Alpha-Syn-Cu (II) modified electrode and application thereof

Abstract

The invention discloses an alpha-Syn-Cu (II) modified electrode and application thereof. The alpha-Syn-Cu (II) modified electrode comprises a gold electrode, a covalent connecting layer, alpha-Syn and Cu (II), wherein the surface of the gold electrode is covered with the covalent connecting layer, the alpha-Syn is connected to the covalent connecting layer, and the Cu (II) is combined with the alpha-Syn. According to the alpha-Syn-Cu (II) modified electrode provided by the invention, ECL and CV double signals reflecting the alpha-Syn aggregation condition and the accompanying ROS generation condition can be obtained at the same time by utilizing a single test, and a potential anti-PD drug can be comprehensively evaluated based on the double signals. In addition, the alpha-Syn-Cu (II) modified electrode provided by the invention has the advantages of being short in test time, capable of being repeatedly used, capable of saving the dosage cost of alpha-Syn and the like.

Description

Technical Field

[0001] This invention relates to the field of electrochemistry, and more particularly to an α-Syn-Cu(II) modified electrode and its application. Background Technology

[0002] Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease, with its incidence increasing significantly with age, posing a serious threat to public health in aging societies worldwide. Pathologically, one of the most prominent features of PD is the development of contents within the Lewy bodies at the synaptic terminals of dopaminergic neurons in the substantia nigra, the main component of which is misfolded and aggregated α-synuclein (α-Syn). In PD patients, α-Syn has been shown to undergo rearrangement and remodeling, misfolding to form β-sheet-rich oligomers, which further aggregate into insoluble oligomers and filaments. Multivalent metal ions, including Cu(II), are thought to bind to α-Syn via complexes, where α-Syn acts as a ligand and the multivalent metal ion acts as a metal center, promoting the fibrillation process of α-Syn. On the other hand, in addition to enhancing Lewy body formation, Cu(II) also synergistically promotes the production of reactive oxygen species (ROS) with α-Syn.

[0003] Current efficacy assays for potential anti-PD drugs targeting α-Syn mainly focus on functional testing for inhibiting aggregation / depolymerization. Electrochemical techniques, due to their high sensitivity, ease of operation, and low cost, have been designed for the quantitative detection of different forms of α-Syn aggregates. The signal primarily originates from antibody- or aptamer-modified electrodes capturing α-Syn in solution. However, the requirement for antibodies and the presence of proteins in the solution phase contribute to high costs. Furthermore, most existing electrochemical sensors can only detect the quantitative or aggregated state of α-Syn independently.

[0004] As mentioned above, altered aggregation state of α-Syn and metal ion-induced ROS production are considered important causes of degenerative neurodegenerative diseases. Detecting only altered aggregation state of α-Syn or only ROS is a rather one-sided evaluation of the efficacy of potential anti-PD drugs targeting α-Syn.

[0005] Therefore, it is necessary to develop a screening / evaluation system for potential anti-PD drugs targeting α-Syn by simultaneously detecting the inhibitory aggregation / depolymerization function against α-Syn and detecting ROS. Summary of the Invention

[0006] The purpose of this invention is to provide an α-Syn-Cu(II) modified electrode and its use in screening potential anti-PD drugs targeting α-Syn.

[0007] To achieve the above objectives, a first aspect of the present invention provides an α-Syn-Cu(II) modified electrode, comprising:

[0008] Gold electrode,

[0009] A covalent bonding layer covering the surface of the gold electrode.

[0010] α-Syn connected to the covalently linked layer, and

[0011] Cu(II) that is combined with the α-Syn.

[0012] In some embodiments, the covalent linking layer comprises mercaptoundecanoic acid and mercaptohexanol.

[0013] In some embodiments, the molar ratio of mercaptoundecanoic acid and mercaptohexanol in the covalent linking layer is 1:2-3.

[0014] In some implementations, the α-Syn is attached to the covalently linked layer via the following process:

[0015] The gold electrode covered with the covalent bonding layer is contacted with an α-Syn solution with a concentration of 30-70 μM for 6-12 hours.

[0016] In some embodiments, Cu(II) binds to the α-Syn via the following process:

[0017] The gold electrode connected to the α-Syn was brought into contact with a Cu(II) solution with a Cu(II) concentration of 30-70 μM for 1-3 hours.

[0018] In some embodiments, the Cu(II) solution and the α-Syn solution used to attach α-Syn to the covalent bonding layer have the same concentrations of Cu(II) and α-Syn, respectively.

