Finding promiscuous old drugs for new uses

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Finding promiscuous old drugs for new uses

  1. 1. PerspectiveFinding Promiscuous Old Drugs For New UsesSean Ekins1, 2, 3, 4, Antony J. Williams5.1 Collaborations in Chemistry, 601 Runnymede Avenue, Jenkintown, PA 19046, U.S.A.2 Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA94010, U.S.A.3 Department of Pharmaceutical Sciences, University of Maryland, MD 21201, U.S.A.4 Department of Pharmacology, University of Medicine & Dentistry of New Jersey(UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ08854.5 Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC-27587, U.S.A.Running head: Repurposing old drugsCorresponding Author: Sean Ekins, Collaborations in Chemistry, 601 Runnymede Ave,Jenkintown, PA 19046, Email ekinssean@yahoo.com, Tel 215-687-1320. 1
  2. 2. From research published in the last 6 years we have identified 34 studies that havescreened various libraries of FDA approved drugs against various whole cell or targetassays. These studies have each identified one or more compounds with a suggested newbioactivity that had not been described previously. We now show that thirteen of thesedrugs were active against more than one additional disease, thereby suggesting a degreeof promiscuity. We also show that following compilation of all the studies, 109molecules were identified by screening in vitro. These molecules appear to be statisticallymore hydrophobic with a higher molecular weight and AlogP than orphan designatedproducts with at least one marketing approval for a common disease indication or onemarketing approval for a rare disease from the FDA’s rare disease research database.Capturing these in vitro data on old drugs for new uses will be important for potentialreuse and analysis by others to repurpose or reposition these or other existing drugs. Wehave created databases which can be searched by the public and envisage that these canbe updated as more studies are published.Keywords: cheminformatics, Old drugs, repositioning, repurposing, HTS 2
  3. 3. IntroductionAs productivity of the pharmaceutical industry continues to stagnate we call attention tothe merits of reconsidering new potential applications of drugs that are already approved,whether they be old or new (1). This is commonly termed drug repositioning, drugrepurposing or finding “new uses for old drugs”, and has been reviewed extensively inthe context of finding uses for drugs applied to major diseases (2) but is also of value fororphan or rare diseases. The benefits of repositioning include: the availability of chemicalmaterials and previously generated data that can be used and presented to regulatoryauthorities and, as a result, the potential for a significantly more time- and cost-effectiveresearch and development effort than typically experienced when bringing a new drug tomarket. To date multiple academic groups have screened 1,000-2,000 drugs againstdifferent targets or cell types relevant to rare, neglected and common diseases and thisinformation has not been thoroughly compared or captured in a database for analysis untilnow (Supplemental Table 1). We have identified at least 34 such studies published in thelast 6 years which have identified one or more drug molecule active in either whole cellor target-based assays. Several of these studies attempt to find new molecules activeagainst diseases like malaria and tuberculosis for which there are several approved drugs,yet there is still a need to find molecules with a better side effect profile or as areplacement for drugs for which resistance has been shown. These issues alone justify thecontinued search for drugs perhaps with novel mechanisms of action. 3
