Cone snail toxin has inspired a breakthrough in drug discovery

Toxins can give valuable insights into how molecules interact with biological targets, helping scientists design safer and more effective compounds.

Whether for life-saving drugs, species control, or agriculture, understanding a molecule’s precise targets is crucial for ensuring its safe and effective use.

Researchers at the Weizmann Institute in Israel have developed an innovative AI-powered pipeline to predict how natural toxins interact with proteins.

By combining artificial intelligence with traditional research methods, they are unlocking new possibilities in ecological studies and drug development.

Secrets of a deadly snail toxin

The journey of these scientists kicked off from an unlikely source – a toxin from the cone snail (Conus striatus) that affects both insects and fish. This protein is composed of 60 amino acids and is shot into the prey by the snail using a sharp barb.

Dr. Izhar Karbat and Dr. Eitan Reuveny set out to investigate how the cone snail toxin Conkunitzin-S1 (Cs1) works to immobilize fish, despite not affecting mammals or mollusks.

The experts found that Cs1 blocks potassium channels that are central to cell function in fruit flies and other insects. However, the molecular target of this toxin in fish remained a mystery.

Turning to AI for answers

Unable to pinpoint the target of the Conkunitzin toxin using traditional methods, the scientists turned to artificial intelligence.

“Three years ago, we tried our best tools at the time to find the target of the Conkunitzin toxin, and we failed because the tools were not good enough. And then came a big revolution in structural biology driven by artificial intelligence,” said Karbat.

This presented an invaluable tool for their research, which enabled the experts to use a two-pronged approach to identify the fish potassium channels that were most vulnerable to Cs1.

They harnessed the power of AlphaFold, an AI program, to predict how the toxin might bind to different fish potassium channels.

Next, the researchers developed another AI model, ET3, to analyze how water molecules navigate around these channels.

AI pinpoints the toxin’s true targets

By leveraging ET3 to analyze a broad range of fish potassium channels – beyond what was previously possible – the experts identified the exact channels targeted by Cs1 and how the toxin disrupts their function.

Essentially, if potassium channels act as tiny doors regulating ion flow in and out of cells, Cs1 functions like a lock that jams those doors shut.

“Using molecular dynamics and the new AI-driven structural tools, we were able to find the small subset of channels in fish which bind our toxins with high affinity and are probably the real target of the cone snail,” said Dr. Karbat.

Identifying precise targets for new drugs

Beyond unraveling the mystery of Cs1’s impact on fish, the researchers see broader applications for their AI-powered approach.

“This new pipeline offers exciting opportunities and future prospects with ecological studies, to study real chemical interactions in real ecological systems,” said Dr. Karbat.

Additionally, the same methodology could be applied to drug development, helping to identify precise targets for new drugs while avoiding unintended interactions.

“If you develop a drug that would activate a channel in the human brain, you wouldn’t want the same drug to affect a channel in the human heart and cause a heart attack,” noted Dr. Karbat.

“The power of this pipeline is that we can concentrate on a target, or any molecule that we are interested in, and find its match,” added Dr. Reuveny, emphasizing the effectiveness of this approach. .

Expanding AI’s role in molecular research

The success of this AI-powered pipeline extends far beyond the study of cone snail toxins.

The ability to predict molecular interactions accurately could transform the way scientists approach drug discovery, environmental toxicology, and even disease treatment.

One of the most promising applications lies in developing highly specific drugs that target only the intended receptors, thus minimizing side effects. By refining molecular targeting, AI can help create treatments that are both safer and more effective.

Additionally, this approach could be used to study natural toxins other than Cs1, such as venom components from other marine creatures, snakes, scorpions or even plants.

Understanding how these compounds interact with biological systems could inspire new medical treatments, from pain relief to antimicrobial drugs.

The research also holds promise for ecological conservation. By mapping how toxins influence different species, scientists can better predict how environmental changes or chemical pollutants may affect ecosystems.

As AI continues to revolutionize molecular biology, tools like AlphaFold and ET3 will likely become standard in many areas of research, bridging the gap between computational predictions and real-world biological interactions.

The work will be presented at the 69th Biophysical Society Annual Meeting in Los Angeles.

Image Credit: Courtesy of Eitan Reuveny and Izhar Karbat.

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