Genomics in Drug Discovery

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Genomics in Drug Discovery

• _at_ Organon, Oss
• 2005-08-22
• Tim Hulsen

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Introduction

• Proteins are vital to life
• involved in all kinds of life processes

• Understanding protein functions
• and relationships is very important for
• drug design

• Currently, the molecular function of about
• 40 of the proteins is unknown

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Introduction
Availability of fully sequenced genomes gives us
a wealth of information currently more than 15
eukaryotic genomes have nearly been completely
sequenced, over 148 microbial genomes and over
1000 viruses.

• Determine protein function by using different in
  silico techniques
• sequence comparison to known protein sequences
• sequence clustering with proteins which have the
  same or similar function

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Genomics _at_ OrganonThe Protein World project

• All-against-all sequence comparison of complete
  proteomes from 145 species
• Smith-Waterman algorithm Z-value (Monte-Carlo
  statistics)

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Protein World and its ambitions

• Build and maintain a sequence similarity
  repository of all complete proteomes and aligning
  it with omics research in the Netherlands

• Classification of all proteins into groups of
  related proteins
• A phylogenetic repository
• Annotation of new sequences
• Mining protein families
• Identification of genes common / specific to
  (groups of) species

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Applications of Protein World

• Structural properties
• Protein comparison coupled to structure related
  databases (PDB, SCOP, etc.)
• Systems biology
• Connecting PW to other databases (pathways,
  protein interactions, literature etc.)
• Orthology
• Annotation of new proteins
• To predict discrepancies and similarities between
  species

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Orthology

• Describes the evolutionary relationship between
  homologous genes whose independent evolution
  reflects a speciation event (Fitch, 1970)

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Protein World Drug Discovery

• Orthologies can be used to transfer function of
  proteins in model organisms (mice, rats, dogs,
  etc.) to humans
• Drugs tested on model organisms can have
  different effects in humans. Why?
• Could be explained by looking at proteins in drug
  pathways and their orthologs
• Example trypsin inhibition pathway

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Trypsin inhibition pathway (1)

• Organon thrombin inhibitors
• Needed to stop thrombosis (blood clotting)
• Thrombin inhibitor on the market (xi)melagatran,
  sold as Exanta (AstraZeneca)
• Proven to be better than warfarin, but

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Trypsin inhibition pathway (2)

• Side effect of thrombin inhibitors inhibition of
  trypsin
• Trypsin inhibition -gt rise in cholecystokinin
  (CCK) levels -gt stimulation of pancreas -gt
  pancreatic tumors
• Difficult to test in model organisms
• Rat very strong CCK response
• Mouse weak CCK response
• Human almost no CCK response

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Trypsin inhibition pathway (3)
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Trypsin inhibition pathway (4)

• Ortholog identification methods
• Using functional annotation (SPTrEMBL)
• Best Bidirectional Hit (BBH)
• ? one-to-one relationships
• PhyloGenetic Trees (PGT)
• ? many-to-many relationships

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Best Bidirectional Hit (BBH)

• Very easy and quick
• Human protein (1) ? SW ? best hit in mouse/rat
  (2)
• Mouse/rat protein (2) ? SW ? best hit in human
  (3)
• If 3 equals 1, the human and mouse/rat protein
  are considered to be orthologs

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PhyloGenetic Tree (PGT)

• Human
• All
• eukaryotic
• proteomes
• Zgt20
  RHgt0.5QL
• 25,000
  groups

PROTEOME
Hs-Mm pairs Hs-Rn pairs
TREE SCANNING
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Trypsin inhibition pathway (5)

• Mm Hs Rn
• by annotation
• BBH
• PGT

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Trypsin inhibition pathway (6)

• PGT method in some cases too many orthologous
  relationships, especially for trypsin (73 in
  mouse and 62 in rat!)
• BBH method seems to be more usable for this
  study, but still not gives an explanation for the
  differences in CCK levels
• Our problem (different CCK responses in Human,
  Mouse and Rat) cannot be solved only by orthology
  identification
• ? Combine ortholog analysis with other data
• ? Focus on the molecules that are most likely to
  be responsible for these differences CCK and
  trypsin

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Trypsin inhibition pathway (7)

• Current activities
• Take a better look at regulation promoter
  detection?
• Use expression data?
• Structural explanation? Modelling of interactions
  between the involved molecules

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Possible student projects

• Orthology case study explain differences between
  humans and model organisms
• (like example of trypsin inhibition pathway)
• Chicken project (in collaboration with Wageningen
  University) comparison of immune system in
  chickens to i.s. in humans and other vertebrates
• Cluster algorithms

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People

• Peter Groenen
• Wilco Fleuren
• Tim Hulsen
• Others _at_ MDI
• Students?