They did a virtual screen of a large compound library.
QSAR / QSPR / Virtual Screening has been around since the late 1950s.
The secret sauce here was the large experimental dataset - on the order of 10^5 compounds - they generated to train the model.
Maybe the explainability part is kind of novel for a neural network based approach; but not clear that you couldn’t identify substructure classes better with a pure bioinformatic approach.
"The insight here was that we could see what was being learned by the models to make their predictions that certain molecules would make for good antibiotics," James Collins, professor of Medical Engineering and Science at the Massachusetts Institute of Technology (MIT) and one of the study’s authors, said in a statement.
...
"What we set out to do in this study was to open the black box. These models consist of very large numbers of calculations that mimic neural connections, and no one really knows what's going on underneath the hood," said Felix Wong, a postdoc at MIT and Harvard and one of the study’s lead authors.
> not clear that you couldn’t identify substructure classes better with a pure bioinformatic approach.
Lots of things aren't clear, but what supports your particular claim? Has it ever been done? And is it addressed in the article?
So, yes, it’s been done at scale for decades.
The article makes all sorts of incorrect claims. For example, it says it has been 60 years since the last antibiotic was discovered, and that this works enables computational screening of antibiotics for the first time.
Here’s work from 2022 that used conventional computational screening to discover a novel antibiotic:
https://phys.org/news/2022-10-discovery-antibiotic-resistant...
HN is a forum of intellectual curiosity. The near-universal critiques are the opposite of that.
For greater context, in the drug discovery world, "explainability" of QSAR/QSPR has been a longstanding goal. It's (rightly) not considered sufficient to have "black box" models that make predictions -- it's too expensive and risky to carry drug candidates into the lab based on the output of an algorithm, so subject-matter experts want to know why the algorithms are making the predictions that they make.
Do you see the irony? What better describes social media? Personally, I see plenty of good, valuable, useful science journalism; it's got plenty of flaws, like any human endeavor - including social media comments.
But attacking journalism is normalized, and thus people know they can do it without being questioned and get some social media likes from it. It would be interesting to see the same responses turned on individual social media comments - what flaws could we find? :)
> For greater context, in the drug discovery world, "explainability" of QSAR/QSPR has been a longstanding goal. It's (rightly) not considered sufficient to have "black box" models that make predictions -- it's too expensive and risky to carry drug candidates into the lab based on the output of an algorithm, so subject-matter experts want to know why the algorithms are making the predictions that they make.
Ironically, that's what the OP is about; that was the point of their research.
Social media is not one thing. You've got multiple people in this thread who know the subject, in detail, telling you that the headline is wrong. These aren't youtube video comments.
> Ironically, that's what the OP is about; that was the point of their research.
Yes, I know. That's why I wrote that. The research is about a relatively obscure technical problem. The headline made it sound like a revolutionary breakthrough in antibiotic development.
Fair enough, but science journalism is not just one thing.
> You've got multiple people in this thread who know the subject, in detail, telling you that the headline is wrong.
That appears on every HN discussion of anything. It's not a signal of wrongness or rightness, any more than the color of the banner at the top - if it's orange, the OP must be obviously wrong!
Also, your comment is a baseless claim - like the strawperson journalists you rail against - that HN commenters are more informed than the authors. I expect that very few HN commenters are as informed.
Do you trust journalists that much? Have you ever read an article about something you are an expert on? You shouldn't trust articles that much. I trust HN discussions much more since there are plenty of people who will weigh in when things are wrong or misrepresented, unlike these articles.
Edit: Gell-Mann Amnesia effect, that was what this is called. Don't trust the media just because you aren't an expert.
> I trust HN discussions much more since there are plenty of people who will weigh in when things are wrong or misrepresented, unlike these articles.
Why are those people, with no responsibility, little expertise, etc., more trustworthy than other people? It seems like the common bias of social media - for some reason, people trust strangers with no credibility, which exposes them to the enormous amount of misinformation and just BS that now floods our world. If the article author or a professor wrote the same thing in a HN comment, it seems like you'd believe it.
I don't trust them, I trust the discussion in aggregate. The discussion includes people on all sides in a healthy forum. If you are on a subreddit you are in an echo chamber so many voices will be missing, but HN has good representation of experts and people from all sorts of fields so I trust these discussions to unearth better truths than what a typical journalist can.
> If the article author or a professor wrote the same thing in a HN comment, it seems like you'd believe it.
No, if they wrote the article in a comment with that headline it would get comments saying why it is wrong, just like here. The ability for people like you to object is why I trust it more.
Regarding things I already know - or even OPs I've read but which most commenters have not - HN is mostly misinformation.
I participate in HN, obviously - only because I've found nothing better (a complement to it, in a way, and maybe there's no known way to improve).
If you are saying that most discussions here on HN have zero people who are right, then I strongly disagree. It is very rare for there to be no truths in HN discussions. On reddit however it is very common for me to see not a single reasonable post to be found.