.png){kind=icon}
.png){kind=icon}
Return
Permeable by design
.png){kind=icon}
PRE
AI
DOI：10.1038/s41570-026-00871-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Mycobacterial drug discovery is held back by the challenge of limited compound penetration across the mycomembrane. An experimentally enabled machine-learning approach identifies permeability-promoting molecular features that could help guide medicinal chemistry toward more permeable antibacterial candidates.
Journal
IF:
51.7
Papers:
1.0K
Citations:
1.6W