  4. 4. Several libraries of FDA-approved or foreign-approved drugs have been screenedbut there is currently not one definitive source of all these molecules that researcherscould access at cost for themselves. For example, the John Hopkins Clinical CompoundLibrary (JHCCL) consists of plated compounds available for screening at a relativelysmall charge and has been examined by more than 20 groups with more than a half dozenpublications to date (3-6). A number of new uses for FDA approved drugs have beenidentified by screening these or other commercially available libraries of drugs or off-patent molecules e.g. the NINDS/Microsource US drug collection and PrestwickChemical library (see Supplemental Table 1). In total a conservative estimate indicates atleast 109 previously approved drugs have shown activity in vitro against additionaldiseases different than those for which the drugs were originally approved. For thesemolecules to have any impact on their respective diseases they will obviously have toshow in vivo efficacy. Upon manual curation of this dataset we were able to create adatabase of validated structures which is now publically available(www.collaborativedrug.com). In addition we were able to generate molecular propertiesfor these molecules. We invite others to speculate as to which may show in vivo relevantactivity. We have performed several analyses of the dataset to understand how theycompare to drugs already repurposed for rare diseases.Promiscuous in vitro repurposed drugs Thirteen of these 109 drugs, (Figure 1), showed activity against more than oneadditional disease, thereby suggesting a degree of promiscuity which we believe has notbeen widely acknowledged elsewhere. We found through our meta-analysis that the class 4
  5. 5. III antiarrhythmic amiodarone was active in neurodegeneration assays and could alsoselectively remove embryonic stem cells. The antidepressants amitriptyline andclomipramine suppressed glial fibrially acidic protein (7) and inhibited mitochondrialpermeability transition (8). The anti-psychotic chlorprothixene showed antimalarialactivity (9) and suppressed glial fibrially acidic protein (7). The anti-cancer drugdaunorubicin was active against neuroblastoma (10) and was an NF-kB inhibitor (11).The cardiac glycoside digoxin was active against retinoblastoma (12) and an inhibitor ofhypoxia inducible factor (13). The progestrogen hydroxyprogesterone has antimalarial (9)and glucocorticoid receptor modulator activity. The antineoplastic mitoxantrone wasactive against neuroblastoma and was a glucocorticoid receptor modulator (14). Thecardiac glycoside ouabain was an inhibitor of hypoxia inducible factor (13) and NF-kB(11). The antipsychotic prochlorperazine was an inhibitor of mitochondrial permeabilitytransition (8) and myosin-II associated S100A4 (15). The antihelmintic Pyrviniumpamoate has antituberculosis activity (6) and antiprotozoal activity against C. parvum(16) and T. Brucei (17). The anti-psychotic thioridazine had antimalarial activity (9) andwas an inhibitor of mitochondrial permeability transition (8). Finally, the anti-psychotictrifluoperazine was active in neurodegeneration assays (18), an inhibitor of mitochondrialpermeability transition (8) and myosin-II associated S100A4 (15). Interestingly, the mean predicted molecular properties of these ‘promiscuouscompounds’ are AlogP 3.6 +/- and molecular weight 443 +/- (Table 1). These values arenot statistically significantly different when compared to the whole dataset of 109molecules (mean AlogP of 3.1+/- and molecular weight of 428 +/-) and are closest to the“natural product lead-like rules” (MW < 460, Log P< 4.2) described elsewhere (19). This 5
  6. 6. is suggestive that the 109 molecules are generally quite large compared to drugs ingeneral as for example, Vieth et al., 1193 oral drugs were shown to have a mean MWT of343.7 and CLOGP of 2.3 (20). Another group has screened 3138 compounds against 79assays, primarily GPCR, and showed that approximately 20-30 of the compounds werepromiscuous compounds and had a mean MWT (493) and AlogP (4.4) that was higherthan for selective compounds, 436 and 3.3, respectively (21). However, no statisticaltesting was presented to show whether this was significant or not. It is possible that ourset of promiscuous compounds is too small to discern any meaningful difference.Preventing rediscoveryFrom our analysis (see Supplemental Table 1) there are several examples in whichindependent groups have screened drug libraries in whole cell assays or used differentassays to discover compounds with similar activity such as glial