Targeting ATP synthase of Acenobacter baumannii
Utilizing Receptor.AI’s novel approach to overcome multidrug resistance
122
hit candidates selected
11
compounds tested
2
potent compounds identified
4 μM
IC50 value reached with the first iteration
01/ Background
- A. baumannii is responsible for threatening hospital infections.
- The goal is to develop inhibitors for A. baumannii ATP synthase, which would counter the drug resistance mechanism.
02/ Methodology
- Pocket identification performed using Receptor.AI's pocket detection pipeline with proprietary AI model.
- 8M stock library subjected to virtual screening.
- AI docking with ArtiDock and target-specific AI rescoring.
- 122 hit candidates selected with smart consensus function.
- 11 compounds subjected to bacterial growth assay.
- The antimicrobial effect of inhibitors (IC50) was determined.
03/ Binding Pockets
- 2 binding pockets identified.
- One pocket identified in the lagging target’s functional state and the other in the leading state.
- Both pockets used for docking with ArtiDock.
*Structure of ATP synthase with the lagging (left)
and leading (right) binding sites
04/ Screening Results
- 2 hits confirmed with IC50 12.5 μM and 4 μM.
- Both shown to be safer on human cells than existing competitors.
