Identification and mapping of functional states

By leveraging the evolutionary information we can identify coevolving residues that are in contact in alternative conformational states than the starting conformation. The strong coupling between function and evolution enables constricted exploration of only functionally relevant states. 

This enables complete mapping of functionally relevant states, and identification of state-dependent pockets and is a perfect start for early drug discovery or in-silico screening for functional profiling.

AI Generation of novel compounds 

By harnessing the big data that is generated by our methodology one can design a by analysing the requirements of complementarity in the drug binding site. Our analysis is generally superior to static methods thanks to the hollistic integration of thermodynamics, structure and allostery to decode molecular interactions and the complex interplay of protein-ligand interactions.

Protein-ligand interaction and allostery analysis

Due to patent pending compounds and abundance of sensitive information, it is important that we can deliver our technology without having any information about the internal research of our clients.

Through this model, we can offer a system that is tested, set-up and ready to be simulated with a modified version of the GROMACS suite where any internally interesting compounds can be added and screened for either function or binding. Any training or knowledge transfer is always included.

Cross-reactivity experiments and in-silico screening of compounds

Inspired by the data-rich sequence datasets available for many protein families, we have successfully built a family-wide sequence-aware decoder through which we can build powerful molecular descriptors applicable to many members of one family simultaneously.

This enables cross-reactivity experiments of the same compounds to many different targets while keeping the molecular detail, experimental accuracy and the speed that are the hallmarks of our technology.