Shining a light on chemical properties with Open Notebook Science ...

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with Open Notebook Science and open strategies. Jean-Claude Bradley. August 20, 2012. Open Notebook Science/Open. Chemistry/Electronic Lab Notebook.
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

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)

Solubility (in 1-octanol saturated water @25C)

Solubility (in water saturated 1-octanol @25C)

logP

Open Chemical Property Matrix (OCPM)

Solubility (in 1-octanol saturated water @25C)

Solubility (in water near 25C)

Solubility (in water saturated 1-octanol @25C)

logP

Solubility (in 1octanol near 25C)

Open Chemical Property Matrix (OCPM) Boiling point

Vapor pressure Flash point

Abraham descriptors

Melting point

logP Aqueous solubility

Octanol solubility

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 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)