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.

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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

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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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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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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

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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

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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

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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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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

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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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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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50. S.A. Peterson, T. Klabunde, H.A. Lashuel, H. Purkey, J.C. Sacchettini, and J.W.

Kelly. Inhibiting transthyretin conformational changes that lead to amyloid fibril

formation. Proc Natl Acad Sci U S A. 95:12956-12960 (1998).

51. X. Wang, S. Zhu, Z. Pei, M. Drozda, I.G. Stavrovskaya, S.J. Del Signore, K.

Cormier, E.M. Shimony, H. Wang, R.J. Ferrante, B.S. Kristal, and R.M.

Friedlander. Inhibitors of cytochrome c release with therapeutic potential for

Huntington's disease. J Neurosci. 28:9473-9485 (2008).

52. H. Wang, Y. Guan, X. Wang, K. Smith, K. Cormier, S. Zhu, I.G. Stavrovskaya,

C. Huo, R.J. Ferrante, B.S. Kristal, and R.M. Friedlander. Nortriptyline delays

disease onset in models of chronic neurodegeneration. The European journal of

neuroscience. 26:633-641 (2007).

53. U.A. Desai, J. Pallos, A.A. Ma, B.R. Stockwell, L.M. Thompson, J.L. Marsh, and

M.I. Diamond. Biologically active molecules that reduce polyglutamine

aggregation and toxicity. Human molecular genetics. 15:2114-2124 (2006).

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).

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and E.W. Rubel. Identification of FDA-approved drugs and bioactives that protect

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utricle. J Assoc Res Otolaryngol. 10:191-203 (2009).

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Bayani, R. Head, M. Lee, M. Bernstein, J.A. Squire, A. Smith, and P. Dirks.

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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

Weight

Number

of

Rotatable

Bonds

Number

of Rings

Number of

Aromatic

Rings

Number of

Hydrogen

bond

Acceptors

Number of

Hydrogen

bond Donors

Molecular

Polar

Surface

Area

Compounds identified in vitro with

new activities (N = 109) *

3.1 ± 2.6

(-4.3 –

13.93)

428.4 ± 202.8

(167-2 –

1255.42)

5.4 ± 3.8

(0 – 20)

3.8 ± 1.9

(0 – 12)

2.0 ± 1.4

(0 – 12)

5.6 ± 4.2

(1 – 27)

2.0 ± 1.9

(0 – 9)

89.6 ± 69.3

(3.2 –

379.6)

23

Compounds identified in vitro with

multiple new activities (N = 13)

3.6 ± 2.7

(-2.2 –

7.2)

442.8 ± 150.0

(277.4 – 780.9)

5.1 ± 3.1

(1 – 12)

4.2 ± 1.5

(3 – 8)

1.8 ± 1.2

(0 – 4)

5.5 ± 4.6

(1 – 14)

2.2 ± 3.3

(0 – 8)

79.5 ± 78.8

(3.2 –

206.6)

Orphan designated products with at

least one marketing approval for a

common disease indication (N = 79) #

1.4 ± 3.0 b

(-12.6 –

6.4)

353.2 ± 218.8 a

(78.1 –

1462.71)

5.3 ± 6.4

(0 – 37)

2.8 ± 1.7 a

(0 – 8)

1.2 ± 1.3 b

(0 – 6)

5.3 ± 6.0

(1 – 51)

2.5 ± 3.0

(0 – 18)

99.2 ± 110.7

(12.5 –

839.2)

Orphan designated products with at

least one marketing approval for a rare

disease indication (N = 52) #

0.9 ± 3.3 b

(-13.1 –

8.3)

344.4 ± 233.5 a

(30.0 – 1394.6)

5.3 ± 5.3

(0 – 34)

2.4 ± 1.9 b

(0- 10)

1.3 ± 1.4 b

(0 – 6)

6.2 ± 4.2

(2 – 25)

2.7 ± 2.8

(0 – 17)

114.2 ± 85.3

a

(37.3 –

544.8)

*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)

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

25

Hydroxyprogesterone Mitoxantrone

Ouabain Prochlorperazine

Pyrvinium Thioridazine

Trifluoperazine

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.