[0019] A second aspect of the present invention provides a method for screening potential anti-Parkinson's disease (PD) drugs targeting α-Syn, comprising:

[0020] The electrochemiluminescence (ECL) signal intensity E of the aforementioned α-Syn-Cu(II) modified electrode was measured before contact with the drug to be screened. 0 And cyclic voltammetry (CV) oxidation peak current intensity I pa 0 ;

[0021] The α-Syn-Cu(II) modified electrode is brought into contact with the drug to be screened;

[0022] The ECL signal intensity E of the α-Syn-Cu(II) modified electrode was measured after contact with the drug to be screened. 1 and CV oxidation peak current intensity I pa 1 ;

[0023] The rate of change of ECL signal intensity E' and the rate of change of CV oxidation peak current intensity I' before and after the α-Syn-Cu(II) modified electrode was contacted with the drug to be screened were determined. pa ,in,

[0024] E' = (E1 - E0) / E0,

[0025] I' pa =(I pa 1 -I pa 0 ) / I pa 0 ;

[0026] E' and I' pa The samples are sent to a pre-trained drug screening model for drug screening. This model is a linear discriminant analysis model trained using the ECL signal intensity change rate and CV oxidation peak current intensity change rate of compounds known to have inhibitory effects on α-Syn aggregation / deaggregation and reactive oxygen species (ROS) removal effects.

[0027] Output the filtering results, wherein the filtering results include:

[0028] (1) Invalid;

[0029] (2) It has a depolymerization effect;

[0030] (3) Has the effect of removing ROS; or

[0031] (4) It has depolymerization and ROS removal effects.

[0032] In some embodiments, the testing process for the ECL signal intensity and CV oxidation peak current intensity of the α-Syn-Cu(II) modified electrode includes:

[0033] The α-Syn-Cu(II) modified electrode was immersed in a first buffer solution containing probe molecules and DNA.

[0034] Using the α-Syn-Cu(II) modified electrode as the working electrode, the ECL signal intensity and CV oxidation peak current intensity of the α-Syn-Cu(II) modified electrode were measured.

[0035] In some embodiments, the α-Syn-Cu(II) modified electrode is contacted with the drug to be screened, specifically including:

[0036] The α-Syn-Cu(II) modified electrode was immersed in a second buffer solution containing the drug to be screened for 0.5 to 3 hours.

[0037] In some embodiments, the concentration of the probe molecule in the first buffer solution is 0.8 mM and / or the concentration of the DNA is 0.3 mg·mL⁻¹; and / or

[0038] In the second buffer solution, the concentration of the drug to be screened is 50 μM.

[0039] Beneficial effects

[0040] The α-Syn-Cu(II) modified electrode provided by this invention can simultaneously obtain ECL and CV signals reflecting the α-Syn aggregation and its associated ROS generation in a single test, and based on these dual signals, a comprehensive evaluation of potential anti-PD drugs can be carried out.

[0041] In addition, the α-Syn-Cu(II) modified electrode provided by the present invention has the advantages of short testing time, reusability, and saving cost of α-Syn dosage. Attached Figure Description

[0042] Figure 1 The EIS characterization results of the α-Syn modified electrode are shown, where (A) is the result of 5 mM Fe(CN)6 at 0.17 V. 3- / 4- The Nyquist curve (illustration: R corresponding to the Nyquist curve) CT (A) represents the concentration of 0.8 mM Ru(bpy)3 in a pH 7.4 buffer solution. 2+ Under the specified conditions, the CV (top) and ECL (bottom) curves obtained simultaneously during the assembly of the α-Syn modified electrode correspond to (a) the bare gold electrode, (b) after the formation of the MUA / MCH layer, (c) after EDC / NHS activation, (d) after α-Syn loading, and (e) the modified electrode after EA (ethanolamine) capping. Error bars represent the standard deviation of the experimental results (n=3).

[0043] Figure 2 The images are AFM images, where (A) shows the surface morphology of the MUA / MCH modified electrode and (B) shows the α-Syn modified electrode.

[0044] Figure 3 CV curves of α-Syn-Cu(II) modified electrodes Figure 3 (A) and ECL curve ( Figure 3(B), scan rate 0.05 V·s -1 The tests were conducted in a pH 7.4 buffer containing 0.8 mM Ru(bpy)32+ and 0.3 mg·mL⁻¹ DNA. (a) shows the results of the α-Syn modified electrode, (b) shows the results of the α-Syn-Cu(II) modified electrode obtained after soaking in 50 μM Cu(II) buffer solution for 2 h, and (c) shows the results after further treatment with 50 μM ethylenediaminetetraacetic acid (EDTA) buffer solution.

[0045] Figure 4 ECL test results for α-Syn modified electrodes after immersion in Cu(II) buffer solution are shown. (A) shows the results after immersion in 50 μM Cu(II) for different times, and (B) shows the results after immersion in Cu(II) buffer solution for different concentrations. Cu(II) (C) shows the results of soaking in buffer solution for 2 h. (D) shows the change in ECL intensity of the α-Syn modified electrode with soaking time in buffer solution (a) without 50 μM Cu(II) and buffer solution (b) with 50 μM Cu(II), respectively. (E) shows the change with different concentrations of Cu(II) after soaking for 2 h. Cu(II) The changes in DNA were measured using a buffer solution at pH 7.4 containing 0.3 mg·mL⁻¹ DNA and 0.8 mM Ru(bpy)³²⁺, with a scan rate of 0.05 V·s. -1 The error bars represent the standard deviation of the experimental results (n=3).

