Drug Repurposing Against Infectious Diseases by Integrating Chemical Genomics and Structural Systems Biology

Philip E. Bourne1, Lei Xie2

1Skaggs School of Pharmacy and Pharmaceutical Sciences

University of California, San Diego2Department of Computer Science, Hunter College

Ph.D. Program in Computer Science, Biology, and Biochemistry

The City University of New York

Infectious Disease: A Growing Problem

Infectious diseases account for 25% of deaths worldwide Antimicrobial resistance is increasing

Wide-spread bacteria use antibiotics for nourishmentClatworthy et al., Nature Chemical Biology, 3(2007), 541 - 548

Teaching New Tricks to Old Drugs

Ashburn et al. Nat Rev Drug Disc 3(2004), 673-683

Challenges in Drug Repurposing Against Infectious Diseases

Phenotype-based methods (e.g. gene expression profiles)

- Difficult to compare phenotypes across organisms

- Unknown targets for a large number of bioactive compounds

Ligand-based chemoinformatics methods

- Limited target coverage of pathogen genomes in bioassay databases

- Insufficient models for 3D protein-ligand interactions

Target-based molecular modeling methods (e.g. protein-ligand docking, MD simulation, structural bioinformatics)

- Not scalable to millions of chemicals and ten thousands of targets

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Reconstruction of Genome-Scale 3D Drug-Target Interaction Models

Integrating chemical genomics and structural systems biology

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MDsimulation

Mj

Q

Refinedinteractionmodel

MjQ

geneSAR SMAP

Protein-liganddocking

Mj

Q

Mi

3D model of novelTarget

3D model ofannotated target

Initialinteractionmodel

Querychemical

Networkmodeling

Experimentalsupport

generalized networkenrichment of Structure-Activity Relationships

Similarity Search Revisit

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1

1

0 1

0

0

Query

False Negative

False Positive

Query

2.8

2.8

2.2 1.7

1.2

1.2

Generalized Network Enrichment of Structure-Activity Relationship (geneSAR)

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BioassayDatabase

(ChEMBL, PubChem etc.)

TiTj

Fingerprintsimilarity

Q

Random walk with restart(RWR)

TiTj

LigandSet

RandomSet

GlobalStatistics

Score Distribution

Ti Tj

Q

Ti Tj

geneSAR Considerably Improves the Performance of Drug-Target Interactions

RWR improves both the sensitivity/specificity and coverage of chemical similarity search compared with 2D fingerprints.

When false positive ratio < 0.05, geneSAR detects >3 times more drug-target interactions than SEA.

The success of geneSAR comes from its combination of RWR and global statistics.

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Detecting Protein Binding Promiscuity across Fold Space

35% of biologically active compounds bind to two or more targets that do not have similar sequences or global shapes

Paolini et al. Nat. Biotechnol. 2006 24:805–815

HASSTRVCTVREPRTSEQAENCE

SMAP v2.0

Experimental Validation of SMAP Predictions on Multiple Organisms

Primary Target Off-target Pharmacology implication

Publication

Human protein kinase

Bacteria carboxylase

Drug repurposing for antibiotics

Miller et al. Proc Natl Acad Sci USA 106(2009):1737

HIV Protease Human protein kinase

Drug repurposing for cancer

Xie et al. PLoS Comp Biol 7(2011):e1002037

Human ER P. auroginosa PhzB

Drug repurposing for anti-virulence

Ho Sui et al.  Int. J. of Antimicrobial Agents 40(2012):246-251

T. brucei RNA-ligase

Human MECR/ETR1

Serious side effects Durrant et al PLoS Comp Biol 6(2010):e1000648

Human COMT M. tb InhA Drug repurposing for MDR TB

Kinings et al. PLoS Comp Biol 5(2009):e1000423

http://www.sdsc.edu/pb/ - Drug Discovery Work

Case Studies

Repurposing selective estrogen receptor modulators (SERMs) as anti-virulence agents

Target fishing from the “Malaria Box” and subsequent drug repurposing

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Case Studies

Repurposing selective estrogen receptor modulators (SERMs) as anti-virulence agents

Target fishing from the “Malaria Box” and subsequent drug repurposing

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Target Species: Pseudomonas aeruginosa

Opportunistic pathogen causes infections in individuals with weak immunity, burn victims, and patients of cystic fibrosis.

