In silico repositioning of approved drugs for rare and neglected diseases

Drug Discovery Today - Tập 16 Số 7-8 - Trang 298-310 - 2011
Sean Ekins1,2,3,4, Antony Williams5, Matthew D. Krasowski6, Joel S. Freundlich7
1Collaborations in Chemistry, 601 Runnymede Avenue, Jenkintown, PA 19046, USA
2Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA 94010, USA
3Department of Pharmaceutical Sciences, University of Maryland, College Park, MD 21201, USA
4Department of Pharmacology, University of Medicine & Dentistry of New Jersey–Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ 08854, USA
5Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC, 27587, USA
6Department of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
7Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA

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Fidock, 2010, Drug discovery: priming the antimalarial pipeline, Nature, 465, 297, 10.1038/465297a

Balganesh, 2008, Rising standards for tuberculosis drug development, Trends Pharmacol. Sci., 29, 576, 10.1016/j.tips.2008.08.001

Griggs, 2009, Clinical research for rare disease: opportunities, challenges, and solutions, Mol. Genet. Metab., 96, 20, 10.1016/j.ymgme.2008.10.003

Brewer, 2009, Drug development for orphan diseases in the context of personalized medicine, Transl. Res., 154, 314, 10.1016/j.trsl.2009.03.008

Ashburn, 2004, Drug repositioning: identifying and developing new uses for existing drugs, Nat. Rev. Drug Discov., 3, 673, 10.1038/nrd1468

Lehar, 2008, High-order combination effects and biological robustness, Mol. Syst. Biol., 4, 215, 10.1038/msb.2008.51

Borisy, 2003, Systematic discovery of multicomponent therapeutics, Proc. Natl. Acad. Sci. U.S.A., 100, 7977, 10.1073/pnas.1337088100

Cavalla, 2009, APT drug R&D: the right active ingredient in the right presentation for the right therapeutic use, Nat. Rev. Drug Discov., 8, 849, 10.1038/nrd2981

Boguski, 2009, Drug discovery. Repurposing with a difference, Science, 324, 1394, 10.1126/science.1169920

Uliana, S.R. and Barcinski, M.A. (2009) Repurposing for neglected diseases. Science 326, 935; author reply, 935

Payne, 2007, Drugs for bad bugs: confronting the challenges of antibacterial discovery, Nat. Rev. Drug Discov., 6, 29, 10.1038/nrd2201

Fischbach, 2009, Antibiotics for emerging pathogens, Science, 325, 1089, 10.1126/science.1176667

Miller, 2009, A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore, Proc. Natl. Acad. Sci. U.S.A., 106, 1737, 10.1073/pnas.0811275106

Walsh, 2009, Repurposing libraries of eukaryotic protein kinase inhibitors for antibiotic discovery, Proc. Natl. Acad. Sci. U.S.A., 106, 1689, 10.1073/pnas.0813405106

Ekins, 2007, In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling, Br. J. Pharmacol., 152, 9, 10.1038/sj.bjp.0707305

Ekins, 2010, Precompetitive preclinical ADME/Tox data: set it free on the web to facilitate computational model building to assist drug development, Lab Chip, 10, 13, 10.1039/B917760B

Chong, 2007, New uses for old drugs, Nature, 448, 645, 10.1038/448645a

Krejsa, 2003, Predicting ADME properties and side effects: the BioPrint approach, Curr. Opin. Drug Discov. Dev., 6, 470

Lougheed, 2009, New anti-tuberculosis agents amongst known drugs, Tuberculosis, 89, 364, 10.1016/j.tube.2009.07.002

O’Connor, 2005, Finding new tricks for old drugs: an efficient route for public-sector drug discovery, Nat. Rev. Drug Discov., 4, 1005, 10.1038/nrd1900

Ekins, 2007, In silico pharmacology for drug discovery: applications to targets and beyond, Br. J. Pharmacol., 152, 21, 10.1038/sj.bjp.0707306

Kauvar, 1995, Predicting ligand binding to proteins by affinity fingerprinting, Chem. Biol., 2, 107, 10.1016/1074-5521(95)90283-X

Kauvar, 1998, The diversity challenge in combinatorial chemistry, Curr. Opin. Drug Discov. Dev., 1, 66

Kauvar, 1998, Protein affinity map of chemical space, J. Chromatogr. B, 715, 93, 10.1016/S0378-4347(98)00045-0

Ma’ayan, 2007, Network analysis of FDA approved drugs and their targets, Mt Sinai J. Med., 74, 27, 10.1002/msj.20002

