinen, PhD
Senior scientist in chemometrics
Protein Analysis, R&D
GE Healthcare Bio-Sciences AB
Uppsala, Sweden
1
GE Title or job number
3/31/2014
GE Healthcare
Life Sciences
Without on you are off!
With slow off you might still be on even
when the drug is gone!
Markku Hämäläinen, PhD
Senior scientist in chemometrics
Protein Analysis, R&D
GE Healthcare Bio-Sciences AB
Uppsala, Sweden
2
GE Title or job number
3/31/2014
1/
GE /
Outline
•Short overview on the use of SPR in drug
discovery
•Why binding kinetics is closely connected with
PK/PD and therefore also efficacy
•The value of residence/recognition time for
Structure Kinetic Relations (SKR)
•Q&A session
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GE Title or job number
3/31/2014
SPR, ITC & DSC fits into the interface
between different DD-disciplines
Medicinal Chemistry
• SAR and QSAR based on
on/off/KD-maps & enthalpy
• Direct binding gives pure
interaction info
• Fragment and focused
libraries gives new scaffolds
• Do not misuse your time with
frequent hitters
Screening
• Improved quality on hit
identification by elimination
of promiscuous binders and
false positive/negatives
• Selectivity screening using
panels of proteins
• Binding site ranking using
LF-competition assays
• Intell. stepwise screening
• Screening of fragment,
target focused and diversity
libraries
Protein & Structural
Chemistry
Biophysical Chemistry
• Primary screen of fragments
before NMR/X-ray
• Identify binding pockets
with competition
• DSC for QC
• Validate mutations
• Adds kinetic and
thermodynamic resolution
and throughput
• Transition state
thermodynamics
Label-free
Interaction Analysis
Biology
• Interaction proteomics
• Protein panels for the
understanding of
binding/biological effect
mechanism
• Selectivity
• Validate binding difference in
animal disease models
Computational
Chemistry
• Validate your virtual binding
site model with pure binding
data
• 3D structure gives not
on/only off, i.e. not equal to
function/affinity/efficacy
• LF-screening can feed insilico models
ADME & Bioanalytical
Chemistry
• HSA/AGP-maps for ranking of
plasma protein binding
• Fa% from interaction
analysis with liposomes
• Compare binding with the
serum albumin from disease
model animals
4
2/
GE /
Label-free biophysical screening in Drug
Discovery
Primary
Screen
Up to ~10 000
compounds:
Fragment libraries
Selected diversities
Hits from HTS
Directed libraries
Content:
Active to
Hit
Hit To
Lead
Lead
Optimization
CD
Selection
100
1000 New
compounds
1-5%
0.50%
5-x
scaffolds
~ 10
scaffolds
~all
Low
2-3 scaffolds
Medium
Binding:
Intent:
Yes/No
Promiscuous?
Covalent?
False positive?
Medium/High
Ranking:
KD or IC50
1:1 binding
Binding site ID
Technologies:
High
SAR:
SAR:
Full kinetic profile
Full kinetic
(kon, koff,KD)
selectivity profile
Target selectivity Thermodynamics
Early ADME
SPR and ITC
X-ray/NMR
In-silico
5
GE Title or job number
3/31/2014
What do Biacore™ instruments measure?
Compound
Immobilized
target
buffer
sample
buffer
association
Response (RU)
Lead
dissociation
Sensorgram
X
Binding late
report point
Binding
response
Fragment
Baseline
Time
6
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Kinetic analysis of lmw drug-target interactions
Fc=2 Spot=1-r corr
Estrogen receptor
Fc=1 Spot=1-r corr
6
6
Thrombin
5.3
5
4.6
4
3.9
CD80
Adenosine
receptor A2a
3.2
3
2.5
2
1.8
1
1.1
0
0.4
-1
-0.3
-2
-100
-50
0
50
100
150
200
Carbonic anhydrase
-1
-100
0
100
-60
400
500
600
700
800
900
DNA sequence
-10
40
90
140
s
Albumin
21
100
17
Response (RU)
300
CDK2 Kinase
RU
16
14
12
10
8
6
4
2
0
-2
HIV protease
25
200
80
13
60
9
40
5
20
1
0
-3
900
1100
1300
1500
Time (s)
1700
1900
2100
0
10
20
30
40
s
Increasing the number of targets!!
7
GE Title or job number
3/31/2014
Binding kinetics data to
understand drug efficacy
4/
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Affinity – Kinetics - Thermodynamics
Transition state
SPR/Biacore™
KD = koff/kon
Lead series
Affinity
1*106
ka
100 pM 1 nM
10 nM
7
100 nM
6
1 µM
log (ka )
100pM
1nM
10nM
100nM
1M
10M
100M
1 mM
kathermodynamics
(M-1s-1)
1*107
Kinetics
5
10 µM
4
100 µM
3
1 mM
2 -4
-3
-2
-1
1*105
0.1
kd
0
log (kd)
Equilibrium
How strong?
