indications discovery and drug repurposing
DESCRIPTION
Slides for meeting to be held March 14th in Philadelphia - indications discovery and drug repurposingTRANSCRIPT
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In silico repositioning of approved drugs and collaboration for rare and neglected
diseases
Sean Ekins
Collaborations in Chemistry, Fuquay Varina, NC.Collaborative Drug Discovery, Burlingame, CA.
Department of Pharmacology, University of Medicine & Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, NJ.
School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland, Baltimore, MD.
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Abigail Alliance for Better Access to Developmental DrugsAddi & Cassi FundAmerican Behcet's Disease AssociationAmschwand Sarcoma Cancer Foundation BDSRA (Batten Disease Support and Research Association)Beyond Batten Disease FoundationBlake’s Purpose Foundation Breakthrough Cancer Coalition Canadian PKU & Allied DisordersCenter for Orphan Disease Research and Therapy, University of PennsylvaniaChildren’s Cardiomyopathy FoundationCooley's Anemia FoundationDani’s Foundation Drew’s Hope Research Foundation EveryLife Foundation for Rare DiseasesGIST Cancer Awareness FoundationHannah's Hope Fund Hope4Bridget FoundationHypertrophic Cardiomyopathy Association - HCMAI Have IIH ISRMD (International Society for Mannosidosis and Related Diseases)Jacob’s Cure Jain FoundationJonah's Just Begun-Foundation to Cure Sanfilippo Inc.Kids V CancerKurt+Peter FoundationLGMD2I Research FundLymphangiomatosis & Gorham's Disease Alliance MAGIC FoundationManton Center for Orphan Disease ResearchMarbleRoadMary Payton's Miracle Foundation Midwest Asian Health Association (MAHA)
MPD SupportNational Gaucher FoundationNational MPS SocietyNational Organization Against Rare Cancers National PKU AllianceNational Tay-Sachs & Allied Diseases AssociationNew Hope Research Foundation NextGEN Policy Noah's Hope - Batten disease research fundOur Promise to Nicholas Foundation Oxalosis and Hyperoxaluria FoundationPartnership for Cures Periodic Paralysis AssociationRARE ProjectRyan Foundation for MPS Children Sanfilippo Foundation for ChildrenSarcoma Foundation of AmericaSolving Kids' Cancer Taylor's Tale: Fighting Batten Disease Team Sanfilippo FoundationThe Alliance Against Alveolar Soft Part SarcomaThe Life Raft Group The NOMID AllianceThe Transverse Myelitis AssociationThe XLH Network, Inc.United Pompe Foundation
Many of these groups are doing R&D on a shoestring how can we help?
Just some of the many rare disease groups
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Jonah has Sanfilippo Syndrome
Jonah’s mum, Jill Wood started a foundation, raises money, awareness, funds ground breaking research happening globally. Willing to sell her house to fund research to save Jonah.
She is in a race against time – what can we do to translate ideas from bench to patient faster?
How do we get more ideas tested, who funds the research
How can we help parents and families ?
One example of why Pharmaceutical R&D needs disrupting
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How to do it better?
What can we do with software to facilitate it ?
The future is more collaborative
We have tools but need integration
• Groups involved traverse the spectrum from pharma, academia, not for profit and government
• More free, open technologies to enable biomedical research• Precompetitive organizations, consortia..• How can it help orphan and rare diseases?
