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.

[1]  Judith A. Blake,et al.  The Mouse Genome Database genotypes::phenotypes , 2008, Nucleic Acids Res..

[2]  G. Superti-Furga,et al.  Target profiling of small molecules by chemical proteomics. , 2009, Nature chemical biology.

[3]  Russ B Altman,et al.  PharmGKB: a logical home for knowledge relating genotype to drug response phenotype , 2007, Nature Genetics.

[4]  S. Ramaswamy,et al.  Systematic identification of genomic markers of drug sensitivity in cancer cells , 2012, Nature.

[5]  A. Pellicer,et al.  FSH receptor in vitro modulation by testosterone and hCG in human luteinized granulosa cells. , 2012, European journal of obstetrics, gynecology, and reproductive biology.

[6]  Richard M Weinshilboum,et al.  Genomics and drug response. , 2011, The New England journal of medicine.

[7]  Shuxing Zhang,et al.  Polypharmacology: drug discovery for the future , 2013, Expert review of clinical pharmacology.

[8]  A. Hopkins.  Network pharmacology: the next paradigm in drug discovery. , 2008, Nature chemical biology.

[9]  Michel Eichelbaum,et al.  Pharmacogenomics and individualized drug therapy. , 2006, Annual review of medicine.

[10]  Dietrich Rebholz-Schuhmann,et al.  Improving Disease Gene Prioritization by Comparing the Semantic Similarity of Phenotypes in Mice with Those of Human Diseases , 2012, PloS one.

[11]  Damian Smedley,et al.  Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome , 2014, Science Translational Medicine.

[12]  J. Hardelin,et al.  Biased signaling through G‐protein‐coupled PROKR2 receptors harboring missense mutations , 2014, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[13]  Thomas Lengauer,et al.  ROCR: visualizing classifier performance in R , 2005, Bioinform..

[14]  Monica Campillos,et al.  Systematic analysis of gene properties influencing organ system phenotypes in mammalian perturbations , 2014, Bioinform..

[15]  Norio Ozaki,et al.  Variants of dopamine and serotonin candidate genes as predictors of response to risperidone treatment in first-episode schizophrenia. , 2008, Pharmacogenomics.

[16]  R. Vossen,et al.  Complete Sequencing of TP 53 Predicts Poor Response to Systemic Therapy of Advanced Breast Cancer 1 , 2000 .

[17]  Anton Glieder,et al.  New opportunities by synthetic biology for biopharmaceutical production in Pichia pastoris , 2013, Current opinion in biotechnology.

[18]  R. Higgs,et al.  Small-molecule affinity chromatography coupled mass spectrometry for drug target deconvolution , 2009, Expert opinion on drug discovery.

[19]  P. Robinson,et al.  The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. , 2008, American journal of human genetics.

[20]  P. Clemons,et al.  Target identification and mechanism of action in chemical biology and drug discovery. , 2013, Nature chemical biology.

[21]  J. Holly,et al.  Effect of low dose oxandrolone and testosterone treatment on the pituitary‐testicular and GH axes in boys with constitutional delay of growth and puberty , 1997, Clinical endocrinology.

[22]  Michael Goodman.  Market watch: Sales of biologics to show robust growth through to 2013 , 2009, Nature Reviews Drug Discovery.

[23]  Michael J. Keiser,et al.  Predicting new molecular targets for known drugs , 2009, Nature.

[24]  David M. Reif,et al.  In Vitro Screening of Environmental Chemicals for Targeted Testing Prioritization: The ToxCast Project , 2009, Environmental health perspectives.

[25]  Cynthia L. Smith,et al.  The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information , 2004, Genome Biology.

[26]  G. Labesse,et al.  PROKR2 missense mutations associated with Kallmann syndrome impair receptor signalling activity. , 2009, Human molecular genetics.

[27]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[28]  P. Hindmarsh,et al.  The effects of oxandrolone on the growth hormone and gonadal axes in boys with constitutional delay of growth and puberty , 1993, Clinical endocrinology.

[29]  A. Sands,et al.  Knockouts model the 100 best-selling drugs—will they model the next 100? , 2003, Nature Reviews Drug Discovery.

[30]  David S. Wishart,et al.  DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs , 2010, Nucleic Acids Res..

[31]  D. Herndon,et al.  Five-year outcomes after oxandrolone administration in severely burned children: a randomized clinical trial of safety and efficacy. , 2012, Journal of the American College of Surgeons.

[32]  Kenji F. Tanaka,et al.  Leptin-dependent serotonin control of appetite: temporal specificity, transcriptional regulation, and therapeutic implications , 2011, The Journal of experimental medicine.

[33]  R. Vossen,et al.  Complete sequencing of TP53 predicts poor response to systemic therapy of advanced breast cancer. , 2000, Cancer research.

[34]  E J Licitra,et al.  A three-hybrid system for detecting small ligand-protein receptor interactions. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[35]  Gary Walsh,et al.  Post-translational modifications in the context of therapeutic proteins , 2006, Nature Biotechnology.

[36]  Nisha S. Sipes,et al.  In vitro and modelling approaches to risk assessment from the U.S. Environmental Protection Agency ToxCast programme. , 2014, Basic & clinical pharmacology & toxicology.

[37]  R. McLendon,et al.  A PK2/Bv8/PROK2 Antagonist Suppresses Tumorigenic Processes by Inhibiting Angiogenesis in Glioma and Blocking Myeloid Cell Infiltration in Pancreatic Cancer , 2013, PloS one.