[0046] Figure 5 The CV response of the α-Syn modified electrode is shown, where (A) shows the test results after immersion in 50 μM Cu(II) buffer solution for different times, and (B) shows the results after immersion in Cu(II) buffer solution of different concentrations (C) Cu(II) The test results of the buffer solution for 2 hours are shown in (C), which shows the oxidation peak current (I) of the α-Syn modified electrode. pa The changes in (a) buffer solution and (b) 50 μM Cu(II) solution with soaking time, and (D) after soaking for 2 h with different c Cu(II) The changes were measured in a buffer solution containing 0.3 mg·mL⁻¹ DNA at a rate of 0.05 V·s⁻¹. -1 The scanning rate was adjusted. Error bars represent the standard deviation of the experimental results (n=3).

[0047] Figure 6The XPS analysis results are shown, where (A) is the Cu2p spectrum in XPS; (c) is the α-Syn modified electrode; (b) is the α-Syn-Cu(II) modified electrode; and (a) is the α-Syn-Cu(II) modified electrode after being treated with 50 μM EDTA buffer solution for 2 h; (B) shows the position of the corresponding Cu2p characteristic peak and the assigned valence state.

[0048] Figure 7 The results show the effects of using 0.8 mM Ru(bpy)3 in (A) without PMP and (B) with PMP. 2+ ECL and CV test results were obtained in a pH 7.4 buffer solution containing 0.3 mg·mL⁻¹ DNA. (a) shows the test results of the α-Syn-Cu(II) modified electrode, (b) shows the test results of the α-Syn-Cu(II) electrode after soaking in a buffer solution containing 50 μM adrenaline (EPI) for 2 h, and (c) shows the test results of the α-Syn-Cu(II) electrode after soaking in a buffer solution containing 50 μM dopamine (DA) for 2 h.

[0049] Figure 8 The relative changes in ECL signal (E') and (B)CV signal (I′) induced by different potential small molecule drugs are shown. pa The potential drugs tested were N,N,N',N'-tetramethyl-p-phenylenediamine dihydrochloride (TMPD), pyrrolquinone (PQQ), α-ketoglutarate (α-KG), EPI, glutathione (GSH), cysteine ​​(Cys), EDTA, DA, and chloroquine (CQ), with buffer solution as a control. Error bars represent the standard deviation of the experimental results (n=3).

[0050] Figure 9 The results of constructing the drug screening model based on LDA are shown. (A) is an LDA scatter plot of potential small molecule drugs obtained by analyzing the ECL and CV signals obtained from the α-Syn-Cu(II) interface. In (A), the category codes "0" represent "invalid", "1" represent "depolymerization", "2" represent "ROS removal", and "3" represent "dual effect". Different categories of samples are marked with different colors, and the confidence interval of each category is represented by an ellipse. In (B), the receiver operating characteristic (ROC) curve, true positive rate (TPR), and false positive rate (FPR) analysis show that the LDA drug screening model can distinguish small molecule drugs with different effects with high accuracy (AUC = 1). (C) is a hierarchical clustering analysis (HCA) dendrogram. Detailed Implementation

[0051] To provide a clearer understanding of the technical solution, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in conjunction with the accompanying drawings.

[0052] It should be noted that, unless otherwise specified in the following examples, the conditions should be performed under standard conditions or conditions recommended by the manufacturer. Reagents or instruments whose manufacturers are not specified are all commercially available products.

[0053] Example 1: Preparation of α-Syn-Cu(II) Modified Electrode

[0054] First, the gold electrode was polished sequentially using alumina powders with particle sizes of 1.0, 0.3, and 0.05 μm. Then, it was ultrasonically treated sequentially in deionized water, ethanol, and deionized water for 5 minutes each time. Next, the electrode was immersed in a "piranha solution" (prepared from a 3:1 volume mixture of concentrated sulfuric acid and hydrogen peroxide) for 10 minutes to remove organic contaminants and enhance hydrophilicity. Finally, a clean electrode was obtained by ultrasonic treatment in deionized water and ethanol for 3 minutes each.

[0055] The treated gold electrode was then immersed in 25 μL of an ethanol solution containing 65 μM mercaptoundecanoic acid (MUA) and 170 μM mercaptohexanol (MCH) for 8 h to introduce carboxyl groups onto the surface. Next, the carboxyl groups were activated for 20 min with a mixed aqueous solution containing 400 mM 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) and 100 mM N-hydroxysuccinimide (NHS). Subsequently, 25 μL of 50 μM α-Syn HEPES buffer solution was added dropwise to the electrode surface and incubated for 2 h. Unreacted sites (activated carboxyl groups) were blocked with 0.5 M ethanolamine (EA) aqueous solution for 30 min, thus obtaining the α-Syn modified electrode.