A starting point is collaboration; software may help
A core root of the current inefficiencies in drug discovery are due to organizations’ and individual’s barriers to collaborate effectivelyBunin & Ekins DDT
16: 643-645, 2011
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Example ; Collaborative Drug Discovery Platform
• CDD Vault – Secure web-based place for private data – private by default
• CDD Collaborate – Selectively share subsets of data
• CDD Public –public data sets - Over 3 Million compounds, with molecular properties, similarity and substructure searching, data plotting etc
will host datasets from companies, foundations etc
vendor libraries (Asinex, TimTec, ChemBridge)
• Unique to CDD – simultaneously query your private data, collaborators’ data, & public data, Easy GUI
www.collaborativedrug.com
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3 Academia/ Govt lab – Industry screening partnerships
CDD used for data sharing / collaboration – along with cheminformatics expertise
Previously supported larger groups of labs – many continued as customers
How CDD software has been used: BMGF
CDD is a partner on a 5 year project supporting >20 labs and proving cheminformatics support www.mm4tb.org
More Medicines for Tuberculosis
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Ekins et al,Trends in Microbiology
19: 65-74, 2011
Fitting into the drug discoveryprocess
Insert your disease here…
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Searching for TB molecular mimics; collaboration
Lamichhane G, et al Mbio, 2: e00301-10, 2011
Modeling – CDDBiology – Johns HopkinsChemistry – Texas A&M
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Combining cheminformatics methods and pathway analysis Identified essential TB targets that had not been exploited Used resources available to both to identify targets and molecules that
mimic substrates Computationally searched >80,000 molecules - tested 23 compounds in
vitro (3 picked as inactives), lead to 2 proposed as mimics of D-fructose 1,6 bisphosphate, (MIC of 20 and 40 ug/ml)
POC took < 6mths - - Submitted phase II STTR, Submitted manuscript Still need to test vs target - verify hits vs suggested target
Ekins et al,Trends in Microbiology Feb 2011
Phase I STTR - NIAID funded collaboration with Stanford Research International
Sarker et al, submitted 2011
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Finding Promiscuous Old Drugs for New Uses
Research published in the last six years - 34 studies - Screened libraries of FDA approved drugs against various whole cell or target assays in vitro.
1 or more compounds with a suggested new bioactivity
13 drugs were active against more than one additional disease in vitro Perhaps screen these first?
Ekins and Williams, Pharm Res 28(8):1785-91, 2011
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Finding Promiscuous Old Drugs for New Uses
109 molecules were identified by screening in vitro
Statistically more hydrophobic (log P) and higher MWT 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.
Created multiple structure searchable databases in CDD This work was unfunded
Data for repurposing in publications is increasing but who is tracking it?
FDA databases for rare disease research are XL files!!
After this paper published NCGC released NPC browser….but
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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 ± 2.6 428.4 ± 202.8 5.4 ± 3.8 3.8 ± 1.9 2.0 ± 1.4 5.6 ± 4.2 2.0 ± 1.9 89.6 ± 69.3
Compounds identified in vitro with multiple new activities (N = 13)
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 79.5 ± 78.8
Orphan designated
products with at least one marketing
approval for a common disease
indication (N = 79) #
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 99.2 ± 110.7
Orphan designated
products with at least one marketing
approval for a rare disease
indication (N = 52) #
0.9 ± 3.3 b 344.4 ± 233.5 a
5.3 ± 5.3 2.4 ± 1.9 b
1.3 ± 1.4 a
6.2 ± 4.2 2.7 ± 2.8 114.2 ± 85.3
Ekins and Williams, Pharm Res 28(8):1785-91, 2011
Analysis of datasets
•Promiscuous repurposed compounds are more hydrophobic •orphan repurposed hits are less hydrophobic
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Dataset Intersection
Orphan +CommonUse
Orphan + Rare use
In vitro hits
0
53
0
Do these represent frequent actives or promiscuous compounds?
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Government Databases Should Come With a Health Warning
Openness Can Bring Serious Quality Issues
NPC Browser http://tripod.nih.gov/npc/Database released and within days 100’s of errors found in structures
Williams and Ekins, DDT, 16: 747-750 (2011)
Science Translational Medicine 2011
This work was unfunded
Science Translational Medicine 2011
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Substructure # of
Hits
# of
Correct
Hits
No
stereochemistry
Incomplete
Stereochemistry
Complete but
incorrect
stereochemistry
Gonane 34 5 8 21 0
Gon-4-ene 55 12 3 33 7
Gon-1,4-diene 60 17 10 23 10
Towards a Gold Standard: Regarding Quality in Public Domain Chemistry Databases and Approaches to Improving the Situation Antony J. Williams, Sean Ekins and Valery Tkachenko , Drug Discovery Today, In Press 2012
Data Errors in the NPC Browser: Analysis of Steroids
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http://www.slideshare.net/ekinsseanEkins S and Williams AJ, MedChemComm, 1: 325-330, 2010.
