Accelerating the search for antimicrobial peptides with Google Antigravity

Pengfei Tian, Maxwell L. Bileschi, Zoi Tsangalidou, Sukhdeep Singh and Lucy J. Colwell

New antibiotics are urgently needed to help with rising levels of antimicrobial resistance, but searching for new therapeutics is often a slow, labor-intensive process. With Google Antigravity, our agentic development platform, this process can now be made easier.

Google Antigravity provides an agentic science workbench that empowers biologists to discover, structurally evaluate, and prioritize promising targets quickly, compressing what used to be a fragmented search over multiple databases into a single session. It also helps researchers scan through millions of previously uncharacterized proteins in the UniProt database using ProtNLM, a model that predicts biological function from amino acid sequences.

A protein's 3D structure can help us understand its biological function. Examining a candidate’s predicted fold in space is key. To provide this end-to-end workflow in a single workspace, we are introducing the Biomolecular Structure Viewer , a 3D visualization tool embedded directly into Antigravity.

Historically, uncovering insights like those in the workflow demonstrated above required fragmented and specialised software: writing custom scripts to query databases, manually exporting files to 3D modelling programs, managing disconnected genomic tools and working with multiple experts to design the wet lab assays. Because wet-lab validation remains resource-intensive, narrowing the search space to only the highest-confidence leads upfront is critical. Using Google Antigravity allows researchers to navigate the vast biological search space efficiently while leveraging accurate protein function predictions from a domain-specific model.

This technical walkthrough shows how biologists used Google Antigravity to uncover a novel antimicrobial peptide candidate which has predicted activity against the pathogens involved in respiratory tract infections. The lead identified here is now undergoing wet-lab validation.

Rising antimicrobial resistance is one of the most pressing global health crises of our time and could result in an estimated 10 million annual deaths globally by 2050. To prevent this, we urgently need to discover novel therapeutics. Antimicrobial peptides (AMPs), particularly bacteriocins, offer a promising alternative to traditional antibiotics because they have naturally evolved to target fundamental vulnerabilities in competing bacteria, from cell envelopes to essential intracellular machinery, making it difficult for pathogens to develop resistance.

The exponential growth of genomic and metagenomic sequencing has populated global databases with billions of natural amino acid sequences. This pool of natural data has already produced globally used bacteriocins like Nisin, alongside recent genome-mined breakthroughs such as Darobactin, Dynobactin, and Lariocidin.