fibrially acidic proteinand mitochondrial permeability transition for neurodegeneration, and hypoxia induciblefactor and NF-kB for cancer. Additionally, several groups have screened FDA approveddrugs against malaria (9, 22). How do researchers now avoid repeating the samediscoveries that others have made? One way would be to capture all of the published usesof these drugs in vitro and combine with information on uses that have already beenidentified in the laboratory or clinic. This has not been done to date. The FDA hasrecently provided a resource, the rare disease research database (RDRD), which listsOrphan-designated products(http://www.fda.gov/ForIndustry/DevelopingProductsforRareDiseasesConditions/Howtoa 6
  7. 7. pplyforOrphanProductDesignation/ucm216147.htm) with at least one marketing approvalfor a common disease indication, for a rare disease indication, or for both common andrare disease indications. In the last category there are less than 50 molecules (includinglarge biopharmaceutical drugs). These tables from the FDA do not capture the highthroughput screening (HTS) data generated to date from diverse laboratories involved inscreening libraries of drugs (Supplemental Table 1). We have curated the molecular structures for these datasets and generated theirphysicochemical properties. The mean predicted molecular properties of thesecompounds in the RDRD databases with at least one marketing approval for a commondisease indication include AlogP 1.4 and molecular weight 353 (Table 2), while thosewith at least one marketing approval for a rare disease indication have AlogP 0.9 andmolecular weight 344. Although these values have large standard deviations they areclose to the published “lead-like” rules (MW < 350, LogP< 3, Affinity ~0.1uM) (23, 24)and closer to the properties of ‘oral drugs’ highlighted by Vieth et al., (20). When thesetwo datasets are compared with the 109 previously approved drugs shown to haveactivity in vitro against additional diseases (Table 1) the differences in AlogP and MWTare statistically significant. Also, the number of rings and aromatic rings are higher in thein vitro dataset. It should be noted that these datasets are relatively small with severalshowing skewed property distributions, hence the use of non-parametric testing and someof the properties like LogP and MW correlate weakly (r2 = 0.07), while other propertiessuch as the number of rings and MW more strongly (r2 = 0.61). Such correlationsbetween physicochemical properties in large sets of FDA approved drugs have beenindicated by others (20). However, our analysis may suggest for the first time that 7
  8. 8. compounds with activity and approved for rare diseases have different LogP and MWT tothose compounds that have been shown to have in vitro activity for various diseases(including rare and neglected). The excel files provided by the FDA are not structure searchable or connected todata in other NIH databases that may be of utility for assisting researchers. There areother useful resources that are less well known. The Collaborative Drug Discovery(CDD) database (25) has focused on collecting data for neglected diseases (26-28). Dr.Chris Lipinski (Melior Discovery) provided a database of 1055 FDA approved drugs withdesignated orphan indications, sponsor name and chemical structures. In addition, CDDhas collated and provided a database of 2815 FDA approved drugs from a list of allapproved drugs since 1938 (22). These data, can enable cheminformatics analysis of thephysicochemical properties of compounds (27, 29, 30) and are available for free accessand searchable by substructure, similarity or Boolean searches upon registration (e.g.,see: http://www.collaborativedrug.com/register). We have therefore made the datasetsfrom this study, and those curated based on the content in RDRD, publically accessible inthe CDD database. The curation of datasets of available drugs or orphan drugs with their uses couldbe used for searching with pharmacophore models (31) or other machine-learningmethods to find new compounds for testing in vitro and to accelerate the repositioningprocess or focusing of in vitro screening on select compounds (32, 33). A study usingsimilarity ensemble analysis, applying Bayesian models to predict off-target effects of3665 FDA approved drugs and investigational compounds (34) and showed the 8