Need to learn from neglected disease research
Do we really need to screen massive libraries of compounds as we have for TB and malaria?
And groups are screening compounds already screened by others!
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2D Similarity search with “hit” from screening
Export database and use for 3D searching with a pharmacophore or other model
Suggest approved
drugs for testing - may also
indicate other uses if it is
present in more than one database
Suggest in silico hits for in vitro screening
Key databases of structures and bioactivity data FDA drugs
database
Repurpose FDA drugs in silico
Ekins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
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PXR antagonist drug discovery
Cancer drugs act as PXR agonists, increasing own metabolism and transport out of cells
How could we block this? Preferably find a clinically used drug?
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PXR Antagonist Pharmacophore Compounds can “switch off” PXR 3 azoles shown to antagonize PXR ~ equipotent (10-20M) mutagenesis
data indicates they bind outer surface of PXR – AF-2 binding pocket
Can a pharmacophore infer features needed to antagonize hPXR?
Ekins et al., Mol Pharmacol 72:592–603, (2007)
Huang et al., Oncogene 26: 258-268 (2007), Wang et al., Clin Cancer Res 13: 2488-2495
Hydrophobe / ring aromatic
H-bond acceptors
Antagonists require a balance between hydrophobic and hydrogen bonding features.
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PXR Antagonist Binding Site/s - Docking
Ekins et al., Mol Pharmacol 72:592–603, (2007)
2 separate binding sites on either side of Lys277- identified with GOLD rigid docking in 1NRL chain A
azoles would interfere with SRC-1 binding in the AF-2 site. One site is predominantly hydrophobic -15 amino acids.
Lys277 most likely serves as a “charge clamp” for interaction between the co-activator SRC1 (His687) and PXR
Azoles compete with SRC-1 for AF-2
Piperazine etc may not be necessary- Solvent exposed
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Screened four databases – known drugs and commercially available molecules, N = 3533
67 hits retrieved We tested in vitro a small number based on
their pharmacophore fit values and mapping to the pharmacophore features
Followed up hits with similarity searching using ChemSpider.com, emolecules.com
PXR Antagonist Database Searching
Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
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SPB00574 2.14 24.8
SPB03255 2.22 6.3
Catalyst fit IC50 (M)
PXR Antagonist Database Searching Finds New Hits
Further similarity searching retrieved 4 active analogs of SPB03255 Also tested leflunomide – FDA approved drug
O
N
O
NH
FF
F 6.8 M
Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
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We can do the same for rare diseases: Searching for Potential Chaperones for Sanfilippo Syndrome
Pshezhetsky et al showed Glucosamine rescues HGSNAT mutants
Glucosamine used to create a 3D common features pharmacophore using Discovery Studio.
The pharmacophore + ligand van der Waals shape was used to search multiple 3D databases
FDA drugs, natural products, orphan drugs, KEGG, CSF metabolome etc.
The pharmacophore consists of a positive ionizable (red) and 3 hydrogen bond donor groups (purple).
Selected hits for experimental testing Collaboration ongoing!
e.g. Isofagomine maps pharmacophore
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Crowdsourcing Project “Off the Shelf R&D”
All pharmas have assets on shelf that reached clinic
“Off the Shelf R&D”
Get the crowd to help in repurposing / repositioning these assets
How can software help?
- Create communities to test
- Provide informatics tools that are accessible to the crowd - enlarge user base
- Data storage on cloud – integration with public data
- Crowd becomes virtual pharma-CROs and the “customer” for enabling services
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LundbeckPfizer
Merck
GSKNovartis
Lilly
BMS
AllerganBayer
AZ
Roche BI
Merk KGaA
Massive models – using open tools
Gupta RR, et al., Drug Metab Dispos, 38: 2083-2090, 2010
CDK +fragment descriptors MOE 2D +fragment descriptorsKappa 0.65 0.67
sensitivity 0.86 0.86specificity 0.78 0.8
PPV 0.84 0.84
Can we get pharmas to share models rather than data – precompetitive?
