Experimental-accuracy RBFE calculations (call for collaborations)

At Acellera we’re developing QuantumBind®, our new platform for automated small-molecule potency optimization via binding free energy calculations and ML.

In a recent publication, we demonstrate our competitive performance versus industry leader FEP+ on several targets in terms of correlation and accuracy for Relative Binding Free Energy (RBFE) calculations. Our ATM-based implementation of RBFE together with existing Neural Network Potentials (NNPs) achieves sub-1 kcal/mol accuracies for a series of congeneric ligands.

On top of these results, we’re developing new active learning protocols, more accurate ML models, and improved quantum mechanics-based NNPs to fully streamline potency optimization for hit-to-lead and lead optimization discovery stages. Stay tuned for more news in this front.

Looking for beta testers

If you’re a pharma or biotech company looking for better binding affinity prediction and optimization capabilities, we want to hear from you. We’re looking to partner with companies large and small to continuously improve our technology and together find better novel drugs.

If you’re interested, get in touch.