Drug—target network

The global set of relationships between protein targets of all drugs and all disease-gene products in the human protein–protein interaction or 'interactome' network remains uncharacterized. We built a bipartite graph composed of US Food and Drug Administration–approved drugs and proteins linked by drug–target binary associations. The resulting network connects most drugs into a highly interlinked giant component, with strong local clustering of drugs of similar types according to Anatomical Therapeutic Chemical classification. Topological analyses of this network quantitatively showed an overabundance of 'follow-on' drugs, that is, drugs that target already targeted proteins. By including drugs currently under investigation, we identified a trend toward more functionally diverse targets improving polypharmacology. To analyze the relationships between drug targets and disease-gene products, we measured the shortest distance between both sets of proteins in current models of the human interactome network. Significant differences in distance were found between etiological and palliative drugs. A recent trend toward more rational drug design was observed.

[1]  M. DePamphilis,et al.  HUMAN DISEASE , 1957, The Ulster Medical Journal.

[2]  K. Johnson An Update. , 1984, Journal of food protection.

[3]  G. Scangos,et al.  Drug discovery in the postgenomic era , 1997, Nature Biotechnology.

[4]  J. Hopfield,et al.  From molecular to modular cell biology , 1999, Nature.

[5]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[6]  D. Fell,et al.  The small world inside large metabolic networks , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[7]  Leena Peltonen,et al.  Dissecting Human Disease in the Postgenomic Era , 2001, Science.

[8]  David Valle,et al.  Human disease genes , 2001, Nature.

[9]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

[11]  Nicola J. Rinaldi,et al.  Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.

[12]  K. Lindpaintner The impact of pharmacogenetics and pharmacogenomics on drug discovery , 2002, Nature Reviews Drug Discovery.

[13]  Alan F. Scott,et al.  Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders , 2002, Nucleic Acids Res..

[14]  Alex Matter,et al.  Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug , 2002, Nature Reviews Drug Discovery.

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

[16]  Leland J. Gershell,et al.  A brief history of novel drug discovery technologies , 2003, Nature Reviews Drug Discovery.

[17]  Sumit K Chanda,et al.  Fulfilling the promise: drug discovery in the post-genomic era. , 2003, Drug discovery today.

[18]  D. Searls Pharmacophylogenomics: genes, evolution and drug targets , 2003, Nature Reviews Drug Discovery.

[19]  M. Gerstein,et al.  Structure and evolution of transcriptional regulatory networks. , 2004, Current opinion in structural biology.

[20]  E. Kunkel Systems biology in drug discovery , 2004, Nature Biotechnology.

[21]  B. Roth,et al.  Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia , 2004, Nature Reviews Drug Discovery.

[22]  T. Hubbard,et al.  A census of human cancer genes , 2004, Nature Reviews Cancer.

[23]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[24]  Lan V. Zhang,et al.  Evidence for dynamically organized modularity in the yeast protein–protein interaction network , 2004, Nature.

[25]  Andrey Rzhetsky,et al.  Emergent behavior of growing knowledge about molecular interactions , 2005, Nature Biotechnology.

[26]  J. Greef,et al.  Rescuing drug discovery: in vivo systems pathology and systems pharmacology , 2005, Nature Reviews Drug Discovery.

[27]  Simon K. Mencher,et al.  Promiscuous drugs compared to selective drugs (promiscuity can be a virtue) , 2005, BMC clinical pharmacology.

[28]  H. Lehrach,et al.  A Human Protein-Protein Interaction Network: A Resource for Annotating the Proteome , 2005, Cell.

[29]  S. Lampel,et al.  The druggable genome: an update. , 2005, Drug discovery today.

[30]  Ricard V Solé,et al.  Topology, tinkering and evolution of the human transcription factor network , 2005, The FEBS journal.

[31]  Marc Vidal,et al.  Interactome modeling , 2005, FEBS letters.

[32]  H. Aburatani,et al.  Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. , 2005, Genomics.

[33]  Judith A. Blake,et al.  The Mouse Genome Database (MGD): from genes to mice—a community resource for mouse biology , 2004, Nucleic Acids Res..

[34]  S. L. Wong,et al.  Towards a proteome-scale map of the human protein–protein interaction network , 2005, Nature.

[35]  John P. Overington,et al.  Can we rationally design promiscuous drugs? , 2006, Current opinion in structural biology.

[36]  John P. Overington,et al.  How many drug targets are there? , 2006, Nature Reviews Drug Discovery.

[37]  Celerino Abad-Zapatero,et al.  Faculty Opinions recommendation of DrugBank: a comprehensive resource for in silico drug discovery and exploration. , 2006 .

[38]  G. V. Paolini,et al.  Global mapping of pharmacological space , 2006, Nature Biotechnology.

[39]  Neda Nategh,et al.  Evidence for dynamically organized modularity in the yeast protein-protein interaction network , 2006 .

[40]  P. Imming,et al.  Drugs, their targets and the nature and number of drug targets , 2006, Nature Reviews Drug Discovery.

[41]  David S. Wishart,et al.  DrugBank: a comprehensive resource for in silico drug discovery and exploration , 2005, Nucleic Acids Res..

[42]  A. Barabasi,et al.  The human disease network , 2007, Proceedings of the National Academy of Sciences.