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Protein Ligand Interactions:


A Method and its
Application to Drug
Discovery


PHAR
201/Bioinformatics I

Philip E. Bourne

Department of Pharmacology,
UCSD

pbourne@ucsd.edu







PHAR201 Lecture 12 2012

Today’s Lecture in Context


Prof
Abagyan

provided an overview of tools and
considerations in looking at protein
-
ligand interactions


Today we will explore only one methodology in structural
bioinformatics in some detail. A method for examining
protein
-
ligand interactions and its implications for drug
discovery


In a forthcoming lecture Roger Chang will describe how
this approach can be extended into the
realm
of systems
biology, also for drug discovery

PHAR201 Lecture 12 2012

Drug Discovery is a Major Reason to Study
Protein
-
Ligand Interactions But..



Failure is telling us that Ehrlich

s idea of a
magic bullet ie a highly specific drug for a
known receptor is rarely the case

PHAR201 Lecture 12 2012

One Drug Binds to Multiple Targets



Tykerb


Breast cancer




Gleevac


Leukemia, GI
cancers




Nexavar


Kidney and liver
cancer




Staurosporine


natural product


alkaloid


uses many e.g.,
antifungal antihypertensive


Collins and Workman 2006

Nature
Chemical Biology
2 689
-
700

PHAR201 Lecture 12 2012


The truth is we know very little about how the
major drugs we take work


We know even less about what side effects they
might have


Drug discovery seems to be approached in a
very consistent and conventional way


The cost of bringing a drug to market is huge
~$800M


The cost of failure is even higher e.g. Vioxx
-

$4.85Bn
-

Hence fail early and cheaply


Further Motivators

PHAR201 Lecture 12 2012


The truth is we know very little about how the
major drugs we take work


receptors are
unknown


We know even less about what side effects they
might have
-

receptors are unknown


Drug discovery seems to be approached in a
very consistent and conventional way


The cost of bringing a drug to market is huge
~$800M


drug reuse is a big business


The cost of failure is even higher e.g. Vioxx
-

$4.85Bn
-

fail early and cheaply


Further Motivators

PHAR201 Lecture 12 2012

What if…


We can characterize a protein
-
ligand
binding site from a 3D structure (primary
site) and search for that site on a
proteome wide scale?



We could perhaps find alternative binding
sites for existing pharmaceuticals?



We could use it for lead optimization and
possible ADME/Tox prediction

PHAR201 Lecture 12 2012

What Methods Exist to Find Binding
Sites?

PHAR201 Lecture 12 2012

Template Methods e.g.
MSDmotif


MSDsite

queries descriptions of
existing

sites
e.g. all SHD sites


MSDsite

finds
unknown

sites based on motif
search


limited and sequence order dependent


Pocketome



known to exist experimentally
-

limited


We
describe here a method that finds
unknown

sites based on structure and is sequence order
independent

PHAR201 Lecture 12 2012

Golovin

A,
Henrick

K:
MSDmotif
:
exploring

protein

sites and motifs.

BMC
Bioinformatics

2008, 9:312
.


http://
www.ebi.ac.uk
/
pdbe
-
site
/
pdbemotif
/

Other Methods


3D structure based methods


Electrostatic potential based methods


4 point
pharmacophore

fingerprint and
cavity shape descriptors


Henrich

S,
Salo
-
Ahen

OM, Huang B,
Rippmann

FF,
Cruciani

G, et al.

Computational approaches to identifying and characterizing protein binding sites for ligand design.


J
Mol

Recognit

2010 23
: 209
-
219.


PHAR201 Lecture 12 2012

The Method Described Here Starts
with a 3D
Drug
-
Receptor Complex
-

The PDB Contains
Many Examples

Generic Name

Other Name

Treatment

PDBid

Lipitor

Atorvastatin

High cholesterol

1HWK, 1HW8…

Testosterone

Testosterone

Osteoporosis

1AFS, 1I9J ..