[0056] The obtained α-Syn modified electrode was further immersed in a HEPES buffer solution containing 50 μM Cu(II) (copper chloride) for 2 h to obtain an α-Syn-Cu(II) modified electrode.

[0057] It should be noted that in the examples and the subsequent characterization and testing sections, the buffer solution mentioned refers to the HEPES buffer solution (containing 20 mM 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) buffer substance) with a pH of approximately 7.4.

[0058] Characterization and Testing

[0059] First, the equipment and chemicals involved in the following tests will be explained.

[0060] ECL (electrochemiluminescence) and CV (cyclic voltammetry) measurements were performed simultaneously on an MPI-E electrochemical workstation (Xi'an Ruimai) using a standard three-electrode system: a modified gold electrode as the working electrode, a platinum electrode as the counter electrode, and an Ag / AgCl electrode as the reference electrode. During the detection process, the photomultiplier tube (PMT) voltage was set to 600V. Unless otherwise specified, both ECL and CV measurements were performed in HEPES buffer (20 mM) at pH 7.4, containing 0.8 mM Ru(bpy)3. 2+ and 0.3 mg·mL -1 DNA. The DNA used in this paper is natural double-stranded DNA derived from salmon sperm. When the above ECL and CV measurements involve Cu(II), an appropriate amount of Cu(II) salt is added to the solution to obtain a solution containing the desired Cu(II) concentration. Electrochemical impedance spectroscopy (EIS) was performed on a CHI 660E electrochemical workstation (Shanghai Chenhua), using a modified gold electrode as the working electrode, a saturated calomel electrode (SCE) as the reference electrode, and a platinum electrode as the counter electrode, forming a three-electrode system. To obtain stable and reproducible signals, all ECL and CV results were taken from the second cycle of the test. EIS measurements were performed at 5.0 mM Fe(CN)6. 3- / 4- (5mM[Fe(CN)6] 3- 5mM[Fe(CN)6] 4- The experiment was conducted in HEPES buffer (containing 0.1 M NaCl) at frequencies ranging from 0.1 to 10. 5 The frequency was Hz, the amplitude was 5mV, and the test potential was 0.17V (vs. SCE). The obtained EIS data were fitted using the Randles equivalent circuit model in ZsimpWin software. The CV test used to determine the metal-protein complex potential was performed in blank buffer (HEPES buffer only), using a modified gold electrode as the working electrode, an Ag / AgCl electrode as the reference electrode, and a platinum electrode as the counter electrode, forming a three-electrode system.

[0061] Characterization of electrochemical impedance spectroscopy

[0062] First, the assembly process of α-Syn on the gold electrode surface was characterized using electrochemical impedance spectroscopy (EIS). During the modification process, changes in the surface state of the gold electrode can be observed via charge transfer resistance (Ro). CT This is reflected in Fe(CN)6. 3- / 4- As an electroactive probe, EIS tests were performed on electrodes at different stages of the modification process under pH 7.4 conditions. Figure 1 MUA has a relatively long main chain and terminal -COO. -Groups. Due to the hydrophobicity of MUA and MCH, and the interaction between -COO- and Fe(CN)6 3- / 4- The electrostatic repulsion between them causes the MUA / MCH layer to hinder probe diffusion, resulting in R... CT Value increases ( Figure 1 (Curve A, Curve b). After EDC / NHS treatment, the negatively charged -COO- residues at the MUA terminal were replaced by succinimide esters, partially eliminating the electrostatic repulsion, thereby causing R... CT The decrease in value ( Figure 1 In section A, curve c). When the low-conductivity peptide α-Syn is further covalently linked through the EDC / NHS-activated MUA surface, R CT Value increases ( Figure 1 (A, curve d). After covering other active sites with EA, R CT The value increased further ( Figure 1 (A in the middle, curve e).

[0063] During the electrode modification process, Ru(bpy)3 2+ As a probe, in addition to the modification process of MUA / MCH, CV and ECL signals were observed. Figure 1 The changing trend of B) and the results obtained from EIS ( Figure 1 Similar to A). Because the -COO- residues on the MUA / MCH layer are similar to Ru(bpy)3 in the solution. 2+ There is an electrostatic attraction between them, which slightly increases the CV signal, but has no significant effect on the ECL intensity (E). Figure 1 (Curves B, curves a and b).

[0064] Atomic force microscopy (AFM) characterization

[0065] In addition, AFM was also used to characterize the fabrication of α-Syn modified electrodes. Figure 2 Height distribution and root mean square roughness (R) in AFM images rms It can reflect the microstructure and smoothness of the interface. MUA / MCH is uniformly distributed on the surface of the gold-coated silicon wafer, and its R... rms 2.1nm ( Figure 2 (A). After attaching α-Syn with a flexible conformation to the MUA / MCH surface, many trenches and depressions on the silicon wafer surface were filled, and the surface roughness was reduced to 1.3 nm. Figure 2 (B) The morphological results of AFM visually confirm the successful assembly of the α-Syn modified electrode.

