Antimicrobial resistance now kills at least 1.27 million people a year and is linked to almost five million deaths, making common infections progressively harder to treat. Meanwhile, the pipeline for new antibiotics has slowed, but animal venom offers new hope amid fears of a post‑antibiotic era.

Using deep-learning tools, researchers mined 40 million venom‑encoded peptides collected from snakes, scorpions, spiders, and other animals. They pinpointed 386 molecules with the hallmarks of powerful antibiotics.

The work was led by César de la Fuente at the University of Pennsylvania, who specializes in machine biology and antibiotic discovery.

Old toxins, new treatments

Decades ago, a peptide from the Brazilian pit viper inspired captopril, the first ACE inhibitor for hypertension, proving that toxins can be tamed for therapy.

More recently, FDA‑approved ziconotide, derived from cone snail venom, has provided severe pain relief without opioids.

Those successes hint at a vast pharmacological trove hidden in venoms, yet only a fraction of the peptides they contain have been examined.

Digital screening can accelerate that search beyond what manual experiments allow.

Venom holds rare chemistry

Venomous animals have evolved specialized chemistries for offense or defense over millions of years. These chemistries generate peptides that slice into nervous systems, coagulation pathways, and bacterial membranes.

Because each species fine‑tunes its arsenal, the combined library covers many chemical shapes rarely found in conventional drug collections.

The Penn team compiled proteins from four databases, representing cone snails, spiders, snakes, scorpions, and more. This diversity fed the AI with sequences spanning more than 16,000 proteins.

The model then shredded these sequences into over 40 million candidate peptides.

Antibiotic candidates found in venom

APEX turns each animal venom peptide’s sequence into numbers that reflect traits like charge and water-repellence. Then, it predicts how much of each peptide is needed to stop the growth of 34 different bacterial strains.

Sequences predicted to inhibit growth at 32 micromoles per liter or less advanced to a similarity filter that weeded out peptides too close to known antibiotics.

The filter left 386 candidates that occupied unexplored corners of peptide sequence space. This ensured any hits would add new chemical diversity. Crucially, the whole triage ran in a few hours on standard graphics‑processing hardware, a pace impossible for wet‑lab screening.

“Venoms are evolutionary masterpieces, yet their antimicrobial potential has barely been explored,” said César de la Fuente. His lab’s strategy turns that evolutionary advantage into a search engine for urgently needed drugs.

The platform also found over 2,000 new short sequence patterns that help break bacterial membranes -useful building blocks for future antibiotics.

Peptides killed drug-resistant bugs

The researchers synthesized 58 of the AI‑ranked peptides and challenged them against drug‑resistant strains of Escherichia coli and Staphylococcus aureus; 53 wiped out the bacteria at doses that left human red blood cells unharmed.

“By pairing computational triage with traditional lab experimentation, we delivered one of the most comprehensive investigations of venom‑derived antibiotics to date,” said Marcelo Torres, a research associate at Penn.

Torres noted that the most potent peptides came from spiders, mirroring the predators’ need to immobilize prey quickly.

One standout candidate knocked down Acinetobacter baumannii infections in mice by up to 99 percent after a single topical dose. The animals showed no weight loss or other toxicity signs, an early but encouraging safety signal.

Venom bypasses resistance paths

Most classic antibiotics block enzymes, so single genetic tweaks can disarm them, but venom peptides that destabilize bacterial membranes face fewer resistance routes.

Animal venom hits carried strong positive charges and balanced hydrophobic residues, a combination that latches onto the negatively charged bacterial surface and punches holes in it.

Fluorescence assays confirmed that 26 peptides swiftly collapsed the cytoplasmic membrane potential in Pseudomonas aeruginosa.

Outer membrane permeabilization played a smaller role, suggesting depolarization is their primary kill step.

This mechanism works like human defensins but uses new sequences that bacteria haven’t seen, making resistance unlikely – and because human cells have cholesterol and a neutral charge, they aren’t harmed in the same way.

Venom worked without harming cells

Testing in human kidney cells found that most scorpion and cone snail peptides were benign at concentrations far above their antibacterial doses.

A handful of spider peptides showed cytotoxicity, guiding the team to prioritize safer scaffolds.

In the mouse skin‑infection model, the lead spider peptide cut bacterial counts by roughly three orders of magnitude without harming the animals.

Pharmacokinetic tweaks such as end‑capping or non‑natural amino acids could further prolong its activity and reduce dosing frequency.

Computational screens suggest 40 percent of candidates likely avoid potassium channels, a common off-target for cationic peptides. Electrophysiology studies now under way will test that prediction before systemic trials begin.

What’s next for venom-based antibiotics

Medicinal chemists are refining the top animal venom hits to sharpen selectivity, resist protease degradation and improve serum half‑life.

Machine‑learning feedback loops will retrain APEX with every new data point, steadily raising prediction accuracy.

Regulatory hurdles remain, yet the researchers argue that topical use in skin or burn infections could reach patients faster than systemic applications.

Researchers can also pair peptide antibiotics with existing drugs to delay resistance evolution.

The goal is a pipeline where venom data trains artificial intelligence, AI guides chemistry, and chemistry delivers antibiotics in months. If realized, that loop could turn the tide in the struggle against superbugs.

The study is published in Nature Communications.

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