Transcript Folie 1
3D Structures of Biological Macromolecules
Part 3: Drug Research and Design
Jürgen Sühnel
[email protected]
Leibniz Institute for Age Research, Fritz Lipmann Institute,
Jena Centre for Bioinformatics
Jena / Germany
Supplementary Material: www.fli-leibniz.de/www_bioc/3D/
Example of Drug Discovery
Example of Drug Discovery
Example of Drug Discovery
Pacific yew tree
(Eibe)
Drug Research is
the Search for a Needle in a Haystack.
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Development of Drug Research
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Drug Timeline
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Drug Timeline
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Costs in Drug Research
Cost for discovering and developing a new drug:
several € 100 million up to € 1000 million (average € 802 M)
Time to market:
10 – 15 years
Pharma Sales and Earnings in 1999 - 2002
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The World’s Top-Selling Drugs in 2004
Disciplines Involved in Drug Development
Molecular Conceptor
The Role of Molecular Structure
Molecular Conceptor
The Pharmacophore Concept
Molecular Conceptor
Mechanisms of Drug Action – Definitions I
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Mechanisms of Drug Action – Definitions II
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Serendipity - Penicillin
Molecular Conceptor
Serendipity - Aspirin
Serendipity - Aspirin
Molecular Conceptor
Strategies in Drug Design
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Computational Approaches to Drug Research
Target identification
Lead discovery
Lead optimization
Ligand-based design
Receptor-based design (Docking)
Database screening (Virtual screening)
Supporting combinatorial chemistry
3D Structures in Drug Design
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Lead Structure Identification
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Lead Structure Search Pipeline
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Lead Structures: Endogenous Neurotransmitters
voluntary
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Lead Structures: Endogenous Neurotransmitters
Neurotransmitters are chemicals that are used to relay, amplify and
modulate electrical signals between a neuron and another cell.
Acetylcholine:
Noradrenaline:
Dopamine:
Serotonin:
GABA:
voluntary movement of the muscles
wakefulness or arousal
voluntary movement and emotional arousal
sleep and temperature regulation
(gamma aminobutryic acid) - motor behaviour
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Lead Optimization
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Ligand-based Design: What is QSAR ?
Ligand-based Design: Basic Requirements for QSAR Studies
Ligand-based Design: QSAR
Hansch analysis is the investigation of the quantitative relationship between the
biological activity of a series of compounds and their physicochemical substituent
or global parameters representing hydrophobic, electronic, steric and other effects
using multiple regression correlation methodology.
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
Ligand-based Design: QSAR Parameters - Lipophilicity
Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: QSAR Parameters
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Ligand-based Design: A QSAR Success Story
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Ligand-based Design: A QSAR Success Story
pI50 – concentration of test compound required to reduce the protein content of cell by 50%
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Ligand-based Design: 3D-QSAR CoMFA
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Molecular Superposition of D Receptor Ligands
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Ligand-based Design: 3D-QSAR CoMFA
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Ligand-based Design: 3D-QSAR CoMFA
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Electrostatic and Van-der-Waals Interactions
Ligand-based Design: 3D-QSAR CoMFA
Comparative
Molecular
Field
Analysis
Receptor-based Design (Structure-based Design)
Molecular Conceptor
Receptor-based Design (Structure-based Design)
Molecular Conceptor
Receptor-based Design: Docking
Molecular Conceptor
Receptor-based Design: Docking
Molecular Conceptor
Receptor-based Design: Docking
Molecular Conceptor
Hydrophobic Amino Acids
Molecular Conceptor
Receptor-based Design: Docking
Molecular Conceptor
H-Bond Properties of Amino Acids
Molecular Conceptor
Receptor-based Design: H-bond Effect
IC50 Drug concentration
required for 50% inhibition of a
biological effect
Molecular Conceptor
Receptor-based Design: H-bond Effect
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Charge Properties of Amino Acids
Molecular Conceptor
Receptor-based Design: Salt Bridge
Molecular Conceptor
Receptor-based Design: Docking
Molecular Conceptor
Receptor-based Design: SAR (Pharmacophore Features)
Molecular Conceptor
Receptor-based Design: DNA Receptor
Molecular Conceptor
Receptor-based Design: DNA Intercalating Agents
Molecular Conceptor
Receptor-based Design: DNA Intercalating Agents
Molecular Conceptor
Receptor-based Design: AIDS Drugs
Receptor-based Design: AIDS Drugs
Combinatorial Diversity in Nature
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Classical vs. Combinatorial Chemistry
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Combinatorial Library
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Combinatorial Library
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Types and Features of Combinatorial Libraries
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Receptor-based Design: Virtual Screening
Virtual Screening:
Select subsets of compounds for assay that are more likely to contain
active hits than a sample chosen at random
Time Scales:
Docking of 1 compound
Docking of the 1.1 million data set
30 s
(SGI R10000 processor)
6 days
(64-processor SGI ORIGIN)
ACD-SC: Database from Molecular Design Ltd.
Agonists: Known active compounds
Docking of ligands to the estrogen receptor
(nuclear hormone receptor)
Receptor-based Design: Virtual Screening
Lipinski‘s „Rule of Five“
Compounds are likely to have a good absorption and permeation
in biological systems and are thus more likely to be successful drug candidates
if they meet the following criteria:
• 5 or fewer H-bond donors
• 10 or fewer H-bond acceptors
• Molecular weight less than or equal to 500
• Calculated log P less than or equal to 5
• „Compound classes that are substrates for biological transporters are exceptions to the rule“.
Druggable compounds
ADME
ADME
The Future: Pharmacogenomics and Personalized Medicine
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Prediction Issues
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