Gomella, 2004

Ekins, 2005, In vitro and pharmacophore based discovery of novel hPEPT1 inhibitors, Pharm. Res., 22, 512, 10.1007/s11095-005-2505-y

Chang, 2006, Rapid identification of P-glycoprotein substrates and inhibitors, Drug Metab. Dispos., 34, 1976, 10.1124/dmd.106.012351

Diao, 2010, Quantitative structure activity relationship for inhibition of human organic cation/carnitine transporter, Mol. Pharm., 7, 2120, 10.1021/mp100226q

Diao, 2009, Novel inhibitors of human organic cation/carnitine transporter (hOCTN2) via computational modeling and in vitro testing, Pharm. Res., 26, 1890, 10.1007/s11095-009-9905-3

Zheng, 2009, Computational models for drug inhibition of the human apical sodium-dependent bile acid transporter, Mol. Pharm., 6, 1591, 10.1021/mp900163d

Lamichhane, 2011, Essential metabolites of M. tuberculosis and their mimics, Mbio., 2, e00301, 10.1128/mBio.00301-10

Krasowski, 2009, Molecular similarity methods for predicting cross-reactivity with therapeutic drug monitoring immunoassays, Ther. Drug Monit., 31, 337, 10.1097/FTD.0b013e31819c1b83

Krasowski, M.D. et al. (2010) Immunoassays for tricyclic antidepressants: unsuitable for therapeutic drug monitoring. In Advances in Chromatographic Techniques for Therapeutic Drug Monitoring (Dasgupta, A., ed.), pp. 179–190, CRC Press

Krasowski, 2009, Chemoinformatic methods for predicting interference in drug of abuse/toxicology immunoassays, Clin. Chem., 55, 1203, 10.1373/clinchem.2008.118638

Krasowski, 2009, Using molecular similarity to highlight the challenges of routine immunoassay-based drug of abuse/toxicology screening in emergency medicine, BMC Emerg. Med., 9, 5, 10.1186/1471-227X-9-5

Reid, 2008, LASSO-ligand activity by surface similarity order: a new tool for ligand based virtual screening, J. Comput. Aided Mol. Des., 22, 479, 10.1007/s10822-007-9164-5

Williams, 2008, Internet-based tools for communication and collaboration in chemistry, Drug Discov. Today, 13, 502, 10.1016/j.drudis.2008.03.015

Poroikov, 2000, Robustness of biological activity spectra predicting by computer program PASS for noncongeneric sets of chemical compounds, J. Chem. Inf. Comput. Sci., 40, 1349, 10.1021/ci000383k

Kortagere, 2009, The importance of discerning shape in molecular pharmacology, Trends Pharmacol. Sci., 30, 138, 10.1016/j.tips.2008.12.001

Li, 2006, A large-scale computational approach to drug repositioning, Genome Inform., 17, 239

Ekins, 2009, A systems-biology view of drug transporters, 365

Ekins, 2006, Computers and systems biology for Pharmaceutical Research and Development, 139

Ekins, 2006, Algorithms for network analysis in systems: ADME/Tox using the MetaCore and MetaDrug platforms, Xenobiotica, 36, 877, 10.1080/00498250600861660

Ekins, 2006, Systems-ADME/Tox: resources and network approaches, J. Pharmacol. Toxicol. Methods, 53, 38, 10.1016/j.vascn.2005.05.005

Ekins, 2005, Techniques: application of systems biology to absorption, distribution, metabolism, excretion, and toxicity, Trends Pharmacol. Sci., 26, 202, 10.1016/j.tips.2005.02.006

Fliri, 2005, Biological spectra analysis: linking biological activity profiles to molecular structure, Proc. Natl. Acad. Sci. U.S.A., 102, 261, 10.1073/pnas.0407790101

Fliri, 2005, Biospectra analysis: model proteome characterizations for linking molecular structure and biological response, J. Med. Chem., 48, 6918, 10.1021/jm050494g

Fliri, 2005, Analysis of drug-induced effect patterns to link structure and side effects of medicines, Nat. Chem. Biol., 1, 389, 10.1038/nchembio747

Ekins, 2004, Predicting undesirable drug interactions with promiscuous proteins in silico, Drug Discov. Today, 9, 276, 10.1016/S1359-6446(03)03008-3

Ekins, 2006, A combined approach to drug metabolism and toxicity assessment, Drug Metab. Dispos., 34, 495, 10.1124/dmd.105.008458

Nikolsky, 2005, A novel method for generation of signature networks as biomarkers from complex high throughput data, Toxicol. Lett., 158, 20, 10.1016/j.toxlet.2005.02.004

