Generic placeholder image

Current Drug Research Reviews

Editor-in-Chief

ISSN (Print): 2589-9775
ISSN (Online): 2589-9783

Review Article

Drug Repurposing: An Emerging Tool for Drug Reuse, Recycling and Discovery

Author(s): Supriya Roy, Suneela Dhaneshwar* and Bhavya Bhasin

Volume 13, Issue 2, 2021

Published on: 11 February, 2021

Page: [101 - 119] Pages: 19

DOI: 10.2174/2589977513666210211163711

Price: $65

Abstract

Drug repositioning or repurposing is a revolutionary breakthrough in drug development that focuses on rediscovering new uses for old therapeutic agents. Drug repositioning can be defined more precisely as the process of exploring new indications for an already approved drug while drug repurposing includes overall re-development approaches grounded in the identical chemical structure of the active drug moiety as in the original product. The repositioning approach accelerates the drug development process, curtails the cost and risk inherent to drug development. The strategy focuses on the polypharmacology of drugs to unlocks novel opportunities for logically designing more efficient therapeutic agents for unmet medical disorders. Drug repositioning also expresses certain regulatory challenges that hamper its further utilization. The review outlines the eminent role of drug repositioning in new drug discovery, methods to predict the molecular targets of a drug molecule, advantages that the strategy offers to the pharmaceutical industries, explaining how the industrial collaborations with academics can assist in the discovering more repositioning opportunities. The focus of the review is to highlight the latest applications of drug repositioning in various disorders. The review also includes a comparison of old and new therapeutic uses of repurposed drugs, assessing their novel mechanisms of action and pharmacological effects in the management of various disorders. Various restrictions and challenges that repurposed drugs come across during their development and regulatory phases are also highlighted.

Keywords: Drug reprofiling, retargeting, therapeutic switching, drug rescue, drug repositioning, polypharmacology, serological biomarkers, drug target.