  9. 9. promiscuity of many compounds. While the in vitro validation of the computationalpredictions focused on GPCRs, some of the collated data from the current study couldalso provide a useful method for further validation of this or other future in silicorepositioning methods (35).Making repositioning routine As the availability, at a reasonable cost of FDA approved drugs in a format forHTS is now commonplace, what remains necessary so that the burgeoning numbers ofacademic screening centers or other groups can accelerate repositioning? An exhaustivedatabase that cross references the molecules, papers, and activities would certainly be avaluable starting point and capturing the hit rates of such libraries versus other compoundlibrary screening and clinical data would be valuable. It is not yet obvious whether a drughas progressed straight from these in vitro screens to orphan drug status but the screeningof drug libraries may certainly accelerate this. Evidence of migration from in vitroscreens to orphan status would obviously be immensely valuable. Clearly very old drugslike the tricyclic antidepressants, anti-psychotics and cardiac glycosides appear to bepromiscuous, having been found to possess many activities against additional diseases invitro. Whether these ‘new uses for old promiscuous drugs’ will translate into the clinic,remains in question. The follow up of compounds from in vitro screening to appearancein the clinic is limited as in the case of Ara-C (cytarabine) for Ewing’s sarcoma whichwent to a Phase II clinical study and showed toxicity and minimal activity (36). To ourknowledge, in most cases clinical studies have not been described in over 6 years in 9
  10. 10. which this high throughput screening work has appeared. Perhaps focusing on screeningjust these few classes of promiscuous compounds against any disease of interest wouldyield additional activities and test this hypothesis. In performing our analysis of the literature it appears that many groups have takenthe ‘new uses for old drugs’ approach (37). At the same time it has not been recognizedthat there appears to be a subset of ‘promiscuous’ old drugs (approximately 12% of thecompounds identified to date in vitro). We cannot however distinguish these molecules asdifferent from the complete dataset based on the simple molecular descriptors used in thisstudy. The 109 molecules identified by screening in vitro appear to be statistically morehydrophobic and with a higher molecular weight and AlogP than orphan designatedproducts with at least one marketing approval for a common disease indication or onemarketing approval for a rare disease from the FDA RDRD. These may be usefulinsights, suggesting that some compounds that may have different molecular properties tothose already orphan designated, may have many potential repositioning activities andcould be the focus of more aggressive screening against many more diseases. It will alsobe important to rule out in vitro false positives due to aggregation (38) or other causes.Capturing these in vitro data on promiscuous old drugs for new uses in a format that isreadily mined will be important for reuse and analysis by others and we welcomesuggestions as to who should be responsible for funding, developing and maintaining it. Since this perspective was originally submitted for publication and passed throughthe peer review process it has come to our attention that the NIH Chemical GenomicsCenter has released a database described as a comprehensive resource of clinicallyapproved drugs to enable repurposing and chemical genomics (39). This will be used 10