Taxol

Paclitaxel

Cancer

1JFF, 2HXF, 2HXH

Viagra

Sildenafil citrate

ED, pulmonary
arterial
hypertension

1TBF, 1UDT,
1XOS..

Digoxin

Lanoxin

Congestive heart
failure

1IGJ

PHAR201 Lecture 12 2012

A Reverse Engineering Approach to


Drug Discovery Across Gene Families

Characterize ligand binding

site of primary target

(Geometric Potential)

Identify off
-
targets by ligand

binding site similarity

(Sequence order independent

profile
-
profile alignment)


Extract known drugs

or inhibitors of the

primary and/or off
-
targets

Search for similar
small molecules

Dock molecules to both

primary and off
-
targets

Statistics analysis

of docking score

correlations



PHAR201 Lecture 12 2012


Initially assign C
a

atom with a
value that is the distance to the
environmental boundary



Update the value with those of
surrounding C
a

atoms
dependent on distances and
orientation


atoms within a
10A radius define i












Conceptually similar to hydrophobicity


or electrostatic potential that is


dependant on both global and local


environments

Characterization of the Ligand Binding
Site
-

The Geometric Potential

Xie and Bourne 2007
BMC Bioinformatics,

8(
Suppl

4):S9

PHAR201 Lecture 12 2012

Discrimination Power of the Geometric
Potential




Geometric
potential can
distinguish
binding and
non
-
binding
sites




100

0

Geometric Potential Scale

Xie and Bourne 2007
BMC Bioinformatics,

8(
Suppl

4):S9

Local Sequence
-
order Independent Alignment with
Maximum
-
Weight Sub
-
Graph Algorithm

L E R

V K D L

L E R

V K D L

Structure A

Structure B



Build an associated graph from the graph representations of two
structures being compared. Each of the nodes is assigned with a weight
from the similarity matrix


The maximum
-
weight clique corresponds to the optimum alignment of
the two structures

Xie and Bourne 2008
PNAS
, 105(14) 5441

PHAR201 Lecture 12 2012

Nothing in Biology
{including Drug
Discovery}

Makes Sense

Except in the Light of Evolution






Theodosius Dobzhansky (1900
-
1975)

PHAR201 Lecture 12 2012

Similarity Matrix of Alignment

Chemical Similarity


Amino acid grouping: (LVIMC), (AGSTP), (FYW), and (EDNQKRH)


Amino acid chemical similarity matrix


Evolutionary Correlation


Amino acid substitution matrix such as BLOSUM45


Similarity score between two sequence profiles


f
a
,
f
b

are the 20 amino acid target frequencies of profile
a

and
b
, respectively

S
a
,
S
b

are the PSSM of profile
a

and
b
, respectively



Xie and Bourne 2008
PNAS
, 105(14) 5441

PHAR201 Lecture 12 2012

Lead Discovery from Fragment
Assembly


Privileged molecular moieties
in medicinal chemistry



Structural genomics and high
throughput screening generate
a large number of protein
-
fragment complexes



Similar sub
-
site detection
enhances the application of
fragment assembly strategies
in drug discovery

1HQC: Holliday junction migration motor protein


from Thermus thermophilus

1ZEF: Rio1 atypical serine protein kinase


from A. fulgidus

PHAR201 Lecture 12 2012

Lead Optimization from

Conformational Constraints


Same ligand can bind to
different proteins, but with
different conformations



By recognizing the
conformational changes in the
binding site, it is possible to
improve the binding specificity
with conformational constraints
placed on the ligand

1ECJ: amido
-
phosphoribosyltransferase


from E. Coli

1H3D: ATP
-
phosphoribosyltransferase


from E. Coli

PHAR201 Lecture 12 2012

This Approach is Called SMAP

http://
funsite.sdsc.edu

PHAR201 Lecture 12 2012

What Have These Off
-
targets and Networks
Told Us So Far?