Next »
Graphical Abstract
[1]
Deotarse PP, Jain A, Baile MB. Drug repositioning: a review. Int J Pharma Res Rev 2015; 4: 51-8.
[2]
Ashburn TT, Thor KB. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov 2004; 3(8): 673-83.
[http://dx.doi.org/10.1038/nrd1468] [PMID: 15286734]
[3]
Napolitano F, Zhao Y, Moreira VM, et al. Drug repositioning: a machine-learning approach through data integration. J Cheminform 2013; 5(1): 30.
[http://dx.doi.org/10.1186/1758-2946-5-30] [PMID: 23800010]
[4]
Zou J, Zheng MW, Li G, Su ZG. Advanced systems biology methods in drug discovery and translational biomedicine. BioMed Res Int 2013; 2013: 742835.
[http://dx.doi.org/10.1155/2013/742835] [PMID: 24171171]
[5]
Swinney DC, Anthony J. How were new medicines discovered? Nat Rev Drug Discov 2011; 10(7): 507-19.
[http://dx.doi.org/10.1038/nrd3480] [PMID: 21701501]
[6]
Novac N. Challenges and opportunities of drug repositioning. Trends Pharmacol Sci 2013; 34(5): 267-72.
[http://dx.doi.org/10.1016/j.tips.2013.03.004] [PMID: 23582281]
[7]
Allarakhia M. Open-source approaches for the repurposing of existing or failed candidate drugs: learning from and applying the lessons across diseases. Drug Des Devel Ther 2013; 7: 753-66.
[http://dx.doi.org/10.2147/DDDT.S46289] [PMID: 23966771]
[8]
Swamidass SJ. Mining small-molecule screens to repurpose drugs. Brief Bioinform 2011; 12(4): 327-35.
[http://dx.doi.org/10.1093/bib/bbr028] [PMID: 21715466]
[9]
Keiser MJ, Setola V, Irwin JJ, et al. Predicting new molecular targets for known drugs. Nature 2009; 462(7270): 175-81.
[http://dx.doi.org/10.1038/nature08506] [PMID: 19881490]
[10]
Campillos M, Kuhn M, Gavin AC, Jensen LJ, Bork P. Drug target identification using side-effect similarity. Science 2008; 321(5886): 263-6.
[http://dx.doi.org/10.1126/science.1158140] [PMID: 18621671]
[11]
Zhu F, Han B, Kumar P, et al. Update of TTD: Therapeutic Target Database. Nucleic Acids Res 2010; 38(Database issue): D787-91.
[http://dx.doi.org/10.1093/nar/gkp1014] [PMID: 19933260]
[12]
Overington JP, Al-Lazikani B, Hopkins AL. How many drug targets are there? Nat Rev Drug Discov 2006; 5(12): 993-6.
[http://dx.doi.org/10.1038/nrd2199] [PMID: 17139284]
[13]
Cheng F, Liu C, Jiang J, et al. Prediction of drug-target interactions and drug repositioning via network-based inference. PLOS Comput Biol 2012; 8(5): e1002503.
[http://dx.doi.org/10.1371/journal.pcbi.1002503] [PMID: 22589709]
[14]
O’Connor KA, Roth BL. Finding new tricks for old drugs: an efficient route for public-sector drug discovery. Nat Rev Drug Discov 2005; 4(12): 1005-14.
[http://dx.doi.org/10.1038/nrd1900] [PMID: 16341065]
[15]
Pammolli F, Magazzini L, Riccaboni M. The productivity crisis in pharmaceutical R&D. Nat Rev Drug Discov 2011; 10(6): 428-38.
[http://dx.doi.org/10.1038/nrd3405] [PMID: 21629293]
[16]
Tobinick EL. The value of drug repositioning in the current pharmaceutical market. Drug News Perspect 2009; 22(2): 119-25.
[http://dx.doi.org/10.1358/dnp.2009.22.2.1303818] [PMID: 19330170]
[17]
Sleigh SH, Barton CL. Repurposing strategies for therapeutics. Pharmaceut Med 2010; 24(3): 151-9.
[http://dx.doi.org/10.1007/BF03256811]
[18]
Chong CR, Sullivan DJ Jr. New uses for old drugs. Nature 2007; 448(7154): 645-6.
[http://dx.doi.org/10.1038/448645a] [PMID: 17687303]
[19]
Kaitin KI. Deconstructing the drug development process: the new face of innovation. Clin Pharmacol Ther 2010; 87(3): 356-61.
[http://dx.doi.org/10.1038/clpt.2009.293] [PMID: 20130565]
[20]
Liu Z, Fang H, Reagan K, et al. In silico drug repositioning: what we need to know. Drug Discov Today 2013; 18(3-4): 110-5.
[http://dx.doi.org/10.1016/j.drudis.2012.08.005] [PMID: 22935104]
[21]
Méndez-Lucio O, Tran J, Medina-Franco JL, Meurice N, Muller M. Toward drug repurposing in epigenetics: olsalazine as a hypomethylating compound active in a cellular context. ChemMedChem 2014; 9(3): 560-5.
[http://dx.doi.org/10.1002/cmdc.201300555] [PMID: 24482360]
[22]
Keiser MJ, Roth BL, Armbruster BN, Ernsberger P, Irwin JJ, Shoichet BK. Relating protein pharmacology by ligand chemistry. Nat Biotechnol 2007; 25(2): 197-206.
[http://dx.doi.org/10.1038/nbt1284] [PMID: 17287757]
[23]
Kovács D, Simon Z, Hári P, et al. Identification of PPARγ ligands with one-dimensional drug profile matching. Drug Des Devel Ther 2013; 7: 917-28.
[http://dx.doi.org/10.2147/DDDT.S47173] [PMID: 24039401]
[24]
Dudley JT, Sirota M, Shenoy M, et al. Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Sci Transl Med 2011; 3(96): 96ra76.
[http://dx.doi.org/10.1126/scitranslmed.3002648] [PMID: 21849664]
[25]
Nacher JC, Schwartz JM. A global view of drug-therapy interactions. BMC Pharmacol 2008; 8(1): 5.
[http://dx.doi.org/10.1186/1471-2210-8-5] [PMID: 18318892]
[26]
Hopkins AL. Drug discovery: predicting promiscuity. Nature 2009; 462(7270): 167-8.
[http://dx.doi.org/10.1038/462167a] [PMID: 19907483]
[27]
Andronis C, Sharma A, Virvilis V, Deftereos S, Persidis A. Literature mining, ontologies and information visualization for drug repurposing. Brief Bioinform 2011; 12(4): 357-68.
[http://dx.doi.org/10.1093/bib/bbr005] [PMID: 21712342]
[28]
Huang R, Southall N, Wang Y, et al. The NCGC pharmaceutical collection: a comprehensive resource of clinically approved drugs enabling repurposing and chemical genomics. Sci Transl Med 2011; 3(80): 80ps16.
