Atomic insights into the signaling landscape of E. coli PhoQ histidine kinase from molecular dynamics simulations.
Symela LazaridiJing YuanThomas LemminPublished in: Scientific reports (2024)
Bacteria rely on two-component systems to sense environmental cues and regulate gene expression for adaptation. The PhoQ/PhoP system exemplifies this crucial role, playing a key part in sensing magnesium (Mg 2+ ) levels, antimicrobial peptides, mild acidic pH, osmotic upshift, and long-chain unsaturated fatty acids, promoting virulence in certain bacterial species. However, the precise details of PhoQ activation remain elusive. To elucidate PhoQ's signaling mechanism at atomic resolution, we combined AlphaFold2 predictions with molecular modeling and carried out extensive Molecular Dynamics (MD) simulations. Our MD simulations revealed three distinct PhoQ conformations that were validated by experimental data. Notably, one conformation was characterized by Mg 2+ bridging the acidic patch in the sensor domain to the membrane, potentially representing a repressed state. Furthermore, the high hydration observed in a putative intermediate state lends support to the hypothesis of water-mediated conformational changes during PhoQ signaling. Our findings not only revealed specific conformations within the PhoQ signaling pathway, but also hold significant promise for understanding the broader histidine kinase family due to their shared structural features. Our approach paves the way for a more comprehensive understanding of histidine kinase signaling mechanisms across various bacterial species and opens the door for developing novel therapeutics that target PhoQ modulation.
Keyphrases
- molecular dynamics
- molecular dynamics simulations
- gene expression
- density functional theory
- signaling pathway
- escherichia coli
- fatty acid
- single cell
- protein kinase
- pseudomonas aeruginosa
- tyrosine kinase
- staphylococcus aureus
- ionic liquid
- machine learning
- small molecule
- risk assessment
- pi k akt
- artificial intelligence
- single molecule
- genetic diversity
- deep learning
- climate change
- endoplasmic reticulum stress
- induced apoptosis