Amirhosein Naghsh-Nilchi

SIMORGH: Ensemble-Aware Geometric Deep Learning for Apo-State and Cryptic Ligand Binding Site Prediction

SIMORGH consistently outperforms existing static and dynamics-aware methods under the challenging ligand-free setting, while identifying cryptic binding pockets, maintaining strong prediction consistency between paired apo and holo structures, and scaling efficiently to large multi-chain complexes.