  11. 11. along with the NCGC screening resources as a component of the NIH therapeutics forrare and neglected diseases (TRND) program. The database has undergone a preliminaryevaluation by us and may indeed be a useful future resource for the community. Howeverwe urge significant caution due to a large number of errors identified in the molecularstructure representations in the database (40) and hence this database will need furthercuration and correction before the structures can be used for other applications such asvirtual screening. We believe there is scope for several efforts to provide databases ofvalidated compounds and data that may be useful for repurposing.Conflicts of Interest SE consults for Collaborative Drug Discovery, Inc on a Bill and Melinda GatesFoundation Grant#49852 “Collaborative drug discovery for TB through a novel databaseof SAR data optimized to promote data archiving and sharing”.Acknowledgments SE gratefully acknowledges David Sullivan (Johns Hopkins University) fordiscussing and suggesting references for JHCCL. Accelrys are kindly thanked forproviding Discovery Studio. 11
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  21. 21. 54. K. Stegmaier, J.S. Wong, K.N. Ross, K.T. Chow, D. Peck, R.D. Wright, S.L. Lessnick, A.L. Kung, and T.R. Golub. Signature-based small molecule screening identifies cytosine arabinoside as an EWS/FLI modulator in Ewing sarcoma. PLoS medicine. 4:e122 (2007).55. Y. Han, A. Miller, J. Mangada, Y. Liu, A. Swistowski, M. Zhan, M.S. Rao, and X. Zeng. Identification by automated screening of a small molecule that selectively eliminates neural stem cells derived from hESCs but not dopamine neurons. PloS one. 4:e7155 (2009).56. H.C. Ou, L.L. Cunningham, S.P. Francis, C.S. Brandon, J.A. Simon, D.W. Raible, and E.W. Rubel. 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. 10:191-203 (2009).57. S.M. Pollard, K. Yoshikawa, I.D. Clarke, D. Danovi, S. Stricker, R. Russell, J. Bayani, R. Head, M. Lee, M. Bernstein, J.A. Squire, A. Smith, and P. Dirks. Glioma stem cell lines expanded in adherent culture have tumor-specific phenotypes and are suitable for chemical and genetic screens. Cell stem cell. 4:568-580 (2009). 21
  22. 22. Table 1. Calculated mean molecular properties (±SD) of orphan designated products and compounds identified withadditional potential therapeutic uses through in vitro high throughput screening of approved drug libraries. Propertiescalculated using Discovery Studio 2.5.5 (Accelrys, San Diego, CA). The datasets of approved drugs repositioned for common or rarediseases from the FDA’s rare disease research database were compared with the in vitro dataset (N = 109) curated in this study using aNon-parametric Wilcoxon / Kruskal-Wallis 2 sample test, a p < 0.05, b p < 0.0001. Comparison of the mean molecular properties forthe subset of thirteen in vitro inhibitors with the larger dataset (n = 109) did not show a statistically significant difference. Range is inparenthesis. All datasets are available at www.collaborativedrug.com. Dataset ALogP Molecular Number Number Number of Number of Number of Weight of of Rings Aromatic Hydrogen Hydrogen Rotatable Rings bond bond Donors Bonds Acceptors Compounds identified in vitro with 3.1 ± 2.6 428.4 ± 202.8 5.4 ± 3.8 3.8 ± 1.9 2.0 ± 1.4 5.6 ± 4.2 2.0 ± 1.9 new activities (N = 109) * (-4.3 – (167-2 – (0 – 20) (0 – 12) (0 – 12) (1 – 27) (0 – 9) 13.93) 1255.42) 22
  23. 23. Compounds identified in vitro with 3.6 ± 2.7 442.8 ± 150.0 5.1 ± 3.1 4.2 ± 1.5 1.8 ± 1.2 5.5 ± 4.6 2.2 ± 3.3multiple new activities (N = 13) (-2.2 – (277.4 – 780.9) (1 – 12) (3 – 8) (0 – 4) (1 – 14) (0 – 8) 7.2)Orphan designated products with at 1.4 ± 3.0 b 353.2 ± 218.8 a 5.3 ± 6.4 2.8 ± 1.7 a 1.2 ± 1.3 b 5.3 ± 6.0 2.5 ± 3.0least one marketing approval for a (-12.6 – (78.1 – (0 – 37) (0 – 8) (0 – 6) (1 – 51) (0 – 18)common disease indication (N = 79) # 6.4) 1462.71)Orphan designated products with at 0.9 ± 3.3 b 344.4 ± 233.5 a 5.3 ± 5.3 2.4 ± 1.9 b 1.3 ± 1.4 b 6.2 ± 4.2 2.7 ± 2.8least one marketing approval for a rare (-13.1 – (30.0 – 1394.6) (0 – 34) (0- 10) (0 – 6) (2 – 25) (0 – 17)disease indication (N = 52) # 8.3)*disulfiram excluded from this analysis.# Compounds from the FDA rare disease research database (RDRD), which lists Orphan-designated products(http://www.fda.gov/ForIndustry/DevelopingProductsforRareDiseasesConditions/HowtoapplyforOrphanProductDesignation/ucm216147.htm) 23
  24. 24. Figure 1. Structures of FDA approved drugs found to have multiple activities beyondwhat they were approved for when screened in vitro. Structures downloaded fromwww.chemspider.com. Amiodarone Amitriptyline Clomipramine Chlorprothixene Daunorubicin Digoxin 24
