In silico repositioning of approved drugsand 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.
Just some of the many rare disease groupsAbigail Alliance for Better Access to Developmental Drugs MPD SupportAddi & Cassi Fund National Gaucher FoundationAmerican Behcets Disease Association National MPS SocietyAmschwand Sarcoma Cancer Foundation National Organization Against Rare CancersBDSRA (Batten Disease Support and Research Association) National PKU AllianceBeyond Batten Disease Foundation National Tay-Sachs & Allied Diseases AssociationBlake’s Purpose Foundation New Hope Research FoundationBreakthrough Cancer Coalition NextGEN PolicyCanadian PKU & Allied Disorders Noahs Hope - Batten disease research fundCenter for Orphan Disease Research and Therapy, University of Our Promise to Nicholas FoundationPennsylvania Oxalosis and Hyperoxaluria FoundationChildren’s Cardiomyopathy Foundation Partnership for CuresCooleys Anemia Foundation Periodic Paralysis AssociationDani’s Foundation RARE Project Ryan Foundation for MPS ChildrenDrew’s Hope Research Foundation Sanfilippo Foundation for ChildrenEveryLife Foundation for Rare Diseases Sarcoma Foundation of AmericaGIST Cancer Awareness Foundation Solving Kids CancerHannahs Hope Fund Taylors Tale: Fighting Batten DiseaseHope4Bridget Foundation Team Sanfilippo FoundationHypertrophic Cardiomyopathy Association - HCMA The Alliance Against Alveolar Soft Part SarcomaI Have IIH The Life Raft GroupISRMD (International Society for Mannosidosis and Related Diseases) The NOMID AllianceJacob’s Cure The Transverse Myelitis AssociationJain Foundation The XLH Network, Inc.Jonahs Just Begun-Foundation to Cure Sanfilippo Inc. United Pompe FoundationKids V CancerKurt+Peter FoundationLGMD2I Research FundLymphangiomatosis & Gorhams Disease AllianceMAGIC Foundation Many of these groups areManton Center for Orphan Disease ResearchMarbleRoad doing R&D on a shoestring howMary Paytons Miracle FoundationMidwest Asian Health Association (MAHA) can we help?
One example of why Pharmaceutical R&D needs disruptingJonah has Sanfilippo SyndromeJonah’s mum, Jill Wood started a foundation, raises money, awareness, funds ground breakingresearch 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 researchHow can we help parents and families ?
A starting point is collaboration; software may helpHow to doit better?What can wedo withsoftware to A core root of the current inefficiencies infacilitate it ? drug discovery are due to organizations’ and individual’s barriers to collaborate effectively We have tools Bunin & Ekins DDT but need 16: 643-645, 2011 integration The future is more collaborative• 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?
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 GUIwww.collaborativedrug.com
How CDD software has been used: BMGF 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 More Medicines for TuberculosisCDD is a partner on a 5 year project supporting >20 labs and proving cheminformaticssupport www.mm4tb.org
Fitting into the drug discovery process Insert your disease here…Ekins et al,Trends inMicrobiology19: 65-74, 2011
Searching for TB molecular mimics; collaboration Modeling – CDD Biology – Johns Hopkins Chemistry – Texas A&MLamichhane G, et al Mbio, 2: e00301-10, 2011
Phase I STTR - NIAID funded collaboration with Stanford Research International 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 Sarker et al, submitted 2011
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
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
Analysis of datasets Dataset ALogP Molecular Number of Number of Number of Number of Number of Molecular Polar Weight Rotatable Rings Aromatic Hydrogen Hydrogen Surface Area Bonds Rings bond bond Acceptors Donors Compounds 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 identified in vitro with new activities (N = 109) * Compounds 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 identified in vitro with multiple new activities (N = 13) Orphan 1.4 ± 3.0 b 353.2 ± 218.8 5.3 ± 6.4 2.8 ± 1.7 1.2 ± 1.3 5.3 ± 6.0 2.5 ± 3.0 99.2 ± 110.7 designated a a b products with at least one marketing approval for a common disease indication (N = 79) # Orphan 0.9 ± 3.3 b 344.4 ± 233.5 5.3 ± 5.3 2.4 ± 1.9 1.3 ± 1.4 6.2 ± 4.2 2.7 ± 2.8 114.2 ± 85.3 designated a b a products with at least one marketing approval for a rare disease indication (N = 52) # •Promiscuous repurposed compounds are more hydrophobic •orphan repurposed hits are less hydrophobicEkins and Williams, Pharm Res 28(8):1785-91, 2011
Dataset Intersection Orphan + Common Orphan + Use 0 Rare use 0 3 5 In vitro hitsDo these represent frequentactives or promiscuouscompounds?
