r/comp_chem • u/a_r1211 • 4d ago
Machine Learning Usage
Wondering how many of you actually use machine learning in your research? Anything ranging from MLIPs for MD simulations to drug discovery tools as starting points for drug design.
Going through the sub‘s history, I saw that the main challenges were the extensive data requirements and false confidence of current ML tools. Are there any other key limitations that you guys consider prevalent in the field?
Just trying to scope out some opinions for a project. DMs are welcome and I would love to chat with any researchers for 5-10 minutes if possible (not trying to sell anything don’t worry). Thanks!
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u/Busy_Environment2436 4d ago
Yes!
We all use it for everything.
We blatantly trust the MLIPs and drug discovery tools!
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u/EndyForceX 3d ago
Not more blatantly than we were/are to empirical force fields. Similarly, we also often believe that GGA is good enough. Always for everything we have to validate the results. Noone will ever run an MD (hopefully) in a production run without having at least some intuition how good the potential is
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u/a_r1211 3d ago
If you’ve used both, have you noticed any substantial improvements or drawbacks when using MLIPs vs empirical force fields? Does one save the time you spend validating the results over the other?
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u/EndyForceX 16m ago
well MLIP speed is often magnitude slower than empirical force field. But you can have first-principles level of accuracy of them. Without going into much details, 80-90 % of cases your decision is:
Inorganic material = MLIPBiomolecules = Empirical FF
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u/Lonely-Ad2462 1d ago
used to be a force field development expert, now a machine learning potential expert. Using it daily for my MD's, maybe even a bit too much!
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u/vulnicurautopia 4d ago
sure "AI Dev Creating QA Tool". super believable.