[0066] The above results indicate that α-Syn has been successfully fixed on the electrode surface.

[0067] Dual-signal response of electrodes during aggregation and deaggregation

[0068] Response of clustering features

[0069] Metal ions are naturally present in the brain; however, imbalances in metal homeostasis can affect protein structure and oxidative stress, leading to severe neurodegenerative diseases. Cu(II) is a prime example; its excess can increase the risk of PD by inducing conformational changes in α-Syn. In this study, Cu(II) was chosen as a factor promoting the accumulation of α-Syn on the electrode surface to simulate α-Syn accumulation and ROS generation under pathological conditions, while simultaneously shortening the time required to study the interaction between α-Syn and small molecules. After immersion in Cu(II), opposite changes in the two electrical signals were observed (…). Figure 3 The aggregation behavior of α-Syn induced by Cu(II) in dual signals will be discussed in detail below.

[0070] First, the electrochemical properties of α-Syn induced by Cu(II) in solution on the electrode were monitored using ECL signals. When the α-Syn modified electrode was immersed in a 50 μM Cu(II) solution, the ECL intensity gradually decreased with increasing immersion time, until the decrease stabilized after 2 hours. Figure 3 Curves a and b in B, Figure 4 A and 4C). This change is likely due to Cu(II)-induced nonconductive α-Syn aggregation, as this aggregation hinders Ru(bpy)3 through steric hindrance and potential insulating properties. 2+ Electron transfer between the electrode surface and the electrode surface.

[0071] Furthermore, the extent to which Cu(II) promotes the aggregation of α-Syn on the electrode surface also depends on the concentration of Cu(II) (c Cu(II) After soaking in Cu(II) solution for 2 hours, with c Cu(II) As the concentration of α-Syn increases, the ECL intensity of the electrode gradually decreases. Figure 4 (B in middle and D in 4). However, when c Cu(II) At a concentration of 50 μM, further increases in concentration did not lead to a significant change in signal intensity. This suggests that the binding ratio between α-Syn and Cu(II) should be approximately 1:1.

[0072] Furthermore, the α-Syn modified electrode provided by this invention allows for the detection of aggregates of small amounts of Cu(II)-induced α-Syn within 2 hours, which is much faster than the at least 24 hours required by other common testing methods.

[0073] Meanwhile, the CV signal shows the opposite trend with increasing Cu(II) immersion time. Figure 5(A and C in 5). When the α-Syn modified electrode was immersed in a 50 μM Cu(II) solution, Ru(bpy)3 increased with increasing immersion time. 2+ I pa The oxidation peak current gradually increases until it stabilizes after 2 hours. Figure 5 (A and C in 5). In addition, I pa The aggregation of α-Syn-Cu(II) also depends on the concentration of Cu(II) (c Cu(II) ()( Figure 5 (B and D in 5). After soaking in Cu(II) solution for 2 hours, when c Cu(II) =50μM, I pa The value reaches its maximum, then c is further increased. Cu(II) It does not cause a significant change in oxidation current.

[0074] The steric hindrance and potential insulating properties of α-Syn-Cu(II) aggregates should suppress Ru(bpy)3 2+ Electron transfer between electrodes; however, during Cu(II)-induced α-Syn aggregation, the I of CV... pa The significant increase suggests that the reactivity of the α-Syn complex with Cu(II) may affect the electrochemical properties of the interface.

[0075] The increase in CV signal during Cu(II)-induced α-Syn aggregation is attributed to the generation of ROS. In this system, ROS originates from Cu(I) generated by the electroreduction of Cu(II) bound to α-Syn, which reacts with dissolved oxygen in the system to produce ROS.

[0076] Differential response of α-Syn-Cu(II) to drug effects

[0077] EDTA, a classic metal chelating agent, is a broad-spectrum small molecule drug that inhibits protein-Cu(II) aggregation. We investigated its alleviating effect on Cu(II)-induced abnormal α-Syn aggregation. EDTA effectively blocked the formation of some α-Syn-Cu(II) aggregates. This process may reduce the steric hindrance effect of the aggregates on the electrode surface, which was confirmed in the electrochemical signal recovery. Figure 3 In curves A and B, it can be observed that the changes in the two electrical signals caused by immersion in Cu(II) can be recovered to a certain extent by EDTA treatment.

