CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...

In this video, Arc Institute Postdoctoral Fellow Vincent Tran walks through MULTI-evolve, an AI-guided framework that compresses protein engineering from months of iterative experimentation into weeks ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20 100 possible variants—more combinations than atoms in the observable universe.

A generalizable ML framework predicts protein interactions with ligand-stabilized gold nanoclusters, supporting faster design of bioimaging, sensing and drug delivery materials. (Nanowerk News) The ...

Structural biology is shifting from predicting protein shapes to uncovering broader organizational rules; AI tools like AlphaFold have made large-scale protein structure data far ...