Hyunbin Kim

The paper expands the AlphaFold Protein Structure Database to include proteome-scale quaternary structures, predicting 1.81M high-confidence protein complexes and revealing conserved structural clusters across domains of life.

Folddisco efficiently searches for similar protein structural motifs in large databases using a geometric feature index and rarity-based scoring, achieving faster query times and better storage efficiency than existing methods.

This study constructs a reliable PPI network for Magnaporthe oryzae using three computational methods, resulting in a database with 217,531 highly confident interactions.

The paper combines AlphaFold and ESMfold predictions to create a large structural dataset, identifies novel protein folds and domain combinations, and highlights the value of metagenomic data for structural diversity.

The paper identifies and validates four kynureninases using homology searches and protein language models, with the most active one showing significant tumor reduction in mouse models.

This paper uses tertiary-interaction characters to improve structural phylogenetics beyond the twilight zone, achieving accurate results with fast computation.

Foldcomp compresses and indexes large protein structure sets with high efficiency and accuracy, offering faster compression and comparable reconstruction quality.

The paper develops multicolor sensors to directly measure DRD1 and DRD2 receptor crosstalk in a heterodimer and finds differential inhibition of activation by phasic and tonic dopamine levels.

TGFam-Finder re-annotates eukaryotic genomes to identify previously missed protein-coding genes, improving gene family annotation accuracy across multiple species.