Jean-Claude Bradley presents at the American Chemical Society meeting on August 20, 2012. Examples are first presented to demonstrate how access to Open Notebooks can provide critical information not usually shared in the traditional publication process. The use of Google App Scripts to look up chemical properties allows for the use of Google Spreadsheets as a self-contained dashboard to plan and analyze chemical reactions. The concept of the Open Chemical Property Matrix (OCPM) is introduced and a smartphone app to suggest recrystallization solvents is then presented.

1. Shining a light on chemical properties
with Open Notebook Science
and open strategies
Open Notebook Science/Open
Chemistry/Electronic Lab Notebook
ACS Symposium
Jean-Claude Bradley
Associate Professor of Chemistry
Drexel University
August 20, 2012

2. Openness in Chemistry
WHY?

3. Dibenzalacetone derivatives docking against
tubulin (paclitaxel site)
(Andrew Lang)

4. “Simple” aldol condensation synthesis
Top Hit
(no reports
of synthesis)
In top ten
(a few reports
of synthesis)
(Andrew Lang)

5. What is the current standard for “sufficient
information” in communicating organic
chemistry?
By definition, all peer-reviewed
published documentation has
been approved as sufficient by
authors, editors and reviewers.

6. Searching for aldol condensations of acetone
in the Reaction Attempts database
(Andrew Lang)

7. An example of a failed experiment in an Open
Notebook with useful information

8. A failed experiment reveals the importance of aldehyde
solubility

9. An example of a successful experiment in an Open
Notebook

10. Using a Google Spreadsheet for reaction planning and
analysis

11. Calling Google App Scripts

12. Calling Google App Scripts
(Andrew Lang and Rich
Apodaca)

13. Converting Google Apps Scripts Results to Values
(Andrew Lang and Rich
Apodaca)

14. Never having to leave the Google Spreadsheet
dashboard for access to key info
(Andrew Lang and Rich
Apodaca)

15. A click away from an interactive NMR display (using
JCAMP-DX format and ChemDoodle)
(Andrew Lang)

16. A click to all melting point sources contributing to the average

17. Chemistry Google App Scripts Resource page
(Andrew Lang and Rich
Apodaca)

18. Chemistry Google App Scripts description sheet
(Andrew Lang and Rich
Apodaca)

19. Predicted solubilities (M) for reactant and product
(Andrew Lang)

20. Information from the literature on the target synthesis

21. Information from the literature on the target synthesis

22. Information from the literature on the target synthesis

23. A successful synthesis by avoiding water, dramatically
increasing NaOH and long reaction time

24. Open Chemical Property Matrix (OCPM)
Solubility (in 1-octanol Solubility (in water
saturated water @25C) saturated 1-octanol
@25C)
logP

25. Open Chemical Property Matrix (OCPM)
Solubility (in 1-octanol Solubility (in water
saturated water @25C) saturated 1-octanol
@25C)
Solubility (in water logP
near 25C) Solubility (in 1-
octanol near 25C)

26. Open Chemical Property Matrix (OCPM)
Boiling point Vapor
pressure
Flash point
Abraham Melting point
descriptors
logP
Aqueous Octanol
solubility solubility

27. Types of Open Matrix Elements
1. True measurements (from Open Data
collections e.g. Open melting point
dataset of 27,000)
2. Calculatable descriptors (from OSS
e.g. CDK, MOPAC7.1)
3. Predicted properties (from Open
models)

28. What is the solubility of benzoic acid in boiling
benzene?

29. Lack of provenance details generates noise in the
matrix
What questions
do these
numbers
answer?

30. Examples of OCPM relationships

31. Examples of OCPM flash point calculations

32. Examples of OCPM solubility calculations

33. Provenance of the experimental data points

34. Practical applications of the OCPM
1. The automatic open evaluation of models from the dark
literature to determine where they do and where they
don’t work in the chemical space
2. The development of new open models built upon the
population of new measurements, descriptors and
predictions
3. The identification of compounds with desired properties
from virtual libraries

35. Finding a good recrystallization solvent
1. Estimate or look up the solubility at boiling
2. Estimate or look up the solubility at a convenient lower
temperature (e.g. 25C or 0C)
3. Determine the predicted recovery yield
4. Lower the priority for solvents that boil too high (too
hard to dry precipitate)
5. Lower the priority where the solubility at boiling is too
low (wastes solvent and makes it harder to crystallize)

36. Translate these requirements to desired
properties
1. Look up the solvent boiling point
2. Look up the room temperature solubility or predict it via
Abraham descriptors predicted from a model using the
CDK
3. Look up the solute melting point or predict it via a
model using the CDK
4. Use the melting point and the solubility at room
temperature to predict the solubility at boiling
5. Calculate the predicted recrystallization yield

37. Implement as an App
(Andrew Lang)

38. What are good solvents to recrystallize benzoic acid?
(Andrew Lang)

39. Click on the solvent to see temp curve

40. Deliver melting point data via App
(Andrew Lang)

41. Dibenzalacetone libraries are promising for connecting
the OCPM with useful applications

42. Conclusions
More openness in chemistry can make science more efficient
Provide interfaces that make sense to the end users:
Open Data, Open Models and Open Source Software to modelers
Apps (smartphones, Google App Scripts, etc.) for chemists at the bench
Acknowledgements
Andrew Lang (code, modeling)
Bill Acree (modeling, solubility data contribution)
Antony Williams (ChemSpider services, mp data curation)
Matthew McBride and Rida Atif (recrystallization and synthesis)