[http://dx.doi.org/10.1126/scitranslmed.3001862] [PMID: 21525397]
[29]
Feng BY, Simeonov A, Jadhav A, et al. A high-throughput screen for aggregation-based inhibition in a large compound library. J Med Chem 2007; 50(10): 2385-90.
[http://dx.doi.org/10.1021/jm061317y] [PMID: 17447748]
[30]
Yildirim MA, Goh KI, Cusick ME, Barabási AL, Vidal M. Drug- target network. Nat Biotechnol 2007; 25(10): 1119-26.
[http://dx.doi.org/10.1038/nbt1338] [PMID: 17921997]
[31]
Iskar M, Zeller G, Blattmann P, et al. Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding. Mol Syst Biol 2013; 9: 662.
[http://dx.doi.org/10.1038/msb.2013.20] [PMID: 23632384]
[32]
Kolb P, Ferreira RS, Irwin JJ, Shoichet BK. Docking and chemoinformatic screens for new ligands and targets. Curr Opin Biotechnol 2009; 20(4): 429-36.
[http://dx.doi.org/10.1016/j.copbio.2009.08.003] [PMID: 19733475]
[33]
Wu Z, Li W, Liu G, Tang Y. Network-based methods for prediction of drug-target interactions. Front Pharmacol 2018; 9: 1134.
[http://dx.doi.org/10.3389/fphar.2018.01134] [PMID: 30356768]
[34]
Pantziarka P, André N. Editorial: drug repurposing. Front Med (Lausanne) 2019; 6: 154.
[http://dx.doi.org/10.3389/fmed.2019.00154] [PMID: 31334237]
[35]
Reaume AG. Drug repurposing through nonhypothesis driven phenotypic screening. Drug Discov Today Ther Strateg 2011; 8: 85-8.
[http://dx.doi.org/10.1016/j.ddstr.2011.09.007]
[36]
Sardana D, Zhu C, Zhang M, Gudivada RC, Yang L, Jegga AG. Drug repositioning for orphan diseases. Brief Bioinform 2011; 12(4): 346-56.
[http://dx.doi.org/10.1093/bib/bbr021] [PMID: 21504985]
[37]
Ekins S, Williams AJ, Krasowski MD, Freundlich JS. In silico repositioning of approved drugs for rare and neglected diseases. Drug Discov Today 2011; 16(7-8): 298-310.
[http://dx.doi.org/10.1016/j.drudis.2011.02.016] [PMID: 21376136]
[38]
Deftereos SN, Andronis C, Friedla EJ, Persidis A, Persidis A. Drug repurposing and adverse event prediction using high-throughput literature analysis. Wiley Interdiscip Rev Syst Biol Med 2011; 3(3): 323-34.
[http://dx.doi.org/10.1002/wsbm.147] [PMID: 21416632]
[39]
Dudley JT, Deshpande T, Butte AJ. Exploiting drug-disease relationships for computational drug repositioning. Brief Bioinform 2011; 12(4): 303-11.
[http://dx.doi.org/10.1093/bib/bbr013] [PMID: 21690101]
[40]
Loging W, Rodriguez-Esteban R, Hill J, et al. Cheminformatic/bioinformatic analysis of large corporate databases:Application to drug repurposing. Drug Discov Today Ther Strateg 2011; 8: 109-16.
[http://dx.doi.org/10.1016/j.ddstr.2011.06.004]
[41]
Koutsoukas A, Simms B, Kirchmair J, et al. From in silico target prediction to multi-target drug design: current databases, methods and applications. J Proteomics 2011; 74(12): 2554-74.
[http://dx.doi.org/10.1016/j.jprot.2011.05.011] [PMID: 21621023]
[42]
Wang L, Ma C, Wipf P, Liu H, Su W, Xie XQ. TargetHunter: an in silico target identification tool for predicting therapeutic potential of small organic molecules based on chemogenomic database. AAPS J 2013; 15(2): 395-406.
[http://dx.doi.org/10.1208/s12248-012-9449-z] [PMID: 23292636]
[43]
Perez-Nueno VI, Souchet M, Karaboga AS, et al. Predicting drug side effects from drug–target relationships. J Chem Inf Model 2012; 52: 1948-61.
[PMID: 22747187]
[44]
Achenbach J, Klingler FM, Hahn S, et al. Fragment-based identification of multi-target ligands by self-organizing map alignment. J Cheminform 2012; 4(1): 57.
[http://dx.doi.org/10.1186/1758-2946-4-S1-P57]
[45]
Dunkel M, Günther S, Ahmed J, Wittig B, Preissner R. SuperPred: drug classification and target prediction. Nucleic Acids Res 2008; 36(Web Server issue): W55-9.
[http://dx.doi.org/10.1093/nar/gkn307] [PMID: 18499712]
[46]
Allison M. NCATS launches drug repurposing program. Nat Biotechnol 2012; 30(7): 571-2.
[http://dx.doi.org/10.1038/nbt0712-571a] [PMID: 22781662]
[47]
Chen X, Ji ZL, Chen YZ. TTD: Therapeutic target database. Nucleic Acids Res 2002; 30(1): 412-5.
[http://dx.doi.org/10.1093/nar/30.1.412] [PMID: 11752352]
[48]
Pérez-Nueno VI, Karaboga AS, Souchet M, Ritchie DW. GES polypharmacology fingerprints: a novel approach for drug repositioning. J Chem Inf Model 2014; 54(3): 720-34.
[http://dx.doi.org/10.1021/ci4006723] [PMID: 24494653]
[49]
Bender A, Young DW, Jenkins JL, et al. Chemogenomic data analysis: prediction of small-molecule targets and the advent of biological fingerprint. Comb Chem High Throughput Screen 2007; 10(8): 719-31.
[http://dx.doi.org/10.2174/138620707782507313] [PMID: 18045083]
[50]
Jenkins JL, Bender A, Davies JW. In silico target fishing: predicting biological targets from chemical structure. Drug Discov Today Technol 2006; 3(4): 413-21.
[http://dx.doi.org/10.1016/j.ddtec.2006.12.008]
[51]
Schomburg KT, Bietz S, Briem H, Henzler AM, Urbaczek S, Rarey M. Facing the challenges of structure-based target prediction by inverse virtual screening. J Chem Inf Model 2014; 54(6): 1676-86.
[http://dx.doi.org/10.1021/ci500130e] [PMID: 24851945]
[52]
Shen C, Ding Y, Tang J, Xu X, Guo F. An ameliorated prediction of drug-target interactions based on multi-scale discrete wavelet transform and network features. Int J Mol Sci 2017; 18(8): 1781.
[http://dx.doi.org/10.3390/ijms18081781] [PMID: 28813000]
[53]
