The document discusses using collaborative drug discovery software and databases to facilitate drug repositioning efforts for rare and neglected diseases. It provides an example of how the Collaborative Drug Discovery platform was used to share data and enable screening partnerships between multiple academic and industry groups working on tuberculosis. The document also summarizes research that identified over 100 molecules by screening approved drugs for new activities in vitro, finding some drugs with potential activity against multiple diseases. This highlights opportunities for drug repositioning but challenges of data sharing that collaborative platforms could help address.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
Mike generously is sharing this slide set which he presented at the 250th meeting of the ACS 2015 so that others who think they can not afford to run drug discovery can consider this economical distributed, virtual model….and to see CDD Vault in action.
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
A presentation outlining the various processes a chemical compound undergoes (thorough & rigorous screening procedures) before it is finally introduced into the drug market
Mike generously is sharing this slide set which he presented at the 250th meeting of the ACS 2015 so that others who think they can not afford to run drug discovery can consider this economical distributed, virtual model….and to see CDD Vault in action.
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
A presentation outlining the various processes a chemical compound undergoes (thorough & rigorous screening procedures) before it is finally introduced into the drug market
In the last 6 years high-throughput screening has been used to identify FDA approved drugs that are active against multiple targets (also termed promiscuity). We have identified 34 studies that have screened libraries of FDA approved drugs against various whole cell or target assays. Each study has identified one or more compound with a new bioactivity that had not been previously described. Thirteen of these drugs were active against more than one additional disease, thereby suggesting a degree of promiscuity. The 109 molecules identified by screening in vitro were statistically more hydrophobic than orphan designated products with at least one marketing approval for a common disease indication or one marketing approval for a rare disease (FDA rare disease research database). We have created a database of in vitro data on old drugs for new uses that could be applied for repositioning these or other molecules for neglected and rare diseases.
Growing Stronger Research Fund Overview Jan 2012 For DonorsAmer Haider
Website: http://www.growingstroner.org.
Overview of http://www.GrowingStronger.org, a non-profit focused on improving the quality of life of little people through supporting medical research.
5 years of “Rare” Progress Research: Cheryl Rockman-Greenberg, Max Rady College of Medicine, University of Manitoba
Rare Disease Day Conference 2020 March 9-10
Why there needs to be open data for ultra-rare and rare disease drug discoverySean Ekins
ACS presentation 11th Aug San Francisco on the need for open data in ultra rare and rare diseases. Describes efforts of parent/ patient advocates to fund drug discovery research. Also it describes software for open collaboration and what needs to be done to create software champions for rare diseases. Mentions diseases like Sanfilippo Syndrome, giant axonal neuropathy and Charcot Marie Tooth. Apps like ODDT are also mentioned as a means to share data.
I will discuss the formation and subsequent growth of IRDiRC into an organization with nearly 40 public and private funder members who have collectively pledged over 1 billion euros for rare disease research. I will also present the goals of IRDiRC, the plan that has been developed to achieve them, and the progress that has been made thus far. Finally, I will explore how additional organizations can take part in this international collaborative effort
Presentation from AAPS PharmSci360 (October 23, 2023) in which I describe highlights of my Springer/AAPS book Winning Grants (https://link.springer.com/book/10.1007/978-3-031-27516-6) - presenting a 'how to' guide on writing small business grants - e.g. NIH STTR and SBIR grants. Written by someone experienced in winning such grants.
Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic To...Sean Ekins
The presentation was given at SETAC 2022 Nov 16 and describes our work on Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic Toxicity.
We generated many models that are available to license in our MegaTox software. We found that the support vector machines performed the best after assessing many algorithms for both classification and regression models.
The authors of this work are Thomas R Lane, Fabio Urbina and Sean Ekins.
