Jul 17, 2024 05:27 PM
https://www.sequencermag.com/the-drugs-o...-the-past/
EXCERPTS: César de la Fuente’s lab has a knack for finding antibiotics in usual places. He doesn't trudge through swamps or remote forests like a pharmacological Indiana Jones. His lab instead combs through genetic data collected from creatures across all time.
In just the last few years, they’ve documented unreported antimicrobial compounds hidden in the genomes of Neanderthals, the world’s microbes, and within ourselves. Now, their latest feat carries the torch thanks to a brand new machine learning algorithm they call APEX: antibiotic peptide de-extinction.
APEX is sort of like a drug-sniffing dog. But instead of a German Shepherd named Bruce scanning carry-ons for bags that smell like weed, the AI scours extinct animals’ genetic sequences for patterns it has learned to mean “this gene makes germ-killing molecules.”
Before this project, de la Fuente’s team at the University of Pennsylvania had only explored the genetic data of a few animals at a time. They dreamed bigger. “Here, we challenged the team to see if we could explore every extinct organism known to science,” de la Fuente said. “So we had to develop a more powerful AI model.”
What they’ve found are peptides, short chains of amino acids that, in this case, can infiltrate and destroy pathogenic bacteria, just like an antibiotic. When APEX alerted them to promising sequences, the researchers could cook up that molecule and try it out in test tubes and mice infected with the pathogen Acinetobacter baumannii.
[...] We’ve clearly entered a drug discovery era that’s vastly different. I earned my PhD by developing new antibiotics so — if you’ll allow me to editorialize a little right here — this is pretty damn cool. Still, I must emphasize: we’re not mice (“rodent men” aside) so a study like this can only say so much about how a sea cow’s long-extinct peptides can rescue people from superbugs.
Also, as this type of lightning-quick drug discovery amasses piles of potential drugs, I’m left wondering: what happens from here? It’s all but certain that even the five best de-extinction peptides won’t all get clinical trials in humans soon. How can we modernize R&D pipeline after finding cool molecules so that we can pick out the best even faster?
De la Fuente’s reflex is to be optimistic: “If we flood the pipeline with hundreds or thousands or millions of candidates, the likelihood of at least one of them making it through is a lot higher,” he said. “But we may need to build additional AI models to help us filter all those preclinical candidates.” (MORE - missing details)
EXCERPTS: César de la Fuente’s lab has a knack for finding antibiotics in usual places. He doesn't trudge through swamps or remote forests like a pharmacological Indiana Jones. His lab instead combs through genetic data collected from creatures across all time.
In just the last few years, they’ve documented unreported antimicrobial compounds hidden in the genomes of Neanderthals, the world’s microbes, and within ourselves. Now, their latest feat carries the torch thanks to a brand new machine learning algorithm they call APEX: antibiotic peptide de-extinction.
APEX is sort of like a drug-sniffing dog. But instead of a German Shepherd named Bruce scanning carry-ons for bags that smell like weed, the AI scours extinct animals’ genetic sequences for patterns it has learned to mean “this gene makes germ-killing molecules.”
Before this project, de la Fuente’s team at the University of Pennsylvania had only explored the genetic data of a few animals at a time. They dreamed bigger. “Here, we challenged the team to see if we could explore every extinct organism known to science,” de la Fuente said. “So we had to develop a more powerful AI model.”
What they’ve found are peptides, short chains of amino acids that, in this case, can infiltrate and destroy pathogenic bacteria, just like an antibiotic. When APEX alerted them to promising sequences, the researchers could cook up that molecule and try it out in test tubes and mice infected with the pathogen Acinetobacter baumannii.
[...] We’ve clearly entered a drug discovery era that’s vastly different. I earned my PhD by developing new antibiotics so — if you’ll allow me to editorialize a little right here — this is pretty damn cool. Still, I must emphasize: we’re not mice (“rodent men” aside) so a study like this can only say so much about how a sea cow’s long-extinct peptides can rescue people from superbugs.
Also, as this type of lightning-quick drug discovery amasses piles of potential drugs, I’m left wondering: what happens from here? It’s all but certain that even the five best de-extinction peptides won’t all get clinical trials in humans soon. How can we modernize R&D pipeline after finding cool molecules so that we can pick out the best even faster?
De la Fuente’s reflex is to be optimistic: “If we flood the pipeline with hundreds or thousands or millions of candidates, the likelihood of at least one of them making it through is a lot higher,” he said. “But we may need to build additional AI models to help us filter all those preclinical candidates.” (MORE - missing details)