275
Vary
temperature
Rates of complex
formation and dissociation
How fast?
285
295
305
Temp (K)
kd s-1
0.01
0.001
275
285
295
305
Temp (K)
Why that fast?
All affinities and rate constants are
apparent
Ki vs. KD shows “good”
correlation
1000.0
Large differences at
high affinities
100.0
Ki (nM)
Buffer differences
10.0
Ki=PBS, pH 5.5, 1M NaCl.
KD= HBS pH 7.4, 0.15M NaCl
1.0
0.1
0.1
1.0
10.0
100.0
KD (nM)
Clinically used drugs
1000.0
10000.0
1.0e5
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Affinity – Kinetics - Thermodynamics
Lead series
SPR/Biacore™
KD = koff/kon
KD
100 pM 1 nM 10 nM
∆G = ∆H - T∆S
KD
7
100 nM
6
1 µM
5
10 µM
log kon (M-1s-1)
Kinetics
∆G =RTlnKD
5
0
Thermo-
4
100 µM
3
1 mM
2 -4
10
-3
-2
-1
kcal/mole
Affinity
100 pM
1 nM
10 nM
100 nM
1 M
10 M
100 M
1 mM
ITC/MicroCal™
-10
dynamics
-15
A,B,C
0
log koff (s-1)
-5
-20
A
Rates of complex
formation and dissociation
How fast?
Equilibrium
How strong?
B
C
∆ G - Gibbs free energy
∆H - Enthalpy
T∆S - Entropy
Why that strong?
Complementary information
Kinetics
On-off rate map
Thermodynamics
Ethoxzolamide
log kon (M-1s-1)
KD
7
Entropy-Enthalpy map
TS
(kcal mol-1)
KD
5
3
6
1
-1
5
-3
-5
4
-7
3
-3
-2
-1
log koff (s-1)
-9
-18
-16
-14
-12
-10
-8
-6
H (kcal mol-1)
Furosemide
6/
GE /
100 times higher affinity but lower efficacy
Both drugs with identical and rapid clearance (short plasma
half-life)
Concentration
1 M
0 M
100 % occupied
92 % occupied
koff
10-2
10-3
10-4
10-5
10-6
87 % occupied
Residence
time - t½
(s-1)
KD = 10 nM
kon = 103 (M-1s-1)
koff = 10-5 (s-1)
= 2 minutes
= 19 minutes
= 2 hours
= 19 hours
= 8 days
KD = 100 pM
kon = 107 (M-1s-1)
koff = 10-3 (s-1)
0 % occupied
1
Time (h)
2
Higher affinity is not
always better!
13
GE Title or job number
3/31/2014
Binding site occupancy (%) at different on/off/KD-values
at 10/100 nM after 1h of interaction and 1h of dissociation
Rapid off-rate limited efficacy
kon (M-1s-1)
koff (s-1)
A
90
C
B
D
95
99
90
99
0
0
90
0
99
0
90
0
99
0
70 70
92
Slow off-rate protected efficacy
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GE Title or job number
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GE /
Summary – the 4 areas
Ancient medicinal chemistry knowledge!
Affinity limited efficacy
High affinity do not help if
clearance is rapid!
Rapid off-rate limited efficacy
koff (s-1)
kon (M-1s-1)
0/0
99/0
100/100
30/30
Slow off-rate enhanced efficacy
Slow on-rate limited efficacy
Without on you are off!
With slow off you might still be on
even when the drug is ”gone”!
15
GE Title or job number
3/31/2014
When is short residence time better?
Short in relation to the effect wanted:
e.g. Sleeping pills with very long residence time is very bad business
”For pharmacological mechanism requiring the endogenous
ligand to perform routine fysiological functions a fast binding
exogenous ligand displaying short lived interventions might be
advisable.”1
Ion-channel antagonism: Ketamine and MK-801 gives mechanism based
adverse effect probably due to strong and slowly dissociation binding to NMDA2
Dopamin receptor antagonism
Cyclooxygenase inhibitors: naproxen and ibuprofen sometimes better due to
rapid reversible contra aspirin which binds covalently and gives side effects
1)Sara
Núňez et al. DDT (2012) 17:1/2:pp10-22
receptor
2)N-methyl-D-aspartate
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GE Title or job number
3/31/2014
8/
GE /
Lead optimization based on
Residence and recognition
time to understand SAR
Overview of the spread in on/off-rates
KD
HIV-1 Protease inhibitors
7
7
DPP-IV inhibitors
7
Log (kon)
Scaffolds
cluster in
on/off/KDspace
2
-4
Log (koff )
0
7
6
0
2
-4
0
Ago
Anta
3
0
-2
Carbonic anhydrase inhibitors
-4
0
7
DC
BA
E
3
2
0
-5
0 -4
Estrogen receptor inhibitors
CD80/CD28 inhibitors
Range in kon 2-5 orders of magnitude
Range in koff 2-5 orders in magnitude
Leads with
slowest offrates – all
with
scaffold E
had highest
biological
potency
18
GE Title or job number
3/31/2014
Also shown in poster
9/
GE /
The rate of association of the inhibitor to thrombin
is of crucial importance for its in vivo effect
The slope in the dose response curves from the rat arterial
thrombosis model is related with the k
on
efegatran
Thrombin is the key enzyme in the
coagulation process and converts
fibrinogen into clottable fibrin.
