01CAPITAL
The commitment combines funding, data, computation and new measurement technology, and Biohub calls it the largest coordinated commitment to generating AI-ready biological data to date. DOE will invest more than $500 million over five years, NIH will coordinate datasets from more than $500 million in prior federal investment, and Google DeepMind, Isomorphic Labs and Meta are collectively investing $300 million.
Biohub ↗02DEALS
Chai says its models generated designs to GSK targets zero-shot, without target-specific training, and that GSK's internal wet-lab testing found binders to all tested targets. GSK will gain access to Chai's platform, including its protein folding and design models, across its pipeline. GSK's Christopher Austin said the technology complements GSK's internal models, which it continuously retrains against its own wet-lab data.
Chai Discovery (BioSpace) ↗03AI / BIO
AlphaProtein Novo is a machine-learning pipeline that designs enzymes from first principles instead of starting from natural sequences, and Google DeepMind says it outperforms natural sequence mining on challenging chemistry. It produced new-to-nature nitrene transferases that make the pharmacophore piperidine with unprecedented product selectivity, and enzymes that degrade the environmental toxin DEHP under conditions that denature natural enzymes. It also reached state-of-the-art catalytic efficiencies on two well-studied model reactions.
bioRxiv (Google DeepMind) ↗
