6 ms·
Here is the original study published in nature microbiology. https://www.nature.com/articles/s41564-025-02142-0 https://www.nature.com/articles/s41564-025-0214
by KLK2019 1y ago
Here is the original study published in nature microbiology.
https://www.nature.com/articles/s41564-025-02142-0 https://www.nature.com/articles/s41564-025-02142-0
Wanted to share what I thought the interesting parts. From the university press release.
"To date, AI has been leveraged as a tool for predicting which molecules might have therapeutic potential, but this study used it to describe what researchers call “mechanism of action” (MOA) — or how drugs attack disease.
MOA studies, he says, are essential for drug development. They help scientists confirm safety, optimize dosage, make modifications to improve efficacy, and sometimes even uncover entirely new drug targets. They also help regulators determine whether or not a given drug candidate is suitable for use in humans... A thorough MOA study can take up to two years and cost around $2 million; however, using AI, his group did enterololin’s in just six months and for just $60,000.
Indeed, after his lab’s discovery of the new antibiotic, Stokes connected with colleagues at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) to see if any of their emerging machine learning platforms could help fast-track his upcoming MOA studies.
In just 100 seconds, he was given a prediction: his new drug attacked a microscopic protein complex called LolCDE, which is essential to the survival of certain bacteria.
“A lot of AI use in drug discovery has been about searching chemical space, identifying new molecules that might be active,” says Regina Barzilay, a professor in MIT’s School of Engineering and the developer of DiffDock, the AI model that made the prediction. “What we’re showing here is that AI can also provide mechanistic explanations, which are critical for moving a molecule through the development pipeline.”
- zaptheimpaler 1y ago> Indeed, after his lab’s discovery of the new antibiotic, Stokes connected with colleagues at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) to see if any of their emerging machine learning platforms could help fast-track his upcoming MOA studies. It must be so cool to work at a university. You can just walk across campus to meet with experts and learn about or apply the cutting edge of any given field to solve whatever problem you're interested in.
- bongodongobob 1y agoThat's only if there are experts there. The average college is not really what you're thinking it is.
- noosphr 1y agoYou can email them and they are usually quite happy to talk. Of course not when they get a media storm like these people. But I regularly correspond with experts in adjacent fields who have interesting papers put out.
- touisteur 1y agoCan confirm that most of the times when reproducing/implementing a paper or trying to extend it to another field, researchers are pretty OK (some very enthusiastic) to chat over email about it. As long as you've actually read the paper(s) or read the code (if any), and there's no expected free-work... I sometimes get unpublished artefacts (matlab/python/fortran code, data samples) just by... asking nicely, showing interest. And I'm not even in academia or a lab.
- nick__m 1y agoIn my sample of 1 with cold email to a researcher was that they are enthusiastic when someone has read their paper and ask relevant questions. I don't remember the paper subject neither the researcher name (more than 20yr ago) but I remember that she was an ornitologist, the subject was quite niche and the response I received to my questions was longer than the article that prompted me to asks them.
- jancsika 1y agoThe Reverse Gell-Mann Amnesia Effect-- one vastly underestimates the work it took to reach a conclusion in a book they haven't finished reading. Then, without reading another page, they assume everything in the entire bookshelf is at the same shallow level as their own misapprehension of the book they didn't finish. I rankly speculate: for the set of low-effort comments on HN, there are more Reverse Gell-Manns than there are Gell-Manns.
- Izikiel43 1y ago> A thorough MOA study can take up to two years and cost around $2 million; however, using AI, his group did enterololin’s in just six months and for just $60,000. Beautiful, finally something for ai/machine learning that is not a coding autocomplete or image generation usage. It would be very interesting to keep track of this area for the next 10 years, between alpha fold for protein folding and this to predict how it will behave, how cost is reduced and trials get fast tracked
- Zafira 1y agoBased on the paper for DiffDock (https://arxiv.org/abs/2210.01776 https://arxiv.org/abs/2210.01776) it looks like it was a great use case for a diffusion model. > We thus frame molecular docking as a generative modeling problem—given a ligand and target protein structure, we learn a distribution over ligand poses. I just hope work on these very valid use cases doesn’t get negatively impacted when the AI bubble inevitably bursts.
- noosphr 1y agoDoes anyone have the pre-print? I'm not affiliated with a university any more and the usual suspects don't upload papers overnight any more.
- mywacaday 1y agoTheir inboxs might be overflowing but researchers usually happy to email a copy if you don't have access elsewhere
- fmbb 1y agoIs DiffDock a large language model? Because that is what the general public believes AI means, and Open AI say they are building thinking machines with it, and this headline says ”predicted”.
- deleted 1y ago[deleted]
- zachthewf 1y agoNo it’s a diffusion model trained on proteins
- esafak 1y agoIt's a 3D equivariant graph neural network; a class of models that was hot before LLMs stole the limelight. https://en.wikipedia.org/wiki/Graph_neural_network https://en.wikipedia.org/wiki/Graph_neural_network
- FollowingTheDao 1y agoWhat???? We knew that LolCDE was a vulnerability to e coli since well before 2016 and knew inhibitors of the complex, globomycin being one of them, which they knew about since 1978 https://journals.asm.org/doi/full/10.1128/jb.00502-16 https://journals.asm.org/doi/full/10.1128/jb.00502-16 https://pubmed.ncbi.nlm.nih.gov/353012/ https://pubmed.ncbi.nlm.nih.gov/353012/ Is enterololin just another from of globomycin? Is AI smart or are scientists just getting dumber?
- raincom 1y agoAI just picked up these references and gave an answer. Scientists in this field should have read these papers instead of relying on AI.
- rdedev 1y agoFrom what I understand they used a diffusion model (diffdock) to predict the mechanism. These types of models are not LLMs that need to be trained on text
- D-Coder 1y agoThere are probably 37,392 papers on this. So your "should" is probably just impossible for humans.
- FollowingTheDao 1y agoThis is such a ridiculous argument. They could have read five papers, couldn’t they?
- klustregrif 1y agoPicking up five needles is trivial. Picking up five needles in 50000 haystacks is difficult.
- D-Coder 1y agoHow do they know which five papers to read?