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Applying Royal Society of Chemistry
Cheminformatics Skills to Support
the PharmaSea Project
Antony Williams, Alexey Pshenichnov, Valery
Tkachenko, Ken Karapetyan, David Sharpe
ACS San Francisco
August 2014
Cancer Deaths Worldwide
Top Treatments for Cancer
• Over half of all drugs introduced between
1940 and 2006 were of natural origin or
inspired by natural compounds
Importance of Natural Products
Natural Products for all of us!
We Are Doomed I Tell You!!!
We Are Doomed I Tell You!!!
The Dangers of Algal Blooms!
Nature’s Little Pharmacy
O
O
O
O
O
O
O
O
O
O
O
O
O
CH2
CH3
OH
CH3
CH3
CH3
CH3
CH3
CH3
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
We Are Doomed I Tell You!!!
Antibiotic resistance
Discovery Curve Decay
RSC and Natural Products
Focus on Marine Natural Products
• RSC cheminformatics support to include:
• Deliver “PharmaSea website”
• Provide access to natural products subset
• Develop “dereplication techniques”
• Searching NMR features against database
• Develop advanced searches for MS data
• Host Open Data from the PharmaSea project
and make available to the community
http://www.pharma-sea.eu/
The PharmaSea Website
• RSC is open-sourcing a chemical registry
system as a result of Open PHACTS
• Chemical Registry system used to underpin
the PharmaSea website – behind login
• Will be enhanced with data deposition
capabilities and “dereplication”
The PharmaSea Website
The PharmaSea Website
The PharmaSea Website
New Repository Architecture
doi: 10.1007/s10822-014-9784-5
New Repository Architecture
Compounds Reactions Spectra Materials Documents
Compounds
API
Reactions
API
Spectra
API
Materials
API
Documents
API
Compounds
Widgets
Reactions
Widgets
Spectra
Widgets
Materials
Widgets
Documents
Widgets
Data tier
Data access
tier
User
interface
components
tier
Analytical Laboratory application
User
interface tier
(examples) Electronic Laboratory Notebook
Paid 3rd
party integrations (various platforms – SharePoint, Google, etc)
Chemical Inventory application
Compounds
Reactions
Analytical data
Crystallography data
Deposition of Data
Extending PharmaSea Site
• PharmaSea website will be extended
• Spectral data handling: Support Dereplication
Identifying novel compounds
• Compounds are collected from the ocean
• Extraction via chromatography
• Analytical sciences including:
• UV-Vis data (Lambda-max)
• Mass spectrometry (formula/mass)
• NMR spectroscopy (HNMR/2D)
• Utilized for dereplication,,,
Is this already known or not??
4 Me singlets
4 Me doublets
1 OMe singlet
Aromatic protons
Identifying novel compounds
Identifying novel compounds
2D NMR data will give details
regarding substitutions and
this information can be used in
the dereplication process
What we need is…
• If we could have:
• A DB containing known marine natural products
• This would give formula and mass for searching
• The DB has all spectral data available for each
compound
• If experimental data are not available then use
the compound to COMPUTE spectral features
RSC Acquires Marinlit
• All Marinlit chemical compounds in ChemSpider
• Marinlit developers are dereplication experts
• Index literature related to marine natural
products: 26K articles and growing
• Structure searchable database
• Data includes taxonomy, location and literature
• “Spectral features” generated algorithmically
• Utilize the spectral features for dereplication
PharmaSea Dereplication
• Work in progress:
• Produce “dereplication widget” to embed in
the PharmaSea website
• Generate “structure features” file for every
new compound deposited to PharmaSea
• Ideal would be to utilize spectral data directly
to elucidate structures – “Computer Assisted
Structure Elucidation”. ACD/Labs….
CASE-based Elucidation
• Computers can elucidate structures today
with greater efficiency and success than
many scientists – see Patrick Wheeler’s talk
• Natural products specifically can be very
challenging and CASE is well-proven
• ACD/Labs have delivered their CASE-
system (ACD/Structure Eludicator) to the
project
1D & 2D NMR Synchronized
Processing
The Software displays correlations for assigned spectra and structures, and highlights
correlations that are likely to be erroneous.
ChemSpider supporting CASE
RSC delivered entire ChemSpider structure dataset
for inclusion into the Structure Elucidator software.
CASE vs Microscopy?
DOI: 10.1002/anie.201203960
Single Molecule AFM
CASE vs Microscopy?
DOI: 10.1002/anie.201203960
Next:Tagging Natural Products
Next:Tagging Natural Products
Next:Tagging Natural Products
Next:Tagging Natural Products
Future Plans
• Roll out tagging on ChemSpider to crowdsource
marine natural products subset
• Implement tagging for further details onto
PharmaSea website
• Collaborate with other natural product sources
• Mass spectrometry fragmentation prediction
Future Plans – MS Fragmenter
Future Plans – MS Fragmenter
Future Plans
Modern NMR Approaches To The Structure Elucidation
of Natural Products
Volume 1: Instrumentation and Software
Volume 2: Data Acquisition and Applications to Compound
Classes
Edited by Antony Williams, RSC, Gary Martin, Merck and
David Rovnyak, Bucknell University
To be published: 2015 (RSC)
To be published: 2015 (Springer)
Computer-based Structure Elucidation from
Spectral Data
Will include a functional demo version of the
ACD/Structure Elucidator software to teach the
basic approaches to computer-assisted structure
elucidation
Authored by Mikhail Elyashberg, Kirill Blinov and
Antony Williams
Acknowledgments
• Alexey Pshenichnov, Ken Karapapetyan and
Valery Tkachenko (RSC – US Cheminformatics)
• Marcel Jaspars (University of Aberdeen)
• John Blunt and Murray Munro (Marinlit)
• Serin Dabb (RSC, Marinlit)
• Patrick Wheeler and David Hardy (ACD/Labs)
Thank you
Email: williamsa@rsc.org
ORCID: 0000-0002-2668-4821
Twitter: @ChemConnector
Personal Blog: www.chemconnector.com
SLIDES: www.slideshare.net/AntonyWilliams

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Applying Royal Society of Chemistry cheminformatics skills to support the PharmaSea project

Editor's Notes

  1. MarinLit is ‘article-centric’ and not compound centric. Compounds are only indexed when they are newly discovered, revised, or new to marine. All compound records link to the paper they were first mentioned. They are not linked to subsequent articles that describe them.