1. Perspective
Finding Promiscuous Old Drugs For New Uses
Sean 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, CA
94010, 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, NJ
08854.
5
Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC-27587, U.S.A.
Running head: Repurposing old drugs
Corresponding Author: Sean Ekins, Collaborations in Chemistry, 601 Runnymede Ave,
Jenkintown, PA 19046, Email ekinssean@yahoo.com, Tel 215-687-1320.
1

2. From research published in the last 6 years we have identified 34 studies that have
screened various libraries of FDA approved drugs against various whole cell or target
assays. These studies have each identified one or more compounds with a suggested new
bioactivity that had not been described previously. We now show that thirteen of these
drugs were active against more than one additional disease, thereby suggesting a degree
of promiscuity. We also show that following compilation of all the studies, 109
molecules were identified by screening in vitro. These molecules appear to be statistically
more hydrophobic with a higher molecular weight and AlogP than orphan designated
products with at least one marketing approval for a common disease indication or one
marketing 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 potential
reuse and analysis by others to repurpose or reposition these or other existing drugs. We
have created databases which can be searched by the public and envisage that these can
be updated as more studies are published.
Keywords: cheminformatics, Old drugs, repositioning, repurposing, HTS
2

3. Introduction
As productivity of the pharmaceutical industry continues to stagnate we call attention to
the 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, drug
repurposing or finding “new uses for old drugs”, and has been reviewed extensively in
the context of finding uses for drugs applied to major diseases (2) but is also of value for
orphan or rare diseases. The benefits of repositioning include: the availability of chemical
materials and previously generated data that can be used and presented to regulatory
authorities and, as a result, the potential for a significantly more time- and cost-effective
research and development effort than typically experienced when bringing a new drug to
market.
To date multiple academic groups have screened 1,000-2,000 drugs against
different targets or cell types relevant to rare, neglected and common diseases and this
information has not been thoroughly compared or captured in a database for analysis until
now (Supplemental Table 1). We have identified at least 34 such studies published in the
last 6 years which have identified one or more drug molecule active in either whole cell
or target-based assays. Several of these studies attempt to find new molecules active
against 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 a
replacement for drugs for which resistance has been shown. These issues alone justify the
continued search for drugs perhaps with novel mechanisms of action.
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4. Several libraries of FDA-approved or foreign-approved drugs have been screened
but there is currently not one definitive source of all these molecules that researchers
could access at cost for themselves. For example, the John Hopkins Clinical Compound
Library (JHCCL) consists of plated compounds available for screening at a relatively
small charge and has been examined by more than 20 groups with more than a half dozen
publications to date (3-6). A number of new uses for FDA approved drugs have been
identified by screening these or other commercially available libraries of drugs or off-
patent molecules e.g. the NINDS/Microsource US drug collection and Prestwick
Chemical library (see Supplemental Table 1). In total a conservative estimate indicates at
least 109 previously approved drugs have shown activity in vitro against additional
diseases different than those for which the drugs were originally approved. For these
molecules to have any impact on their respective diseases they will obviously have to
show in vivo efficacy. Upon manual curation of this dataset we were able to create a
database of validated structures which is now publically available
(www.collaborativedrug.com). In addition we were able to generate molecular properties
for these molecules. We invite others to speculate as to which may show in vivo relevant
activity. We have performed several analyses of the dataset to understand how they
compare to drugs already repurposed for rare diseases.
Promiscuous in vitro repurposed drugs
Thirteen of these 109 drugs, (Figure 1), showed activity against more than one
additional disease, thereby suggesting a degree of promiscuity which we believe has not
been widely acknowledged elsewhere. We found through our meta-analysis that the class
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5. III antiarrhythmic amiodarone was active in neurodegeneration assays and could also
selectively remove embryonic stem cells. The antidepressants amitriptyline and
clomipramine suppressed glial fibrially acidic protein (7) and inhibited mitochondrial
permeability transition (8). The anti-psychotic chlorprothixene showed antimalarial
activity (9) and suppressed glial fibrially acidic protein (7). The anti-cancer drug
daunorubicin was active against neuroblastoma (10) and was an NF-kB inhibitor (11).
The cardiac glycoside digoxin was active against retinoblastoma (12) and an inhibitor of
hypoxia inducible factor (13). The progestrogen hydroxyprogesterone has antimalarial (9)
and glucocorticoid receptor modulator activity. The antineoplastic mitoxantrone was
active against neuroblastoma and was a glucocorticoid receptor modulator (14). The
cardiac glycoside ouabain was an inhibitor of hypoxia inducible factor (13) and NF-kB
(11). The antipsychotic prochlorperazine was an inhibitor of mitochondrial permeability
transition (8) and myosin-II associated S100A4 (15). The antihelmintic Pyrvinium
pamoate has antituberculosis activity (6) and antiprotozoal activity against C. parvum
(16) and T. Brucei (17). The anti-psychotic thioridazine had antimalarial activity (9) and
was an inhibitor of mitochondrial permeability transition (8). Finally, the anti-psychotic
trifluoperazine was active in neurodegeneration assays (18), an inhibitor of mitochondrial
permeability transition (8) and myosin-II associated S100A4 (15).
Interestingly, the mean predicted molecular properties of these ‘promiscuous
compounds’ are AlogP 3.6 +/- and molecular weight 443 +/- (Table 1). These values are
not statistically significantly different when compared to the whole dataset of 109
molecules (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. is suggestive that the 109 molecules are generally quite large compared to drugs in
general as for example, Vieth et al., 1193 oral drugs were shown to have a mean MWT of
343.7 and CLOGP of 2.3 (20). Another group has screened 3138 compounds against 79
assays, primarily GPCR, and showed that approximately 20-30 of the compounds were
promiscuous compounds and had a mean MWT (493) and AlogP (4.4) that was higher
than for selective compounds, 436 and 3.3, respectively (21). However, no statistical
testing was presented to show whether this was significant or not. It is possible that our
set of promiscuous compounds is too small to discern any meaningful difference.
Preventing rediscovery
From our analysis (see Supplemental Table 1) there are several examples in which
independent groups have screened drug libraries in whole cell assays or used different
assays to discover compounds with similar activity such as glial fibrially acidic protein
and mitochondrial permeability transition for neurodegeneration, and hypoxia inducible
factor and NF-kB for cancer. Additionally, several groups have screened FDA approved
drugs against malaria (9, 22). How do researchers now avoid repeating the same
discoveries that others have made? One way would be to capture all of the published uses
of these drugs in vitro and combine with information on uses that have already been
identified in the laboratory or clinic. This has not been done to date. The FDA has
recently provided a resource, the rare disease research database (RDRD), which lists
Orphan-designated products
(http://www.fda.gov/ForIndustry/DevelopingProductsforRareDiseasesConditions/Howtoa
6

