Approaches making virtual and experimental screening more resource-efficient are vital for identifying effective inhibitors from a vast pool of potential drugs but remain elusive. Here, the authors address this issue by developing an active learning framework leveraging high-throughput molecular dynamics simulations to identify potential inhibitors for therapeutic applications.
- Katarina Elez
- Tim Hempel
- Frank Noé
