SOURCE-LINKED INTELLIGENCE
Conformational determinants of enzymatic per- and polyfluoroalkyl activation and selectivity
varying chain-lengths and fluorinated versus non-fluorinated compounds. Strikingly, fluoro-selectivity already occurs in enzymes in nature. Here, I propose to use a combination of bioluminescence and machine learning to decipher the fluoro-selectivity code of natural enzymes that undergo conformational changes in response to different PFAS. In tandem, I will establish a new method using a fluoro-selective resistance mechanism to discover environmental enzymes capable of breaking down fluorinated compounds. Finally, I will take advantage of the close structural similarity between firefly luciferases - the enzymes that enable fireflies to glow - and natural PFAS-activating enzymes known as acyl-CoA ligases. Leveraging this evolutionary relationship, I will construct fluoro-selective, bioluminescent enzymes to enable the design of real-time, in situ, and chain length-specific PFAS biosensors. Mapping the first blueprint of enzymatic fluoro-selectivity will enable precision applications in environmental PFAS monitoring and remediation. More fundamentally, this work aims to reveal the u
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 1500000
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T04:21:15.460Z. This is not the publication date.