7. pplyforOrphanProductDesignation/ucm216147.htm) with at least one marketing approval
for a common disease indication, for a rare disease indication, or for both common and
rare disease indications. In the last category there are less than 50 molecules (including
large biopharmaceutical drugs). These tables from the FDA do not capture the high
throughput screening (HTS) data generated to date from diverse laboratories involved in
screening libraries of drugs (Supplemental Table 1).
We have curated the molecular structures for these datasets and generated their
physicochemical properties. The mean predicted molecular properties of these
compounds in the RDRD databases with at least one marketing approval for a common
disease indication include AlogP 1.4 and molecular weight 353 (Table 2), while those
with at least one marketing approval for a rare disease indication have AlogP 0.9 and
molecular weight 344. Although these values have large standard deviations they are
close 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 these
two datasets are compared with the 109 previously approved drugs shown to have
activity in vitro against additional diseases (Table 1) the differences in AlogP and MWT
are statistically significant. Also, the number of rings and aromatic rings are higher in the
in vitro dataset. It should be noted that these datasets are relatively small with several
showing skewed property distributions, hence the use of non-parametric testing and some
of the properties like LogP and MW correlate weakly (r2 = 0.07), while other properties
such as the number of rings and MW more strongly (r2 = 0.61). Such correlations
between physicochemical properties in large sets of FDA approved drugs have been
indicated by others (20). However, our analysis may suggest for the first time that
7

8. compounds with activity and approved for rare diseases have different LogP and MWT to
those 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 to
data in other NIH databases that may be of utility for assisting researchers. There are
other 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 with
designated orphan indications, sponsor name and chemical structures. In addition, CDD
has collated and provided a database of 2815 FDA approved drugs from a list of all
approved drugs since 1938 (22). These data, can enable cheminformatics analysis of the
physicochemical properties of compounds (27, 29, 30) and are available for free access
and searchable by substructure, similarity or Boolean searches upon registration (e.g.,
see: http://www.collaborativedrug.com/register). We have therefore made the datasets
from this study, and those curated based on the content in RDRD, publically accessible in
the CDD database.
The curation of datasets of available drugs or orphan drugs with their uses could
be used for searching with pharmacophore models (31) or other machine-learning
methods to find new compounds for testing in vitro and to accelerate the repositioning
process or focusing of in vitro screening on select compounds (32, 33). A study using
similarity ensemble analysis, applying Bayesian models to predict off-target effects of
3665 FDA approved drugs and investigational compounds (34) and showed the
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9. promiscuity of many compounds. While the in vitro validation of the computational
predictions focused on GPCRs, some of the collated data from the current study could
also provide a useful method for further validation of this or other future in silico
repositioning methods (35).
Making repositioning routine
As the availability, at a reasonable cost of FDA approved drugs in a format for
HTS is now commonplace, what remains necessary so that the burgeoning numbers of
academic screening centers or other groups can accelerate repositioning? An exhaustive
database that cross references the molecules, papers, and activities would certainly be a
valuable starting point and capturing the hit rates of such libraries versus other compound
library screening and clinical data would be valuable. It is not yet obvious whether a drug
has progressed straight from these in vitro screens to orphan drug status but the screening
of drug libraries may certainly accelerate this. Evidence of migration from in vitro
screens to orphan status would obviously be immensely valuable. Clearly very old drugs
like the tricyclic antidepressants, anti-psychotics and cardiac glycosides appear to be
promiscuous, having been found to possess many activities against additional diseases in
vitro. 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 appearance
in the clinic is limited as in the case of Ara-C (cytarabine) for Ewing’s sarcoma which
went to a Phase II clinical study and showed toxicity and minimal activity (36). To our
knowledge, in most cases clinical studies have not been described in over 6 years in
9