Some Examples…

1.
Nothing

2.
A possible explanation for a side
-
effect of a drug
already on the market
(SERMs
-

PLoS Comp. Biol.
,
2007
3(11) e217)

3.
A possible repositioning of a drug (Nelfinavir) to treat
a completely different condition
(
PLoS Comp. Biol
. 7(4)
e1002037
)

4.
A multi
-
target/drug strategy to attack a pathogen
(TB
-
drugome
PLoS Comp
Biol


2010 6(11): e1000976)

5.
The reason a drug failed
(Torcetrapib
-

PLoS Comp
Biol

2009 5(5) e1000387)

6.
How to optimize a NCE (
NCE against T.
Brucei

PLoS Comp
Biol. 2010 6(1): e1000648)



PHAR201 Lecture 12 2012

Selective Estrogen Receptor
Modulators (SERM)


One of the largest
classes of drugs


Breast cancer,
osteoporosis, birth
control etc.


Amine and benzine
moiety

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

Adverse Effects of SERMs

cardiac abnormalities

thromboembolic

disorders

ocular toxicities

loss of calcium

homeostatis

?????

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

PHAR201 Lecture 12 2012

Ligand Binding Site Similarity Search
On a Proteome Scale


Searching human proteins covering ~38% of the
drugable genome against SERM binding site


Matching
Sacroplasmic Reticulum

(SR) Ca2+ ion
channel ATPase (SERCA) TG1 inhibitor site


ER
a

ranked top with p
-
value<0.0001 from reversed
search against SERCA


ER
a

SERCA

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

PHAR201 Lecture 12 2012

Structure and Function of SERCA


R
egulating cytosolic
calcium levels in cardiac
and skeletal muscle



Cytosolic and
transmembrane domains



Predicted SERM binding
site locates in the TM,
inhibiting Ca2+ uptake

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

Binding Poses of SERMs in SERCA
from Docking Studies


Salt bridge
interaction between
amine group and
GLU



Aromatic
interactions for both
N
-
, and C
-
moiety

6 SERMS A
-
F (red)

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

Off
-
Target of SERMs

cardiac abnormalities

thromboembolic

disorders

ocular toxicities

loss of calcium

homeostatis

SERCA !




in vivo

and
in vitro

Studies



TAM play roles in regulating calcium uptake activity of cardiac SR



TAM reduce intracellular calcium concentration and release in the
platelets



Cataracts result from TG1 inhibited SERCA up
-
regulation



EDS increases intracellular calcium in lens epithelial cells by
inhibiting SERCA




in silico

Studies



Ligand binding site similarity



Binding

affinity correlation

PLoS Comp. Biol.
, 2007 3(11) e217

PHAR201 Lecture 12 2012

The Challenge


Design modified SERMs that bind as
strongly to estrogen receptors but do not
have strong binding to SERCA, yet
maintain other characteristics of the
activity profile

Side Effects

-

The Tamoxifen Story

PLoS Comp. Biol.
, 2007 3(11) e217

PHAR201 Lecture 12 2012

What Have These Off
-
targets and Networks
Told Us So Far?

Some Examples…

1.
Nothing

2.
A possible explanation for a side
-
effect of a drug
already on the market
(SERMs
-

PLoS Comp. Biol.
,
2007
3(11) e217)

3.
A possible repositioning of a drug (Nelfinavir) to treat
a completely different condition
(
PLoS Comp. Biol
. 7(4)
e1002037
)

4.
A multi
-
target/drug strategy to attack a pathogen
(TB
-
drugome
PLoS Comp
Biol


2010 6(11): e1000976)

5.
The reason a drug failed
(Torcetrapib
-

PLoS Comp
Biol

2009 5(5) e1000387)

6.
How to optimize a NCE (
NCE against T.
Brucei

PLoS Comp
Biol. 2010 6(1): e1000648)



PHAR201 Lecture 12 2012

Nelfinavir


Nelfinavir may have the most potent antitumor
activity of the HIV protease inhibitors


Joell J. Gills et al, Clin Cancer Res, 2007; 13(17)