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

or drug class)

New use and activity How discovered Ref

Itraconazole Antifungal –

lanosterol 14-

demethylase inhibitor

Inhibition of angiogenesis by

inhibiting human lanosterol 14-

demethylase IC50 160nM.

In vitro HUVEC

proliferation screen

against FDA approved

drugs (JHCCL)

(41)

Astemizole Non-sedating

antihistamine

(removed from USA

market by FDA in

1999)

Antimalarial IC50 227nM against

P. falciparum 3D7.

In vitro screen for P.

Falciparum growth of

1937 FDA approved

drugs (JHCCL)

(22)

Mycophenolic

acid

Immunosuppresive

drug inhibits guanine

nucleotide

biosynthesis

Inhibition of angiogenesis by

targeting Type 1 inosine

monophosphate dehydrogenase

IC50 99.2nM.

In vitro HUVEC

proliferation screen 2450

FDA and foreign

approved drugs (JHCCL)

(42)

28

Disulfiram Alcohol deterrent Anti-tuberculosis - MIC 8 to 16

g/ml – screen also identified

sodium diethyldithiocarbamate

(metabolite of disulfiram) and

pyrrolidine diethocarbamate

which were more active.

Mechanism may be due to metal

chelation

Screened 3360

compounds (JHCCL)

against Mtb H37Ra

(3)

Nitazoxanide Infections caused by

Giarda and

cryptosproridium

Anti-tuberculosis – multiple

potential targets.

Screens against

replicating and non

replicating M.

tuberculosis

(43)

(±)-2-amino-3-

phosphonopropio

nic acid,

Acrisorcin,

Harmine

Human metabolite,

mGLUR agonist,

Antifungal,

anticancer

Antimalarial – Inhibits HSP90

against P. falciparum 3D7.

HTS screening 4000

compounds

(44)

Levofloxacin,

Gatifloxacin,

Sarafloxacin,

Moxifloxacin,

Gemifloxacin

DNA gyrase Active against ATCC17978

inactive against BAA-1605 MIC

<0.03 – 0.04 (mg/L)

Screened Microsource

drugs library of 1040

drugs versus A.

baumannii

(45)

Bithionol, Various NF-B inhibitors IC50 0.02- Screened NCGC (11)

29

Bortezomib,

Cantharidin,

Chromomycin

A3,

Daunorubicin,

Digitoxin,

Ectinascidin 743,

Emetine,

Fluorosalan,

Manidipine HCl,

Narasin,

Lestaurtinib,

Ouabain,

Sorafenib

tosylate,

Sunitinib malate,

Tioconazole,

Tribromsalan,

Triclabendazole,

Zafirlukast

39.8M. pharmaceutical collection

of 2816 small molecules

in vitro

Pyrvinium

pamoate

Antihelmintic Anti-tuberculosis – Alamar blue

assay MIC 0.31 M.

In vitro screen against

1514 known drugs –

many other previously

(6)

30

unidentified hits found.

Pyrvinium

pamoate

Antihelmintic Anti-protozoal –

Cryptosporidium parvum IC50

354nM.

In vitro screen for P.

Falciparum growth of

1937 FDA approved

drugs hypothesized to be

active due to confined to

intestinal epithelium.

(16)

Pyrvinium

pamoate

Antihelmintic Anti-protozoal – against T

Brucei IC50 3 M.

Screened 2160 FDA

approved drugs and

natural products from

Microsource. 15 other

drugs active IC50 0.2 – 3

M

(17)

Riluzole Amyotrophic Lateral

Sclerosis - inhibits

glutamate release and

reuptake

Riluzole enhanced Wnt/-

catenin signaling in both the

primary screen in HT22 neuronal

cells and in adult hippocampal

progenitor cells. Metabotropic

glutamate receptor GRM1

regulates Wnt/-catenin

signaling.

Screened 1857

compounds (1500

unique) in vitro treating

melanoma cells with

riluzole in vitro enhances

the ability of WNT3A to

regulate gene expression.

(46)

Closantel A veterinary Onchocerciasis, or river Screened 1514 FDA (4)

31

antihelmintic with

known proton

ionophore activities

blindness IC50 1.6 M

competitive inhibition constant

(Ki) of 468 nM.

approved drugs (JHCCL)

against the chitinase

OvCHT1 from O.

volvulus.

Nitroxoline Antibiotic used

outside USA for

urinary tract

infections.

