Intelligent Screening of Functional Small Molecules for Targeting Metal-Induced Protein Aggregation

Screening small-molecule drugs to suppress protein aggregation and the production of reactive oxygen species (ROS) is one of the primary directions for drug development in neurodegenerative diseases (NDs). However, current methods often have difficulty in striking a balance between accuracy and simplicity. In this work, we constructed active peptide interfaces to intelligently screen potential drugs for metal-induced protein aggregation with a logic network. Taking β-amyloid peptide (Aβ), which is closely related to Alzheimer's disease (AD), as an example, we covalently connected Aβ onto the gold electrode surface and characterized the aggregation state of Aβ induced by copper ions (Cu(II)) through electrochemical impedance spectroscopy (EIS). The formed Aβ-Cu(II) complex interfaces were also used to study the catalytic production of ROS and the ameliorative effect of potential drugs on oxidative stress by the ultraviolet (UV) spectrum of ascorbic acid (AA). By constructing a comparator logic network using EIS and UV signals, the potential small molecules targeting Aβ-Cu(II) aggregations could be classified into 4 different types of effects. Transmission electron microscopy (TEM), cytotoxicity, and ROS assays were used to verify the reliability of the classification. The corresponding results of using α-synuclein (α-Syn) instead of Aβ indicated that this intelligent screening platform might provide a general route for potential NDs' drug screening.