Genomics in Drug Discovery

@ Organon, Oss

2005-08-22

Tim Hulsen

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

Introduction

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

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.

Genomics @ Organon:The Protein World project

• All-against-all sequence comparison of complete proteomes from 145 species

• Smith-Waterman algorithm + Z-value (Monte-Carlo statistics)

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

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

Orthology• Describes “the evolutionary relationship

between homologous genes whose independent evolution reflects a speciation event” (Fitch, 1970)

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

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 …

Trypsin inhibition pathway (2)

• Side effect of thrombin inhibitors: inhibition of trypsin

• Trypsin inhibition -> rise in cholecystokinin (CCK) levels -> stimulation of pancreas -> pancreatic tumors

• Difficult to test in model organisms:– Rat: very strong CCK response– Mouse: weak CCK response– Human: almost no CCK response

Trypsin inhibition pathway (3)

Trypsin inhibition pathway (4)

Ortholog identification methods:

1. Using functional annotation (SPTrEMBL):

2. Best Bidirectional Hit (BBH)

one-to-one relationships3. PhyloGenetic Trees (PGT)

many-to-many relationships

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

PhyloGenetic Tree (PGT) Human

All

eukaryotic

proteomes

Z>20 RH>0.5*QL

~25,000 groups

PHYLOME

SELECTION OF HOMOLOGS

ALIGNMENTS AND TREES

PROTEOME

PROTEOMES

TREE SCANNING

LIST Hs-Mm pairsHs-Rn pairs

Trypsin inhibition pathway (5)

Mm – Hs – Rn - by annotation- BBH- PGT

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

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

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

People

• Peter Groenen• Wilco Fleuren• Tim Hulsen• Others @ MDI

• Students?