Adams JC, Keiser MJ, Basuino L, et al. A mapping of drug space from the viewpoint of small molecule metabolism. PLOS Comput Biol 2009; 5(8): e1000474.
[http://dx.doi.org/10.1371/journal.pcbi.1000474] [PMID: 19701464]
[54]
Chen B, McConnell KJ, Wale N, Wild DJ, Gifford EM. Comparing bioassay response and similarity ensemble approaches to probing protein pharmacology. Bioinformatics 2011; 27(21): 3044-9.
[http://dx.doi.org/10.1093/bioinformatics/btr506] [PMID: 21903625]
[55]
Wu C, Gudivada RC, Aronow BJ, Jegga AG. Computational drug repositioning through heterogeneous network clustering. BMC Syst Biol 2013; 7(Suppl. 5): S6.
[http://dx.doi.org/10.1186/1752-0509-7-S5-S6] [PMID: 24564976]
[56]
Wang L, Xie XQ. Computational target fishing: what should chemogenomics researchers expect for the future of in silico drug design and discovery? Future Med Chem 2014; 6(3): 247-9.
[http://dx.doi.org/10.4155/fmc.14.5] [PMID: 24575960]
[57]
Nettles JH, Jenkins JL, Bender A, Deng Z, Davies JW, Glick M. Bridging chemical and biological space: “target fishing” using 2D and 3D molecular descriptors. J Med Chem 2006; 49(23): 6802-10.
[http://dx.doi.org/10.1021/jm060902w] [PMID: 17154510]
[58]
Gfeller D, Grosdidier A, Wirth M, Daina A, Michielin O, Zoete V. SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucleic Acids Res 2014; 42(Web Server issue): W32-8.
[http://dx.doi.org/10.1093/nar/gku293] [PMID: 24792161]
[59]
Hawkins PCD, Skillman AG, Nicholls A. Comparison of shape- matching and docking as virtual screening tools. J Med Chem 2007; 50(1): 74-82.
[http://dx.doi.org/10.1021/jm0603365] [PMID: 17201411]
[60]
Ballester PJ, Richards WG. Ultrafast shape recognition to search compound databases for similar molecular shapes. J Comput Chem 2007; 28(10): 1711-23.
[http://dx.doi.org/10.1002/jcc.20681] [PMID: 17342716]
[61]
Venkatraman V, Pérez-Nueno VI, Mavridis L, Ritchie DW. Comprehensive comparison of ligand-based virtual screening tools against the DUD data set reveals limitations of current 3D methods. J Chem Inf Model 2010; 50(12): 2079-93.
[http://dx.doi.org/10.1021/ci100263p] [PMID: 21090728]
[62]
Gfeller D, Michielin O, Zoete V. Shaping the interaction landscape of bioactive molecules. Bioinformatics 2013; 29(23): 3073-9.
[http://dx.doi.org/10.1093/bioinformatics/btt540] [PMID: 24048355]
[63]
Reker D, Rodrigues T, Schneider P, Schneider G. Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus. Proc Natl Acad Sci USA 2014; 111(11): 4067-72.
[http://dx.doi.org/10.1073/pnas.1320001111] [PMID: 24591595]
[64]
Bender A, Scheiber J, Glick M, et al. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure. ChemMedChem 2007; 2(6): 861-73.
[http://dx.doi.org/10.1002/cmdc.200700026] [PMID: 17477341]
[65]
Pulley JM, Rhoads JP, Jerome RN, et al. Using what we already have: uncovering new drug repurposing strategies in existing omics data. Annu Rev Pharmacol Toxicol 2020; 60: 333-52.
[http://dx.doi.org/10.1146/annurev-pharmtox-010919-023537] [PMID: 31337270]
[66]
Ptolemy AS, Rifai N. What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema. Scand J Clin Lab Invest Suppl 2010; 242: 6-14.
[http://dx.doi.org/10.3109/00365513.2010.493354] [PMID: 20515269]
[67]
Hampel H, Frank R, Broich K, et al. Biomarkers for Alzheimer’s disease: academic, industry and regulatory perspectives. Nat Rev Drug Discov 2010; 9(7): 560-74.
[http://dx.doi.org/10.1038/nrd3115] [PMID: 20592748]
[68]
Ransohoff DF. Proteomics research to discover markers: what can we learn from Netflix? Clin Chem 2010; 56(2): 172-6.
[http://dx.doi.org/10.1373/clinchem.2009.126698] [PMID: 20040622]
[69]
Goodsaid FM, Mendrick DL. Translational medicine and the value of biomarker qualification. Sci Transl Med 2010; 2(47): 47ps44.
[http://dx.doi.org/10.1126/scitranslmed.3001040] [PMID: 20811041]
[70]
Anderson NL. The clinical plasma proteome: a survey of clinical assays for proteins in plasma and serum. Clin Chem 2010; 56(2): 177-85.
[http://dx.doi.org/10.1373/clinchem.2009.126706] [PMID: 19884488]
[71]
Bauer DC, Hunter DJ, Abramson SB, et al. Osteoarthritis Biomarkers Network. Classification of osteoarthritis biomarkers: a proposed approach. Osteoarthritis Cartilage 2006; 14(8): 723-7.
[http://dx.doi.org/10.1016/j.joca.2006.04.001] [PMID: 16733093]
[72]
Kuo TR, Chen CH. Bone biomarker for the clinical assessment of osteoporosis: recent developments and future perspectives. Biomark Res 2017; 5: 18.
[http://dx.doi.org/10.1186/s40364-017-0097-4] [PMID: 28529755]
[73]
Lindström E, Rizoska B, Henderson I, et al. Nonclinical and clinical pharmacological characterization of the potent and selective cathepsin K inhibitor MIV-711. J Transl Med 2018; 16(1): 125.
[http://dx.doi.org/10.1186/s12967-018-1497-4] [PMID: 29743078]
[74]
Ferreira A, Alho I, Casimiro S, Costa L. Bone remodeling markers and bone metastases: From cancer research to clinical implications. Bonekey Rep 2015; 4: 668.
[http://dx.doi.org/10.1038/bonekey.2015.35] [PMID: 25908969]
[75]
Conversano F, Franchini R, Greco A, et al. A novel ultrasound methodology for estimating spine mineral density. Ultrasound Med Biol 2015; 41(1): 281-300.
[http://dx.doi.org/10.1016/j.ultrasmedbio.2014.08.017] [PMID: 25438845]
[76]
Eastell R, Hannon RA. Biomarkers of bone health and osteoporosis risk. Proc Nutr Soc 2008; 67(2): 157-62.