Anti-angiogenic agent inhibits

Type 2 methionine

aminopeptidase (MetAP2) IC50

54.8nM and HUVEC

proliferation. Also inhibits

Sirtuin 1 IC50 20.2 M and

Sirtuin 2 IC50 15.5 M.

Screened 2687 FDA

approved drugs (JHCCL)

for inhibition of HUVEC

cells. Also found the

same compound in HTS

of 175,000 compounds

screened against

MetAP2. Also active in

mouse and human tumor

growth models.

(5)

Glafenine Analgesic Inhibits ABCG2 IC50 3.2 M

could be used with

chemotherapeutic agents to

counteract tumor resistance.

Screened FDA approved

drugs (JHCCL) with

bioluminescence imaging

HTS assay. Discovered

37 previously unknown

ABCG2 inhibitors.

(47)

Tiagabine Antiepileptic

(enhances gamma –

aminobutyric acid

Neuroprotective in N171-82Q

and R6/2 mouse models of

Huntington’s disease (HD).

Initial screen of NINDS

Microsource database of

drugs (1040 molecules)

(48)

32

activity). against PC12 cell model

of HD found nepecotic

acid which is related to

tiagabine.

Digoxin,

Ouabain,

Proscillardin A

Cardiac glycosides

used to treat

congestive heart

failure and arrthymia.

Anticancer – Inhibition of

hypoxia-inducible factor 1 IC50 <

400 nM

Screened 3120 FDA

approved drugs (JHCCL)

screened against reporter

cell line Hep3B-c1.

Digoxin also tested in

vivo xenograft models.

(13)

Ceftriaxone -lactam antibiotic Neuroprotection – Amyotrophic

lateral sclerosis (ALS) -

increasing glutamate transporter

(GLT1) expression

EC50 3.5 M. Other-lactams

also active.

Screen of NINDS

Microsource database of

drugs (1040 molecules)

against rat spinal cord

cultures followed by

immunoblot for GLT1

protein expression. Also

tested in ALS mouse

model, delaying neuron

loss, increased survival.

(49)

Flufenamic acid Non steroidal anti-

inflammatory drug

Familial amyloid

polyneuropathy – Inhibits

transthyretin.

Screening library not

described.

(50)

33

Chlorprothixene,

Dihydroergotami

-ne, Hycanthone,

Hydroxyprogeste

-rone,

Perhexiline,

Propafenone,

Thioridazine

Anti-psychotics,

vasoconstrictor,

vasodilator,

anhelmintic,

progestrogen,

antiarrhythmic

Antimalarial - EC50 1-3 M

against P. falciparum 3D7.

Used the Microsource

screening and killer

collections (2160

compounds). Many other

compounds identified

e.g. topical and IV drugs.

Perhexiline, propafenone

and thioridazine may be

the most useful

(9)

Methazolamide Carbonic anhydrase

inhibitor, diuretic

Glaucoma

Inhibitors of cyctochrome c

release with therapeutic potential

for Huntington’s disease (HD).

NINDS database of drugs

(1040 molecules),

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.

(51)

Aclacinomycin,

Mitoxantrone,

Antineoplastics,

Antifungal, steroidal

Selective glucocorticoid receptor

(GR) modulators.

NINDS database of drugs

(1040 molecules)

(14)

34

Ciclopirox

olamine, Rosolic

acid,

Pararosaniline,

Hydroxyprogeste

-rone caproate

Anthracyclines were inhibitors

of GR.

screened simultaneously

against 4 promoters,

followed by luciferase

assays.

Trifluoperazine,

Promethazine,

Clomipramine,

Fluphenazine,

Nortriptyline,

Thioridazine,

Mefloquine,

Desipramine,

Chlorpromazine,

Prochlorperazine

, Perphenazine,

Amitriptyline,

Amoxapine,

Maprotiline,

Mianserin,

Antidepressants,

antipychotics,

antihistamine,

antimalarial,

antiemetics, muscle

relaxant,

anticholinergic, anti

ulcer.

Inhibitors of mitochondrial

permeability transition (mPT),

for stroke.

NINDS database of drugs

(1040 molecules)

screened to find those

that delay mPT in

isolated rat liver

mitochondria. 23 out of

32 hits are approved for

human use and 4

molecules were approved

but no longer in use.

