GoKawiilResearchers use AI protein design to create enantioselective metal photocatalysts
Scientists report using generative protein design to build entirely new protein scaffolds that bind metal polypyridine photocatalysts, which previously lacked natural protein partners capable of enantioselective control. Directed evolution refined these designed proteins into artificial metalloenzymes that perform efficient, highly enantioselective light-driven reactions, including with cheap racemic metal complexes, and support high catalyst turnover and recycling. Spectroscopy showed the protein environment extends the photocatalyst's excited-state lifetime and positions substrates to control stereochemistry.
GoKawiil's interpretation of the reporting above, not reported fact.
This suggests a general route for pairing synthetic catalysts with custom-built protein scaffolds rather than relying on naturally occurring proteins, potentially broadening the range of metal catalysts that can be made enantioselective. It could open new possibilities for sustainable, light-driven asymmetric synthesis in pharmaceuticals and fine chemicals, though practical industrial application would likely require further scale-up and optimization.
- Generative AI protein design created new scaffolds for metal photocatalysts lacking natural protein partners
- Directed evolution turned these scaffolds into highly enantioselective, efficient photocatalysts
- The approach works with inexpensive, commercially available racemic metal complexes, aiding practicality
Source: nature.com — Mishra, 2026-10-21
Published there as: “<i>De novo</i> design of enantioselective artificial metalloenzyme photocatalysts”
Read the original report → The summary and analysis above are GoKawiil's own, written from reporting by the source above. Facts and quotes belong to the original publisher.