The approach involves in-depth molecular simulations of the target protein by itself and in complex with its primary partner proteins, paired with ensemble virtual screening that factors in conformational mobility in both the unbound and complex states. The tentative binding pockets are identified at the protein-protein interaction interface and in distant allosteric areas, aiming to capture the full range of mechanisms of action.

Key features that set our library apart include:

• The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.


• The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.


• With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.


• Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.