The contact is sean@collaborationspharma.com
A presentation at the Global Genes rare drug development symposium on governm...Sean Ekins
This presentation from June 12 2020 gives a brief overview of my experience of 15 years of applying for government grants to fund small companies. Prior to this I had no experience of applying for such grants. The bottom line for rare disease groups / families is find a scientist that can do this or assist you. please also see www.collaborationspharma.com
Leveraging Science Communication and Social Media to Build Your Brand and Ele...Sean Ekins
Slides from AAPS Careers session by Maren Katherina Preis, Kyle Bagin, Sean Ekins
Provides some clear steps on how you could use social media to help your career.
Oral presentation given in MEDI session at 2017 ACS in DC.
co-authors Kimberley M. Zorn, Mary A. Lingerfelt, Jair L. de Siqueira-Neto, Alex M. Clark, Sean Ekins
describes drug repurposing and machine learning - for more details see www.collaborationspharma.com
Assay Central: A New Approach to Compiling Big Data and Preparing Machine Lea...Sean Ekins
Oral presentation at 2017 ACS in DC - given by Kimberley Zorn
co-authors include Mary A. Lingerfelt, Alex M. Clark, Sean Ekins
for more details see www.collaborationspharma.com
Five Ways to Use Social Media to Raise Awareness for Your Paper or ResearchSean Ekins
Presentation given at the AAPS 2016 conference in Denver. Some of the slides are from AAPS, Some from Kudos and some from Figshare. One slide is from Tony Williams. All slides used with permission.
CDD: Vault, CDD: Vision and CDD: Models software for biologists and chemists ...Sean Ekins
A perspective on 12 yrs of CDD and developing products and collaborations.
A presentation given at the ACS meeting in San Diego - small business section
This presentation summarizes some early efforts on an open drug discovery collaboration between scientists in Brazil and the US. The amazing virus images were created by John Liebler and can be licensed from him http://www.artofthecell.com/animation/will-the-real-zika-virus-please-stand-up
The homology models were created with Swiss Model by Sean Ekins:
Marco Biasini, Stefan Bienert, Andrew Waterhouse, Konstantin Arnold, Gabriel Studer, Tobias Schmidt, Florian Kiefer, Tiziano Gallo Cassarino, Martino Bertoni, Lorenza Bordoli, Torsten Schwede. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Research; (1 July 2014) 42 (W1): W252-W258; doi: 10.1093/nar/gku340.
Arnold K., Bordoli L., Kopp J., and Schwede T. (2006). The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics, 22,195-201.
Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T (2009). The SWISS-MODEL Repository and associated resources. Nucleic Acids Research. 37, D387-D392.
Guex, N., Peitsch, M.C., Schwede, T. (2009). Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis, 30(S1), S162-S173.
Ensuring Chemical Structure, Biological Data and Computational Model Quality
A talk given at SLAS 2016 mon Jan 25th in San Diego
covers published work and recent forays with BIA 10-2474
Pros and cons of social networking for scientistsSean Ekins
Over the past 4 years I have been using social networking tools for scientists more inspired by Antony Williams. I realized I am using many tools and there are pros and cons of them. Here is my brief summary.
CDD: Vault, CDD: Vision and CDD: Models for Drug Discovery CollaborationsSean Ekins
A talk given at SERMACS 7th Nov 2015 in Memphis, describes CDD Vault, CDD Vision and CDD Models. In addition it also describes how the software is used in large and smaller scale collaborations for drug discovery.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
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- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
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Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
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ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Indications discovery and drug repurposing
1. 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.