slope AT rate
6
CH 1091
4
PPACK
2
melagatran
An intensive effort in several
pharmaceutical companies has lead to
the development of many potent and
selective thrombin inhibitors with
distinct advantages over heparin and
warfarin.
argatroban
inogatran
hirulog
0
1
10
100
The choice of thrombin inhibitors as
antithrombotic drugs depends a.o. on
their affinity for the target and on their
rate of binding.
kon (/µM.s)
from: Elg M, Gustafsson D, Deinum J: The importance of
enzyme inhibition kinetics for the effect of thrombin
inhibitors in a rat model of arterial thrombosis,
Thrombosis and Haemostasis 78 (1997) 1286-1292
19
GE Title or job number
3/31/2014
Structure kinetic relations (SKR) of
P38 map kinase inhibitors
R1 BIRB 796O
O
N
N
N
N
H
H
N
O
Former BI drug candidate for inflammatoric and
auto-immune diseases
The t-Bu induce rearrangement of activation loop
and fills the formed lipofilic pocket
KD
R2
107
1 pM 10 pM 100 pM 1 nM
100 nM
106
kon (M-1s-1)
10 nM
105
1 M
104
10 M
103
100 M
ATP
10-6
10-5
10-4
10-3
10-2
10-1
koff (s-1)
1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104.
20
GE Title or job number
3/31/2014
10 /
GE /
SKR of P38 inhibitors
R1 BIRB 796O
O
N
N
N
N
H
H
Some of the first tool
compounds show rapidon/rapid-off type of binding
SB 203580
N
O
R2
1 pM 10 pM 100 pM 1 nM
107
-OH
-NO2
100 nM
106
kon (M-1s-1)
KD
10 nM
105
1 M
104
10 M
103
100 M
ATP
10-6
10-5
10-4
10-3
10-2
10-1
koff (s-1)
21
GE Title or job number
3/31/2014
1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104.
SKR of P38 inhibitors
R1 BIRB 796O
O
N
N
N
N
H
H
The ”formation” and filling
of the pocket increase the
complex stability  longer
residence time
N
O
R2
107
1 pM 10 pM 100 pM 1 nM
100 nM
R1=
-tBu
kon (M-1s-1)
106
R2=
KD
10 nM
105
1 M
104
10 M
103
100 M
-iPr
-H
10-6
10-5
10-4
koff
10-3
10-2
10-1
(s-1)
22
1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104.
11 /
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Phenyl and tolyl identical
affinity but tolyl better efficacy
due to longer residence time
SKR of P38 inhibitors
R1 BIRB 796O
O
N
N
N
N
H
H
R2 = Phenyl
koff = 1.5*10-5 s-1 ; t1/2 = 13h
N
O
R1=tBu
R2 = Tolyl
-6 -1
-Me koff = 8.3*10 s ; t1/2 = 23h
KD
R2=
R2
Me
1 pM 10 pM 100 pM 1 nM
107
100 nM
106
kon (M-1s-1)
10 nM
105
1 M
104
10 M
103
100 M
10-6
10-5
10-4
10-3
10-2
10-1
koff (s-1)
23
SKR of P38 inhibitors
R1 BIRB 796O
O
N
N
N
N
H
H
N
O
R2=
R1=tBu
N
Me
Me
107
Me
NMe2 Me
-Me
CO2H
NMe2
1 pM 10 pM 100 pM 1 nM
KD
10 nM
100 nM
106
kon (M-1s-1)
R2
Polar R2 gives slower onrates
105
1 M
104
10 M
103
100 M
10-6
10-5
10-4
koff
10-3
10-2
10-1
(s-1)
24
1.) J. Regan, C.A. Pargellis, et. al. (2003) Bioorg. Med.. Chem. Letters 13, 3101-3104.
