Biochemical network-based drug-target prediction.

The use of networks to aid the drug discovery process is a rather new but booming endeavor. A vast variety of different types of networks are being constructed and analyzed for various different tasks in drug discovery. The analysis may be at the level of establishing connectivity, topology, and graphs, or may go to a more quantitative level. We discuss here how computational systems biology approaches can aid the quantitative analysis of biochemical networks for drug-target prediction. We focus on networks and pathways in which the components are related by physical interactions or biochemical processes. We particularly discuss the potential of mathematical modeling to aid the analysis of proteins for druggability.

[1]  Clifford Dobell,et al.  The Life-history and Chromosome Cycle of Aggregata eberthi [Protozoa: Sporozoa: Coccidia] , 1925, Parasitology.

[2]  Paul A. Bates,et al.  Mathematical modeling identifies Smad nucleocytoplasmic shuttling as a dynamic signal-interpreting system , 2008, Proceedings of the National Academy of Sciences.

[3]  Rainer Breitling,et al.  Metabolomic systems biology of trypanosomes , 2010, Parasitology.

[4]  D. Lauffenburger,et al.  Input–output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data , 2009, Molecular systems biology.

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

[6]  Yukiko Matsuoka,et al.  Using process diagrams for the graphical representation of biological networks , 2005, Nature Biotechnology.

[7]  Masamitsu Iino,et al.  System-level identification of transcriptional circuits underlying mammalian circadian clocks , 2005, Nature Genetics.

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

[9]  John P. Overington,et al.  Genomic-scale prioritization of drug targets: the TDR Targets database , 2008, Nature Reviews Drug Discovery.

[10]  Lu Huang,et al.  Update of TTD: Therapeutic Target Database , 2009, Nucleic Acids Res..

[11]  Jens Timmer,et al.  Systems-level interactions between insulin–EGF networks amplify mitogenic signaling , 2009, Molecular systems biology.

[12]  Igor Goryanin,et al.  Kinetic modelling of NSAID action on COX-1: focus on in vitro/in vivo aspects and drug combinations. , 2009, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[13]  Christian von Mering,et al.  STITCH: interaction networks of chemicals and proteins , 2007, Nucleic Acids Res..

[14]  A. Barabasi,et al.  Drug—target network , 2007, Nature Biotechnology.

[15]  Sven Sahle,et al.  A new strategy for assessing sensitivities in biochemical models , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[16]  S. Kuhara,et al.  An integrative in silico approach for discovering candidates for drug-targetable protein-protein interactions in interactome data , 2007, BMC pharmacology.

[17]  Olaf Wolkenhauer,et al.  Report on EU–USA Workshop: How Systems Biology Can Advance Cancer Research (27 October 2008) , 2009, Molecular oncology.

[18]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[19]  Nagasuma R. Chandra,et al.  Flux balance analysis of biological systems: applications and challenges , 2009, Briefings Bioinform..

[20]  R. Solé,et al.  The topology of drug-target interaction networks: implicit dependence on drug properties and target families. , 2009, Molecular bioSystems.

[21]  Jaques Reifman,et al.  A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis , 2009, BMC Systems Biology.

[22]  Holger Fröhlich,et al.  Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance , 2009, BMC Systems Biology.

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

[24]  Steffen Klamt,et al.  The Logic of EGFR/ErbB Signaling: Theoretical Properties and Analysis of High-Throughput Data , 2009, PLoS Comput. Biol..

[25]  Jean Clairambault,et al.  Circadian timing in cancer treatments. , 2010, Annual review of pharmacology and toxicology.

[26]  Paul Brazhnik,et al.  Computational analysis of dynamical responses to the intrinsic pathway of programmed cell death. , 2009, Biophysical journal.

[27]  Edda Klipp,et al.  TIde: a software for the systematic scanning of drug targets in kinetic network models , 2009, BMC Bioinformatics.

[28]  Robert B. Russell,et al.  SuperTarget and Matador: resources for exploring drug-target relationships , 2007, Nucleic Acids Res..

[29]  Hiroaki Kitano,et al.  Structure of Protein Interaction Networks and Their Implications on Drug Design , 2009, PLoS Comput. Biol..

[30]  Steven A. Brown,et al.  Molecular insights into human daily behavior , 2008, Proceedings of the National Academy of Sciences.

[31]  Anton Yuryev,et al.  Pathway analysis for drug discovery : computational infrastructure and applications , 2008 .

[32]  Matthias Stein,et al.  SYCAMORE - a systems biology computational analysis and modeling research environment , 2008, Bioinform..

[33]  Xiaomin Luo,et al.  PDTD: a web-accessible protein database for drug target identification , 2008, BMC Bioinformatics.

[34]  Martin Vingron,et al.  A systems biological approach suggests that transcriptional feedback regulation by dual‐specificity phosphatase 6 shapes extracellular signal‐related kinase activity in RAS‐transformed fibroblasts , 2009, The FEBS journal.

[35]  David S. Wishart,et al.  DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..

[36]  Giovanni Colonna,et al.  Modeling of the Bacterial Mechanism of Methicillin-Resistance by a Systems Biology Approach , 2009, PloS one.

[37]  J. Mestres,et al.  Drug‐Target Networks , 2010, Molecular informatics.

[38]  Ueli Schibler,et al.  Circadian rhythms: mechanisms and therapeutic implications. , 2007, Annual review of pharmacology and toxicology.

[39]  Edda Klipp,et al.  Constraint-Based Modeling and Kinetic Analysis of the Smad Dependent TGF-β Signaling Pathway , 2007, PloS one.

[40]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[41]  Reinhart Heinrich,et al.  The Roles of APC and Axin Derived from Experimental and Theoretical Analysis of the Wnt Pathway , 2003, PLoS biology.

[42]  P. Sorger,et al.  Systems biology and combination therapy in the quest for clinical efficacy , 2006, Nature chemical biology.

[43]  Renate Kania,et al.  Storing and Annotating of Kinetic Data , 2007, Silico Biol..

[44]  R Nussinov,et al.  Towards drugs targeting multiple proteins in a systems biology approach. , 2007, Current topics in medicinal chemistry.

[45]  J. Timmer,et al.  Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Damian Szklarczyk,et al.  STITCH 2: an interaction network database for small molecules and proteins , 2009, Nucleic Acids Res..

[47]  Alexander N. Gorban,et al.  Robust simplifications of multiscale biochemical networks , 2008, BMC Systems Biology.

[48]  P. Bork,et al.  iPath: interactive exploration of biochemical pathways and networks. , 2008, Trends in biochemical sciences.

[49]  James Vlasblom,et al.  Challenges and Rewards of Interaction Proteomics * , 2009, Molecular & Cellular Proteomics.

[50]  Wei Jiang,et al.  The analysis of the drug–targets based on the topological properties in the human protein–protein interaction network , 2009, Journal of drug targeting.

[51]  V. Grantcharova,et al.  Therapeutically Targeting ErbB3: A Key Node in Ligand-Induced Activation of the ErbB Receptor–PI3K Axis , 2009, Science Signaling.