2. Just some of the many rare disease groups
Abigail Alliance for Better Access to Developmental Drugs MPD Support
Addi & Cassi Fund National Gaucher Foundation
American Behcet's Disease Association National MPS Society
Amschwand Sarcoma Cancer Foundation National Organization Against Rare Cancers
BDSRA (Batten Disease Support and Research Association) National PKU Alliance
Beyond Batten Disease Foundation National Tay-Sachs & Allied Diseases Association
Blake’s Purpose Foundation New Hope Research Foundation
Breakthrough Cancer Coalition NextGEN Policy
Canadian PKU & Allied Disorders Noah's Hope - Batten disease research fund
Center for Orphan Disease Research and Therapy, University of Our Promise to Nicholas Foundation
Pennsylvania Oxalosis and Hyperoxaluria Foundation
Children’s Cardiomyopathy Foundation Partnership for Cures
Cooley's Anemia Foundation Periodic Paralysis Association
Dani’s Foundation RARE Project
Ryan Foundation for MPS Children
Drew’s Hope Research Foundation Sanfilippo Foundation for Children
EveryLife Foundation for Rare Diseases Sarcoma Foundation of America
GIST Cancer Awareness Foundation Solving Kids' Cancer
Hannah's Hope Fund Taylor's Tale: Fighting Batten Disease
Hope4Bridget Foundation Team Sanfilippo Foundation
Hypertrophic Cardiomyopathy Association - HCMA The Alliance Against Alveolar Soft Part Sarcoma
I Have IIH The Life Raft Group
ISRMD (International Society for Mannosidosis and Related Diseases) The NOMID Alliance
Jacob’s Cure The Transverse Myelitis Association
Jain Foundation The XLH Network, Inc.
Jonah's Just Begun-Foundation to Cure Sanfilippo Inc. United Pompe Foundation
Kids V Cancer
Kurt+Peter Foundation
LGMD2I Research Fund
Lymphangiomatosis & Gorham's Disease Alliance
MAGIC Foundation
Many of these groups are
Manton Center for Orphan Disease Research
MarbleRoad doing R&D on a shoestring how
Mary Payton's Miracle Foundation
Midwest Asian Health Association (MAHA) can we help?
3. One example of why Pharmaceutical R&D needs disrupting
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 ?
4. A starting point is collaboration; software may help
How to do
it better?
What can we
do with
software to A core root of the
current inefficiencies in
facilitate 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?
5. 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
6. 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 Tuberculosis
CDD is a partner on a 5 year project supporting >20 labs and proving cheminformatics
support www.mm4tb.org
7. Fitting into the drug discovery
process
Insert your disease here…
Ekins et al,
Trends in
Microbiology
19: 65-74, 2011
8. Searching for TB molecular mimics; collaboration
Modeling – CDD
Biology – Johns Hopkins
Chemistry – Texas A&M
Lamichhane G, et al Mbio, 2: e00301-10, 2011
9. 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
10. 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
11. 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
12. 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 hydrophobic
Ekins and Williams, Pharm Res 28(8):1785-91, 2011
13. Dataset Intersection
Orphan +
Common Orphan +
Use 0 Rare use
0
3 5
In vitro hits
Do these represent frequent
actives or promiscuous
compounds?
14. Government Databases Should Come With a Health Warning
Openness Can Bring Serious Quality Issues
Database 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)
15. 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 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
16. 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.
17. 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 screening
Ekins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
18. 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?
19. 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)
20. PXR Antagonist Binding Site/s - Docking
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
Ekins et al., Mol Pharmacol 72:592–603, (2007)
21. 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)
22. PXR Antagonist Database Searching Finds New Hits
Catalyst fit IC50 (µM)
SPB00574 2.14 24.8
SPB03255 2.22 6.3
Further similarity searching retrieved 4 active analogs of SPB03255
Also 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)
23. 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
24. 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
25. Massive models – using open tools
Allergan
Bayer
Merk KGaA
CDK +fragment descriptors
Merck
MOE 2D +fragment descriptors
Lilly
Kappa 0.65 0.67 Pfizer
sensitivity 0.86 0.86 Lund
specificity 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
26. 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.
27. Mobile Apps for Drug Discovery
•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?