[http://dx.doi.org/10.1017/S002966510800699X] [PMID: 18412989]
[77]
Henriksen K, Christiansen C, Karsdal MA. Serological biochemical markers of surrogate efficacy and safety as a novel approach to drug repositioning. Drug Discov Today 2011; 16(21-22): 967-75.
[http://dx.doi.org/10.1016/j.drudis.2011.06.010] [PMID: 21745584]
[78]
Gns HS, Gr S, Murahari M, Krishnamurthy M. An update on Drug Repurposing: Re-written saga of the drug’s fate. Biomed Pharmacother 2019; 110: 700-16.
[http://dx.doi.org/10.1016/j.biopha.2018.11.127] [PMID: 30553197]
[79]
Shankar S, Hosking DJ. Biochemical assessment of Paget’s disease of bone. J Bone Miner Res 2006; 21(Suppl. 2): 22-7.
[http://dx.doi.org/10.1359/jbmr.06s204] [PMID: 17229003]
[80]
Qvist P, Christgau S, Pedersen BJ, Schlemmer A, Christiansen C. Circadian variation in the serum concentration of C-terminal telopeptide of type I collagen (serum CTx): effects of gender, age, menopausal status, posture, daylight, serum cortisol, and fasting. Bone 2002; 31(1): 57-61.
[http://dx.doi.org/10.1016/S8756-3282(02)00791-3] [PMID: 12110413]
[81]
Pantziarka P, Pirmohamed M, Mirza N. New uses for old drugs. BMJ 2018; 361: k2701.
[http://dx.doi.org/10.1136/bmj.k2701] [PMID: 29945952]
[82]
Sachs RE, Ginsburg PB, Goldman DP. Encouraging New Uses for Old Drugs. JAMA 2017; 318(24): 2421-2.
[http://dx.doi.org/10.1001/jama.2017.17535] [PMID: 29204602]
[83]
Frail DE, Brady M, Escott KJ, et al. Pioneering government-sponsored drug repositioning collaborations: progress and learning. Nat Rev Drug Discov 2015; 14(12): 833-41.
[http://dx.doi.org/10.1038/nrd4707] [PMID: 26585533]
[84]
Pantziarka P, Bouche G, Meheus L, Sukhatme V, Sukhatme VP, Vikas P. The Repurposing Drugs in Oncology (ReDO) Project. Ecancermedicalscience 2014; 8: 442.
[http://dx.doi.org/10.3332/ecancer.2014.485] [PMID: 25075216]
[85]
Prague JK, Roberts RE, Comninos AN, et al. Neurokinin 3 receptor antagonism as a novel treatment for menopausal hot flushes: a phase 2, randomised, double-blind, placebo-controlled trial. Lancet 2017; 389(10081): 1809-20.
[http://dx.doi.org/10.1016/S0140-6736(17)30823-1] [PMID: 28385352]
[86]
Talevi A, Bellera CL. Challenges and opportunities with drug repurposing: finding strategies to find alternative uses of therapeutics. Expert Opin Drug Discov 2020; 15(4): 397-401.
[http://dx.doi.org/10.1080/17460441.2020.1704729] [PMID: 31847616]
[87]
Pushpakom S, Iorio F, Eyers PA, et al. Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov 2019; 18(1): 41-58.
[http://dx.doi.org/10.1038/nrd.2018.168] [PMID: 30310233]
[88]
Bloom BE. Creating new economic incentives for repurposing generic drugs for unsolved diseases using social finance. Assay Drug Dev Technol 2015; 13(10): 606-11.
[http://dx.doi.org/10.1089/adt.2015.29015.beddrrr] [PMID: 26284286]
[89]
Kowal SL, Dall TM, Chakrabarti R, Storm MV, Jain A. The current and projected economic burden of Parkinson’s disease in the United States. Mov Disord 2013; 28(3): 311-8.
[http://dx.doi.org/10.1002/mds.25292] [PMID: 23436720]
[90]
Strittmatter SM. Overcoming drug development bottlenecks with repurposing: old drugs learn new tricks. Nat Med 2014; 20(6): 590-1.
[http://dx.doi.org/10.1038/nm.3595] [PMID: 24901567]
[91]
Corsello SM, Bittker JA, Liu Z, et al. The Drug Repurposing Hub: a next-generation drug library and information resource. Nat Med 2017; 23(4): 405-8.
[http://dx.doi.org/10.1038/nm.4306] [PMID: 28388612]
[92]
Meissner WG, Frasier M, Gasser T, et al. Priorities in Parkinson’s disease research. Nat Rev Drug Discov 2011; 10(5): 377-93.
[http://dx.doi.org/10.1038/nrd3430] [PMID: 21532567]
[93]
Rakshit H, Chatterjee P, Roy D. A bidirectional drug repositioning approach for Parkinson’s disease through network-based inference. Biochem Biophys Res Commun 2015; 457(3): 280-7.
[http://dx.doi.org/10.1016/j.bbrc.2014.12.101] [PMID: 25576361]
[94]
Johnston TH, Lacoste AMB, Visanji NP, Lang AE, Fox SH, Brotchie JM. Repurposing drugs to treat l-DOPA-induced dyskinesia in Parkinson’s disease. Neuropharmacology 2019; 147: 11-27.
[http://dx.doi.org/10.1016/j.neuropharm.2018.05.035] [PMID: 29907424]
[95]
Fuchikami M, Yamamoto S, Morinobu S, Okada S, Yamawaki Y, Yamawaki S. The potential use of histone deacetylase inhibitors in the treatment of depression. Prog Neuropsychopharmacol Biol Psychiatry 2016; 64: 320-4.
[http://dx.doi.org/10.1016/j.pnpbp.2015.03.010] [PMID: 25818247]
[96]
Hobara T, Uchida S, Otsuki K, et al. Molecular mechanisms of the antidepressant actions by histone deacetylase inhibitors. Neurosci Res 2010; 68: E316.
[http://dx.doi.org/10.1016/j.neures.2010.07.1405]
[97]
Covington HE III, Maze I, LaPlant QC, et al. Antidepressant actions of histone deacetylase inhibitors. J Neurosci 2009; 29(37): 11451-60.
[http://dx.doi.org/10.1523/JNEUROSCI.1758-09.2009] [PMID: 19759294]
[98]
Gao S, Cui YL, Yu CQ, Wang QS, Zhang Y. Tetrandrine exerts antidepressant-like effects in animal models: role of brain-derived neurotrophic factor. Behav Brain Res 2013; 238: 79-85.
[http://dx.doi.org/10.1016/j.bbr.2012.10.015] [PMID: 23085478]
[99]
Yang SH, Li S, Lu G, et al. Metformin treatment reduces temozolomide resistance of glioblastoma cells. Oncotarget 2016; 7(48): 78787-803.
[http://dx.doi.org/10.18632/oncotarget.12859] [PMID: 27791206]
[100]
