Biomathematical screening of amyloid radiotracers with clinical usefulness index

Sensing and modulation of amyloid fibrils by photo-switchable organic dots

Abnormal aggregation of amyloidogenic proteins (like Aβ 42, amylin, α-synuclein, insulin) and the deposition of these aggregates is believed to be associated with several diseases known as amyloidosis. The pathway of aggregation involves three distinct phases: the oligomeric, elongation and plateau phases. Among them, the oligomeric phase of Aβ 42 and α-synuclein involves the generation of transient oligomeric species suspected to cause several neurological disorders, including Alzheimer's and Parkinson's diseases. Over the past few years, scientists have devoted much more effort to devising new fluorescent molecular probes to estimate the mechanisms of formation, and have gained vital information about possible therapeutic routes for amyloidosis. However, such fluorescent probes face serious limitations because of self-quenching at high concentrations of the probe; therefore, they are inappropriate for quantitative analysis and bio-imaging experiments. Hence, smart biocompatible fluorescent probes are indispensable, as they not only overcome the drawbacks of conventional fluorescent probes, but also have the potential ability to fight amyloidosis through modulation of the pathways involved. In this work, for the first time we introduce a series of promising photo-switchable aggregation-induced emission (AIE) dots (DPAPMI, CPMI) and aggregation caused quenching (ACQ) dots (DMAPMI) which can detect amyloid fibrils in terms of switching and enhancing their fluorescence emission. Interestingly, the organic dots enhance the aggregation rate of insulin by speeding up the microscopic processes, specifically secondary nucleation (with rate constant k2) and the elongation process (with rate constant k+). Moreover, the comparison of kinetics studies with ThT suggests that our organic dots can sense pre-fibrillar aggregates of insulin during the aggregation process, which may be beneficial for the early detection of amyloid fibrils. In summary, our study indicates that these organic dots can be used for the imaging and early stage detection of amyloid fibril formation and the modulation of amyloid formation pathways.

Evaluation of the Feasibility of Screening Tau Radiotracers Using an Amyloid Biomathematical Screening Methodology

The purpose of this study is to evaluate the feasibility of extending a previously developed amyloid biomathematical screening methodology to support the screening of tau radiotracers during compound development. 22 tau-related PET radiotracers were investigated. For each radiotracer, in silico MLogP, V _x, and in vitro K _D were input into the model to predict the in vivo K ₁, k ₂, and BP_ND under healthy control (HC), mild cognitive impaired (MCI), and Alzheimer's disease (AD) conditions. These kinetic parameters were used to simulate the time activity curves (TACs) in the target regions of HC, MCI, and AD and a reference region. Standardized uptake value ratios (SUVR) were determined from the integrated area under the TACs of the target region over the reference region within a default time window of 90-110 min. The predicted K ₁, k ₂, and BP_ND values were compared with the clinically observed values. The TACs and SUVR distributions were also simulated with population variations and noise. Finally, the clinical usefulness index (CUI) ranking was compared with clinical comparison results. The TACs and SUVR distributions differed for tau radiotracers with lower tau selectivity. The CUI values ranged from 0.0 to 16.2, with 6 out of 9 clinically applied tau radiotracers having CUI values higher than the recommend CUI value of 3.0. The differences between the clinically observed TACs and SUVR results showed that the evaluation of the clinical usefulness of tau radiotracer based on single target binding could not fully reflect in vivo tau binding. The screening methodology requires further study to improve the accuracy of screening tau radiotracers. However, the higher CUI rankings of clinically applied tau radiotracers with higher signal-to-noise ratio supported the use of the screening methodology in radiotracer development by allowing comparison of candidate radiotracers with clinically applied radiotracers based on SUVR, with respect to binding to a single target.