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3D Structures of Biological Macromolecules Part
3 Drug Research and Design
Jürgen Sühnel jsuehnel_at_fli-leibniz.de
Leibniz Institute for Age Research, Fritz Lipmann
Institute, Jena Centre for Bioinformatics Jena /
Germany
Supplementary Material www.fli-leibniz.de/www_bio
c/3D/
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Example of Drug Discovery
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Example of Drug Discovery
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Example of Drug Discovery
Pacific yew tree (Eibe)
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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

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Global Company Sales 2006
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Top Ethical Drugs by Sales in 2006
http//www.p-d-r.com/ranking/Top_100_Ethical_Drugs
_by_Sales.pdf
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New Products Marketed for the First Time
http//www.p-d-r.com/ranking/Prous_TYND_2005.pdf
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Disciplines Involved in Drug Development
 
Molecular Conceptor
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The Role of Molecular Structure
Molecular Conceptor
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The Pharmacophore Concept
Molecular Conceptor
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Mechanisms of Drug Action Definitions I
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Mechanisms of Drug Action Definitions II
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Serendipity - Penicillin
 
Molecular Conceptor
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Serendipity - Penicillin
 
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Serendipity - Aspirin
 
Serendipity - Aspirin
Molecular Conceptor
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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

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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
 
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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 voluntary movement of the muscles
Noradrenaline wakefulness or arousal
Dopamine voluntary movement and emotional
arousal Serotonin sleep and temperature
regulation GABA (gamma aminobutryic acid) -
motor behaviour
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Lead Optimization
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Ligand-based Design What is QSAR ?
 
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Ligand-based Design Basic Requirements for QSAR
Studies
 
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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
 
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Ligand-based Design QSAR Parameters -
Lipophilicity
 
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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 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
 
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Ligand-based Design 3D-QSAR CoMFA
Comparative Molecular Field Analysis
 
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Receptor-based Design (Structure-based Design)
 
Molecular Conceptor
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Receptor-based Design (Structure-based Design)
 
Molecular Conceptor
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Receptor-based Design Docking
 
Molecular Conceptor
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Receptor-based Design Docking
 
Molecular Conceptor
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Receptor-based Design Docking
 
Molecular Conceptor
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Hydrophobic Amino Acids
 
Molecular Conceptor
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Receptor-based Design Docking
 
Molecular Conceptor
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H-Bond Properties of Amino Acids
 
Molecular Conceptor
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Receptor-based Design H-bond Effect
 
IC50 - Drug concentration required for 50
inhibition of a biological effect
Molecular Conceptor
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Receptor-based Design H-bond Effect
 
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Charge Properties of Amino Acids
 
Molecular Conceptor
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Receptor-based Design Salt Bridge
116.
 
Molecular Conceptor
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Receptor-based Design Docking
 
Molecular Conceptor
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Receptor-based Design SAR (Pharmacophore
Features)
 
Molecular Conceptor
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Receptor-based Design DNA Receptor
 
Molecular Conceptor
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Receptor-based Design DNA Intercalating Agents
 
Molecular Conceptor
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Receptor-based Design DNA Intercalating Agents
 
Molecular Conceptor
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Receptor-based Design AIDS Drugs
 
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Receptor-based Design AIDS Drugs
 
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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 30 s (SGI
R10000 processor) Docking of the 1.1
million data set 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)
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Receptor-based Design Virtual Screening
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Lipinskis 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
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ADME
ADME
 
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The Future Pharmacogenomics and Personalized
Medicine
 
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Prediction Issues
 
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