Wang D, Berglund A, Kenchappa RS, Forsyth PA, Mulé JJ, Etame AB. BIRC3 is a novel driver of therapeutic resistance in Glioblastoma. Sci Rep 2016; 6: 21710.
[http://dx.doi.org/10.1038/srep21710] [PMID: 26888114]
[101]
Wishart DS, Knox C, Guo AC, et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 2006; 34(Database issue): D668-72.
[http://dx.doi.org/10.1093/nar/gkj067] [PMID: 16381955]
[102]
Lazzeroni D, Bini M, Camaiora U, et al. Serum uric acid level predicts adverse outcomes after myocardial revascularization or cardiac valve surgery. Eur J Prev Cardiol 2018; 25(2): 119-26.
[http://dx.doi.org/10.1177/2047487317744045] [PMID: 29164926]
[103]
Grassi D, Ferri L, Desideri G, et al. Chronic hyperuricemia, uric acid deposit and cardiovascular risk. Curr Pharm Des 2013; 19(13): 2432-8.
[http://dx.doi.org/10.2174/1381612811319130011] [PMID: 23173592]
[104]
Taghizadeh N, Vonk JM, Boezen HM. Serum uric acid levels and cancer mortality risk among males in a large general population-based cohort study. Cancer Causes Control 2014; 25(8): 1075-80.
[http://dx.doi.org/10.1007/s10552-014-0408-0] [PMID: 24906474]
[105]
Bennett DA, Holmes MV. Mendelian randomisation in cardiovascular research: an introduction for clinicians. Heart 2017; 103(18): 1400-7.
[http://dx.doi.org/10.1136/heartjnl-2016-310605] [PMID: 28596306]
[106]
Satoh K. Development of novel therapies for cardiovascular diseases by clinical application of basic research. Circ J 2017; 81(11): 1557-1563..
[http://dx.doi.org/10.1253/circj.CJ-17-1029]
[107]
Bhatt MP, Lim YC, Kim YM, Ha KS. C-peptide activates AMPKα and prevents ROS-mediated mitochondrial fission and endothelial apoptosis in diabetes. Diabetes 2013; 62(11): 3851-62.
[http://dx.doi.org/10.2337/db13-0039] [PMID: 23884890]
[108]
He G, Pedersen SB, Bruun JM, Lihn AS, Richelsen B. Metformin, but not thiazolidinediones, inhibits plasminogen activator inhibitor-1 production in human adipose tissue in vitro. Horm Metab Res 2003; 35(1): 18-23.
[http://dx.doi.org/10.1055/s-2003-38386] [PMID: 12669266]
[109]
Mangoni AA, Zinellu A, Sotgia S, et al. Methotrexate and cardiovascular protection: current evidence and future directions. Clin Med Insights Ther 2017; 9: 1179559X1774128.
[http://dx.doi.org/10.1177/1179559X17741289]
[110]
Ameen SM, Drancourt M. In vitro susceptibility of Mycobacterium tuberculosis to trimethoprim and sulfonamides in France. Antimicrob Agents Chemother 2013; 57(12): 6370-1.
[http://dx.doi.org/10.1128/AAC.01683-13] [PMID: 24060877]
[111]
Tiberi S, Payen MC, Sotgiu G, et al. Effectiveness and safety of meropenem/clavulanate-containing regimens in the treatment of MDR- and XDR-TB. Eur Respir J 2016; 47(4): 1235-43.
[http://dx.doi.org/10.1183/13993003.02146-2015] [PMID: 26965290]
[112]
Sotgiu G, Pontali E, Migliori GB. Linezolid to treat MDR-/XDR- tuberculosis: available evidence and future scenarios. Eur Respir J 2015; 45(1): 25-9.
[http://dx.doi.org/10.1183/09031936.00145014] [PMID: 25552734]
[113]
Yassin MA, Jaramillo E, Wandwalo E, et al. Investing in a novel shorter treatment regimen for multidrug-resistant tuberculosis: to be repeated. Eur Respir J 2017; 49(3): 1700081.
[http://dx.doi.org/10.1183/13993003.00081-2017] [PMID: 28331045]
[114]
Banga R, Procopio FA, Noto A, et al. PD-1(+) and follicular helper T cells are responsible for persistent HIV-1 transcription in treated aviremic individuals. Nat Med 2016; 22(7): 754-61.
[http://dx.doi.org/10.1038/nm.4113] [PMID: 27239760]
[115]
Larsson M, Shankar EM, Che KF, et al. Molecular signatures of T-cell inhibition in HIV-1 infection. Retrovirology 2013; 10: 31.
[http://dx.doi.org/10.1186/1742-4690-10-31] [PMID: 23514593]
[116]
Wightman F, Solomon A, Kumar SS, et al. Effect of ipilimumab on the HIV reservoir in an HIV-infected individual with metastatic melanoma. AIDS 2015; 29(4): 504-6.
[http://dx.doi.org/10.1097/QAD.0000000000000562] [PMID: 25628259]
[117]
Schor S, Einav S. Repurposing of kinase inhibitors as broad-spectrum antiviral drugs. DNA Cell Biol 2018; 37(2): 63-9.
[http://dx.doi.org/10.1089/dna.2017.4033] [PMID: 29148875]
[118]
Weller ML, Amornphimoltham P, Schmidt M, Wilson PA, Gutkind JS, Chiorini JA. Epidermal growth factor receptor is a co-receptor for adeno-associated virus serotype 6. Nat Med 2010; 16(6): 662-4.
[http://dx.doi.org/10.1038/nm.2145] [PMID: 20473307]
[119]
Panic G, Duthaler U, Speich B, Keiser J. Repurposing drugs for the treatment and control of helminth infections. Int J Parasitol Drugs Drug Resist 2014; 4(3): 185-200.
[http://dx.doi.org/10.1016/j.ijpddr.2014.07.002] [PMID: 25516827]
[120]
Keiser J, Adelfio R, Vargas M, Odermatt P, Tesana S. Activity of tribendimidine and praziquantel combination therapy against the liver fluke Opisthorchis viverrini in vitro and in vivo. J Helminthol 2013; 87(2): 252-6.
[http://dx.doi.org/10.1017/S0022149X12000387] [PMID: 22892101]
[121]
Knopp S, Steinmann P, Keiser J, Utzinger J. Nematode infections: soil-transmitted helminths and trichinella. Infect Dis Clin North Am 2012; 26(2): 341-58.
[http://dx.doi.org/10.1016/j.idc.2012.02.006] [PMID: 22632643]
[122]
Zhao Z, Martin C, Fan R, Bourne PE, Xie L. Drug repurposing to target Ebola virus replication and virulence using structural systems pharmacology. BMC Bioinformatics 2016; 17: 90.
[http://dx.doi.org/10.1186/s12859-016-0941-9] [PMID: 26887654]