Government Databases Should Come With a Health Warning Openness Can Bring Serious Quality IssuesDatabase released and within days 100’s of errors found in structures Science Translational Medicine 2011 NPC Browser http://tripod.nih.gov/npc/ Science Translational Medicine 2011 Williams and Ekins, This work was unfunded DDT, 16: 747-750 (2011)
Data Errors in the NPC Browser: Analysis of Steroids Substructure # of # of No Incomplete Complete but Hits Correct stereochemistry Stereochemistry incorrect Hits stereochemistry Gonane 34 5 8 21 0 Gon-4-ene 55 12 3 33 7 Gon-1,4-diene 60 17 10 23 10Towards a Gold Standard: Regarding Quality in Public Domain Chemistry Databases and Approaches to Improvingthe Situation Antony J. Williams, Sean Ekins and Valery Tkachenko, Drug Discovery Today, In Press 2012
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! Ekins S and Williams AJ, MedChemComm,http://www.slideshare.net/ekinssean 1: 325-330, 2010.
Repurpose FDA drugs in silico Key databases of structures and 2D Similarity search with “hit” bioactivity data FDA drugs from screening database Export database and Suggest use for 3D searching approved with a pharmacophore drugs for testing or other model - may also indicate other uses if it is present in more than one database Suggest in silico hits for in vitro screeningEkins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
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?
PXR Antagonist Pharmacophore Compounds can “switch off” PXR 3 azoles shown to antagonize PXR ~ equipotent (10-20µM) mutagenesis data indicates they bind outer surface of PXR – AF-2 binding pocket Huang et al., Oncogene 26: 258-268 (2007), Wang et al., Clin Cancer Res 13: 2488-2495 Can a pharmacophore infer features needed to antagonize hPXR? H-bond acceptors Hydrophobe / ring aromatic Antagonists require a balance between hydrophobic and hydrogen bonding features. Ekins et al., Mol Pharmacol 72:592–603, (2007)
PXR Antagonist Binding Site/s - Docking2 separate binding sites on either side of Lys277- identified with GOLDrigid docking in 1NRL chain Aazoles would interfere with SRC-1 binding in the AF-2 site. One site ispredominantly hydrophobic -15 amino acids.Lys277 most likely serves as a “charge clamp” for interaction betweenthe co-activator SRC1 (His687) and PXRAzoles compete with SRC-1 for AF-2 Piperazine etc may not be necessary - Solvent exposed Ekins et al., Mol Pharmacol 72:592–603, (2007)
PXR Antagonist Database Searching 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 Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
PXR Antagonist Database Searching Finds New Hits Catalyst fit IC50 (µM) SPB00574 2.14 24.8 SPB03255 2.22 6.3Further similarity searching retrieved 4 active analogs of SPB03255Also tested leflunomide – FDA approved drug F F 6.8 µM O F N O H N Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
We can do the same for rare diseases: Searching forPotential 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
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
Massive models – using open tools Allergan Bayer Merk KGaA CDK +fragment descriptors Merck MOE 2D +fragment descriptors Lilly Kappa 0.65 0.67 Pfizersensitivity 0.86 0.86 Lundspecificity 0.78 0.8 Roche BI PPV 0.84 0.84 Novartis GSK AZ BMS 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 Gupta RR, et al., Drug Metab Dispos, 38: 2083-2090, 2010
Future Drug DiscoveryPharma R&D already looking like this – a bignetworkI think we are seeing something like this with allthe orphan disease networks tooMassive collaboration networks – softwareenabled. We are in “Generation App”Crowdsourcing will have a role in R&D. Drugdiscovery possible by anyone with “app access” Ekins & Williams, Pharm Res, 27: 393-395, 2010.
Mobile Apps for Drug Discovery•Make science more accessible =>communication•Mobile – take a phone into field /lab anddo science more readily than on a laptop•MolSync + DropBox + MMDS = Sharemolecules as SDF files on the cloud =collaborate•How could orphan disease researchleverage apps? Williams et al DDT 16:928-939, 2011
Apps for collaboration ODDT – Open drug discovery teams Flipboard-like app for aggregating social media for diseases etc Create virtual drug discovery teams link to open notebook scienceAlex Clark, Molecular Materials Informatics, Inc Williams et al DDT 16:928-939, 2011 Clark et al submitted 2012 Ekins et al submitted 2012
Found on the internet http://dl.dropbox.com/u/14511423/VRU.pptx The Evolving Pfizer R&D Ecosystem 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 potential Mon, Aug 23 2010 By Kate Kelland LONDON (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. 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.Contacts: Travis Wager (firstname.lastname@example.org) Paul Galatsis (email@example.com)
The newest drug discovery realityGone full circlePharma now becoming more like rare disease groupsWorking on a shoestring, limited resources, leverages academics,partners with disease foundations, funded by them – open innovationCollaboration is a core elementIf Jill Wood or others can become a virtual pharma, if they have enoughdomain knowledge and drivePfizer and other pharmas can be more like Jill, smaller, leaner, workingon many more diseases as collaboratorsIn silico approaches and collaboration = central to rare disease drugdiscovery
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: firstname.lastname@example.org Slideshare: http://www.slideshare.net/ekinssean Twitter: collabchem Blog: http://www.collabchem.com/ Website: http://www.collaborations.com/CHEMISTRY.HTM