Open access
Oct 2026
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.
Omid Mokhtari, Amirhosein Naghsh-Nilchi, B. Grüning et al.
· bioRxiv · 0 citations