Download Wet-lab drug discovery process

Introduction to Chemoinformatics
and Drug Discovery
Irene Kouskoumvekaki
Associate Professor
February 15th, 2013
The Chemical Space
There are atoms and space. Everything else is opinion.
—Democritus (ca. 460 BC – ca. 370 BC)
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CBS, Department of Systems Biology
Systems Chemical Biology
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CBS, Department of Systems Biology
Today’s Learning Objectives
• To introduce you to the field of chemoinformatics and the most
commonly used terms and methods
• To show examples of the use of chemoinformatics in modern drug
research
• To give you practical experience through hands-on exercises
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CBS, Department of Systems Biology
Drug Discovery Process
Disease
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Drug target
CBS, Department of Systems Biology
Drug
candidate
Animal
studies
Clinical
studies
Marketed
drug
A drug candidate…
... is a (ligand) compound that binds to a biological
target (protein, enzyme, receptor, ...) and in this way
either initiates a process (agonist) or inhibits it
(antagonist/inhibitor)
The structure/conformation of the ligand is
complementary to the space defined by the protein’s
active site
The binding is caused by favorable interactions
between the ligand and the side chains of the amino
acids in the active site. (electrostatic interactions,
hydrogen bonds, hydrophobic contacts...)
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CBS, Department of Systems Biology
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CBS, Department of Systems Biology
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
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Actives
103 actives
CBS, Department of Systems Biology
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
Actives
103 actives
High rate of false actives!!!
High throughput is not enough to get high output…..
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CBS, Department of Systems Biology
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
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Follow-up
Actives
103 actives
CBS, Department of Systems Biology
Chemical structure
Purity
Mechanism
Activity value
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
Follow-up
Actives
Hits
103 actives
1-10 hits
Analogues synthesis and
testing
ADMET properties
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CBS, Department of Systems Biology
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
Follow-up
Actives
Hits
103 actives
1-10 hits
Hit-to-lead
Lead series
0-3 lead series
Analogues synthesis and
testing
ADMET properties
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CBS, Department of Systems Biology
Wet-lab drug discovery process
HTS
Screening
collection
106 cmp.
Follow-up
Actives
Hits
103 actives
1-10 hits
Hit-to-lead
Lead-to-drug
Lead series
0-3 lead series
Drug
candidate
0-1
Analogues synthesis and
testing
ADMET properties
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CBS, Department of Systems Biology
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CBS, Department of Systems Biology
Failures
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CBS, Department of Systems Biology
We need more.. to find less..
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CBS, Department of Systems Biology
Drug Discovery Process
Chemoinformatics
Disease
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Drug target
CBS, Department of Systems Biology
Drug
candidate
Animal
studies
Clinical
studies
Marketed
drug
Wet-lab + Dry-lab drug discovery
in vitro
in silico + in vitro
Diverse set of molecules tested Computational methods to select
in the lab
subsets (to be tested in the lab) based
on prediction of drug-likeness,
solubility, binding,
pharmacokinetics, toxicity, side
effects, ...
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CBS, Department of Systems Biology
The Lipinski ‘rule of five’ for druglikeness prediction




Octanol-water partition coefficient (logP) ≤ 5
Molecular weight ≤ 500
# hydrogen bond acceptors (HBA) ≤ 10
# hydrogen bond donors (HBD) ≤ 5
If two or more of these rules are violated, the compound might
have problems with oral bioavailability.
(Lipinski et al., Adv. Drug Delivery Rev., 23, 1997, 3.)
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CBS, Department of Systems Biology
Exercise :
Drug-likeness by ’rule of five’
•Go to the following webpage
www.molsoft.com/mprop
•Draw proguanil, calculate properties and
decide if this compound is a drug
according to ’rule of five’
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CBS, Department of Systems Biology
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CBS, Department of Systems Biology
Proguanil antimalarian tablets
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Chemoinformatics
Gathering and systematic use of
chemical information, and
application of this information to
predict the behavior of unknown
compounds in silico.
data
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prediction
Major Aspects of Chemoinformatics
•Databases: Development of databases for
storage and retrieval of small molecule
structures and their properties.
•Machine learning: Training of Decision Trees,
Neural Networks, Self Organizing Maps, etc. on
molecular data.
•Predictions: Molecular properties relevant to
drugs, virtual screening of chemical libraries,
system chemical biology networks…
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CBS, Department of Systems Biology
Major Aspects of Chemoinformatics
•Databases: Development of databases for
storage and retrieval of small molecule
structures and their properties.
•Machine learning: Training of Decision Trees,
Neural Networks, Self Organizing Maps, etc. on
molecular data.
•Predictions: Molecular properties relevant to
drugs, virtual screening of chemical libraries,
system chemical biology networks…
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CBS, Department of Systems Biology
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
C8H9NO3
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
OH
CH2
H2N
O
CH
OH
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
(aromatic ring identification)
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
OH
CH2
H2N
O
CH
OH
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
OH
CH2
H2N
O
CH
OH
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
OH
CH2
+
H3N
O
CH
O
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
OH
CH2
H2N
O
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CH
OH
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CBS, Department of Systems Biology
Representing a chemical structure
• How much information do you want to include?
– atoms present
– connections between atoms
• bond types
– stereochemical configuration
– charges
– isotopes
– 3D-coordinates for atoms
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CBS, Department of Systems Biology
From chemists to representations
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CBS, Department of Systems Biology
Structural representation of molecules
Line notations
Structural representation of molecules
Connection tables
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SMILES
(Simplified Molecular Input Line Entry
System)
Canonical SMILES: unique for each
structure
Isomeric SMILES: describe isotopism,
configuration around double bonds and
tetrahedral centers, chirality
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CBS, Department of Systems Biology
InChI
(IUPAC International Chemical Identifier)
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CBS, Department of Systems Biology
MOLfile format (.sdf)
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CBS, Department of Systems Biology
Small molecule databases
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CBS, Department of Systems Biology
Try it yourself!
• Go to PubChem: pubchem.ncbi.nlm.nih.gov/
• Type proguanil and press Go
• Click on the first result on the list
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CBS, Department of Systems Biology
Try it yourself!
• Scroll down and find the SMILES and InChI
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CBS, Department of Systems Biology
Try it yourself!
• Click on SDF (top right icon)
• Select: 2D SDF: Display
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CBS, Department of Systems Biology
Try it yourself!
• Go back and click again on SDF
• Select: 3D SDF: Display
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Questions?
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CBS, Department of Systems Biology
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CBS, Department of Systems Biology