[38]  G. Terstappen,et al.  Target deconvolution strategies in drug discovery , 2007, Nature Reviews Drug Discovery.

[39]  P. Bork,et al.  Drug Target Identification Using Side-Effect Similarity , 2008, Science.

[40]  Howard L McLeod,et al.  Pharmacogenomics--drug disposition, drug targets, and side effects. , 2003, The New England journal of medicine.

[41]  M. Niv,et al.  Modeling of Human Prokineticin Receptors: Interactions with Novel Small-Molecule Binders and Potential Off-Target Drugs , 2011, PloS one.

[42]  Shiaoching Gong,et al.  Signaling Role of Prokineticin 2 on the Estrous Cycle of Female Mice , 2014, PloS one.

[43]  A. Y. Lu,et al.  Pharmacogenomics and Individualized Medicine , 2012 .

[44]  Damian Szklarczyk,et al.  The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored , 2010, Nucleic Acids Res..

[45]  Monica Campillos,et al.  HitPick: a web server for hit identification and target prediction of chemical screenings , 2013, Bioinform..

[46]  Nigel W. Hardy,et al.  Mouse model phenotypes provide information about human drug targets , 2013, Bioinform..

[47]  P. Bork,et al.  Systematic identification of proteins that elicit drug side effects , 2013, Molecular systems biology.

[48]  Damian Szklarczyk,et al.  STITCH 3: zooming in on protein–chemical interactions , 2011, Nucleic Acids Res..

[49]  A. Egberts,et al.  Polymorphisms of the LEP- and LEPR Gene and Obesity in Patients Using Antipsychotic Medication , 2009, Journal of clinical psychopharmacology.

[50]  M. Campillos,et al.  Molecularly and clinically related drugs and diseases are enriched in phenotypically similar drug-disease pairs , 2014, Genome Medicine.

[51]  Peer Bork,et al.  Drug-Induced Regulation of Target Expression , 2010, PLoS Comput. Biol..

[52]  V. Mahesh.  Hirsutism, virilism, polycystic ovarian disease, and the steroid-gonadotropin-feedback system: a career retrospective. , 2012, American journal of physiology. Endocrinology and metabolism.

[53]  Michael J. Keiser,et al.  Large Scale Prediction and Testing of Drug Activity on Side-Effect Targets , 2012, Nature.

[54]  Dan Chen,et al.  Functional Rescue of Kallmann Syndrome-associated Prokineticin Receptor 2 (PKR2) Mutants Deficient in Trafficking* , 2014, The Journal of Biological Chemistry.

[55]  A. Hopkins,et al.  The druggable genome , 2002, Nature Reviews Drug Discovery.

[56]  Sandy Wilson,et al.  Identification and Pharmacological Characterization of Prokineticin 2β as a Selective Ligand for Prokineticin Receptor 1 , 2005, Molecular Pharmacology.

[57]  R. de Kanter,et al.  Species differences between mouse, rat, dog, monkey and human CYP-mediated drug metabolism, inhibition and induction , 2006, Expert opinion on drug metabolism & toxicology.

[58]  A. Cato,et al.  Rapid Actions of Steroid Receptors in Cellular Signaling Pathways , 2002, Science's STKE.

[59]  A. Y. Lu,et al.  Pharmacogenetics, Pharmacogenomics, and Individualized Medicine , 2011, Pharmacological Reviews.

[60]  Christian von Mering,et al.  STRING: known and predicted protein–protein associations, integrated and transferred across organisms , 2004, Nucleic Acids Res..

[61]  Kenji F. Tanaka,et al.  A Serotonin-Dependent Mechanism Explains the Leptin Regulation of Bone Mass, Appetite, and Energy Expenditure , 2009, Cell.

[62]  S. Salvadori,et al.  Triazine compounds as antagonists at Bv8-prokineticin receptors. , 2008, Journal of medicinal chemistry.

[63]  A. Karim,et al.  Oxandrolone disposition and metabolism in man , 1973, Clinical pharmacology and therapeutics.

[64]  Alberto Inga,et al.  The expanding universe of p53 targets , 2009, Nature Reviews Cancer.

[65]  C. Anfinsen,et al.  Selective enzyme purification by affinity chromatography. , 1968, Proceedings of the National Academy of Sciences of the United States of America.

[66]  Alan R. Aronson,et al.  Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program , 2001, AMIA.

[67]  Allen C. Browne,et al.  UMLS language and vocabulary tools. , 2003, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[68]  Jing Chen,et al.  Improved human disease candidate gene prioritization using mouse phenotype , 2007, BMC Bioinformatics.

[69]  E. Brown,et al.  The Medical Dictionary for Regulatory Activities (MedDRA) , 1999, Drug safety.

[70]  P. Ng,et al.  Phen-Gen: combining phenotype and genotype to analyze rare disorders , 2014, Nature Methods.

[71]  J. Drews.  Stategic trends in the drug industry. , 2003, Drug discovery today.

[72]  K. Brower.  Anabolic steroid abuse and dependence , 2002, Current psychiatry reports.

[73]  D. Chinkes,et al.  Anabolic Effects of Oxandrolone After Severe Burn , 2001, Annals of surgery.

[74]  R. Quinton,et al.  Mutations in prokineticin 2 and prokineticin receptor 2 genes in human gonadotrophin-releasing hormone deficiency: molecular genetics and clinical spectrum. , 2008, The Journal of clinical endocrinology and metabolism.