10. which this high throughput screening work has appeared. Perhaps focusing on screening
just these few classes of promiscuous compounds against any disease of interest would
yield additional activities and test this hypothesis.
In performing our analysis of the literature it appears that many groups have taken
the ‘new uses for old drugs’ approach (37). At the same time it has not been recognized
that there appears to be a subset of ‘promiscuous’ old drugs (approximately 12% of the
compounds identified to date in vitro). We cannot however distinguish these molecules as
different from the complete dataset based on the simple molecular descriptors used in this
study. The 109 molecules identified by screening in vitro appear to be statistically more
hydrophobic and with a higher molecular weight and AlogP than orphan designated
products with at least one marketing approval for a common disease indication or one
marketing approval for a rare disease from the FDA RDRD. These may be useful
insights, suggesting that some compounds that may have different molecular properties to
those already orphan designated, may have many potential repositioning activities and
could be the focus of more aggressive screening against many more diseases. It will also
be 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 is
readily mined will be important for reuse and analysis by others and we welcome
suggestions as to who should be responsible for funding, developing and maintaining it.
Since this perspective was originally submitted for publication and passed through
the peer review process it has come to our attention that the NIH Chemical Genomics
Center has released a database described as a comprehensive resource of clinically
approved drugs to enable repurposing and chemical genomics (39). This will be used
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11. along with the NCGC screening resources as a component of the NIH therapeutics for
rare and neglected diseases (TRND) program. The database has undergone a preliminary
evaluation by us and may indeed be a useful future resource for the community. However
we urge significant caution due to a large number of errors identified in the molecular
structure representations in the database (40) and hence this database will need further
curation and correction before the structures can be used for other applications such as
virtual screening. We believe there is scope for several efforts to provide databases of
validated compounds and data that may be useful for repurposing.
Conflicts of Interest
SE consults for Collaborative Drug Discovery, Inc on a Bill and Melinda Gates
Foundation Grant#49852 “Collaborative drug discovery for TB through a novel database
of SAR data optimized to promote data archiving and sharing”.
Acknowledgments
SE gratefully acknowledges David Sullivan (Johns Hopkins University) for
discussing and suggesting references for JHCCL. Accelrys are kindly thanked for
providing Discovery Studio.
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21

22. Table 1. Calculated mean molecular properties (±SD) of orphan designated products and compounds identified with
additional potential therapeutic uses through in vitro high throughput screening of approved drug libraries. Properties
calculated using Discovery Studio 2.5.5 (Accelrys, San Diego, CA). The datasets of approved drugs repositioned for common or rare
diseases from the FDA’s rare disease research database were compared with the in vitro dataset (N = 109) curated in this study using a
Non-parametric Wilcoxon / Kruskal-Wallis 2 sample test, a p < 0.05, b p < 0.0001. Comparison of the mean molecular properties for
the subset of thirteen in vitro inhibitors with the larger dataset (n = 109) did not show a statistically significant difference. Range is in
parenthesis. 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. 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 ± 3.3
multiple 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 ± 3.0
least 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 ± 2.8
least 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/ucm2161
47.htm)
23

24. Figure 1. Structures of FDA approved drugs found to have multiple activities beyond
what they were approved for when screened in vitro. Structures downloaded from
www.chemspider.com.
Amiodarone Amitriptyline
Clomipramine Chlorprothixene
Daunorubicin Digoxin
24

25. Hydroxyprogesterone Mitoxantrone
Ouabain Prochlorperazine
Pyrvinium Thioridazine
Trifluoperazine
25

26. Supplemental data for:
Perspective
Finding Promiscuous and Non-promiscuous Old Drugs For New Uses
Sean 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, CA
94010, 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, NJ
08854.
5
Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC-27587, U.S.A.
Running head: Repurposing old drugs
Corresponding Author: Sean Ekins, Collaborations in Chemistry, 601 Runnymede Ave,
Jenkintown, PA 19046, Email ekinssean@yahoo.com, Tel 215-687-1320.
26

