Yehlin Cho

The paper measures protein stability for 1.8 million domains using a new experimental method and develops models that accurately predict stability with high precision.

This study presents a joint optimization approach for modeling protein conformational landscapes and sequence design, showing improved stability prediction and sequence generation.

This study shows that large protein language models can predict homo-oligomeric interface contacts, with performance improving with model size and alignment diversity.

Protein Hunter uses diffusion models to design proteins de novo by iteratively improving sequence and structure through hallucination and re-design.

BoltzDesign1 inverts AlphaFold3 to design protein binders for diverse targets without model finetuning, achieving high in silico success rates and structural diversity.

Hallucinating binders by backpropagating through AlphaFold2 weights gave, across 12 targets, binders in 10-100% of the designs tested per target, mostly at nanomolar affinity.