Radoslav Krivák

The paper analyzes AlphaFold's predicted binding pockets to determine their similarity to apo or holo states, finding most are holo-like and showing how state affects docking success.

CryptoBench introduces a dataset and benchmark for cryptic protein-ligand binding sites, showing sequence-based methods outperform structure-based ones in prediction accuracy.

AHoJ retrieves apo and holo protein structures for user-defined ligands by aligning and classifying structures based on binding site similarity.

PrankWeb provides a web interface for ligand binding site prediction using P2Rank, allowing visualization and export of results.