Daichi Shonai

Reward-guided inference-time search over the Proteína-Complexa sequence-structure codesign model yields validated binders across 127 targets, kinases and a free carbohydrate, with codesigned sequences outperforming ProteinMPNN redesign.

The paper uses in vivo proteomics and CRISPR screening to identify STXBP1 as a protective factor against α-synuclein toxicity in dopamine neurons in Parkinson's disease models.

The paper introduces KolossuS, a deep learning framework for kinase-substrate prediction, integrated with CRISPR-based proximity proteomics to identify kinase substrates in vivo, including novel substrates associated with sleep deprivation.

Raygun is a generative AI framework that miniaturizes, modifies, and expands proteins while preserving function and structural integrity, validated through cell-based experiments.

The paper develops a proximity proteomics method in mice to identify protein interactions relevant to autism, revealing new genetic risk factors and functional interactions.