Intrinsic antibiotic resistance mainly through efflux pump

PhzB2 as a Potential Drug Target Interacting with Selective Estrogen Receptor Modulators

PhzB2 involved in pyocyanin biosynthesis although its molecular function remains unknown

Pyocyanin is both a virulence factor of bacteria that induce oxidative stress in host cells and a quorum sensing signaling molecule

No human orthologs Raloxifene (antagonist of ER,

preventive therapy for osteoporosis) can be docked into an uncharacterized pocket

PhzB2

Experimental Validation

Increased survival rate of infected C. elegans Reduced virulence factor pyocyanin production

0 39 43 62 67 70 91 9520

30

40

50

60

70

80

90

100

OP50PAO1PA01+RALPAO1+RALPA14PA14+RAL

Time (h)

Su

rviv

al R

ate

(%

)

(1.6 mg/ml)(100 mg/ml)

(100 mg/ml)PA14

g/ml)

PA14

+ R

al (1

2.5

g/ml)

PA14

+ R

al (2

5 g/m

l)

PA14

+ R

al (5

0 g/m

l)

PA14 +

Ral

(100

0.0

0.5

1.0

1.5

2.0

2.5

Pyo

cyan

in,

g/m

l of

cult

ure

su

per

nat

ant

S.J. Ho Sui, et al. 2012 Int. J. of Antimicrobial Agents (40)3: 246-251

Case Studies

Repurposing selective estrogen receptor modulators (SERMs) as anti-virulence agents

Target fishing from the “Malaria Box” and subsequent drug repurposing

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Malaria

Malaria is a widespread disease, caused by Plasmodium (P. falciparum and P. vivax)

219 million cases, 1.2 million deaths in 2010 Resistance has developed to anti-malaria drugs.

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P. falciparum Drugome

116 drugs, 268 P. falciparum proteins, and 1120 interactions.

Antimicrobial drugs are most likely to be anti-malarial drugs

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P fal Drugome: Y. Zhang et al. 2013 Submitted.TB Drugome: S.L. Kinnings, et al. 2011 PLoS Comp. Biol. 6(11): e1000976

Open Access Malaria Box

400 diverse compounds with anti-malaria activity (200 drug-like, 200 probe-like) from whole cell screening of ~4 million of compound.

Molecular targets are unknown. in vivo anti-malaria activities are unknown Potential side effects are unknown

The identification of molecular targets in both P. fal and human will:

Optimize these drug-like compounds to be effective therapeutics Predict potential side effects Provide insight into potential drug resistance

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Targets of Drug-like Compounds from Chemical Genomics Data (ChEMBL)

157 drug-like compounds are predicted to interact with 427 targets from multiple organisms using geneSAR (FDR<0.05)

Implication of side effects and drug repurposing for other infectious diseases

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Target organism phamarcology

Heparanase Human cancer and thrombosis

PDE5A Human Cardiac effect

Dihydroorotate dehydrogenase

Human inflammation

Sporulation kinase A B. subtilis Gut side effects

hexokinase T. bruci African sleeping sickness

Bontoxilysin-A C. botulinum Neurotoxin

Link Approved Drugs with Malaria Box viaTarget Interaction Profiling (TIP)

Novel Essential P. fal Target Safe Drug

Dihydroorotate dehydrogenase Leflunomide (anti-inflammation)

Beta-hydroxyacyl-ACP dehydratase Hesperetin ( lowering cholesterol)

Cysteine protease falcipain-3 ?

3-oxoacyl-acyl-carrier protein reductase Desonide (anti-inflammation)

DNA topoisomerase 2 Genistein (cancer prevention)

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genome

Malaria Box

Drugbank

Summary

A new chemical genomics algorithm to identify drug-target interactions

An integrated chemical genomics and structural systems biology computational pipeline is able to generate testable hypotheses for drug repurposing

This is only the beginning in making a difference

Acknowledgement

• Dr. Li Xie (SSPPS, UCSD)• Mr. Joshua Lerman (Bioengineering, UCSD)• Ms. Yinliang Zhang (SSPPS, UCSD)

• Ms. Clara Ng (Hunter, CUNY)

• Prof. Fiona Brinkman (Simon Fraser Univ.)• Dr. Shannan Ho Sui (Harvard University)

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IIS-1242451

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Thank You

lei.xie@hunter.cuny.edu

pbourne@ucsd.edu

http://www.sdsc.edu/pb/ - Drug Discovery Work

Funding: NIH