Scientists discover first new antibiotics in over 60 years using AI

It sounds like they trained a classification model using 39,000 molecules with known reactivity to MRSA. The molecules are vectorized text representations of the structures. Once trained, they can run arbitrary molecules through the model and see which ones are predicted to have antibiotic properties, or at least MRSA reactivity.

They likely fed in molecules from families of structures that seem likely to contain an antibiotic but are too numerous to manually test them all. They get a prediction of which ones are likely to have the properties they want, and then start the slow process of creating and testing the molecules in the lab.

But it's going to be. Until we do something to stop them, it's absolutely going to be that way. There's no serious view of human history that will tell you anything different.

We can't just sit here and marvel at technology without acknowledging who controls it, who uses it, and what they're going to use it for. Without people, AI is just a bunch of code sitting there waiting for input.

Think of how many more species we can drive to extinction now!

🫠

Yeah but think of all the bacteria it's putting out of work.

My dad was allergic to practically every antibiotic. He only developed the allergy in his senior years. It was a big problem for him. Even if the antibiotic seemed to be working okay, he had to take a lot of Benadryl just in case and keep an epi pen around.

Anti-antibiotics... Isn't that just biotics? Like from Mass Effect? IDK, could be cool 👀

It would be long overdue. The scientific consensus for vast harms from antibiotics has been strong for many years. https://humanmicrobiome.info/antibiotics/

It doesn't sound like it but they don't have enough detail in the article to say.

It sounds likey they are using a classification model that takes a vectorized text representation of molecules and classifies or scores them by their expected properties/reactivity. They took 39,000 molecules with known reactivity to MRSA to train the model, I assume to classify the structures. Once trained they can feed in arbitrary molecules into the trained model and see which ones are predicted to have antibiotic properties, which they can verify with bench work.

They likely fed in molecules from classes of likely candidate structures, and the model helped focus and direct the wet work.

I'm not up on the latest, but years ago I helped a similar project using FPGAs running statistical models to direct lab work.

llms have progressed beyond cut and paste way more than a year ago. they have shown understanding of what items are and how they behave and interact. I know it's popular here to call it a parrot or whatever but most people don't have access to the high level stuff and most seem afraid/snobby/parroting things themselves.

Virtual screening libraries are usually some form of expanded chemical space meaning they contain real and previously unknown compounds. The article says the 12 million compounds screened virtually were commercially available, but I couldn't see enough of the nature paper to verify. It could be that the virtual screening set was acquired from a private company, but that doesn't necessarily mean all the compounds are known.

This is a simplified to the point of absurdity comment. Microbiome is important, but is absolutely not enough to prevent antibiotic resistance.

Bacterial infections can kill people.

Don't be stupid