Insilico Cryptic Pocket Detection and ligandability assessment

Find allosteric sites, expand IP, explore sub-pockets, determine selectivity, and distinguish ligandable from non-ligandable binding sites.

Using enhanced sampling simulations, sample conformations of an apo or holo protein structure to generate a conformation ensemble to detect pockets, then rank the pockets based on our AI-based ligandability model. 

Detect pockets that are both induced fit and conformationally selected using exposon analysis, dynamic probe binding (invented at OE), and probe binding analysis.

Start with normal mode- and experimentally-driven (Cryo-EM map) coordinates.