Each year, snake bites kill upwards of 100,000 people and permanently disable hundreds of thousands more, according to estimates from the World Health Organization. Promising new science, enabled by state-of-the-art technology, could help quell the threat.
Researchers have successfully designed two proteins to neutralize some of the most lethal venom toxins, using a suite of artificial intelligence tools, per a study published January 15 in the journal Nature. These “de novo” proteins–molecules not found anywhere in nature–protected 100% of mice from certain death when mixed with the deadly snake compounds and administered in lab experiments.
“I think we could revolutionize the treatment [of snake bites],” says Susana Vázquez Torres, lead study author and a biochemist who completed this research as part of her doctoral thesis in David Baker’s lab at the University of Washington. Baker won the 2024 Nobel Prize in Chemistry for his work creating new proteins. This week’s publication is a continuation of that line of inquiry. “This study, of course, doesn’t solve the whole problem, but it demonstrates that we can develop molecules super quickly compared to traditional methods–and it works,” Vázquez Torres tells Popular Science. The strategy could lead to cheaper, safer, and more effective remedies than the status quo, she adds.
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“It’s fantastic work,” says Joseph Jardine, an assistant professor of immunology and microbiology at the Scripps Research Institute. Jardine wasn’t involved in the new study, but has previously published research developing synthetic antivenoms for the same sorts of compounds. This new research is both a demonstration of how far protein design has come in recent years, enabled by rapidly improving AI, and also an exciting practical advance in medicine, he says.
Despite the toll that snake bites take, the treatment for envenomings has been the same for more than a century: Antibodies collected from horses or other animals inoculated with sub-lethal amounts of venom. These antivenoms save lives, but they have some serious downsides.
For one, they’re expensive and difficult to make as producing them involves maintaining stables of animals. Plus, they vary in quality as relying on imperfect immune systems yields uneven results, and antivenoms tend to work better against some toxins than others–only partially neutralizing the smallest components of the complex cocktail that is venom, and performing poorly against some species’ bites. They can trigger allergic reactions and other adverse side effects in recipients. And, because they’re a biological product, traditional antivenoms are very sensitive to temperature and need to be refrigerated for storage and transport–adding to the cost and inaccessibility. In rural areas of Global South countries where snake bites are especially common, the treatment is particularly difficult to get.
In contrast, the newly designed proteins are stable across a much wider range of temperatures, can potentially be produced in bulk using microorganisms like yeast, may prompt fewer side effects, and would be easier to fine tune and keep consistent. “These small de novo proteins have a number of really interesting advantages, including thermal stability, the cost of manufacturing, and the fact that they can target something in a way that an antibody might not be able to,” Jardine explains. One day, such a product might be deliverable in an “EpiPen-like device,” readily available out in the field where it’s most needed, he suggests.
Snake venoms are made up of many different toxins mixed together. Vázquez Torres and her colleagues focused their work on three-finger toxins (3FTx), deadly compounds that traditional antivenoms often perform poorly against. 3FTxs are especially prominent in the venom of elapids, the family of snakes which includes cobras, mambas, and coral snakes. These toxins (proteins themselves) wreak havoc in the mammalian body. Some are paralyzing neurotoxins, others destroy cells and damage tissue.
The scientists sought to identify antidote proteins to combat three representative target toxins: a short-chain alpha neurotoxin, a long-chain alpha neurotoxin, and a cytotoxin. All three representative toxins are well studied, and so the scientists knew their intricate shapes from the start. From that base, they could identify the key binding sites they’d need to block to render each toxin inactive. They fed this information into the first of their AI tools called RoseTTAFold diffusion, a model similar to image generators like Dall-E and Midjourney, but one trained and specialized to output mock-ups of protein structures in accordance with requested criteria. In this case, the criteria were the toxin structures and the selected binding “hot spots,” that the researchers were hoping to clog up. The AI offered up dozens of suggestions for neutralizing proteins (in the form of detailed images of protein configurations) that might fill those binding sites–like formulating keys for mystery locks.