Williams et al DDT 16:928-939, 2011
28. 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 science
Alex Clark, Molecular Materials Informatics, Inc
Williams et al DDT 16:928-939, 2011
Clark et al submitted 2012
Ekins et al submitted 2012
29. 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 (travis.t.wager@pfizer.com)
Paul Galatsis (paul.galatsis@pfizer.com)
30. 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
31. 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: ekinssean@yahoo.com
Slideshare: http://www.slideshare.net/ekinssean
Twitter: collabchem
Blog: http://www.collabchem.com/
Website: http://www.collaborations.com/CHEMISTRY.HTM
Editor's Notes
CDD Experienced Team Innovates and Executes Barry Bunin, PhD (Pres. & Cofounder as first Eli Lilly EIR) Libraria (CEO, Pres.-CSO), Arris Pharmaceuticals (Sr. Scientist), Genentech, UC Berkeley (Ellman), Columbia University, author. Moses Hohman, PhD (Director Software Engineering) Northwestern Assoc. Director of Bioinformatics, Thoughtworks, Inc., U of Chicago (PhD), Harvard ( magna cum laude, Physics) Sylvia Ernst, PhD (Director Community Growth & Sales) Left 800-lb Gorillas: Accelrys-Scitegic, MDL-Elsevier-Beilstein Peter Cohan (BOD & Overall Sales Strategy) Symyx (VP Bus Dev & President-Discovery Tools), MDL (VP Customer Marketing), www.secondderivative.com, author. Omidyar Network, Founders Fund, & Lilly (BOD observers) WSGR (Corporate Counsel), Rina Accountancy (GAAP compliance) Partners: Hub Consortium Members, ChemAxon, DNDi, MMV, Sandler Center… CDD SAB: Christopher Lipinski PhD, James McKerrow, MD PhD, David Roos PhD, Adam Renslo PhD, Wes Van Voorhis, MD PhD
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CDD Experienced Team Innovates and Executes Barry Bunin, PhD (Pres. & Cofounder as first Eli Lilly EIR) Libraria (CEO, Pres.-CSO), Arris Pharmaceuticals (Sr. Scientist), Genentech, UC Berkeley (Ellman), Columbia University, author. Moses Hohman, PhD (Director Software Engineering) Northwestern Assoc. Director of Bioinformatics, Thoughtworks, Inc., U of Chicago (PhD), Harvard ( magna cum laude, Physics) Sylvia Ernst, PhD (Director Community Growth & Sales) Left 800-lb Gorillas: Accelrys-Scitegic, MDL-Elsevier-Beilstein Peter Cohan (BOD & Overall Sales Strategy) Symyx (VP Bus Dev & President-Discovery Tools), MDL (VP Customer Marketing), www.secondderivative.com, author. Omidyar Network, Founders Fund, & Lilly (BOD observers) WSGR (Corporate Counsel), Rina Accountancy (GAAP compliance) Partners: Hub Consortium Members, ChemAxon, DNDi, MMV, Sandler Center… CDD SAB: Christopher Lipinski PhD, James McKerrow, MD PhD, David Roos PhD, Adam Renslo PhD, Wes Van Voorhis, MD PhD
CDD Experienced Team Innovates and Executes Barry Bunin, PhD (Pres. & Cofounder as first Eli Lilly EIR) Libraria (CEO, Pres.-CSO), Arris Pharmaceuticals (Sr. Scientist), Genentech, UC Berkeley (Ellman), Columbia University, author. Moses Hohman, PhD (Director Software Engineering) Northwestern Assoc. Director of Bioinformatics, Thoughtworks, Inc., U of Chicago (PhD), Harvard ( magna cum laude, Physics) Sylvia Ernst, PhD (Director Community Growth & Sales) Left 800-lb Gorillas: Accelrys-Scitegic, MDL-Elsevier-Beilstein Peter Cohan (BOD & Overall Sales Strategy) Symyx (VP Bus Dev & President-Discovery Tools), MDL (VP Customer Marketing), www.secondderivative.com, author. Omidyar Network, Founders Fund, & Lilly (BOD observers) WSGR (Corporate Counsel), Rina Accountancy (GAAP compliance) Partners: Hub Consortium Members, ChemAxon, DNDi, MMV, Sandler Center… CDD SAB: Christopher Lipinski PhD, James McKerrow, MD PhD, David Roos PhD, Adam Renslo PhD, Wes Van Voorhis, MD PhD
Added 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”