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Alex M. Clark 1 , Antony J. Williams 2 and Sean Ekins 3,4 1 Molecular Materials Informatics, 2 Royal Society of Chemistry, 3 Collaborations in Chemistry, 4 Collaborative Drug Discovery, Inc., Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Cheminformatics Workflows Using Mobile Apps for Drug Discovery

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Page 1: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Alex M. Clark1, Antony J. Williams2 and Sean Ekins3,4

1 Molecular Materials Informatics, 2 Royal Society of Chemistry, 3Collaborations in

Chemistry, 4 Collaborative Drug Discovery, Inc.,

Cheminformatics Workflows Using Mobile

Apps for Drug Discovery

Page 2: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

• mobile is revolutionary: a clean break

entirely new user interface

no backward compatibility

highly constrained resources

applicable to entirely new situations

mainframes

minicomputers

personal computers

portable laptops

mobile tablets

smartphones

?

The Computing Revolution #3

Page 3: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Williams et al DDT

16:928-939, 2011

Arnold and Ekins, PharmacoEconomics 28: 1-5, 2010

Williams et al., In collaborative computational technologies for

biomedical research 2011

Fitting Mobile Apps into R&D Workflow

Page 4: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Chemistry Apps • Reference data

• Education

• Structure drawing

• Database searching

• 3D viewing

• Reactions & collections

• Property calculation

• Model building

• Graphical presentation

• Data sharing

Page 5: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

http://goo.gl/Goa4e

Need for dedicated website / store for science Apps

– find out more at www.scimobileapps.com

Page 6: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Simple App Workflows

• Look up structure in ChemSpider

• Saving structure as molfile - open in MMDS

• Run substructure search in ChEBI using MMDS webservice

• Open molecule from MMDS and assign scaffolds in SAR Table

Generate substituents

• Predict missing activities for compounds in SAR Table

• Suggest compounds to make in SAR Table

• Find a reaction in SPRESImobile

• Use Yield101 to calculate synthesis yield

• Share data with Dropbox using MolSync app

• Tweet a reaction with MolSync

• Read the data with ODDT mobile app

Clark AM, Williams AJ and Ekins S, Chem-Bio Informatics Journal, 13: 1-18 2013.

Page 7: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

A Bigger Vision

• Mobile chemistry originally intended to support

desktop workflows

• Mobile+Cloud can be a total replacement

• Entirely new user expectations for apps:

- easy to learn

- delightful to use

- trivial to install

- inexpensive or FREE

• Extremely disruptive to existing software vendors!

Page 8: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

APPIFYING DATA - From PDF to Mobile App

Lots of data

but how to

make it useful

for chemists?

Chemists see

structures

PDF not

accessible,

small text- too

much data

http://bit.ly/GzQ5ty

Page 9: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Green Solvents and Lab Solvents FREE Apps

Alex Clark made the App in 3 days

Android version – Lab Solvents

Includes GSK solvent data

ACS Sustain Chem Eng 1: 8-13 (2013)

Page 10: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

TB Kills 1.6-1.7m/yr (~1 every 8 seconds)

1/3rd of worlds population infected!!!!

Multi drug resistance in 4.3% of cases

Extensively drug resistant increasing incidence

No new drugs in over 40 yrs until Bedaquiline

Drug-drug interactions and Co-morbidity with HIV

Increase in HTS phenotypic screening

1000’s of hits no idea of target Use of computational methods with TB is rare

Page 11: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

30 years with little TB mouse in vivo data MIND THE TB GAP

IN V

IVO

INA

CT

IVE

IN V

IVO

AC

TIV

E

Page 12: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Pathway analysis

Binding site similarity to Mtb proteins

Docking

Bayesian Models - ligand similarity

Predicting the target/s for small molecules

Page 13: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

TB molecules and target information database connects

molecule, gene, pathway and literature for >700 molecules

Page 14: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

iPhone Android

TB Mobile layout on iPhone and Android

Page 15: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

TB Mobile Molecule Detail and Links

iPhone Android

Page 16: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Molecules active against Mtb evaluated in TB Mobile app

Page 17: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Workflow from sketching molecules in MMDS mobile app

to exporting and opening with TB Mobile

Page 18: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

http://goo.gl/UTTH0

TB Mobile – poster on Jan 2013

Page 19: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

http://goo.gl/vPOKS http://goo.gl/iDJFR

TB Mobile – Is on iTunes and Google play

and it is FREE

http://goo.gl/7fGFW

Page 20: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

What next ?

Update with more data

Add a weighting or scoring function to account

for heavily populated targets

Expand beyond the similarity measure

Add algorithms to predict activity

Could we appify data for other diseases/ targets

Page 21: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Connecting

data/tools

like a TB Spider

In vitro data

In vivo data

Target data

ADME/Tox data

& models

Drug-like scaffold creation

TB prediction tools TB publications

Page 22: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

• Preliminary work done with desktop software: com.mmi

• Fragment TB Mobile structures, scaffold-like

• Perform scaffold-substructure vs. 7000 in vitro

• Derive R-groups, tidy, present graphically, browse...

TB Mobile in a TB Workflow

Page 23: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Source Materials • Scaffold:

• Scaffold origin: inhibitor of Glf target

• 87 molecules with in vitro activity (yes/no)

• Scaffold seems to elicit an activity pattern

• Next step: load it into the app ecosystem...

http://molmatinf.com/

venice.html

To see the rest

of the TB

workflow……

Page 24: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Open Drug Discovery Teams

• Curation of open data, e.g. Twitter & RSS feeds

• Rare & neglected diseases, precompetitive

areas

Page 25: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Harvested Tweet

• Tweet got harvested into Tuberculosis topic

• Inline preview browsed, with other

thumbnails

Page 26: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

What we can do now… Take HTS screening hits Query public databases Propose targets Design / purchase analogs Predict activity All on a mobile device / anywhere

Page 27: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Conclusion

• Cheminformatics workflows historically the role of

specialists: expensive and/or complex

• Mobile apps are much cheaper and much more

accessible to experimentalists

• Mobile+cloud can:

- replace simple-to-medium tasks

- coexist with complex tasks run on desktop software

• Other advantages:

- anywhere/anytime portability

- excellent collaboration and sharing

- non-existent installation or maintenance burden

27

Page 28: Cheminformatics Workflows Using Mobile Apps for Drug Discovery

Malabika Sarker, Carolyn Talcott, Joel Freundlich, Barry Bunin

2R42AI088893-02 “from the National Institute of Allergy And

Infectious Diseases. (PI: S. Ekins)

You can find me @. CDD Booth 653..

Poster 224

PAPER TITLE: “Dual Response and dataset Fusion for

Machine Learning Models for Hit to lead Optimization in

Mycobacterium Tuberculosis Drug Discovery”

Monday, January 20, 2014

Presentation Time: 1:00 PM – 3:00 PM

Acknowledgments