[0078] Furthermore, X-ray photoelectron spectroscopy (XPS) analysis further confirmed the mitigating effect of EDTA on Cu(II)-induced α-Syn aggregation on the electrode surface. When the α-Syn-modified film was immersed in Cu(II) solution, significant Cu 2p3 aggregates were observed at 933.73 eV in the XPS spectrum. / 2 peaks ( Figure 6 In section A, curve b), and Cu 2p at 953.63 eV. 1 / Peak 2 indicates the presence of divalent copper ions on the electrode surface. Subsequently, the α-Syn-Cu(II) modified electrode was treated with EDTA ( Figure 6 In the middle A, curve a), Cu2p3 / 2 peaks and Cu 2p 1 / The intensity of peak 2 is significantly reduced, but the peak position still belongs to Cu(II). Figure 6 (See Figure B). This suggests that EDTA removed some Cu(II) ions from the electrode surface. This indicates that EDTA removes Cu(II) from α-Syn-Cu(II) by forming a stable chelate complex. This result is consistent with the reported strong chelating properties of EDTA for divalent metal ions, and its mechanism may involve the hexadectic coordination of the four carboxylic acid groups and two amino groups of EDTA with Cu(II), forming a spatially stable Cu-EDTA complex. XPS data support the inference, observed using CV and ECL, that potential small molecule drugs can counteract the effect of Cu(II) on α-Syn aggregation.

[0079] To further investigate the effects of potential small molecule drugs that can alleviate aggregation or remove ROS on the CV and ECL signals of α-Syn-Cu(II) modified electrodes, free radical scavengers were used to verify that our designed α-Syn-Cu(II) interface can monitor oxidative stress behavior or the generation of reactive oxygen species (ROS) caused by protein aggregation.

[0080] Edaravone (PMP) is a typical free radical scavenger that can remove oxygen-containing ROS in a system, such as hydroxyl radicals (OH·) and superoxide anions (O2·). - •) and hydrogen peroxide. The α-Syn modified electrode was tested with and without PMP, and CV and ECL signals were acquired simultaneously. Figure 7 Adrenaline (EPI) and dopamine (DA) are typical inhibitors of α-Syn aggregation, and their effects on the depolymerization of α-Syn have been extensively studied. Using EPI and DA as potential small molecule drug templates, this study investigated the alleviating response of small molecules to α-Syn-Cu(II) aggregation and ROS generation processes by monitoring ECL and CV signals.

[0081] Without PMP ( Figure 7 When ROS generated by the α-Syn-Cu(II) system (A) is not eliminated, after soaking in EPI for 2 hours ( Figure 7 In the upper part of Figure A, curve b), the CV of the α-Syn-Cu(II) modified electrode is I. pa Similar to the case without EPI processing ( Figure 7 The upper part of the graph (a and b) shows that the value of A is significantly higher than that of the case without Cu(II). Figure 4 In section A, curve a). Conversely, the ECL results show that after EPI processing, the ECL signal of the α-Syn-Cu(II) modified electrode ( Figure 7 In the lower graph of A, curve b) increases. This means that the addition of EPI can somewhat recover the ECL signal changes caused by Cu(II), but it does not affect the I of CV. pa There was no significant impact.

[0082] However, when PMP is present, i.e., the ROS effect of the system is eliminated, the signal change is slightly different. Figure 7 (B). Similarly, after EPI treatment, the oxidation peak current of the α-Syn-Cu(II) modified electrode increased slightly in CV. Figure 7 In the upper part of the graph (b), the intensity of ECL also showed a significant rebound. Figure 7 In the lower part of diagram B, curve b). At this point, EPI alleviates the aggregation of α-Syn-Cu(II), making the α-Syn-Cu(II) structure on the electrode surface more open, allowing Ru(bpy)32+ to more easily reach the electrode surface and react, which in turn allows I... pa Both EPI and ECL strength rebounded, demonstrating the efficacy of EPI in depolymerizing proteins on the electrode surface, but its effect in eliminating ROS was relatively weak.

[0083] EPI after processing pa The recovery differs with and without PMP. Based on the aforementioned analysis, Cu(II) may have generated ROS while inducing α-Syn aggregation. During this process, the increase in CV signal due to ROS generation exceeds the decrease in CV signal caused by aggregation, resulting in an overall increase in CV signal. Figure 7 The upper part of graph A, curve a). After adding EPI, both the oxidation peak current and ECL peak signal of CV increased to some extent. Figure 7 (Figures A and B, curve b). This is attributed to the fact that EPI only alleviates protein aggregation on the electrode surface, but does not remove ROS-related components. This is consistent with the results reported in the literature. 36The above experimental results demonstrate that by observing the changes in ECL and CV signals of the α-Syn-Cu(II) modified electrode before and after treatment with potential small molecule drugs, it is possible to reflect whether the small molecule has a mitigating effect on α-Syn-Cu(II) aggregation or an effect on ROS elimination.

[0084] Similarly, with and without PMP, DA was used instead of EPI to treat the α-Syn-Cu(II) modified electrode, and the same experimental methods were used for the study. Figure 7 The results showed that in the presence of PMP ( Figure 7 In the case of electrode B), the signal effect of DA on α-Syn-Cu(II) modified electrodes is similar to that of EPI. As mentioned earlier, this may be due to the fact that DA also has the effect of depolymerizing proteins on the electrode surface. Furthermore, in the absence of PMP, DA treatment improves the I... pa Significant decline ( Figure 7 In the upper part of the graph (A), curve c) is close to the condition before Cu(II) treatment, and at the same time, the ECL intensity also recovers. Figure 7 The figure below (curve c) shows that, in addition to its depolymerization effect, DA may also have an antioxidant effect related to ROS scavenging. This is consistent with reports in the literature.

