Introduction to Chemoinformatics

Irene KouskoumvekakiAssociate Professor

December 12th, 2012Biological Sequence Analysis course

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Drug Discovery Process

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The 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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Wet-lab drug discovery process

Screening collection

HTS

Actives

103 actives106 cmp.

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Screening collection

HTS

Actives

103 actives106 cmp.

High rate of false actives!!!

High throughput is not enough to get high output…..

Wet-lab drug discovery process

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Screening collection

HTS

Actives

103 actives106 cmp.

Follow-up Chemical structure

Purity

Mechanism

Activity value

Wet-lab drug discovery process

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Screening collection

HTS

Actives

103 actives106 cmp.

Follow-up

Hits

1-10 hits

Analogues synthesis and testing

ADMET properties

Wet-lab drug discovery process

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Wet-lab drug discovery process

Screening collection

HTS

Actives

103 actives106 cmp.

Follow-up

Hits

1-10 hits

Lead series

0-3 lead series

Hit-to-lead

Analogues synthesis and testing

ADMET properties

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Wet-lab drug discovery process

Screening collection

HTS

Actives

103 actives106 cmp.

Follow-up

Hits

1-10 hits

Lead series

0-3 lead series

Hit-to-lead

Drug candidate

0-1

Lead-to-drug

Analogues synthesis and testing

ADMET properties

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Failures

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We need more.. to find less..

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Drug Discovery Process

Chemoinformatics

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Wet-lab + Dry-lab drug discovery

Diverse set of molecules tested in the lab

in vitro in silico + in vitro

Computational methods to select subsets (to be tested in the lab) based on prediction of drug-likeness, solubility, binding, pharmacokinetics, toxicity, side effects, ...

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The Lipinski ‘rule of five’ for drug-likeness prediction

Molecular weight ≤ 500 # hydrogen bond acceptors (HBA) ≤ 10 # hydrogen bond donors (HBD) ≤ 5 Octanol-water partition coefficient (logP) ≤ 5 (MlogP ≤ 4.15)

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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Exercise : Prediction of drug-likeness

•Go to the following webpagewww.molsoft.com/mprop

•Draw proguanil and decide if it is a drug-like compound

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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 prediction

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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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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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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

CHNH2OH

O

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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

CHNH2OH

O

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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

CHNH2OH

O

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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

CHNH3+

O

O

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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

C14 HNH2OH

O

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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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From chemists to representations

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Structural representation of molecules

Structural representation of moleculesLine notations

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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InChI(IUPAC International Chemical Identifier)

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MOLfile format (.sdf)

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Small molecule databases

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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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Try it yourself!

• Scroll down and find the SMILES and InChI

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Try it yourself!

• Click on SDF (top right icon)

• Select: 2D SDF: Display

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Try it yourself!

• Go back and click again on SDF

• Select: 3D SDF: Display

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Questions?