[123]
Ng C, Hauptman R, Zhang Y, Bourne PE, Xie L. Anti-infectious drug repurposing using an integrated chemical genomics and structural systems biology approach. Pac Symp Biocomput 2014; 19: 136-47.
[PMID: 24297541]
[124]
Battegay M, Kuehl R, Tschudin-Sutter S, Hirsch HH, Widmer AF, Neher RA. 2019-novel Coronavirus (2019-nCoV): estimating the case fatality rate - a word of caution. Swiss Med Wkly 2020; 150: w20203.
[http://dx.doi.org/10.4414/smw.2020.20203] [PMID: 32031234]
[125]
Li G, De Clercq E. Therapeutic options for the 2019 novel coronavirus (2019-nCoV). Nat Rev Drug Discov 2020; 19(3): 149-50.
[http://dx.doi.org/10.1038/d41573-020-00016-0] [PMID: 32127666]
[126]
Dayer MR, Taleb-Gassabi S, Dayer MS. Lopinavir; a potent drug against coronavirus infection: insight from molecular docking study. Arch Clin Infect Dis 2017; 12: e13823.
[http://dx.doi.org/10.5812/archcid.13823]
[127]
Wang M, Cao R, Zhang L, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res 2020; 30(3): 269-71.
[http://dx.doi.org/10.1038/s41422-020-0282-0] [PMID: 32020029]
[128]
Vincent MJ, Bergeron E, Benjannet S, et al. Chloroquine is a potent inhibitor of SARS coronavirus infection and spread. Virol J 2005; 2: 69.
[http://dx.doi.org/10.1186/1743-422X-2-69] [PMID: 16115318]
[129]
Park CS, Bang BR, Kwon HS, et al. Metformin reduces airway inflammation and remodeling via activation of AMP-activated protein kinase. Biochem Pharmacol 2012; 84(12): 1660-70.
[http://dx.doi.org/10.1016/j.bcp.2012.09.025] [PMID: 23041647]
[130]
Gabasa M, Ikemori R, Hilberg F, Reguart N, Alcaraz J. Nintedanib selectively inhibits the activation and tumour-promoting effects of fibroblasts from lung adenocarcinoma patients. Br J Cancer 2017; 117(8): 1128-38.
[http://dx.doi.org/10.1038/bjc.2017.270] [PMID: 28898237]
[131]
Bueno M, Lai YC, Romero Y, et al. PINK1 deficiency impairs mitochondrial homeostasis and promotes lung fibrosis. J Clin Invest 2015; 125(2): 521-38.
[http://dx.doi.org/10.1172/JCI74942] [PMID: 25562319]
[132]
Pryor R, Cabreiro F. Repurposing metformin: an old drug with new tricks in its binding pockets. Biochem J 2015; 471(3): 307-22.
[http://dx.doi.org/10.1042/BJ20150497] [PMID: 26475449]
[133]
Ito K, Colley T, Mercado N. Geroprotectors as a novel therapeutic strategy for COPD, an accelerating aging disease. Int J Chron Obstruct Pulmon Dis 2012; 7: 641-52.
[http://dx.doi.org/10.2147/COPD.S28250] [PMID: 23055713]
[134]
Cameron AR, Morrison VL, Levin D, et al. Anti-inflammatory effects of metformin irrespective of diabetes status. Circ Res 2016; 119(5): 652-65.
[http://dx.doi.org/10.1161/CIRCRESAHA.116.308445] [PMID: 27418629]
[135]
Hyun B, Shin S, Lee A, et al. Metformin down-regulates TNF-α secretion via suppression of scavenger receptors in macrophages. Immune Netw 2013; 13(4): 123-32.
[http://dx.doi.org/10.4110/in.2013.13.4.123] [PMID: 24009539]
[136]
Lumeng CN, Saltiel AR. Inflammatory links between obesity and metabolic disease. J Clin Invest 2011; 121(6): 2111-7.
[http://dx.doi.org/10.1172/JCI57132] [PMID: 21633179]
[137]
Mowers J, Uhm M, Reilly SM, et al. Inflammation produces catecholamine resistance in obesity via activation of PDE3B by the protein kinases IKKε and TBK1. eLife 2013; 2: e01119.
[http://dx.doi.org/10.7554/eLife.01119] [PMID: 24368730]
[138]
Glass CK, Olefsky JM. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metab 2012; 15(5): 635-45.
[http://dx.doi.org/10.1016/j.cmet.2012.04.001] [PMID: 22560216]
[139]
Karyekar CS, Frederich R, Ravichandran S. Clinically relevant reductions in HbA1c without hypoglycaemia: results across four studies of saxagliptin. Int J Clin Pract 2013; 67(8): 759-67.
[http://dx.doi.org/10.1111/ijcp.12212] [PMID: 23795975]
[140]
Xu G, Chen J, Jing G, Shalev A. Preventing β-cell loss and diabetes with calcium channel blockers. Diabetes 2012; 61(4): 848-56.
[http://dx.doi.org/10.2337/db11-0955] [PMID: 22442301]
[141]
Xu G, Chen J, Jing G, Shalev A. Thioredoxin-interacting protein regulates insulin transcription through microRNA-204. Nat Med 2013; 19(9): 1141-6.
[http://dx.doi.org/10.1038/nm.3287] [PMID: 23975026]
[142]
Chen J, Saxena G, Mungrue IN, Lusis AJ, Shalev A. Thioredoxin-interacting protein: a critical link between glucose toxicity and beta-cell apoptosis. Diabetes 2008; 57(4): 938-44.
[http://dx.doi.org/10.2337/db07-0715] [PMID: 18171713]
[143]
Yin T, Kuo SC, Chang YY, Chen YT, Wang KK. Verapamil use is associated with reduction of newly diagnosed diabetes mellitus. J Clin Endocrinol Metab 2017; 102(7): 2604-10.
[http://dx.doi.org/10.1210/jc.2016-3778] [PMID: 28368479]
[144]
Khodneva Y, Shalev A, Frank SJ, Carson AP, Safford MM. Calcium channel blocker use is associated with lower fasting serum glucose among adults with diabetes from the REGARDS study. Diabetes Res Clin Pract 2016; 115: 115-21.
[http://dx.doi.org/10.1016/j.diabres.2016.01.021] [PMID: 26818894]
[145]
Koning SH, Hoogenberg K, Lutgers HL, van den Berg PP, Wolffenbuttel BH. Gestational Diabetes Mellitus: current knowledge and unmet needs. J Diabetes 2016; 8(6): 770-81.
[http://dx.doi.org/10.1111/1753-0407.12422] [PMID: 27121958]
[146]
Flossmann E, Rothwell PM. British Doctors Aspirin Trial and the UK-TIA Aspirin Trial. Effect of aspirin on long-term risk of colorectal cancer: consistent evidence from randomised and observational studies. Lancet 2007; 369(9573): 1603-13.
