Using side effects for drug target identification

Using side effects fordrug target identification

Lars Juhl Jensen

the problem

new uses for old drugs

drug–drug network

shared target(s)

chemical similarity

Campillos & Kuhn et al., Science, 2008

similar drugs share targets

only trivial predictions

the idea

chemical perturbations

phenotypic readouts

drug treatment

side effects

the hard work

information on side effects

no database

package inserts

text mining

side-effect ontology

backtracking

manual validation

Kuhn et al., Molecular Systems Biology, 2010

side-effect correlations

GSC weighting

side-effect frequencies

raw similarity score

p-values

side-effect similarity

chemical similarity

confidence scores

reference set

incomplete databases

text mining

manual validation

MATADOR

Günther et al., Nucleic Acids Research, 2008

text mining

reflect.ws

Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009

collaborate with industry

the results

drug–drug network

categorization

20 drug–drug pairs

in vitro binding assays

Ki<10 µM for 11 of 20

cell assays

9 of 9 showed activity

the future

link side-effects to targets

direct target prediction

Acknowledgments

Side effects– Monica Campillos– Michael Kuhn– Anne-Claude Gavin– Peer Bork

Reflect– Heiko Horn– Sune Frankild– Evangelos Pafilis– Reinhardt Schneider– Sean O’Donoghue

larsjuhljensen

Using side effects for drug target identification

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