Agentic cheminformatics with Google Antigravity
Agentic cheminformatics with Google Antigravity
Google describes Cheminformatics Skills for Google Antigravity that pair a language model for workflow orchestration and scientific reasoning with deterministic RDKit-based tools and ChEMBL/PubChem connectors. In a lung cancer walkthrough, an agent retrieved thousands of compounds, ran matched molecular pair analysis, built potency models, and proposed rigidified macrocycles with synthesis routes in about an hour. The authors note that sparse data and assay noise limit predictive precision, so computational designs remain testable hypotheses requiring experimental validation.
It offers a concrete, technically detailed example of agent-assisted drug discovery, including both demonstrated capabilities and stated limitations.
Source: Google DeepMind · deepmind.google