Ekins, 2005, Systems biology: applications in drug discovery, 123

Ekins, 2007, Pathway mapping tools for analysis of high content data, Methods Mol. Biol., 356, 319

Paolini, 2006, Global mapping of pharmacological space, Nat. Biotechnol., 24, 805, 10.1038/nbt1228

Wishart, 2008, DrugBank: a knowledgebase for drugs, drug actions and drug targets, Nucleic Acids Res., 36, D901, 10.1093/nar/gkm958

Yildirim, 2007, Drug-target network, Nat. Biotechnol., 25, 1119, 10.1038/nbt1338

Keiser, 2007, Relating protein pharmacology by ligand chemistry, Nat. Biotechnol., 25, 197, 10.1038/nbt1284

Metz, 2010, Rational approaches to targeted polypharmacology: creating and navigating protein–ligand interaction networks, Curr. Opin. Chem. Biol., 14, 498, 10.1016/j.cbpa.2010.06.166

Cases, 2009, A chemogenomic approach to drug discovery: focus on cardiovascular diseases, Drug Discov. Today, 14, 479, 10.1016/j.drudis.2009.02.010

Berg, 2010, Chemical target and pathway toxicity mechanisms defined in primary human cell systems, J. Pharmacol. Toxicol. Methods, 61, 3, 10.1016/j.vascn.2009.10.001

Bender, 2007, Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure, ChemMedChem, 2, 861, 10.1002/cmdc.200700026

Azzaoui, 2007, Modeling Promiscuity based on in vitro safety pharmacology profiling data, ChemMedChem, 2, 874, 10.1002/cmdc.200700036

Scheiber, 2009, Gaining insight into off-target mediated effects of drug candidates with a comprehensive systems chemical biology analysis, J. Chem. Inf. Model., 49, 308, 10.1021/ci800344p

Scheiber, 2009, Mapping adverse drug reactions in chemical space, J. Med. Chem., 52, 3103, 10.1021/jm801546k

Keiser, 2009, Predicting new molecular targets for known drugs, Nature, 462, 175, 10.1038/nature08506

Hammann, 2010, Prediction of adverse drug reactions using decision tree modeling, Clin. Pharmacol. Ther., 88, 52, 10.1038/clpt.2009.248

Gurulingappa, 2009, Concept-based semi-automatic classification of drugs, J. Chem. Inf. Model., 49, 1986, 10.1021/ci9000844

Chiang, 2009, Systematic evaluation of drug–disease relationships to identify leads for novel drug uses, Clin. Pharmacol. Ther., 86, 507, 10.1038/clpt.2009.103

von Eichborn, 2011, PROMISCUOUS: a database for network-based drug-repositioning, Nucleic Acids Res., 39, D1060, 10.1093/nar/gkq1037

Ha, 2008, IDMap: facilitating the detection of potential leads with therapeutic targets, Bioinformatics, 24, 1413, 10.1093/bioinformatics/btn138

Jensen, 2008, Massively parallel screening of the receptorome, Comb. Chem. High Throughput Screen, 11, 420, 10.2174/138620708784911483

Strachan, 2006, Screening the receptorome: an efficient approach for drug discovery and target validation, Drug Discov. Today, 11, 708, 10.1016/j.drudis.2006.06.012

Roth, 2004, Screening the receptorome to discover the molecular targets for plant-derived psychoactive compounds: a novel approach for CNS drug discovery, Pharmacol. Ther., 102, 99, 10.1016/j.pharmthera.2004.03.004

Schadt, 2009, A network view of disease and compound screening, Nat. Rev. Drug Discov., 8, 286, 10.1038/nrd2826

Pujol, 2010, Unveiling the role of network and systems biology in drug discovery, Trends Pharmacol. Sci., 31, 115, 10.1016/j.tips.2009.11.006

Kinnings, 2009, Drug discovery using chemical systems biology: repositioning the safe medicine Comtan to treat multi-drug and extensively drug resistant tuberculosis, PLoS Comput. Biol., 5, e1000423, 10.1371/journal.pcbi.1000423

Cockell, 2010, An integrated dataset for in silico drug discovery, J. Integr. Bioinform., 10.1515/jib-2010-116

Prathipati, 2008, Global Bayesian models for the prioritization of antitubercular agents, J. Chem. Inf. Model., 48, 2362, 10.1021/ci800143n

Jones, 2007, Computational approaches that predict metabolic intermediate complex formation with CYP3A4 (+b5), Drug Metab. Dispos., 35, 1466, 10.1124/dmd.106.014613