[http://dx.doi.org/10.1016/S0140-6736(07)60747-8] [PMID: 17499602]
[147]
González-Pérez A, García Rodríguez LA, López-Ridaura R. Effects of non-steroidal anti-inflammatory drugs on cancer sites other than the colon and rectum: a meta-analysis. BMC Cancer 2003; 3: 28.
[http://dx.doi.org/10.1186/1471-2407-3-28] [PMID: 14588079]
[148]
Sloan EK, Priceman SJ, Cox BF, et al. The sympathetic nervous system induces a metastatic switch in primary breast cancer. Cancer Res 2010; 70(18): 7042-52.
[http://dx.doi.org/10.1158/0008-5472.CAN-10-0522] [PMID: 20823155]
[149]
Springer J, Tschirner A, Haghikia A, et al. Prevention of liver cancer cachexia-induced cardiac wasting and heart failure. Eur Heart J 2014; 35(14): 932-41.
[http://dx.doi.org/10.1093/eurheartj/eht302] [PMID: 23990596]
[150]
Raghavendra PB, Sreenivasan Y, Ramesh GT, Manna SK. Cardiac glycoside induces cell death via FasL by activating calcineurin and NF-AT, but apoptosis initially proceeds through activation of caspases. Apoptosis 2007; 12(2): 307-18.
[http://dx.doi.org/10.1007/s10495-006-0626-3] [PMID: 17203245]
[151]
Ishida J, Konishi M, Ebner N, Springer J. Repurposing of approved cardiovascular drugs. J Transl Med 2016; 14: 269.
[http://dx.doi.org/10.1186/s12967-016-1031-5] [PMID: 27646033]
[152]
Zoppini G, Targher G, Chonchol M, et al. Serum uric acid levels and incident chronic kidney disease in patients with type 2 diabetes and preserved kidney function. Diabetes Care 2012; 35(1): 99-104.
[http://dx.doi.org/10.2337/dc11-1346] [PMID: 22028277]
[153]
Kanji T, Gandhi M, Clase CM, Yang R. Urate lowering therapy to improve renal outcomes in patients with chronic kidney disease: systematic review and meta-analysis. BMC Nephrol 2015; 16: 58.
[http://dx.doi.org/10.1186/s12882-015-0047-z] [PMID: 25928556]
[154]
Navarro-González JF, Mora-Fernández C, Muros de Fuentes M, et al. Effect of pentoxifylline on renal function and urinary albumin excretion in patients with diabetic kidney disease: the PREDIAN trial. J Am Soc Nephrol 2015; 26(1): 220-9.
[http://dx.doi.org/10.1681/ASN.2014010012] [PMID: 24970885]
[155]
Liu D, Wang LN, Li HX, Huang P, Qu LB, Chen FY. Pentoxifylline plus ACEIs/ARBs for proteinuria and kidney function in chronic kidney disease: a meta-analysis. J Int Med Res 2017; 45(2): 383-98.
[http://dx.doi.org/10.1177/0300060516663094] [PMID: 28415944]
[156]
Boycott KM, Vanstone MR, Bulman DE, MacKenzie AE. Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat Rev Genet 2013; 14(10): 681-91.
[http://dx.doi.org/10.1038/nrg3555] [PMID: 23999272]
[157]
Schumacher KR, Stringer KA, Donohue JE, et al. Social media methods for studying rare diseases. Pediatrics 2014; 133(5): e1345-53.
[http://dx.doi.org/10.1542/peds.2013-2966] [PMID: 24733869]
[158]
Vissers LE, Veltman JA. Standardized phenotyping enhances Mendelian disease gene identification. Nat Genet 2015; 47(11): 1222-4.
[http://dx.doi.org/10.1038/ng.3425] [PMID: 26506899]
[159]
Briggs MD, Bell PA, Wright MJ, Pirog KA. New therapeutic targets in rare genetic skeletal diseases. Expert Opin Orphan Drugs 2015; 3(10): 1137-54.
[http://dx.doi.org/10.1517/21678707.2015.1083853] [PMID: 26635999]
[160]
Coskun M, Salem M, Pedersen J, Nielsen OH. Involvement of JAK/STAT signaling in the pathogenesis of inflammatory bowel disease. Pharmacol Res 2013; 76: 1-8.
[http://dx.doi.org/10.1016/j.phrs.2013.06.007] [PMID: 23827161]
[161]
Sandborn WJ, Ghosh S, Panes J, Vranic I, Wang W, Niezychowski W. Study A3921043 Investigators. A phase 2 study of tofacitinib, an oral Janus kinase inhibitor, in patients with Crohn’s disease. Clin Gastroenterol Hepatol 2014; 12(9): 1485-93.e2.
[http://dx.doi.org/10.1016/j.cgh.2014.01.029] [PMID: 24480677]
[162]
Panés J, Su C, Bushmakin AG, Cappelleri JC, Mamolo C, Healey P. Randomized trial of tofacitinib in active ulcerative colitis: analysis of efficacy based on patient-reported outcomes. BMC Gastroenterol 2015; 15: 14.
[http://dx.doi.org/10.1186/s12876-015-0239-9] [PMID: 25651782]
[163]
Dignass A, Van Assche G, Lindsay JO, et al. European Crohn’s and Colitis Organisation (ECCO). The second European evidence-based Consensus on the diagnosis and management of Crohn’s disease: Current management. J Crohn’s Colitis 2010; 4(1): 28-62.
[http://dx.doi.org/10.1016/j.crohns.2009.12.002] [PMID: 21122489]
[164]
Xue H, Li J, Xie H, Wang Y. Review of drug repositioning approaches and resources. Int J Biol Sci 2018; 14(10): 1232-44.
[http://dx.doi.org/10.7150/ijbs.24612] [PMID: 30123072]
[165]
Jin G, Wong STC. Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines. Drug Discov Today 2014; 19(5): 637-44.
[http://dx.doi.org/10.1016/j.drudis.2013.11.005] [PMID: 24239728]
[166]
Bertolini F, Sukhatme VP, Bouche G. Drug repurposing in oncology-patient and health systems opportunities. Nat Rev Clin Oncol 2015; 12(12): 732-42.
[http://dx.doi.org/10.1038/nrclinonc.2015.169] [PMID: 26483297]
[167]
Hernandez JJ, Pryszlak M, Smith L, et al. Giving drugs a second chance: overcoming regulatory and financial hurdles in repurposing approved drugs as cancer therapeutics. Front Oncol 2017; 7: 273.
[http://dx.doi.org/10.3389/fonc.2017.00273] [PMID: 29184849]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy