QSAR in Development of Antidepressants

The Next Generation of
Antidepressants
James Fells
Organic Medicinal Chemistry
Spring 2005

Outline
• Depression as a disease
• Treatment Past, Present, and Future
• Determining the target
• QSAR model
• Proposed lead
• Synthetic method
• Conclusions & Questions

Depression as a Disease
• 1 out 5 adults affected by depression
• 11 th most common reason for visiting
doctor
• By 2020 2 nd largest cause for illness
induced disability
• 3 rd most commonly sold drug
• lifetime risk
– 12.7% male
– 21.3% female

Treatment Past and Present
• First generation
– Monoamine oxidase
inhibitors(MAOIs)
• mechanism-based irreversible
inhibitors
– Tricyclic
antidepressants(TCAs)
• three ring molecular core
• Second generation
– Selective serotonin (5-HT)
reuptake inhibitors(SSRIs)
– Selective
norepinephrine(NE)
reuptake inhibitors (SNRIs)
N
Imipramine
NH 2
Cl
Cl
sertaline
N
O
N
N
N
H
H
N
phenelzine
amoxapine
NH 2

Serotonin Hypothesis
• serotonergic neurotransmission in forebrain
– key determinant of mood
• euphoria-high activity
• dyphoria-low activity
• depression response to low levels
• Serotonin inhibitors interfere with 5-HT activity
– removes serotonin from synapse
– elevating low levels of synaptic serotonin

Stagnant progression
• Serious Drawback to SSRIs
– delay of therapeutic benefit
• two to six weeks for response
– low rate of response
– low rate of remission
• Delayed response due to 5-HT 1a inhibition
• 5-HT 1A desensitization normal firing
– therapeutic effect

Serotonin effect
Phil Skolnick, P. P., Aaron Janowsky, Bernard Beer, Arnold S. Lippa. European journal of pharmacology.
2003, 461, 99-104.

Future drugs
• SSRI current drug of choice
– less side effects and toxicity than1 st
generation
– Toxicity
– almost equal efficacy
• Ideal drug
– Faster effect, specificity, fewer side effects
• 5-HT 1A antagonist augmented with SSRI
show biological effect in one week

Project Aim
• explore a faster acting antidepressant by
coupling an SSRI with some 5-HT 1A
derivative

Leads and biological activity
IC 50
(nM)
Drug
TCAs
imipramine
nortriptyline
protriptyline
trimipramine
Second generation
Amoxapine
mirtazapine
venlafazine
fluoxetine
fluvoxamine
paroxetine
sertaline
Norepinephrine
25
6
10
5000
25
40
300
200
500
70
300
5-HT
50
200
250
10000
600
20000
50
15
5
1
4

QSAR Design
• Create training set
– consisting of known antidepressant and biological activity
• activity –log IC 50
– structures built in MOE
– 20 current antidepressant
• all descriptors for Cerius2 used
– except alignment family
• Generate QSAR equation
– Genetic Function Approximation(GFA)
• Activity independent variable
• Descriptors dependent variable
• Validate the equation
– Test set
• 5 other antidepressant with known biological activity
• Predict activity
– New leads

GFA
• Statistical analysis method
– Generates multiple QSAR models
• Scans for most efficient QSAR equation
• Incorporates genetic algorithm
• Models created and screened during evolution
– QSAR randomly constructed
– Population
• repeatedly selecting parent models
• creating child model
Rogers, D. Relationship. Journal of Chemical Information and Computational Science 1994,
34, 854-866.

