Agentic cheminformatics with Google Antigravity
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
Drugs like crizotinib, a first-generation tyrosine kinase inhibitor used to treat non-small cell lung carcinoma, are composed of five major rotatable bonds. Lorlatinib, a third-generation TKI, shares similarities with crizotinib but has undergone cyclization at its end, effectively reducing rotatable bonds to zero and increasing potency.
The cheminformatics skills integrated into Google Antigravity enable an agent to extract molecules from literature, associate them with the reported data, and prepare them for analysis. With these skills, the agent is capable of searching through literature for drugs and their analogues, performing matched molecular pair analysis, and building predictive models using molecular machine learning.
This workflow streamlines drug discovery processes, allowing chemists to focus on hypothesis generation rather than data wrangling.
Written by urgent.news from Google DeepMind's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