[0085] The above experimental results further illustrate that the CV and ECL dual signals simultaneously obtained through the α-Syn modified electrode are simultaneously affected by the cross-influence of Cu(II)-induced α-Syn protein aggregation and ROS generation. Specifically, when protein aggregation occurs, the ECL signal and CV oxidation peak current decrease synchronously; while when ROS is generated, ROS causes the ECL and CV signals to show opposite trends, i.e., the ECL intensity decreases while the CV I pa The levels of small molecules that alleviate protein aggregation and remove ROS can be increased. Small molecules that can alleviate protein aggregation and remove ROS can restore the corresponding electrical signals by exerting their effects. Therefore, by analyzing the changes in CV and ECL signals of α-Syn-Cu(II) modified electrodes before and after treatment with candidate small molecule drugs, the potential efficacy of small molecule drugs in alleviating α-Syn-Cu(II) aggregation and ROS generation can be reflected. Based on this, it is necessary to find a scientifically feasible method to quantify the relationship between protein aggregation / ROS generation and changes in CV and ECL signals, establish a potential small molecule drug screening model, and achieve a simple classification of drug efficacy based on changes in CV and ECL signals.

[0086] Construction of LDA-based drug screening model

[0087] Linear Discriminant Analysis (LDA) has become an ideal choice due to its supervised learning characteristics, feature interpretability, efficient dimensionality reduction capabilities, and adaptability to small- to medium-scale experimental data. It provides a quantitative tool for extracting key patterns from data and guiding experimental optimization, while avoiding the training costs and overfitting risks of complex models. Its potential is increasingly being realized in practical applications. Applying LDA in this research scenario not only allows for the visualization of feature parameters through feature weights and dimensionality reduction, revealing the hidden correlation between electrochemical phenomena and protein aggregation / ROS generation on the α-Syn-Cu(II) modified electrode surface, but also enables the development of a screening model for potential small molecule drugs targeting α-Syn through training.

[0088] First, using the same method as the previous experiments, the α-Syn-Cu(II) modified electrode prepared in Example 1 was used to perform electrochemical tests on nine known and potentially effective small drug molecules, simultaneously obtaining the corresponding ECL / CV signals. We used the rate of change (E') of ECL intensity before and after drug treatment to measure the degree of change in ECL, defined as (E'...). 1 -E 0 ) / E 0 E 0 and E 1 The corresponding ECL signal intensities (E) are before and after the α-Syn-Cu(II) modified electrode is immersed in the small molecule to be tested for 2 hours. Figure 8 (A). Similarly, the rate of change of the oxidation peak current intensity at 1.05V in the CV curve (I') pa The degree of change is measured by (I) and is defined as (I) pa 1 -I pa 0 ) / I pa 0 Among them, I pa 0 and I pa 1 The CV curves corresponding to the oxidation peak current intensity (I) at 1.05 V are shown before and after the α-Syn-Cu(II) modified electrode is immersed in the small molecule to be tested for 2 hours. pa )value( Figure 8 (B)

[0089] Compare E' and I' pa As input, LDA is used to perform classification calculations for different linear combinations, selecting two discriminant factors: Factor 1 and Factor 2 (Table 1). Factor 1 and Factor 2 are derived from E′ and I′. paThe discriminant factors with the largest group intervals in the discriminant direction (dimension) obtained by different linear combinations have contribution rates of 76.41% and 23.59%, respectively. The combined contribution rate of factors 1 and 2 exceeds 90%, indicating that these two factors are key discriminant factors in the screening model, covering almost all the discriminant information in the data and highly representing the classification characteristics of the data. The receiver operating characteristic (ROC) curve is used to further evaluate the classification performance of the LDA algorithm. Generally, the performance of a diagnostic test is reflected by two parameters: the true positive rate (TPR) and the false positive rate (FPR). The ROC curve shows the ideal diagnostic results, i.e., a TPR of 1, an FPR of 0, and an area under the curve (AUC) of 1 (…). Figure 9 (B). Therefore, for this drug screening model, two dimensions are sufficient to effectively distinguish different groups, without relying on more dimensions. Using the two discriminant factors as the horizontal and vertical axes, the LDA two-dimensional scatter classification results are plotted ( Figure 9 In the study (A), nine small molecules were divided into four groups based on the maximum intergroup distance. Within each group, two to three potential small molecule drugs (two replicate data points for each drug) were clustered together by the minimum intragroup distance after LDA calculation, corresponding to four different efficacies: ineffective (0), depolymerization (1), ROS removal (2), and dual-effect (3). Furthermore, in... Figure 9 In group A, the cluster of "ROS removal (2)" is relatively farther away from the other groups, indicating that the model has a relatively higher discrimination ability for ROS removal drugs. In summary, LDA successfully distinguished four types of drug efficacy, indicating that LDA can be successfully used in the CV and ECL dual-signal platform established in this study to screen and classify drugs that alleviate protein depolymerization and ROS generation.