  25. 25. Hydroxyprogesterone Mitoxantrone Ouabain Prochlorperazine Pyrvinium Thioridazine Trifluoperazine 25
  26. 26. Supplemental data for:PerspectiveFinding Promiscuous and Non-promiscuous Old Drugs For New UsesSean Ekins1, 2, 3, 4, Antony J. Williams5.1 Collaborations in Chemistry, 601 Runnymede Avenue, Jenkintown, PA 19046, U.S.A.2 Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA94010, U.S.A.3 Department of Pharmaceutical Sciences, University of Maryland, MD 21201, U.S.A.4 Department of Pharmacology, University of Medicine & Dentistry of New Jersey(UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ08854.5 Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC-27587, U.S.A.Running head: Repurposing old drugsCorresponding Author: Sean Ekins, Collaborations in Chemistry, 601 Runnymede Ave,Jenkintown, PA 19046, Email ekinssean@yahoo.com, Tel 215-687-1320. 26
  27. 27. Supplemental Table 1. Drugs identified with new uses using HTS methods. Thistable greatly extends a previously published version (35).CCR5, Chemokine receptor 5; DHFR, Dihydrofolate reductase; DOA, Drugs of abuse,FDA, Food and Drug Administration; GLT1, Glutamate transporter 1; HSP-90, Heatshock protein 90; JHCCL, John Hopkins Clinical Compound Library; Mtb,Mycobacterium tuberculosis; NK-1, neurokinin- 1 receptor; OCTN2.Molecule Original use (Target New use and activity How discovered R or drug class)Itraconazole Antifungal – Inhibition of angiogenesis by In vitro HUVEC ( lanosterol 14- inhibiting human lanosterol 14- proliferation screen demethylase inhibitor demethylase IC50 160nM. against FDA approved drugs (JHCCL)Astemizole Non-sedating Antimalarial IC50 227nM against In vitro screen for P. ( antihistamine P. falciparum 3D7. Falciparum growth of (removed from USA 1937 FDA approved market by FDA in drugs (JHCCL) 1999)Mycophenolic Immunosuppresive Inhibition of angiogenesis by In vitro HUVEC (acid drug inhibits guanine targeting Type 1 inosine proliferation screen 2450 nucleotide monophosphate dehydrogenase FDA and foreign biosynthesis IC50 99.2nM. approved drugs (JHCCL) 27
  28. 28. Disulfiram Alcohol deterrent Anti-tuberculosis - MIC 8 to 16 Screened 3360 ( g/ml – screen also identified compounds (JHCCL) sodium diethyldithiocarbamate against Mtb H37Ra (metabolite of disulfiram) and pyrrolidine diethocarbamate which were more active. Mechanism may be due to metal chelationNitazoxanide Infections caused by Anti-tuberculosis – multiple Screens against ( Giarda and potential targets. replicating and non cryptosproridium replicating M. tuberculosis(±)-2-amino-3- Human metabolite, Antimalarial – Inhibits HSP90 HTS screening 4000 (phosphonopropio mGLUR agonist, against P. falciparum 3D7. compoundsnic acid, Antifungal,Acrisorcin, anticancerHarmineLevofloxacin, DNA gyrase Active against ATCC17978 Screened Microsource (Gatifloxacin, inactive against BAA-1605 MIC drugs library of 1040Sarafloxacin, <0.03 – 0.04 (mg/L) drugs versus A.Moxifloxacin, baumanniiGemifloxacinBithionol, Various NF-B inhibitors IC50 0.02- Screened NCGC ( 28
  29. 29. Bortezomib, 39.8M. pharmaceutical collectionCantharidin, of 2816 small moleculesChromomycin in vitroA3,Daunorubicin,Digitoxin,Ectinascidin 743,Emetine,Fluorosalan,Manidipine HCl,Narasin,Lestaurtinib,Ouabain,Sorafenibtosylate,Sunitinib malate,Tioconazole,Tribromsalan,Triclabendazole,ZafirlukastPyrvinium Antihelmintic Anti-tuberculosis – Alamar blue In vitro screen against (pamoate assay MIC 0.31 M. 1514 known drugs – many other previously 29
  30. 30. unidentified hits found.Pyrvinium Antihelmintic Anti-protozoal – In vitro screen for P. (pamoate Cryptosporidium parvum IC50 Falciparum growth of 354nM. 1937 FDA approved drugs hypothesized to be active due to confined to intestinal epithelium.Pyrvinium Antihelmintic Anti-protozoal – against T Screened 2160 FDA (pamoate Brucei IC50 3 M. approved drugs and natural products from Microsource. 15 other drugs active IC50 0.2 – 3 MRiluzole Amyotrophic Lateral Riluzole enhanced Wnt/- Screened 1857 ( Sclerosis - inhibits catenin signaling in both the compounds (1500 glutamate release and primary screen in HT22 neuronal unique) in vitro treating reuptake cells and in adult hippocampal melanoma cells with progenitor cells. Metabotropic riluzole in vitro enhances glutamate receptor GRM1 the ability of WNT3A to regulates Wnt/-catenin regulate gene expression. signaling.Closantel A veterinary Onchocerciasis, or river Screened 1514 FDA ( 30