Warren A. Chow et al, The Lancet Oncology, 2009, 10(1)


Nelfinavir can inhibit receptor tyrosine kinase(s)


Nelfinavir can reduce Akt activation



Our goal:


to identify off
-
targets of Nelfinavir in the human
proteome


to construct an off
-
target binding network


to explain the mechanism of anti
-
cancer activity


Possible Nelfinavir Repositioning

PLoS Comp. Biol
. 2011 7(4) e1002037

PHAR201 Lecture 12 2012

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

binding site comparison

protein ligand docking

MD simulation & MM/GBSA

Binding free energy calculation

structural proteome

off
-
target?

network construction

& mapping

drug

target

Clinical
Outcomes

1OHR

PHAR201 Lecture 12 2012

PLoS Comp. Biol
. 2011 7(4) e1002037

Binding Site Comparison


5,985 structures or models that cover approximately
30% of the human proteome are searched against the
HIV protease dimer (PDB id: 1OHR)



Structures with SMAP p
-
value less than 1.0e
-
3 were
retained for further investigation



A total 126 structures have significant p
-
values < 1.0e
-
3

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

PLoS Comp. Biol
. 2011 7(4) e1002037

Enrichment of Protein Kinases in
Top Hits


The top 7 ranked off
-
targets belong to the same EC
family
-

aspartyl proteases
-

with HIV protease



Other off
-
targets are dominated by protein kinases (51
off
-
targets) and other ATP or nucleotide binding proteins
(17 off
-
targets)



14 out of 18 proteins with SMAP p
-
values < 1.0e
-
4 are
protein kinases

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

PLoS Comp. Biol
. 2011 7(4) e1002037

p
-
value < 1.0e
-
3

p
-
value < 1.0e
-
4

Distribution of
Top Hits on the
Human Kinome

Manning et al.,
Science
,

2002, V298, 1912

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012


1. Hydrogen bond with main chain amide of Met793 (without it 3700 fold loss of
inhibition)

2. Hydrophobic interactions of aniline/phenyl with gatekeeper Thr790 and other
residues


H
-
bond: Met793 with quinazoline N1

H
-
bond: Met793 with benzamide

hydroxy O38

EGFR
-
DJK

Co
-
crys ligand

EGFR
-
Nelfinavir

Interactions between Inhibitors and Epidermal Growth Factor
Receptor (EGFR)


74% of binding site resides are comparable

DJK = N
-
[4
-
(3
-
BROMO
-
PHENYLAMINO)
-
QUINAZOLIN
-
6
-
YL]
-
ACRYLAMIDE

PHAR201 Lecture 12 2012

Off
-
target Interaction Network

Identified off
-
target

Intermediate protein

Pathway

Cellular effect

Activation

Inhibition

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

PLoS Comp. Biol
. 2011 7(4) e1002037

Other Experimental Evidence to Show Nelfinavir inhibition on
EGFR, IGF1R, CDK2 and Abl is Supportive

The inhibitions of Nelfinavir on IGF1R, EGFR, Akt activity

were detected by immunoblotting.


The inhibition of Nelfinavir on Akt activity is less than a

known PI3K inhibitor


Joell J. Gills et al.

Clinic Cancer Research September 2007 13; 5183


Nelfinavir inhibits growth of human melanoma cells

by induction of cell cycle arrest


Nelfinavir induces G1 arrest through inhibition

of CDK2 activity.


Such inhibition is not caused by inhibition of Akt

signaling.


Jiang W el al. Cancer Res. 2007 67
(3)

BCR
-
ABL is a constitutively activated tyrosine kinase

that causes chronic myeloid leukemia (CML)

Druker, B.J., et al New England Journal of Medicine, 2001.
344
(14): p. 1031
-
1037


Nelfinavir can induce apoptosis in leukemia cells as a single agent

Bruning, A., et al. , Molecular Cancer, 2010.
9
:19


Nelfinavir may inhibit BCR
-
ABL

Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

Summary


The HIV
-
1 drug Nelfinavir appears to be
a broad spectrum low affinity kinase
inhibitor


Most targets are upstream of the
PI3K/Akt pathway


Findings are consistent with the
experimental literature


More direct experiment is needed






Possible Nelfinavir Repositioning

PHAR201 Lecture 12 2012

PLoS Comp. Biol
. 2011 7(4) e1002037

What Have These Off
-
targets and Networks
Told Us So Far?

