[Calculation Example Released] High-Accuracy, High-Speed Binding Energy Evaluation of Cyclin-Dependent Kinase 2 Inhibitors

We have published a new Matlantis application example on the Calculation Cases page.
In this case study, we used universal Machine Learning Potential (PFP) to evaluate the protein-ligand binding energies of six CDK2 inhibitors. This method achieves approximately 34,000 times faster processing while maintaining accuracy comparable to the FMO method, making quantum chemical-level interaction analysis feasible for large-scale compound discovery.

Read the full article here: High-Accuracy, High-Speed Binding Energy Evaluation of Cyclin-Dependent Kinase 2 Inhibitors