12 /
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HIV1-protease inhibitors: on-off rate map
Ritonavir
10 pM
100 pM
1 nM
XM232 A008
3.8 nM 7 nM
Cyclic urea
KD
10 nM
B376
27 nM
O
100 nM
N
HO
O
U75875
107
B369
Ind
106
Nelf
Saq
B440
B408
B409
B429 B412
kon (M-1s-1)
B388
Rit Amp
A037
105
B268
B439
B435
10 M
O
N
HO
O
A017 B249
103
102
0.0001
0.001
N
H
O
P1´
B268
O
H
N
0.1
OH
O
Symmetric B268
TS-analoges
P2
0.01
N
OH
AHA-021
1 mM
A016
O
S
HO
100 M
B347
B277
O
Cyclic
sulfonamides
A015
A038
104
OH
OH
AHA-008
1 M
B322
B355
B425 A021
B295
A030
A045
A024
A018
B365
A047 A023
Drugs
Cyclic urea
Cyclic sulfonamides
B268 analogues
P1/P1´ - modified
P2/P2´- modified
Other
N
HO
OH
O
O
O
H
N
OH
N
H
O
P2´
1
koff (s-1)
P1
25 / Markku Hämäläinen, Orion Finland Sep 2007 /
HIV1-protease inhibitors – SKR
10 pM
100 pM
1 nM
XM232 A008
3.8 nM 7 nM
10 nM
B376
27 nM
KD
100 nM
U75875
107
B369
Rit Amp
kon (M-1s-1)
106
105
B268
B425 A021
B439
B435
OH
O
H
N
N
H
O
P2
End amid  ester
B249
100 M
Chirality of dihydroxy
S,S  R,R
1 mM
A038
B347
104
103
P1/P1´ Bz  i-Pr
B277
102
0.0001
O
Di-  Mono-hydroxy
10 M
B365
B409
B429 B412
A037
O
1 M
B322
B408
N
H
P1
OH
O
O
B388
Ind
Nelf
Saq
B440
B268
H
N
0.001
0.01
koff (s-1)
0.1
1
Higher rotational
freedom - ~1000 times
slower on-rate
26 / Markku Hämäläinen, Orion Finland Sep 2007 /
13 /
GE /
HIV1 protease inhibitors: COMFA-QSAR
38 Inhibitors (22 in the training set, 16 in the test set) from 5 different
scaffolds and the clinically used drugs.
•
The structures were aligned and 3D-CoMFA was used for obtaining a
QSAR model describing on-rates and off-rates.
Predicted pkoff
•
Observed pkoff
Predictive COMFA-QSAR model only for offrate - not for
on-rate
nor
affinity
27 / Markku
Hämäläinen,
Orion Finland
Sep 2007 /
28 / Markku Hämäläinen, Orion Finland Sep 2007 /
14 /
GE /
Qualitative chemodynamics: HIV-p
100 pM
1 nM
10 nM
107
Indinavir
A = pH 7.4
B = pH 5.1
C = pH 4.1
B
A
C
106
B
B Scaffold 1
Scaffold 2
A
kon
100 nM
C
A 1 M
C
B
105
A
peptide
0.001
0.010
koff
29
20110303
0.100
The “unknown binding site/binder situation”
Remedy - label-free/in-silico combination
Hit identification and validation
1. Label free selectivity
screening – 1-50k
compounds
4. LF-competition
screen – b.sites
Scaffolds
identification
2. Target
3. Structure feeds
selective hits
in-silico selection
Binding site
classification
5. Binding site
selective hits
6. B-site classes
feeds in-silico
Lead identification and optimization
Co-cryst.
Xray
Kinetic
charact.
Kinetic
screening
Lead
identification &
Thermodyn. optimization.
charact.
Early ADME
CADD
SAR/QSAR
Cell based
assays
Animal
models
Candidate
Drug
30
GE Title or job number
3/31/2014
15 /
GE /
Conclusions
1. Binding kinetics resolve affinity into
”new” more ”close to efficacy” type of
data
2. Residence time/off-rate of slowly
dissociating compounds often
dominates the binding site occupancy
over time and cannot be neglected
when judging the quality of a lead
3. Compounds with slow off-rates need
only a peak in bioavailable
concentration to have a broader
therapeutic window
4. You cannot properly judge
pharmacokinetic data without knowing
the binding kinetics of the interaction
5. High residence time selectivity is
important to minimize side effects
6. The “slowness” of the off-rate should be
judged in relation to the time constant
of the biological system and the effect
wanted
7. Rapid on-rate is important if the
bioavailability is low or if a rapid effect
is needed
8. There is also a wealth of other
information in the Biacore™/MicroCal™
measurements which can be used for
identification of ”good/bad” binders:
(on/off-rates, enthalpy/entropy,
stoichiometry, selectivity, ”shape”, affinity,
specificity)
9. Label-free screening, binding kinetics
and thermodynamics are now on the
way of being fully integrated into the
DD-process of most pharma/biotec
companies
31
GE Title or job number
3/31/2014
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