Concentration-Dependent Interactions of Amphiphilic PiB Derivative Metal Complexes with Amyloid Peptides Aβ and Amylin*.
Saida MajdoubZoltán GardaAlexandre C OliveiraInga RelichAgnès PallierSara LacerdaChristelle HureauCarlos F G C GeraldesJean-François MorfinÉva TóthPublished in: Chemistry (Weinheim an der Bergstrasse, Germany) (2020)
Metal chelates targeted to amyloid peptides are widely explored as diagnostic tools or therapeutic agents. The attachment of a metal complex to amyloid recognition units typically leads to a decrease in peptide affinity. We show here that by separating a macrocyclic GdL chelate and a PiB targeting unit with a long hydrophobic C10 linker, it is possible to attain nanomolar affinities for both Aβ1-40 (Kd =4.4 nm) and amylin (Kd =4.5 nm), implicated, respectively in Alzheimer's disease and diabetes. The Scatchard analysis of surface plasmon resonance data obtained for a series of amphiphilic, PiB derivative GdL complexes indicate that their Aβ1-40 or amylin binding affinity varies with their concentration, thus micellar aggregation state. The GdL chelates also affect peptide aggregation kinetics, as probed by thioflavin-T fluorescence assays. A 2D NMR study allowed identifying that the hydrophilic region of Aβ1-40 is involved in the interaction between the monomer peptide and the Gd3+ complex. Finally, ex vivo biodistribution experiments were conducted in healthy mice by using 111 In labeled analogues. Their pancreatic uptake, ∼3 %ID g-1 , is promising to envisage amylin imaging in diabetic animals.
Keyphrases
- pet imaging
- type diabetes
- high resolution
- photodynamic therapy
- cancer therapy
- cardiovascular disease
- magnetic resonance
- positron emission tomography
- electronic health record
- metabolic syndrome
- cognitive decline
- liquid chromatography
- water soluble
- high throughput
- mass spectrometry
- drug delivery
- capillary electrophoresis
- data analysis
- computed tomography
- transcription factor
- machine learning
- binding protein
- high fat diet induced
- wound healing
- artificial intelligence
- energy transfer
- single cell
- deep learning
- molecularly imprinted
- tandem mass spectrometry