What can be developed with very large training and test sets?training 194,000 and testing 39,000
Open molecular descriptors / models vs commercial descriptors
Potential to share models selectively with collaborators e.g. academics, rare & neglected disease researchers
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Future Drug Discovery
Pharma R&D already looking like this – a big network
I think we are seeing something like this with all the orphan disease networks too
Massive collaboration networks – software enabled. We are in “Generation App”
Crowdsourcing will have a role in R&D. Drug discovery possible by anyone with “app access”
Ekins & Williams, Pharm Res, 27: 393-395, 2010.
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•Make science more accessible = >communication
•Mobile – take a phone into field /lab and do science more readily than on a laptop
•MolSync + DropBox + MMDS = Share molecules as SDF files on the cloud = collaborate
•How could orphan disease research leverage apps?
Mobile Apps for Drug Discovery
Williams et al DDT 16:928-939, 2011
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Apps for collaborationODDT – Open drug discovery teamsFlipboard-like app for aggregating social media for diseases etcCreate virtual drug discovery teams link to open notebook science
Alex Clark, Molecular Materials Informatics, Inc
Williams et al DDT 16:928-939, 2011Clark et al submitted 2012Ekins et al submitted 2012
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Evolving paradigm for the discovery of medicines (Collaborative) A vision that points towards open innovation and collaborations Open research model to collectively share scientific expertise
Enhance speed of drug discovery beyond individual resource capabilities (Speed) Limited research budgets and capabilities driving greater shared resources Goal to see all partners succeed by accelerating the SCIENCE Synergize Pfizer’s strengths with Research Partners (Knowledge) Pair Pfizer’s design, cutting edge tools, synthetic excellence with research partners (academics, not-for-profits,
venture capitalists, or biotechs) to develop break through science, novel targets, and indications of unmet medical need
Current example of academic and not-for-profits partners (Discover and Publish) Drive to publish in top journal with science receiving high visibility and interest
Body clock mouse study suggests new drug potentialMon, Aug 23 2010By Kate KellandLONDON (Reuters) - Scientists have used experimental drugs being developed by Pfizer to reset and restart the body clock of mice in a lab and say their work may offer clues on a range of human disorders, from jetlag to bipolar disorder.
Contacts: Travis Wager ([email protected]) Paul Galatsis ([email protected])
a few months ago we entered into a collaboration with the giant pharmaceutical industry Pfizer to test some of their leading molecules for potential relevance to HD.
The Evolving Pfizer R&D EcosystemFound on the internet http://dl.dropbox.com/u/14511423/VRU.pptx
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The newest drug discovery reality
Gone full circle
Pharma now becoming more like rare disease groups
Working on a shoestring, limited resources, leverages academics, partners with disease foundations, funded by them – open innovation
Collaboration is a core element
If Jill Wood or others can become a virtual pharma, if they have enough domain knowledge and drive
Pfizer and other pharmas can be more like Jill, smaller, leaner, working on many more diseases as collaborators
In silico approaches and collaboration = central to rare disease drug discovery
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Acknowledgments Jill Wood Antony J. Williams (RSC) Rishi Gupta, Eric Gifford, Ted Liston, Chris Waller (Pfizer) Joel Freundlich (Texas A&M), Gyanu Lamichhane (Johns
Hopkins) Carolyn Talcott, Malabika Sarker, Peter Madrid, Sidharth
Chopra (SRI International) MM4TB colleagues Matthew D. Krasowski (University of Iowa) Sridhar Mani (Albert Einstein College of Medicine) Alex Clark (Molecular Materials Informatics, Inc) Vladyslav Kholodovych, Ni Ai, Dima Chekmarev, Sandhya
Kortagere, Chia-Wei Li, J Don Chen, William J. Welsh (UMDNJ)
Accelrys CDD – Barry Bunin Funding BMGF, NIAID. Everyone that has shared data in CDD..
Email: [email protected] Slideshare: http://www.slideshare.net/ekinssean Twitter: collabchem Blog: http://www.collabchem.com/ Website: http://www.collaborations.com/CHEMISTRY.HTM