Some Examples…

1.
Nothing

2.
A possible explanation for a side
-
effect of a drug
already on the market
(SERMs
-

PLoS Comp. Biol.
,
2007
3(11) e217)

3.
A possible repositioning of a drug (Nelfinavir) to treat
a completely different condition
(
PLoS Comp. Biol
. 7(4)
e1002037
)

4.
A multi
-
target/drug strategy to attack a pathogen
(TB
-
drugome
PLoS Comp
Biol


2010 6(11): e1000976)

5.
The reason a drug failed
(Torcetrapib
-

PLoS Comp
Biol

2009 5(5) e1000387)

6.
How to optimize a NCE (
NCE against T.
Brucei

PLoS Comp
Biol. 2010 6(1): e1000648)



PHAR201 Lecture 12 2012

A
s
a High Throughput
Approach…..

PHAR201 Lecture 12 2012

The Problem with
Tuberculosis


One third of global population infected


1.7 million deaths per year


95% of deaths in developing countries


Anti
-
TB drugs hardly changed in 40 years


MDR
-
TB and XDR
-
TB pose a threat to
human health worldwide


Development of novel, effective and
inexpensive drugs is an urgent priority

PHAR201 Lecture 12 2012

The TB
-
Drugome

1.
Determine the TB structural proteome


2.
Determine all known drug binding sites
from the PDB


3.
Determine which of the sites found in 2
exist in 1


4.
Call the result the TB
-
drugome


A Multi
-
target/drug Strategy

Kinnings et al 2010 PLoS Comp
Biol

6(11): e1000976

PHAR201 Lecture 12 2012

1. Determine the TB Structural
Proteome

284

1, 446

3, 996

2, 266


High quality homology models from
ModBase

(http://
modbase.compbio.ucsf.edu
) increase structural
coverage from 7.1% to 43.3%

A Multi
-
target/drug Strategy

PHAR201 Lecture 12 2012

Kinnings et al 2010 PLoS Comp
Biol

6(11): e1000976

0
20
40
60
80
100
120
140
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
2. Determine all Known Drug
Binding Sites in the PDB


Searched the PDB for protein crystal structures
bound with FDA
-
approved drugs


268

drugs bound in a total of
931

binding sites

No. of drug binding sites

No. of drugs

Methotrexate

Chenodiol

Alitretinoin

Conjugated
estrogens

Darunavir

Acarbose

A Multi
-
target/drug Strategy

PHAR201 Lecture 12 2012

Kinnings et al 2010 PLoS Comp
Biol

6(11): e1000976

Map 2 onto 1


The TB
-
Drugome

http://funsite.sdsc.edu/drugome/TB/

Similarities between the binding sites of
M.tb

proteins (blue),

and binding sites containing approved drugs (red).


PHAR201 Lecture 12 2012

0
2
4
6
8
10
12
14
16
18
20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
From a Drug Repositioning Perspective


Similarities between drug binding sites and
TB proteins are found for 61/268 drugs