Zientek, 2010, Integrated in silico-in vitro strategy for addressing cytochrome P450 3A4 time-dependent inhibition, Chem. Res. Toxicol., 23, 664, 10.1021/tx900417f

Pan, Y. et al. Identification and validation of novel hPXR activators amongst prescribed drugs via ligand-based virtual screening. Drug Metab. Dispos. (in press)

Ekins, 2010, A predictive ligand-based bayesian model for human drug induced liver injury, Drug Metab. Dispos., 38, 2302, 10.1124/dmd.110.035113

Ekins, 2009, Challenges predicting ligand–receptor interactions of promiscuous proteins: the nuclear receptor PXR, PLoS Comput. Biol., 5, e1000594, 10.1371/journal.pcbi.1000594

Ananthan, 2009, High-throughput screening for inhibitors of Mycobacterium tuberculosis H37Rv, Tuberculosis, 89, 334, 10.1016/j.tube.2009.05.008

Ekins, 2010, Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis, Mol. BioSyst., 6, 2316, 10.1039/c0mb00104j

Maddry, 2009, Antituberculosis activity of the molecular libraries screening center network library, Tuberculosis, 89, 354, 10.1016/j.tube.2009.07.006

Hohman, 2009, Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery, Drug Discov. Today, 14, 261, 10.1016/j.drudis.2008.11.015

Ekins, 2010, A collaborative database and computational models for tuberculosis drug discovery, Mol. BioSyst., 6, 840, 10.1039/b917766c

Ekins, S. et al. (2011) Pioneering use of the cloud for development of the collaborative drug discovery (cdd) database In Collaborative Computational Technologies for Biomedical Research (Ekins, S. et al., eds), pp. 335–361, John Wiley & Sons (in press)

Ekins, 2010, Meta-analysis of molecular property patterns and filtering of public datasets of antimalarial ‘hits’ and drugs, MedChemComm, 1, 325, 10.1039/c0md00129e

Ekins, 2010, When pharmaceutical companies publish large datasets: an abundance of riches or fool's gold?, Drug Discov. Today, 15, 812, 10.1016/j.drudis.2010.08.010

Wang, 2010, An overview of the PubChem BioAssay resource, Nucleic Acids Res., 38, D255, 10.1093/nar/gkp965

Williams, A.J. et al. (2009) Free online resources enabling crowdsourced drug discovery. Drug Discov. World 10, winter, 33–38

Louise-May, 2009, Towards integrated web-based tools in drug discovery, Touch Briefings: Drug Discov., 6, 17

Bisson, 2007, Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs, Proc. Natl. Acad. Sci. U.S.A., 104, 11927, 10.1073/pnas.0609752104

Jenwitheesuk, 2008, Novel paradigms for drug discovery: computational multitarget screening, Trends Pharmacol. Sci., 29, 62, 10.1016/j.tips.2007.11.007

Ekins, 2011, Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery, Trends Microbiol, 65, 10.1016/j.tim.2010.10.005

Manak, 2010, Anti-HIV-1 activity of the neurokinin-1 receptor antagonist aprepitant and synergistic interactions with other antiretrovirals, AIDS, 24, 2789, 10.1097/QAD.0b013e3283405c33

Wang, 2007, Neurokinin-1 receptor antagonist (aprepitant) inhibits drug-resistant HIV-1 infection of macrophages in vitro, J. Neuroimmune Pharmacol., 2, 42, 10.1007/s11481-006-9059-6

Robinson, 2008, Substance P receptor antagonism for treatment of cryptosporidiosis in immunosuppressed mice, J. Parasitol., 94, 1150, 10.1645/GE-1458.1

Oldfield, 2010, Targeting isoprenoid biosynthesis for drug discovery: bench to bedside, Acc. Chem. Res., 43, 1216, 10.1021/ar100026v

Ting, 2010, Glybenclamide: an antidiabetic with in vivo antithrombotic activity, Eur. J. Pharmacol., 649, 249, 10.1016/j.ejphar.2010.09.009

Miguel, 2008, Tamoxifen is effective in the treatment of Leishmania amazonensis infections in mice, PLoS Negl. Trop. Dis., 2, e249, 10.1371/journal.pntd.0000249

Miguel, 2007, Tamoxifen is effective against Leishmania and induces a rapid alkalinization of parasitophorous vacuoles harbouring Leishmania (Leishmania) amazonensis amastigotes, J. Antimicrob. Chemother., 60, 526, 10.1093/jac/dkm219

