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Neural Networks for the Prediction of Organic Chemistry Reactions

pubs.acs.org

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Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#21

Post by duvenaud »

HarryHirsch wrote: post #4
duvenaud wrote: post #3

One 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 al…

That diagram is just meant to show what type the inputs and outputs of the neural network are. I'm not a chemist myself, but the other two authors are.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#23

Post by walrus »

Roboprog wrote: post #10
kenrick95 wrote: post #9

I 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.

Somewhat off-topic, but there's a professor at UC Davis whose blog I've followed for several years who advocates open, reproducible science. Your daughter might be interested in the the workshops his lab runs: https://dib-training.readthedocs.io/en/pub/. The next one is Nov 17.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#24

Post by chillacy »

duvenaud wrote: post #21
HarryHirsch wrote: post #4

Earlier quoted context omitted.

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 al…

That diagram is just meant to show what type the inputs and outputs of the neural network are. I'm not a chemist myself, but the other two authors are.

Heh, not a chemist either, but the parent probably has the same feeling I get when I watch "hackers" in crime dramas break into systems and see a bunch of HTML and CSS on their terminals.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#25

Post by jnwei »

HarryHirsch wrote: post #4
duvenaud wrote: post #3

One 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 al…

This is Jennifer, another of the authors. You're absolutely right about the graphical abstract figure. For this first paper, we used very simple rules to generate our data set of reaction, so you end up with reactions that don't fully capture a human chemist's intuition.

We hope in the future to have access to real experimental data sets for real chemistry, complete with accurate temperatures, pressures, solvents, and reaction yields. Then our algorithm would be able to use all the information and predict reactions accurately. Right now, there just aren't many well-curated data sets with this kind of detail that would work for this kind of training. Happy to receive feedback from any experimental chemists out there with data from their research that they'd like to train on.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#26

Post by jnwei »

pama wrote: post #17
duvenaud wrote: post #15

Earlier quoted context omitted.

Good points. However, even if chemists already know how to predict reactions, giving this knowledge to a machine will allow a much faster search over possible synthetic routes. I agree that reaction outcomes depend on many other factors besides the reagents. In the future, I'm sure we'll create reaction prediction frameworks that also take these other factors as inputs. The problem right now is that there aren't many…

Did you consider working with a chemistry CRO (say WuXi) to train models using their proprietary datasets? Is there some solution that's a win-win for everyone?

We are definitely considering it. In fact the next iteration of this project will be in collaboration with Wiley ChemPlanner and their database of reactions.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#27

Post by jnwei »

andrew-lucker wrote: post #5
duvenaud wrote: post #3

One 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?

For predicting of reactions using computers, there are several methods out there, some of which use physical (quantum mechanics) calculations. Each reaction can take a long time to run, which is why we've turned to machine learning.

We chose to use fingerprints, i.e. a vector representation of the graphical features of a molecule, for the inputs of our reactions, which is often used when machine learning properties of molecules, or for classifying the entire reaction as David pointed mentioned before. There's one paper from the Baldi group that uses inputs that are more like orbitals, and tries to predict the mechanisms of reactions directly : http://pubs.acs.org/doi/abs/10.1021/ci3003039

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#28

Post by jnwei »

amelius wrote: post #22

I'm not a chemist, and didn't read the paper, but would it be helpful if the neural network had additional inputs coming from e.g. a (simplified) Schrodinger equation solver?

Orbital energies, or other solutions from the Schrodinger equation, would probably help the prediction if they were included as inputs. If you were to do this, you'd have to be a little careful about the cost of doing the quantum mechanics calculation on a whole data set of reactants in your reaction database, but it could be feasible with a cheap method.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#29

Post by dnautics »

ghaff wrote: post #11
echelon wrote: post #7

Earlier quoted context omitted.

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 chirali…

One of the things that I didn't quite get when I started taking organic chemistry was that I really couldn't figure out (didn't have enough background knowledge) why many reactions happened the way they did and that I just had to memorize things. (Accounting is the same way though for very different reasons. You could justify recording some transactions in about 5 different ways--but FASB says only a particular one i…

At the grad level students get really good at rationalizing and predicting reactions. We did bimonthly exercise called mechanism club where someone would pick some chemical reactions from the literature and basically volunteers would come up to the chalkboard and push electrons till the reaction was complete.

Re: Neural Networks for the Prediction of Organic Chemistry Reactions

#30

Post by Roboprog »

walrus wrote: post #23
Roboprog wrote: post #10

Earlier quoted context omitted.

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.

Somewhat off-topic, but there's a professor at UC Davis whose blog I've followed for several years who advocates open, reproducible science. Your daughter might be interested in the the workshops his lab runs: https://dib-training.readthedocs.io/en/pub/ . The next one is Nov 17.

Thanks, passing it on.
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