41 of these drugs could potentially inhibit
more than one TB protein

No. of potential TB targets

No. of drugs

raloxifene

alitretinoin

conjugated
estrogens &

methotrexate

ritonavir

testosterone

levothyroxine

chenodiol

A Multi
-
target/drug Strategy

PHAR201 Lecture 12 2012

Kinnings et al 2010 PLoS Comp
Biol

6(11): e1000976

Top 5 Most Highly Connected
Drugs

Drug

Intended targets

Indications

No. of
connections

TB proteins

levothyroxine

transthyretin, thyroid
hormone receptor
α

&
β
-
1,
thyroxine
-
binding globulin,
mu
-
crystallin homolog,
serum albumin

hypothyroidism, goiter,
chronic lymphocytic
thyroiditis, myxedema coma,
stupor

14

adenylyl cyclase,
argR
, bioD,
CRP/FNR trans. reg
.,
ethR
,
glbN
, glbO,
kasB
,
lrpA
,
nusA
,
prrA
,
secA1
,
thyX
,
trans. reg.
protein

alitretinoin

retinoic acid receptor RXR
-
α
,
β

&
γ
, retinoic acid receptor
α
,
β

&
γ
-
1&2, cellular retinoic
acid
-
binding protein 1&2

cutaneous lesions in patients
with Kaposi's sarcoma

13

adenylyl cyclase,
aroG
,
bioD,

bpoC,
CRP/FNR trans.
reg.
,

cyp125
,
embR
,
glbN
,
inhA
,
lppX
,
nusA
,
pknE
,
purN

conjugated
estrogens

estrogen receptor

menopausal vasomotor
symptoms, osteoporosis,
hypoestrogenism, primary
ovarian failure

10

acetylglutamate kinase,
adenylyl cyclase,
bphD
,
CRP/FNR trans. reg.
,
cyp121
,
cysM,
inhA
,
mscL
,
pknB
,
sigC

methotrexate

dihydrofolate reductase,
serum albumin

gestational choriocarcinoma,
chorioadenoma destruens,
hydatidiform mole, severe
psoriasis, rheumatoid arthritis

10

acetylglutamate kinase,

aroF
,
cmaA2
,
CRP/FNR trans. reg.
,
cyp121
,
cyp51
,
lpd
,
mmaA4
,
panC
,
usp


raloxifene

estrogen receptor, estrogen
receptor
β

osteoporosis in post
-
menopausal women

9

adenylyl cyclase,
CRP/FNR

trans. reg.,
deoD,
inhA, pknB
,
pknE
,
Rv1347c
,
secA1, sigC


PHAR201 Lecture 12 2012

Vignette within Vignette


Entacapone and tolcapone shown to have potential
for repositioning


Direct mechanism of action avoids
M. tuberculosis

resistance mechanisms


Possess excellent safety profiles with few side effects


already on the market


In vivo
support


Assay of direct binding of entacapone and tolcapone
to InhA reveals a possible lead with no chemical
relationship to existing drugs

Kinnings et al. 2009
PLoS Comp Biol
5(7) e1000423

PHAR201 Lecture 12 2012

Summary from the TB Alliance


Medicinal Chemistry


The minimal inhibitory concentration (MIC)
of 260 uM is higher than usually
considered


MIC is 65x the estimated plasma
concentration


Have other InhA inhibitors in the pipeline

Repositioning

-

The TB Story

Kinnings et al. 2009
PLoS Comp Biol
5(7) e1000423

PHAR201 Lecture 12 2012

What Have These Off
-
targets and Networks
Told Us So Far?

Some Examples…

1.
Nothing

2.
A possible explanation for a side
-
effect of a drug
already on the market
(SERMs
-

PLoS Comp. Biol.
,
2007
3(11) e217)

3.
A possible repositioning of a drug (Nelfinavir) to treat
a completely different condition
(
PLoS Comp. Biol
. 7(4)
e1002037
)

4.
A multi
-
target/drug strategy to attack a pathogen
(TB
-
drugome
PLoS Comp
Biol


2010 6(11): e1000976)

5.
The reason a drug failed
(Torcetrapib
-

PLoS Comp
Biol

2009 5(5) e1000387)

6.
How to optimize a NCE (
NCE against T.
Brucei

PLoS Comp
Biol. 2010 6(1): e1000648)



PHAR201 Lecture 12 2012

In An Upcoming Lecture..


Roger Chang will describe how systems
Biology can be used to further model
protein
-
drug interactions in a dynamic way.

PHAR201 Lecture 12 2012