Senkovich, 2005, Lipophilic antifolate trimetrexate is a potent inhibitor of Trypanosoma cruzi: prospect for chemotherapy of Chagas’ disease, Antimicrob. Agents Chemother., 49, 3234, 10.1128/AAC.49.8.3234-3238.2005

Namkoong, 2007, Metabotropic glutamate receptor 1 and glutamate signaling in human melanoma, Cancer Res., 67, 2298, 10.1158/0008-5472.CAN-06-3665

Peng, 2008, The antidepressant sertraline improves the phenotype, promotes neurogenesis and increases BDNF levels in the R6/2 Huntington's disease mouse model, Exp. Neurol., 210, 154, 10.1016/j.expneurol.2007.10.015

Chong, 2007, Inhibition of angiogenesis by the antifungal drug itraconazole, ACS Chem. Biol., 2, 263, 10.1021/cb600362d

Chong, 2006, A clinical drug library screen identifies astemizole as an antimalarial agent, Nat. Chem. Biol., 2, 415, 10.1038/nchembio806

Chong, 2006, Identification of type 1 inosine monophosphate dehydrogenase as an antiangiogenic drug target, J. Med. Chem., 49, 2677, 10.1021/jm051225t

de Carvalho, 2009, Nitazoxanide kills replicating and nonreplicating Mycobacterium tuberculosis and evades resistance, J. Med. Chem., 52, 5789, 10.1021/jm9010719

Shahinas, 2010, A repurposing strategy identifies novel synergistic inhibitors of Plasmodium falciparum heat shock protein 90, J. Med. Chem., 53, 3552, 10.1021/jm901796s

Chopra, 2010, Repurposing FDA-approved drugs to combat drug-resistant Acinetobacter baumannii, J. Antimicrob. Chemother., 65, 2598, 10.1093/jac/dkq353

Miller, 2010, Identification of known drugs that act as inhibitors of NF-kappaB signaling and their mechanism of action, Biochem. Pharmacol., 79, 1272, 10.1016/j.bcp.2009.12.021

Downey, 2008, Efficacy of pyrvinium pamoate against Cryptosporidium parvum infection in vitro and in a neonatal mouse model, Antimicrob. Agents Chemother., 52, 3106, 10.1128/AAC.00207-08

Mackey, 2006, Discovery of trypanocidal compounds by whole cell HTS of Trypanosoma brucei, Chem. Biol. Drug Des., 67, 355, 10.1111/j.1747-0285.2006.00389.x

Biechele, 2010, Chemical-genetic screen identifies riluzole as an enhancer of Wnt/beta-catenin signaling in melanoma, Chem. Biol., 17, 1177, 10.1016/j.chembiol.2010.08.012

Gloeckner, 2010, Repositioning of an existing drug for the neglected tropical disease Onchocerciasis, Proc. Natl. Acad. Sci. U.S.A., 107, 3424, 10.1073/pnas.0915125107

Shim, 2010, Effect of nitroxoline on angiogenesis and growth of human bladder cancer, J. Natl. Cancer Inst., 102, 1855, 10.1093/jnci/djq457

Zhang, 2009, Identification of inhibitors of ABCG2 by a bioluminescence imaging-based high-throughput assay, Cancer Res., 69, 5867, 10.1158/0008-5472.CAN-08-4866

Masuda, 2008, Tiagabine is neuroprotective in the N171-82Q and R6/2 mouse models of Huntington's disease, Neurobiol. Dis., 30, 293, 10.1016/j.nbd.2008.01.014

Zhang, 2008, Digoxin and other cardiac glycosides inhibit HIF-1alpha synthesis and block tumor growth, Proc. Natl. Acad. Sci. U.S.A., 105, 19579, 10.1073/pnas.0809763105

Ou, 2009, Identification of FDA-approved drugs and bioactives that protect hair cells in the zebrafish (Danio rerio) lateral line and mouse (Mus musculus) utricle, J. Assoc. Res. Otolaryngol., 10, 191, 10.1007/s10162-009-0158-y

Peterson, 1998, Inhibiting transthyretin conformational changes that lead to amyloid fibril formation, Proc. Natl. Acad. Sci. U.S.A., 95, 12956, 10.1073/pnas.95.22.12956

Ekins, 2009, Drug transporter pharmacophores, Vol. 44, 215

Guiguemde, 2010, Chemical genetics of Plasmodium falciparum, Nature, 465, 311, 10.1038/nature09099

Gamo, 2010, Thousands of chemical starting points for antimalarial lead identification, Nature, 465, 305, 10.1038/nature09107