NOV 15, 2020 8:06 AM PST

Chemical reactivity flowcharts assist chemists in interpreting reaction outcomes

New research published in Organic Letters from Purdue University scientists presents the design and development of chemical reactivity flowcharts that assist chemists in interpreting reaction outcomes. The flowcharts are trained by machine learning models.

"Developing new and fast reactions is essential for chemical library design in drug discovery," said Gaurav Chopra, an assistant professor of analytical and physical chemistry in Purdue's College of Science. "We have developed a new, fast and one-pot multicomponent reaction (MCR) of N-sulfonylimines that was used as a representative case for generating training data for machine learning models, predicting reaction outcomes, and testing new reactions in a blind prospective manner.

"We expect this work to pave the way in changing the current paradigm by developing accurate, human-understandable machine learning models to interpret reaction outcomes that will augment the creativity and efficiency of human chemists to discover new chemical reactions and enhance organic and process chemistry pipelines."

The exciting part of this innovation is that it does not require large-scale robotics, but rather can be used within labs by chemists doing reaction screenings. The team says this means the innovation could be translated to other chemical reactions.

"We provide the first report of a framework to combine fast synthetic chemistry experiments and quantum chemical calculations for understanding reaction mechanism and human-interpretable statistically robust machine learning models to identify chemical patterns for predicting and experimentally testing heterogeneous reactivity of N-sulfonylimines," Chopra said.

The work comes out of a collaboration with the Purdue Research Foundation Office of Technology Commercialization and highlights the wide range of applications for machine learning.

Photo: Pexels

"The unprecedented use of a machine learning model in generating chemical reactivity flowcharts helped us to understand the reactivity of traditionally used different N-sulfonylimines in MCRs," said co-author Krupal Jethava. "We believe that working hand-to-hand with organic and computational chemists will open up a new avenue for solving complex chemical reactivity problems for other reactions in the future."

"In this work, we strived to ensure that our machine learning model can be easily understood by chemists not well versed in this field," said fellow co-author Jonathan Fine. "We believe that these models have the ability not only be used to predict reactions but also be used to better understand when a given reaction will occur. To demonstrate this, we used our model to guide additional substrates to test whether a reaction will occur."

Sources: Organic Letters, Science Daily

About the Author
  • Kathryn is a curious world-traveller interested in the intersection between nature, culture, history, and people. She has worked for environmental education non-profits and is a Spanish/English interpreter.
You May Also Like
SEP 22, 2021
Chemistry & Physics
XENON1T Physicists May Have Directly Detected Dark Energy
SEP 22, 2021
XENON1T Physicists May Have Directly Detected Dark Energy
In what could be a revolutionary discovery, a team of physicists from the XENON Collaboration may have detected dark ene ...
SEP 29, 2021
Space & Astronomy
When a Meteor Destroyed an Ancient City, It May Have Inspired Biblical Tales
SEP 29, 2021
When a Meteor Destroyed an Ancient City, It May Have Inspired Biblical Tales
This meteor may have caused a blast as large as the one in the Tunguska Event, and totally flattened a city.
OCT 05, 2021
Chemistry & Physics
Researchers Propose Pathway to Plastics Free of Carbon Emissions
OCT 05, 2021
Researchers Propose Pathway to Plastics Free of Carbon Emissions
Plastics may, in general, be a product of fossil fuels like petroleum, but that has not stopped an international team of ...
NOV 10, 2021
Chemistry & Physics
Turning Plastic Bags into Fuel
NOV 10, 2021
Turning Plastic Bags into Fuel
By now, we all know that plastic waste is a huge problem. More than 350,000,000 tons of plastic waste are generated annu ...
NOV 13, 2021
Earth & The Environment
Human Waste Contributions to Global Pollution Exceed Expectations
NOV 13, 2021
Human Waste Contributions to Global Pollution Exceed Expectations
River ecosystems receive many inputs from human activities upstream. Rivers bring these inputs out to the ocean, where t ...
NOV 16, 2021
Cell & Molecular Biology
Modeling the Separation of Liquids in Cells
NOV 16, 2021
Modeling the Separation of Liquids in Cells
Oil and water are both liquids, but they don't mix well, demonstrating a phenomenon known as liquid-liquid phase separat ...
Loading Comments...