  31. 31. antihelmintic with blindness IC50 1.6 M approved drugs (JHCCL) known proton competitive inhibition constant against the chitinase ionophore activities (Ki) of 468 nM. OvCHT1 from O. volvulus.Nitroxoline Antibiotic used Anti-angiogenic agent inhibits Screened 2687 FDA ( outside USA for Type 2 methionine approved drugs (JHCCL) urinary tract aminopeptidase (MetAP2) IC50 for inhibition of HUVEC infections. 54.8nM and HUVEC cells. Also found the proliferation. Also inhibits same compound in HTS Sirtuin 1 IC50 20.2 M and of 175,000 compounds Sirtuin 2 IC50 15.5 M. screened against MetAP2. Also active in mouse and human tumor growth models.Glafenine Analgesic Inhibits ABCG2 IC50 3.2 M Screened FDA approved ( could be used with drugs (JHCCL) with chemotherapeutic agents to bioluminescence imaging counteract tumor resistance. HTS assay. Discovered 37 previously unknown ABCG2 inhibitors.Tiagabine Antiepileptic Neuroprotective in N171-82Q Initial screen of NINDS ( (enhances gamma – and R6/2 mouse models of Microsource database of aminobutyric acid Huntington’s disease (HD). drugs (1040 molecules) 31
  32. 32. activity). against PC12 cell model of HD found nepecotic acid which is related to tiagabine.Digoxin, Cardiac glycosides Anticancer – Inhibition of Screened 3120 FDA (Ouabain, used to treat hypoxia-inducible factor 1 IC50 < approved drugs (JHCCL)Proscillardin A congestive heart 400 nM screened against reporter failure and arrthymia. cell line Hep3B-c1. Digoxin also tested in vivo xenograft models.Ceftriaxone -lactam antibiotic Neuroprotection – Amyotrophic Screen of NINDS ( lateral sclerosis (ALS) - Microsource database of increasing glutamate transporter drugs (1040 molecules) (GLT1) expression against rat spinal cord EC50 3.5 M. Other-lactams cultures followed by also active. immunoblot for GLT1 protein expression. Also tested in ALS mouse model, delaying neuron loss, increased survival.Flufenamic acid Non steroidal anti- Familial amyloid Screening library not ( inflammatory drug polyneuropathy – Inhibits described. transthyretin. 32
  33. 33. Chlorprothixene, Anti-psychotics, Antimalarial - EC50 1-3 M Used the Microsource (Dihydroergotami vasoconstrictor, against P. falciparum 3D7. screening and killer-ne, Hycanthone, vasodilator, collections (2160Hydroxyprogeste anhelmintic, compounds). Many other-rone, progestrogen, compounds identifiedPerhexiline, antiarrhythmic e.g. topical and IV drugs.Propafenone, Perhexiline, propafenoneThioridazine and thioridazine may be the most usefulMethazolamide Carbonic anhydrase Inhibitors of cyctochrome c NINDS database of drugs ( inhibitor, diuretic release with therapeutic potential (1040 molecules), Glaucoma for Huntington’s disease (HD). Methazolamide used in transgenic muse model of neurodegeneration resembling HD. 20 other compounds (including antibiotics) identified that inhibit cytochrome c and cross the blood-brain barrier.Aclacinomycin, Antineoplastics, Selective glucocorticoid receptor NINDS database of drugs (Mitoxantrone, Antifungal, steroidal (GR) modulators. (1040 molecules) 33
  34. 34. Ciclopirox Anthracyclines were inhibitors screened simultaneouslyolamine, Rosolic of GR. against 4 promoters,acid, followed by luciferasePararosaniline, assays.Hydroxyprogeste-rone caproateTrifluoperazine, Antidepressants, Inhibitors of mitochondrial NINDS database of drugs (Promethazine, antipychotics, permeability transition (mPT), (1040 molecules)Clomipramine, antihistamine, for stroke. screened to find thoseFluphenazine, antimalarial, that delay mPT inNortriptyline, antiemetics, muscle isolated rat liverThioridazine, relaxant, mitochondria. 23 out ofMefloquine, anticholinergic, anti 32 hits are approved forDesipramine, ulcer. human use and 4Chlorpromazine, molecules were approvedProchlorperazine but no longer in use., Perphenazine, Promethazine protectedAmitriptyline, mice in vivo fromAmoxapine, occlusion/ repurfusion.Maprotiline, Nortriptyline delayedMianserin, disease onset and 34
