Partitioning of an Enzyme-Polymer Surfactant Nanocomplex into Lipid-Rich Cellular Compartments Drives In Situ Hydrolysis of Organophosphates.
Benjamin M CarterGraham J DayWilliam H ZhangRichard B SessionsColin J JacksonAdam W PerrimanPublished in: Small (Weinheim an der Bergstrasse, Germany) (2024)
Most organophosphates (OPs) are hydrophobic, and after exposure, can sequester into lipophilic regions within the body, such as adipose tissue, resulting in long term chronic effects. Consequently, there is an urgent need for therapeutic agents that can decontaminate OPs in these hydrophobic regions. Accordingly, an enzyme-polymer surfactant nanocomplex is designed and tested comprising chemically supercharged phosphotriesterase (Agrobacterium radiobacter; arPTE) electrostatically conjugated to amphiphilic polymer surfactant chains ([cat.arPTE][S - ]). Experimentally-derived structural data are combined with molecular dynamics (MD) simulations to provide atomic level detail on conformational ensembles of the nanocomplex using dielectric constants relevant to aqueous and lipidic microenvironments. These show the formation of a compact admicelle pseudophase surfactant corona under aqueous conditions, which reconfigures to yield an extended conformation at a low dielectric constant, providing insight into the mechanism underpinning cell membrane binding. Significantly, it demonstrated that [cat.arPTE][S - ] spontaneously binds to human mesenchymal stem cell membranes (hMSCs), resulting in on-cell OP hydrolysis. Moreover, the nanoconstruct can endocytose and partition into the intracellular fatty vacuoles of adipocytes and hydrolyze sequestered OP.
Keyphrases
- molecular dynamics
- adipose tissue
- ionic liquid
- density functional theory
- mesenchymal stem cells
- cell therapy
- insulin resistance
- high fat diet
- bone marrow
- single cell
- anaerobic digestion
- molecular dynamics simulations
- photodynamic therapy
- fatty acid
- reactive oxygen species
- stem cells
- aqueous solution
- big data
- deep learning
- machine learning
- dna binding
- data analysis
- low cost