Drug target identification through systems biology

Levy, 2004, Antibacterial resistance worldwide: causes, challenges and responses, Nat Med, 10, S122, 10.1038/nm1145 Wu, 2014, Multi-drug resistance in cancer chemotherapeutics: mechanisms and lab approaches, Cancer Lett, 347, 159, 10.1016/j.canlet.2014.03.013 Barrett, 2011, Drug resistance in human African trypanosomiasis, Future Microbiol, 6, 1037, 10.2217/fmb.11.88 Krauth-Siegel, 2012, Low-molecular-mass antioxidants in parasites, Antioxid Redox Signal, 17, 583, 10.1089/ars.2011.4392 Hanahan, 2011, Hallmarks of cancer: the next generation, Cell, 144, 646, 10.1016/j.cell.2011.02.013 Marrero, 2013, Glucose phosphorylation is required for Mycobacterium tuberculosis persistence in mice, PLoS Pathog, 9, e1003116, 10.1371/journal.ppat.1003116 Haanstra, 2011, A domino effect in drug action: from metabolic assault towards parasite differentiation, Mol Microbiol, 79, 94, 10.1111/j.1365-2958.2010.07435.x Zambrowicz, 2003, Knockouts model the 100 best-selling drugs – will they model the next 100?, Nat Rev Drug Discov, 2, 38, 10.1038/nrd987 Wang, 2013, One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering, Cell, 153, 910, 10.1016/j.cell.2013.04.025 Hartman, 2014, Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation, Microbiology, 160, 1252, 10.1099/mic.0.076091-0 Shameer, 2015, TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei, Nucleic Acids Res, 43, D637, 10.1093/nar/gku944 Mintz-Oron, 2012, Reconstruction of Arabidopsis metabolic network models accounting for subcellular compartmentalization and tissue-specificity, Proc Natl Acad Sci U S A, 109, 339, 10.1073/pnas.1100358109 Thiele, 2013, A community-driven global reconstruction of human metabolism, Nat Biotechnol, 31, 419, 10.1038/nbt.2488 Rossell, 2013, Inferring metabolic states in uncharacterized environments using gene-expression measurements, PLoS Comput Biol, 9, e1002988, 10.1371/journal.pcbi.1002988 Rossell, 2011, Towards a quantitative prediction of the fluxome from the proteome, Metab Eng, 13, 253, 10.1016/j.ymben.2011.01.010 Jerby, 2010, Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism, Mol Syst Biol, 6, 401, 10.1038/msb.2010.56 Ruppin, 2010, Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks, Curr Opin Biotechnol, 21, 502, 10.1016/j.copbio.2010.07.002 Ghozlane, 2012, Flux analysis of the Trypanosoma brucei glycolysis based on a multiobjective-criteria bioinformatic approach, Adv Bioinform, 2012, 159423, 10.1155/2012/159423 Kim, 2011, Integrative genome-scale metabolic analysis of Vibrio vulnificus for drug targeting and discovery, Mol Syst Biol, 7, 460, 10.1038/msb.2010.115 Chavali, 2012, Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease, BMC Syst Biol, 6, 27, 10.1186/1752-0509-6-27 Guell, 2014, Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis, PLoS Comput Biol, 10, e1003637, 10.1371/journal.pcbi.1003637 Lankelma, 1999, Doxorubicin gradients in human breast cancer, Clin Cancer Res, 5, 1703 Jasmer, 2004, Recurrent tuberculosis in the United States and Canada: relapse or reinfection?, Am J Respir Crit Care Med, 170, 1360, 10.1164/rccm.200408-1081OC Pratt, 2014, Genetic validation of Trypanosoma brucei glutathione synthetase as an essential enzyme, Eukaryot Cell, 13, 614, 10.1128/EC.00015-14 Albert, 2005, Experimental and in silico analyses of glycolytic flux control in bloodstream form Trypanosoma brucei, J Biol Chem, 280, 28306, 10.1074/jbc.M502403200 Bakker, 1997, Glycolysis in bloodstream form Trypanosoma brucei can be understood in terms of the kinetics of the glycolytic enzymes, J Biol Chem, 272, 3207, 10.1074/jbc.272.6.3207 Kerkhoven, 2013, Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei, PLoS Comput Biol, 9, e1003371, 10.1371/journal.pcbi.1003371 Teusink, 2000, Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry, Eur J Biochem/FEBS, 267, 5313, 10.1046/j.1432-1327.2000.01527.x Holzhutter, 2004, The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks, Eur J Biochem/FEBS, 271, 2905, 10.1111/j.1432-1033.2004.04213.x Konig, 2012, Quantifying the contribution of the liver to glucose homeostasis: a detailed kinetic model of human hepatic glucose metabolism, PLoS Comput Biol, 8, e1002577, 10.1371/journal.pcbi.1002577 Lambeth, 2002, A computational model for glycogenolysis in skeletal muscle, Ann Biomed Eng, 30, 808, 10.1114/1.1492813 van Eunen, 2013, Biochemical competition makes fatty-acid beta-oxidation vulnerable to substrate overload, PLoS Comput Biol, 9, e1003186, 10.1371/journal.pcbi.1003186 Geenen, 2013, Glutathione metabolism modeling: a mechanism for liver drug-robustness and a new biomarker strategy, Biochim Biophys Acta, 1830, 4943, 10.1016/j.bbagen.2013.04.014 Fell, 1997 Bakker, 1999, What controls glycolysis in bloodstream form Trypanosoma brucei?, J Biol Chem, 274, 14551, 10.1074/jbc.274.21.14551 Bakker, 1999, Contribution of glucose transport to the control of the glycolytic flux in Trypanosoma brucei, Proc Natl Acad Sci U S A, 96, 10098, 10.1073/pnas.96.18.10098 Alsford, 2013, Genetic dissection of drug resistance in trypanosomes, Parasitology, 140, 1478, 10.1017/S003118201300022X Palmer, 2014, Opposing effects of target overexpression reveal drug mechanisms, Nat Commun, 5, 4296, 10.1038/ncomms5296 Hornberg, 2006, Oncogenes are to lose control on signaling following mutation: should we aim off target?, Mol Biotechnol, 34, 109, 10.1385/MB:34:2:109 Hernandez Patino, 2012, Systems biology of cancer: moving toward the integrative study of the metabolic alterations in cancer cells, Front Physiol, 3, 481 Shlomi, 2011, Genome-scale metabolic modeling elucidates the role of proliferative adaptation in causing the Warburg effect, PLoS Comput Biol, 7, e1002018, 10.1371/journal.pcbi.1002018 Tiemann, 2011, Parameter adaptations during phenotype transitions in progressive diseases, BMC Syst Biol, 5, 174, 10.1186/1752-0509-5-174 Alsford, 2012, High-throughput decoding of antitrypanosomal drug efficacy and resistance, Nature, 482, 232, 10.1038/nature10771 Bakker, 2002, Network-based selectivity of antiparasitic inhibitors, Mol Biol Rep, 29, 1, 10.1023/A:1020397513646 Folger, 2011, Predicting selective drug targets in cancer through metabolic networks, Mol Syst Biol, 7, 501, 10.1038/msb.2011.35 Olivier, 2004, Web-based kinetic modelling using JWS Online, Bioinformatics, 20, 2143, 10.1093/bioinformatics/bth200 Li, 2010, BioModels Database: an enhanced, curated and annotated resource for published quantitative kinetic models, BMC Syst Biol, 4, 92, 10.1186/1752-0509-4-92 Bazzani, 2012, Network-based assessment of the selectivity of metabolic drug targets in Plasmodium falciparum with respect to human liver metabolism, BMC Syst Biol, 6, 118, 10.1186/1752-0509-6-118 Penkler, 2013