  35. 35. Cyclobenzaprine, mortality in ALS miceImipramine, and R6/2 mice (amodelClozapine, for HD) (52)Doxepin,Loratidine,Thiothixene,Propantheline,PirenzepineFosfosal, NSAID, -adrenergic Neurodegeneration, reduce NINDS database of (Levonordefrin, agonist, nitric oxide polyglutamine aggregation and drugs, annotatedMolsidomine, releasing prodrug, - toxicity for Huntington’s disease compound library andNadolol, adrenergic receptor and X-linked spinolbulbar Kinase library (>4000Gefitinib antagonist muscular atrophy molecules) screened in FRET assay of androgen receptor aggregation, follow up testing in Drosophila. 5 other compounds identified.Fluspirilene, Antipsychotics, Neurodegeneration – regulate Biomol known bioactive (Trifluoperazine, Calcium channel autophagy a target for library (480 molecules)Pimozide, antagonists Huntington’s disease Alzheimers screened against a humanNicardipine, (cardiovascular), disease glioblastoma cell lineNiguldipine, opiod receptor using an image based 35
  36. 36. Loperamide, antagonist method and a long-livedAmiodarone protein degradation assay. Penitrem A was also identified (non-FDA approved).Cytosine- Nucleoside analog Ewing sarcoma targeting NINDS database of drugs (arabinoside that inhibits DNA EWS/FLI oncoprotein (1040 molecules)(ARA-C) synthesis. screened with a ligation- mediated amplification assay with a bead-based detection. The study used a gene expression signature (14 genes) of EWS/FLI off state. Also showed efficacy in mouse Ewing’s sarcoma model.5-Azacytidine, Anticancer drugs Neuroblastoma (NB) Screened 96 drugs (Colchicine, with different against the SK-N-AS cellDactinomycin, mechanisms line derived from a stageDaunorubicin, 4 neuroblastoma tumor.Mitoxantrone, Secondary screening in aPaclitaxel, second NB cell line. 30 36
  37. 37. Teniposide, compounds active, 15Thioguanine, FDA approved (5Valrubicin currently used for NB)Digoxin, Cardiac glycoside Retinoblastoma Microsource and (Pyrithione zinc used for treating heart Prestwick libraries (2640 failure, antimicrobial molecules) screened against retinoblastoma cell lines followed by xenograft model of retinoblastoma. 9 other compounds identifiedAmiodarone Class III Selective removal of 720 FDA approved drugs ( antiarrhythmic undifferentiated embryonic stem from the NINDS cells (ESC) for cell replacement collection were tested in therapy. ESC and neural stem cells (NSC). 8 other compounds identified as hits that were selectively toxic to NSCs by reducing ATP levels. Follow up in postmitotic neurons.Carvedilol, 2-adrenergic Prevention of hearing loss – NINDS database of drugs ( 37
  38. 38. Phenoxybenzami blocker, diuretic, 1- lowest dose tested that shows (1040 molecules) testedne, Tacrine blocker, protection is 10 M in zebrafish larvae to find anticholinergic those that modulate neomycin induced hair cell toxicity. 4 other non FDA approved molecules were also active. Tacrine was also protective in mouse utricle explants.Rimcazole, Monoamine signaling Malignant glioma NIH clinical collection (Sertraline, modulators (480 molecules) screenedTegaserod, using live cell imaging inRoxatidine, glioma neural stem cells.Paroxetine, 32 other hits identifiedIndatraline including anticancer compounds.Trifluoperazine, Antipsychotics Inhibitors of myosin-II 400 FDA approved drugs (Prochlorperazine associated S100A4 - benign screened using a, Fluphenazine tumors fluorescent biosensor to report on the calcium bound. 9 other diverse compounds had activity.Clomipramine, Antidepressants, Suppression of glial fibrillary Prestwick and spectrum ( 38
  39. 39. Amitriptyline, anticancer, calcium acidic protein – CNS disorders libraries (2880Chlorprothixene, channel antagonist e.g. Alexander Disease molecules) screened forTamoxifen suppression of GFAP. 5citrate, other compounds active –Amlodipine not FDA approved. Reduction in GFAP protein, also see in mice in vivo using clomipramine. 39
  40. 40. 40

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