Why use GFA
• builds multiple models rather than a single
model
• selects descriptors to be used in the
models
• discovers combinations of descriptors
– correlations between multiple features
• Friedman's lack of fit(LOF) error measure
– estimates best number of features
– resists overfitting

QSAR equation
• Activity =4.68834 + 0.15002*Jurs-TPSA – 2.3786*CHI-3_C –
2.55778*Shadow-nu
• Jurs-TPSA-Jurs descriptor
– Spatial descriptor
– Based partial charge mapped or surface area
– Combines shape and electrostatic information to characterize molecule
• Shadow-nu-Shadow indices
– Spatial descriptor
– Characterize shape of molecule
– Depends on conformation and orientation of molecule
• CHI-3_C-Kier & Hall Chi connectivity
– Topological descriptor
– Based on size, degree of branching flexibility
– Molecular connectivity of atoms in molecule

• r 2 =.87
QSAR results
• validated with test set
– predicting 5 other compounds based on known
activity
Predicted Activity vs. Activity
Activity
Predicted
activity
Residual
10
8
4.84
4.341
0.499
Activity
6
4
5.771
8.301
5.003
8.887
0.738
-0.586
2
0
6.602
7.942
-1.339
0 2 4 6 8 10
Predicted activity
5
4.918
0.0082

Lead concept
IC 50
(nM)
Drug
TCAs
imipramine
nortriptyline
protriptyline
trimipramine
Second generation
Amoxapine
mirtazapine
venlafazine
fluoxetine
fluvoxamine
paroxetine
sertaline
Norepinephrine
25
6
10
5000
25
40
300
200
500
70
300
5-HT
50
200
250
10000
600
20000
50
15
5
1
4

Strategy
Nh 2
fluoxetine
F
Cl
O
H
N
O
O
O
5-HT 1a pharmacophore
Cl
N
H
sertaline
S
paroxetine
O
N
duloxetine
Evrard, D., et al. Bioorganic & Medicinal Chemistry Letters 2005, 15, 911-914.

QSAR results
Par
8.695
9
N
O
O
Par C2
8.303
Cl
O
N
N
O
Flu B1
7.756
Cl
Sertaline B1
F
fluoxetine B1
Dul a
8.445
S
O
O
O
Sertaline
B1
7.912
O
O
O
Duloxetine a
N
N
O
N
Paroxetine C2

Synthetic scheme
S
antidepressants
O
O
N
O
Kamal, A., et. al. Tetrahedron letters 2003, 44, 4783-4787

Synthetic scheme
S
OH
N
S
OH
N
O
O C 2
H 5
H
S
OH
N
O NHCH 3
duloxetine
S

Synthetic scheme

Conclusion
• lead compound activity should be as
efficient as current SSRIs yet faster
response
• QSAR done on 5-HT need to address NE

References
• Phil Skolnick, P. P., Aaron Janowsky, Bernard Beer, Arnold S. Lippa
Antidepressant-like actions of DOV 21,947: a "triple" reuptake inhibitor.
European journal of pharmacology. 2003, 461, 99-104.
• Kamal, A., et. al Chemoenzymatic synthesis of duloxetine and its
enantiomer liase-catalyzed resolution of 3hydroxy-3-(2-thienyl)
propanenitrile. Tetrahedron letters 2003, 44, 4783-4787
• Frazer, A. Antidepressants. Journal of Clinical Psychiatry 1997, 58, 9-25.
• Schafer, W. R. Do Antidepressants Work? Prospects for Genetic Analysis of
Drug Mechanisms. Cell 1999, 98, 551-554.
• Evrard, D., Ping Zhou, Soo i, Dahui Zhou, Deborah L. Smith, Kelly M.
Sullivan, Geoffrey A. Hornby, lee E. Schechter, Terrance H. Andree, and
Richard E. Mewshaw Studies towards the next generation of
antidepressants. Part 4: Derivatives of 4-(5fluoro-1H-indol-3-
yl)cyclohexylamine with affinity for the serotonin transporter and the 5-HT1A
receptor. Bioorganic & Medicinal Chemistry Letters 2005, 15, 911-914.
• Owens, M. Selectivity of Antidepressants from Monoamine Hypothesis of
Depression to the SSRI Revolution and Beyond. Journal of Clinical
Psychiatry 2004, 65, 5-10.