Google DeepMind publishes an antimicrobial peptide workflow run in Antigravity
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Google DeepMind publishes the working process of finding antimicrobial peptide candidates with Antigravity — in a single session a researcher and an agent narrowed down the UniProt entries for Streptococcus pseudopneumoniae and picked a 97-amino-acid bacteriocin candidate (A0A0U0D591, of the Lactococcin 972 family); a Swiss-Prot BLAST found no meaningful sequence homolog, but a structural comparison with AlphaFold DB and Foldseek found a fold almost identical to that of an experimentally checked bacteriocin. Genomic neighborhood analysis checked that it sits in an operon 6 base pairs upstream of an ABC transporter permease, and the write-up goes as far as a wet-lab experiment plan
Why it matters
There is not a single experimental result — no activity, minimum inhibitory concentration or toxicity figures, the candidate is still being checked in the wet lab, and the authors wrote that the experimental results are the real test. So what this post contains is not a discovery but the release of a working flow in which an agent ties literature, structure and genome databases together to produce a hypothesis and an experiment plan. A viewer for three-dimensional biomolecular structures was added inside Antigravity. No peer-reviewed paper or preprint was linked
Source — Primary sources first; secondary reports are labelled “Press”
Officialdeepmind.googlehttps://deepmind.google/blog/accelerating-antimicrobial-discovery/Added in Week 44, 2026 · See that week
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