Coming soon: Introducing Scorpius
Scorpius combines our proprietary network methods with new machine-learning infrastructure to address the "affinity gap" that traditional AI models cannot bridge.
It is designed to deploy directly into your existing Proasis environment, providing:
Enhanced protein-ligand affinity
Accurate ranking of low molecular weight, high-affinity leads.
Antibody-antigen ranking
Surface-based descriptors that excel where evolutionary-trained models fail.
Predictive precision
Moving beyond "black-box" AI to interpretable, scientifically grounded results.
Rationalising molecular recognition through small world network theory.
Beyond visualisation
Scorpion goes beyond simple visualisation to provide a quantitative understanding of the binding process. By calculating the network of interactions to produce a Scorpion Score, it helps researchers rank and prioritise compounds based on structural affinity.
Strategic benefits
Data-driven prioritisation
Reduces reliance on trial and error, allowing for more focused and efficient lead optimisation.
Network theory
Applies foundational "small world network" theory to understand the complex forces driving tight binding.
Precision scoring
Integrated with Viper AI to rank automated designs against structural reality.
With Scorpion, you can stop relying on trial and error. Request a demo to see how Scorpion can add value to your workflow.
