Machine learning and AI dominate recent developments in computing.  DesertSci is uniquely placed to apply ML/AI in the field of scoring protein-ligand binding affinity.

With Scorpion, our empirical scoring function developed in collaboration with top experts in the field, we have unparalleled know-how in building ranking methods.

With Proasis, our protein-structure database system, we have extensive knowledge in working with large quantities of 3D protein-ligand coordinate data.

Together, with new AI technology, we will unlock the key factors driving tight ligand binding … ranking better, faster.  Our software will identify the top drug candidates, among a sea of others, and deliver them to your scientists all day, every day.

Better Ranking = Better Drug Candidates in Larger Quantities

Meaning  real savings, in both time and money, during the early stage drug discovery process.

We are creating a ranking scheme based purely on protein structure data rather than relying on experimental affinity data, because the latter is severely limited by the availability of high-quality data. Furthermore, our strategy focuses on creating a ranking scheme based on non-covalent interactions, network descriptors, and protein flexibility.

Our ML technologies are a work in progress but early results are extremely promising.  We are developing the technology at a fast pace and look forward to testing our methods extensively amongst the Desertsci user community.

Watch this space …