Google DeepMind uses Antigravity and ProtNLM to find an antimicrobial peptide candidate
Overview
Google DeepMind says researchers used its Antigravity agentic development platform and the ProtNLM model to identify a novel antimicrobial peptide candidate predicted to act against pathogens in respiratory tract infections.
The workflow, shown in a DeepMind walkthrough, runs in one session and combines UniProt searches, AlphaFold structure analysis and a 3D structure viewer.
The candidate is a computational lead only. DeepMind says it is now undergoing wet-lab validation and that it still requires that validation to be confirmed as biologically active.
Written by AI from the articles below · updated Oct 15, 12:59 PM ET
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- Google DeepMindOfficialGoogle uses Antigravity agent to find a candidate antimicrobial peptide
AIGoogle researchers used its Antigravity agentic development platform and ProtNLM model to identify a novel antimicrobial peptide candidate with predicted activity against pathogens in respiratory tract infections. The candidate is a computational lead that is now undergoing wet-lab validation. The workflow runs in a single session, combining UniProt searches, AlphaFold structure analysis and a 3D structure viewer.
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