[0090] Table 1. LDA results and related equations used for discrimination

[0091]

[0092] Hierarchical clustering analysis (HCA) is an unsupervised machine learning clustering method that constructs a hierarchical clustering structure based on Euclidean distance similarity features. This study further uses HCA to verify the feasibility of the established LDA. Figure 9 The HCA dendrogram in the diagram is shown in Figure C. Small molecules with short Euclidean distances cluster together, clearly distinguishing the effects of four different potential small molecule drugs without overlap. This indicates that the HCA-based drug screening platform has good discriminative power and can be used to screen potential anti-PD drugs targeting α-Syn.

[0093] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An α-Syn-Cu(II) modified electrode, characterized in that, include: Gold electrode, A covalent bonding layer covering the surface of the gold electrode. α-synuclein (α-Syn) connected to the covalently linked layer, and Cu(II) that is combined with the α-Syn.

2. The α-Syn-Cu(II) modified electrode according to claim 1, characterized in that, The covalent bonding layer comprises mercaptoundecanoic acid and mercaptohexanol.

3. The α-Syn-Cu(II) modified electrode according to claim 2, characterized in that, The molar ratio of mercaptoundecanoic acid and mercaptohexanol in the covalent linking layer is 1:2-3.

4. The α-Syn-Cu(II) modified electrode according to claim 1, characterized in that, The α-Syn is connected to the covalently linked layer through the following process: The gold electrode covered with the covalent bonding layer is contacted with an α-Syn solution with a concentration of 30-70 μM for 6-12 hours.

5. The α-Syn-Cu(II) modified electrode according to any one of claims 1-4, characterized in that, Cu(II) binds to α-Syn via the following process: The gold electrode connected to the α-Syn was brought into contact with a Cu(II) solution with a Cu(II) concentration of 30-70 μM for 1-3 hours.

6. The method according to claim 5, characterized in that, The Cu(II) solution and the α-Syn solution used to connect α-Syn on the covalent bonding layer have the same concentrations of Cu(II) and α-Syn, respectively.

7. A method for screening potential anti-Parkinson's disease (PD) drugs targeting α-Syn, characterized in that, include: The electrochemiluminescence (ECL) signal intensity E of the α-Syn-Cu(II) modified electrode according to any one of claims 1-6 was determined before contact with the drug to be screened. 0 And cyclic voltammetry (CV) oxidation peak current intensity I pa 0 ; The α-Syn-Cu(II) modified electrode is brought into contact with the drug to be screened; The ECL signal intensity E of the α-Syn-Cu(II) modified electrode was measured after contact with the drug to be screened. 1 and CV oxidation peak current intensity I pa 1 ; The rate of change of ECL signal intensity E' and the rate of change of CV oxidation peak current intensity I' before and after the α-Syn-Cu(II) modified electrode was contacted with the drug to be screened were determined. pa ,in, E' = (E1 - E0) / E0, I’ pa =(I pa 1 -I pa 0 ) / I pa 0 ; E' and I' pa The samples are sent to a pre-trained drug screening model for drug screening. This model is a linear discriminant analysis model trained using the ECL signal intensity change rate and CV oxidation peak current intensity change rate of compounds known to have inhibitory effects on α-Syn aggregation / deaggregation and reactive oxygen species (ROS) removal effects. Output the filtering results, wherein the filtering results include: (1) Invalid; (2) It has a depolymerization effect; (3) Has the effect of removing ROS; or (4) It has depolymerization and ROS removal effects.

8. The screening method according to claim 7, characterized in that, The testing process for the ECL signal intensity and CV oxidation peak current intensity of the α-Syn-Cu(II) modified electrode includes: The α-Syn-Cu(II) modified electrode was immersed in a first buffer solution containing probe molecules and DNA. Using the α-Syn-Cu(II) modified electrode as the working electrode, the ECL signal intensity and CV oxidation peak current intensity of the α-Syn-Cu(II) modified electrode were measured.

9. The screening method according to claim 7, characterized in that, The α-Syn-Cu(II) modified electrode is brought into contact with the drug to be screened, specifically including: The α-Syn-Cu(II) modified electrode was immersed in a second buffer solution containing the drug to be screened for 0.5 to 3 hours.

10. The screening method according to any one of claims 7-9, characterized in that, In the first buffer solution, the concentration of the probe molecule is 0.8 mM and / or the concentration of the DNA is 0.3 mg·mL⁻¹; and / or In the second buffer solution, the concentration of the drug to be screened is 50 μM.

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