27. Supplemental Table 1. Drugs identified with new uses using HTS methods. This
table 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, Heat
shock 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. 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
chelation
Nitazoxanide 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. compounds
nic acid, Antifungal,
Acrisorcin, anticancer
Harmine
Levofloxacin, DNA gyrase Active against ATCC17978 Screened Microsource (
Gatifloxacin, inactive against BAA-1605 MIC drugs library of 1040
Sarafloxacin, <0.03 – 0.04 (mg/L) drugs versus A.
Moxifloxacin, baumannii
Gemifloxacin
Bithionol, Various NF-B inhibitors IC50 0.02- Screened NCGC (
28

29. Bortezomib, 39.8M. pharmaceutical collection
Cantharidin, of 2816 small molecules
Chromomycin in vitro
A3,
Daunorubicin,
Digitoxin,
Ectinascidin 743,
Emetine,
Fluorosalan,
Manidipine HCl,
Narasin,
Lestaurtinib,
Ouabain,
Sorafenib
tosylate,
Sunitinib malate,
Tioconazole,
Tribromsalan,
Triclabendazole,
Zafirlukast
Pyrvinium Antihelmintic Anti-tuberculosis – Alamar blue In vitro screen against (
pamoate assay MIC 0.31 M. 1514 known drugs –
many other previously
29

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
M
Riluzole 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. 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. 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. Chlorprothixene, Anti-psychotics, Antimalarial - EC50 1-3 M Used the Microsource (
Dihydroergotami vasoconstrictor, against P. falciparum 3D7. screening and killer
-ne, Hycanthone, vasodilator, collections (2160
Hydroxyprogeste anhelmintic, compounds). Many other
-rone, progestrogen, compounds identified
Perhexiline, antiarrhythmic e.g. topical and IV drugs.
Propafenone, Perhexiline, propafenone
Thioridazine and thioridazine may be
the most useful
Methazolamide 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. Ciclopirox Anthracyclines were inhibitors screened simultaneously
olamine, Rosolic of GR. against 4 promoters,
acid, followed by luciferase
Pararosaniline, assays.
Hydroxyprogeste
-rone caproate
Trifluoperazine, Antidepressants, Inhibitors of mitochondrial NINDS database of drugs (
Promethazine, antipychotics, permeability transition (mPT), (1040 molecules)
Clomipramine, antihistamine, for stroke. screened to find those
Fluphenazine, antimalarial, that delay mPT in
Nortriptyline, antiemetics, muscle isolated rat liver
Thioridazine, relaxant, mitochondria. 23 out of
Mefloquine, anticholinergic, anti 32 hits are approved for
Desipramine, ulcer. human use and 4
Chlorpromazine, molecules were approved
Prochlorperazine but no longer in use.
, Perphenazine, Promethazine protected
Amitriptyline, mice in vivo from
Amoxapine, occlusion/ repurfusion.
Maprotiline, Nortriptyline delayed
Mianserin, disease onset and
34

35. Cyclobenzaprine, mortality in ALS mice
Imipramine, and R6/2 mice (amodel
Clozapine, for HD) (52)
Doxepin,
Loratidine,
Thiothixene,
Propantheline,
Pirenzepine
Fosfosal, NSAID, -adrenergic Neurodegeneration, reduce NINDS database of (
Levonordefrin, agonist, nitric oxide polyglutamine aggregation and drugs, annotated
Molsidomine, releasing prodrug, - toxicity for Huntington’s disease compound library and
Nadolol, adrenergic receptor and X-linked spinolbulbar Kinase library (>4000
Gefitinib 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 human
Nicardipine, (cardiovascular), disease glioblastoma cell line
Niguldipine, opiod receptor using an image based
35

36. Loperamide, antagonist method and a long-lived
Amiodarone 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 cell
Dactinomycin, mechanisms line derived from a stage
Daunorubicin, 4 neuroblastoma tumor.
Mitoxantrone, Secondary screening in a
Paclitaxel, second NB cell line. 30
36

37. Teniposide, compounds active, 15
Thioguanine, FDA approved (5
Valrubicin 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 identified
Amiodarone 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. Phenoxybenzami blocker, diuretic, 1- lowest dose tested that shows (1040 molecules) tested
ne, 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) screened
Tegaserod, using live cell imaging in
Roxatidine, glioma neural stem cells.
Paroxetine, 32 other hits identified
Indatraline 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. Amitriptyline, anticancer, calcium acidic protein – CNS disorders libraries (2880
Chlorprothixene, channel antagonist e.g. Alexander Disease molecules) screened for
Tamoxifen suppression of GFAP. 5
citrate, other compounds active –
Amlodipine not FDA approved.
Reduction in GFAP
protein, also see in mice
in vivo using
clomipramine.
39

40. 40