A Novel Drug-Mouse Phenotypic Similarity Method Detects Molecular Determinants of Drug Effects.
The molecular mechanisms that translate drug treatment into beneficial and unwanted effects are largely unknown. We present here a novel approach to detect gene-drug and gene-side effect associations based on the phenotypic similarity of drugs and single gene perturbations in mice that account for the polypharmacological property of drugs. We scored the phenotypic similarity of human side effect profiles of 1,667 small molecules and biologicals to profiles of phenotypic traits of 5,384 mouse genes. The benchmarking with known relationships revealed a strong enrichment of physical and indirect drug-target connections, causative drug target-side effect links as well as gene-drug links involved in pharmacogenetic associations among phenotypically similar gene-drug pairs. The validation by in vitro assays and the experimental verification of an unknown connection between oxandrolone and prokineticin receptor 2 reinforces the ability of this method to provide new molecular insights underlying drug treatment. Thus, this approach may aid in the proposal of novel and personalized treatments.
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research, Helmholtz Zentrum München, Neuherberg, Germany.
Jeanette
J
Prinz
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research, Helmholtz Zentrum München, Neuherberg, Germany.
Ingo
I
Vogt
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research, Helmholtz Zentrum München, Neuherberg, Germany.
Gianluca
G
Adornetto
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.|German Center for Diabetes Research, Helmholtz Zentrum München, Neuherberg, Germany.
Mónica
M
Campillos
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