Bradley Open Notebook Science ACSfall2012
42
Shining a light on chemical properties with Open Notebook Science and open strategies Jean-Claude Bradley August 20, 2012 Open Notebook Science/Open Chemistry/Electronic Lab Notebook ACS Symposium Associate Professor of Chemistry Drexel University
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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.
Transcript of Bradley Open Notebook Science ACSfall2012
Shining a light on chemical properties
with Open Notebook Science and open strategies
Jean-Claude Bradley
August 20, 2012
Open Notebook Science/Open Chemistry/Electronic Lab Notebook
ACS Symposium
Associate Professor of ChemistryDrexel University
Openness in Chemistry
WHY?
Dibenzalacetone derivatives docking against tubulin (paclitaxel site)
(Andrew Lang)
“Simple” aldol condensation synthesis
Top Hit(no reports of synthesis)
In top ten(a few reports of synthesis)(Andrew Lang)
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.
Searching for aldol condensations of acetone in the Reaction Attempts
database
(Andrew Lang)
An example of a failed experiment in an Open Notebook with useful information
A failed experiment reveals the importance of aldehyde solubility
An example of a successful experiment in an Open Notebook
Using a Google Spreadsheet for reaction planning and analysis
Calling Google App Scripts
Calling Google App Scripts
(Andrew Lang and Rich Apodaca)
Converting Google Apps Scripts Results to Values
(Andrew Lang and Rich Apodaca)
Never having to leave the Google Spreadsheet dashboard for access to key info
(Andrew Lang and Rich Apodaca)
A click away from an interactive NMR display (using JCAMP-DX format and ChemDoodle)
(Andrew Lang)
A click to all melting point sources contributing to the average
Chemistry Google App Scripts Resource page
(Andrew Lang and Rich Apodaca)
Chemistry Google App Scripts description sheet
(Andrew Lang and Rich Apodaca)
Predicted solubilities (M) for reactant and product
(Andrew Lang)
Information from the literature on the target synthesis
Information from the literature on the target synthesis
Information from the literature on the target synthesis
A successful synthesis by avoiding water, dramatically increasing NaOH and long reaction
time
Open Chemical Property Matrix (OCPM)
logP
Solubility (in 1-octanol saturated water @25C)
Solubility (in water saturated 1-octanol @25C)
Open Chemical Property Matrix (OCPM)
logP
Solubility (in 1-octanol saturated water @25C)
Solubility (in water saturated 1-octanol @25C)
Solubility (in water near 25C) Solubility (in 1-
octanol near 25C)
Open Chemical Property Matrix (OCPM)
logP
Abraham descriptors
Melting point
Aqueous solubility
Octanol solubility
Vapor pressure
Flash point
Boiling point
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)
What is the solubility of benzoic acid in boiling benzene?
Lack of provenance details generates noise in the matrix
What questions do these numbers answer?
Examples of OCPM relationships
Examples of OCPM flash point calculations
Examples of OCPM solubility calculations
Provenance of the experimental data points
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
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)
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
Implement as an App
(Andrew Lang)
What are good solvents to recrystallize benzoic acid?
(Andrew Lang)
Click on the solvent to see temp curve
Deliver melting point data via App
(Andrew Lang)
Dibenzalacetone libraries are promising for connecting the OCPM with useful applications
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 modelersApps (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)
