Google adds Cheminformatics Skills to Antigravity for chemistry workflow
Google’s Antigravity platform now includes a suite of Cheminformatics Skills that let a language model coordinate data‑wrangling, database navigation and scientific reasoning while deterministic tools perform the actual molecular calculations. The skills are built on the open‑source RDKit toolkit and connect to curated resources such as ChEMBL and PubChem, encoding best‑practice workflows…
Key points
- Google Antigravity now offers Cheminformatics Skills that combine language‑model orchestration with deterministic chemistry tools
- Skills use RDKit and connect to ChEMBL and PubChem to encode domain best practices
- Example shows rigidifying crizotinib into lorlatinib reduces rotatable bonds from five to zero, boosting potency
The walkthrough demonstrates the classic medicinal‑chemistry technique of rigidifying a molecule to improve potency. It compares crizotinib, a first‑generation tyrosine‑kinase inhibitor with five major rotatable bonds, to lorlatinib, a third‑generation analogue that has been cyclized to eliminate rotatable bonds, resulting in higher binding affinity. By adding a second bond in the right location, chemists can lock a molecule into the shape needed for target binding, paying the entropic cost in advance.
The new Cheminformatics Skills aim to free chemists from repetitive data‑integration tasks, allowing them to focus on hypothesis generation and experimental design rather than manual format conversion.
Agentic cheminformatics with Google Antigravity
Google DeepMind · 3 November 2026Loading the full article…
This text was published by Google DeepMind and written by Zoi Tsangalidou, Ruijie (Kelly) Zhang, Sukhdeep Singh and Michael V. LeVine. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
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