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3D Structures of Biological Macromolecules Part
3 Drug Research and Design
Jürgen Sühnel jsuehnel_at_imb-jena.de
Institute of Molecular Biotechnology, Jena Centre
for Bioinformatics Jena / Germany
Supplementary Material http//www.imb-jena.de/www
_bioc/3D/
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Example of Drug Discovery
 
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Drug discovery
Example of Drug Discovery
 
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Example of Drug Discovery
Pacific yew tree (Eibe)
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Development of Drug Research
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Drug Timeline
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Drug Timeline
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Drug Discovery
 

• 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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Costs in Drug Research
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Pharma Sales and Eearnings in 1999-2002
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The Worlds Top-Selling Drugs in 2004
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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 - Aspirin
 
Molecular Conceptor
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Strategíes in Drug Design
 
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3D Structures In Drug Research
 
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Computational Approaches to Drug Discovery
 

• Target identification
• Lead discovery
• Lead optimization
• Ligand-based design
• Receptor-based design (Docking)
• Database screening (Virtual screening)
• Supporting combinatorial chemistry

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Lead Structure Identification
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Lead Structure Search
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Lead Structures Endogeneous Neurotransmitters
 
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Lead Optimization
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What is QSAR ?
 
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Basic Requirements in QSAR Studies
 
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QSAR
 
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QSAR Parameters
 
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QSAR Parameters
 
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QSAR Parameters -Lipophilicity
 
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QSAR Parameters
 
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QSAR Parameters
 
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QSAR Parameters
 
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QSAR Parameters
 
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QSAR Parameters
 
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QSAR Parameters
 
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A QSAR Success Story
 
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A QSAR Success Story
 
pI50 concentration of test compound required to
reduce the protein content of cell by 50
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3D-QSAR - CoMFA
 
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Molecular Superposition of D Receptor Ligands
 
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The Future Pharmagenomics and Personalized
Medicine
 
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3D-QSAR - CoMFA
 
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3D-QSAR - CoMFA
 
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Electrostatic and Van-der-Waals Interactions
 
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Drug Discovery Ligand-based Design
Comparative Molecular Field Analysis
 
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Hydrogen Bonds and Ligand Affinities
 
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
Molecular Conceptor
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
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Drug Discovery Receptor-based Design
(Structure-based Design)
 
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Combinatorial Diversity in Nature
 
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Classical vs. Combinational 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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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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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.

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ADME
 
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The Future Pharmagenomics and Personalized
Medicine
 
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Prediction Issues
 
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