Neural Networks for the Prediction of Organic Chemistry Reactions
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Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#2Abstract:
"Reaction prediction remains one of the major challenges for organic chemistry and is a prerequisite for efficient synthetic planning. It is desirable to develop algorithms that, like humans, “learn” from being exposed to examples of the application of the rules of organic chemistry. We explore the use of neural networks for predicting reaction types, using a new reaction fingerprinting method. We combine this predictor with SMARTS transformations to build a system which, given a set of reagents and reactants, predicts the likely products. We test this method on problems from a popular organic chemistry textbook."
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#3One of the authors here. Ask us anything!
This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules.
I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#4One of the authors here. Ask us anything! This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules. I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
What's worrisome is that on the graphical abstract you have nucleophilic substitution in the neopentyl position, a reaction every chemist knows won't proceed rapidly. And it takes place in dimethyl ether solvent, which every chemist knows it's a gas.
It looks a bit what you see in bad teaching materials, chemistry that is almost correct, but won't work well for some reason we are not telling the kids about. Please alleviate my concerns! :-)
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#5One of the authors here. Ask us anything! This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules. I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
What is the state of the art here? What models do we currently have to predict chemical/organic inputs/outcomes?
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#6One of the authors here. Ask us anything! This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules. I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
Is RPA coming back to Harvard?
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#7One of the authors here. Ask us anything! This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules. I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
I took three semesters of orgo in undergrad, and if it taught me anything, it's that there are exceptions to nearly every rule. There are so many complicated molecular orbital interactions, requiring years of study. And even then there are always things that break these rules in unexpected ways or produce several products.
How do you overcome this? Can you predict yield percentages of each product? What about chirality?
Can your system design synthesis pathways? Can it optimize for final product yield? How does it handle the thermodynamics and kinetics of reactions?
In any case, cool project. It's a very difficult domain.
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#8One of the authors here. Ask us anything! This paper is just a first step - what we'd really like to use this for is designing recipes for synthesizing new molecules. I would also be remiss if I didn't link to a closely-related paper from another group that came out at the same time: http://pubs.acs.org/doi/abs/10.1021/ci5006614
What is the state of the art here? What models do we currently have to predict chemical/organic inputs/outcomes?
Us chemists use retrosynthesis to disconnect the target cpd into accessible fragments of appropiate polarity that can be conveniently joined (that's three issues in one), and consider electron flow (i.e. arrow pushing) to think about what reactions would proceed smoothly.
Manipulation of 2D-connectivity, as seen in the paper is new and not for humans.
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#9I skimmed through the paper (through my university's subscription) and found out that the source code & data is (or will be) available on GitHub (yay): https://github.com/jnwei/neural_reaction_fingerprint
Re: Neural Networks for the Prediction of Organic Chemistry Reactions
#10I skimmed through the paper (through my university's subscription) and found out that the source code & data is (or will be) available on GitHub (yay): https://github.com/jnwei/neural_reaction_fingerprint
I'm just an old geezer programmer, but my daughter is studying e-tox at UC Davis. I have discussed with her how important computer code is becoming in the ability to recreate results in studies.
This is a good example of providing that kind of transparency.