To understand more about these theoretical proteins and decode their makeup, Vázquez Torres, Baker and her co-authors deployed a second generative AI model called ProteinMPNN trained to produce feasible combinations of amino acids that could fold together to replicate the diffusion model’s outputs. Protein folding is complicated and often hard to predict from amino acid sequences alone, and on the flipside, it’s challenging to know what amino acid series will lead to which folded shapes. ProteinMPNN accelerates that computational process. Then, they used a third predictive AI tool called AlphaFold2 to independently predict how each of those amino acid strings would actually fold, thus double-checking the work of the prior two models. Between each step, the researchers applied their own expert human eyes to filter out duds and narrow the candidate pool to the best options.
The study authors reverse-translated the most promising amino acid chains into DNA sequences, and then used modified bacteria to pump out the proteins. They tested their top candidates in a set of petri dish experiments with human muscle and skin cells, and found proteins effective against all three focal toxins. This narrowed the pool even further, down to one frontrunner per category. The scientists tested each of these in a series of mouse experiments.
In initial tests, their anti-cytotoxin candidate didn’t reduce skin lesions associated with envenomation, so the researchers ceased testing it. But the other two candidate proteins proved much more effective. When mixed directly with the target toxin, and injected into mice, both anti-neurotoxin proteins prevented all mouse deaths (without the added protective proteins, 100% of mice died).
To mimic the process of treating a bite, the scientists then tested what happened to the mice when each toxin was administered first and the candidate proteins later. One of the proteins saved 100% of the mice it was given to, even administered up to 30 minutes after the toxin. The second protein prevented 80% of deaths administered after 15 minutes and 60% after half an hour.
“It was shocking to see that these proteins work in animals, out of the box. We didn’t need to do any optimization,” says Vázquez Torres. “To find something that works on the first attempt, that’s incredible.” Moreover, the research went from idea to submitted publication data in just about a year, thanks to AI’s computational assistance. “I think it’s like record time for any kind of scientific paper,” she says–demonstrating how much machine learning can accelerate the research process.
The findings are just the latest in a recent wave of new developments in antivenom research, such as Jardine’s synthetic antibodies and re-purposed pharmaceuticals. WHO designated snake envenomation a Neglected Tropical Disease in 2017, prioritizing snake bites for more investment and public health consideration. Since then, there’s been a steady stream of studies. “This is adding another tool to the arsenal that we have to solve the problem. [The proteins] are going to have unique applications that antibodies don’t and vice versa,” Jardine says.
Yet there’s a long road ahead before de novo proteins can be approved for human use. The mouse trials didn’t reveal any apparent negative side effects, though it’s still unknown how these proteins act in the body and if they’re truly safe. They’re totally new molecules, and they’d need to be extensively screened and tested for off-target reactivity and adverse effects, note both Vázquez Torres and Jardine. “We need to prove these molecules are safe. We need to really understand their mechanisms,” says Vázquez Torres. It will be years (and years) before any designer protein antivenom makes it to market.
If it does, the proteins discovered by Vázquez Torres and her colleagues won’t be enough. They only tackle two isolated toxins within certain venoms. Likely, around ten carefully designed proteins would need to be mixed together to neutralize a complete venom, says Vázquez Torres. In the hunt for a broad spectrum or universal antivenom, scientists are still searching.
Still, the prospect of using microorganisms to pump out new-to-nature proteins on demand is thrilling to scientists. And the excitement goes beyond just antivenoms. De novo proteins could one day yield alternative therapies for all sorts of diseases. The amino acid constructions are somewhere between a biologic drug, made or derived from living organisms, and a small molecule drug like aspirin, which is chemically synthesized. “You can imagine a huge number of problems this could solve, that you couldn’t solve with conventional approaches,” Jardin says. “This is a really new way of doing things, and we’re just scratching the surface.”
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