Promethazine protected

mice in vivo from

occlusion/ repurfusion.

Nortriptyline delayed

disease onset and

(8)

35

Cyclobenzaprine,

Imipramine,

Clozapine,

Doxepin,

Loratidine,

Thiothixene,

Propantheline,

Pirenzepine

mortality in ALS mice

and R6/2 mice (amodel

for HD) (52)

Fosfosal,

Levonordefrin,

Molsidomine,

Nadolol,

Gefitinib

NSAID, -adrenergic

agonist, nitric oxide

releasing prodrug, -

adrenergic receptor

antagonist

Neurodegeneration, reduce

polyglutamine aggregation and

toxicity for Huntington’s disease

and X-linked spinolbulbar

muscular atrophy

NINDS database of

drugs, annotated

compound library and

Kinase library (>4000

molecules) screened in

FRET assay of androgen

receptor aggregation,

follow up testing in

Drosophila. 5 other

compounds identified.

(53)

Fluspirilene,

Trifluoperazine,

Pimozide,

Nicardipine,

Niguldipine,

Antipsychotics,

Calcium channel

antagonists

(cardiovascular),

opiod receptor

Neurodegeneration – regulate

autophagy a target for

Huntington’s disease Alzheimers

disease

Biomol known bioactive

library (480 molecules)

screened against a human

glioblastoma cell line

using an image based

(18)

36

Loperamide,

Amiodarone

antagonist method and a long-lived

protein degradation

assay. Penitrem A was

also identified (non-FDA

approved).

Cytosine-

arabinoside

(ARA-C)

Nucleoside analog

that inhibits DNA

synthesis.

Ewing sarcoma targeting

EWS/FLI oncoprotein

NINDS database of drugs

(1040 molecules)

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.

(54)

5-Azacytidine,

Colchicine,

Dactinomycin,

Daunorubicin,

Mitoxantrone,

Paclitaxel,

Anticancer drugs

with different

mechanisms

Neuroblastoma (NB) Screened 96 drugs

against the SK-N-AS cell

line derived from a stage

4 neuroblastoma tumor.

Secondary screening in a

second NB cell line. 30

(10)

37

Teniposide,

Thioguanine,

Valrubicin

compounds active, 15

FDA approved (5

currently used for NB)

Digoxin,

Pyrithione zinc

Cardiac glycoside

used for treating heart

failure, antimicrobial

Retinoblastoma Microsource and

Prestwick libraries (2640

molecules) screened

against retinoblastoma

cell lines followed by

xenograft model of

retinoblastoma. 9 other

compounds identified

(12)

Amiodarone Class III

antiarrhythmic

Selective removal of

undifferentiated embryonic stem

cells (ESC) for cell replacement

therapy.

720 FDA approved drugs

from the NINDS

collection were tested in

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.

(55)

Carvedilol, 2-adrenergic Prevention of hearing loss – NINDS database of drugs (56)

38

Phenoxybenzami

ne, Tacrine

blocker, diuretic, 1-

blocker,

anticholinergic

lowest dose tested that shows

protection is 10 M

(1040 molecules) tested

in zebrafish larvae to find

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,

Sertraline,

Tegaserod,

Roxatidine,

Paroxetine,

Indatraline

Monoamine signaling

modulators

Malignant glioma NIH clinical collection

(480 molecules) screened

using live cell imaging in

glioma neural stem cells.

32 other hits identified

including anticancer

compounds.

(57)

Trifluoperazine,

Prochlorperazine

, Fluphenazine

Antipsychotics Inhibitors of myosin-II

associated S100A4 - benign

tumors

400 FDA approved drugs

screened using a

fluorescent biosensor to

report on the calcium

bound. 9 other diverse

compounds had activity.

(15)

Clomipramine, Antidepressants, Suppression of glial fibrillary Prestwick and spectrum (7)

39

Amitriptyline,

Chlorprothixene,

Tamoxifen

citrate,

Amlodipine

anticancer, calcium

channel antagonist

acidic protein – CNS disorders

e.g. Alexander Disease

libraries (2880

molecules) screened for

suppression of GFAP. 5

other compounds active –

not FDA approved.

Reduction in GFAP

protein, also see in mice

in vivo using

clomipramine.

40