Determine the synthesis priority

  • Hyper Binding uses artificial intelligence to predict drug-protein binding energy.
  • The stronger the prediction value (binding score), the higher the probability of showing activity.
  • A molecule with a binding score of -10 kcal/mol is more likely to be active compared to a molecule with -8 kcal/mol.
  • This process can be easily performed with just a few clicks.


Easier and more accurate than docking

Millions of drug-protein data and binding structures are used, making it more powerful. Unlike docking, it can be easily used by experimental researchers as well.


Hyper Binding


Number of parameters 

 ~Several miliions


Core technology

Physics informed deep learning

A few simple physics equation


Experimental researchers can also use easily.

Mainly for CADD experts




Show high correlation with experiments

Hyper Binding shows a higher correlation with experimental values compared to conventional docking and other deep learning models.


Visualize the three-dimensional binding structure

  • With just one click, you can visualize the three-dimensional structure and analyze interactions between ligands and proteins.
  •  You can obtain ideas for molecular design to improve biological activity.


Artificial Intelligence Model in Hyper Binding

  • Hyper Binding uses a physics informed deep learning model.
  • By combining physical principles with deep learning, it shows high predictive performance even with limited data.
  • Hyper Binding is continuously becoming more accurate by refining physical principles and learning from an increasing amount of data.