Nanopore probe and application thereof

By designing nanopore probes and combining them with machine learning algorithms, the problem of signal instability in traditional nanopore sensors has been solved, enabling high-precision and wide dynamic range detection of protease activity, which is suitable for point-of-care testing and clinical applications.

CN121737265APending Publication Date: 2026-03-27CHINA UNIV OF GEOSCIENCES (WUHAN)
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Patent Information

Application Number
CN202511745475.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-26
Publication Date
2026-03-27

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Abstract

The invention provides a nanopore probe and application thereof, the nanopore probe comprises a polypeptide, the carboxyl terminal of the polypeptide is connected with a steric hindrance tag, the amino terminal of the polypeptide is connected with polyaspartic acid, and the polypeptide has a restriction enzyme cutting site specifically recognized by target protease. The method can prolong the retention time of the polypeptide in the nanopore, enhance the signal discernibility and improve the signal stability, thereby realizing stable and high-precision quantitative detection of the protease activity.
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Description

Technical Field

[0001] This invention belongs to the field of protease detection technology, specifically relating to a nanopore probe and its application. Background Technology

[0002] Protease activity is a key biomarker reflecting physiological and pathological states, and its dynamic fluctuations are closely related to the occurrence, progression, and clinical outcomes of diseases. Currently, the gold standard for clinical detection of protease activity is enzyme-linked immunosorbent assay (ELISA). However, ELISA mainly quantifies the total abundance of proteases rather than their activity, and its dynamic range is narrow (usually less than three orders of magnitude). The detection procedure is cumbersome, making it difficult to achieve rapid, wide-range quantitative monitoring. Nanopore biosensors, as an emerging point-of-care testing (POCT) technology, offer advantages in portability and real-time analysis. They can identify and quantify target analytes by analyzing the characteristic current blocking signals generated when molecules translocate through nanopores. However, in the detection of protease activity, traditional nanopore sensors suffer from problems such as rapid substrate peptide translocation, resulting in short-lived and volatile current signals that are unstable and difficult to accurately correlate with analyte concentrations. Summary of the Invention

[0003] In view of this, the present invention provides a nanopore probe and its application, which can prolong the residence time of peptides in nanopores, enhance signal discriminability, and improve signal stability, thereby achieving stable and high-precision quantitative detection of protease activity.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a nanopore probe comprising a polypeptide, wherein the carboxyl terminus of the polypeptide is attached to a steric hindrance tag, the amino terminus is attached to a polyaspartic acid, and the polypeptide has an enzyme cleavage site specifically recognized by a target protease.

[0005] It should be noted that the steric hindrance tag is attached to the carboxyl terminus (C-terminus) of the peptide, providing controllable steric hindrance. By optimizing the tag size, a balance can be achieved between high signal intensity and reversible translocation. Polyaspartic acid is attached to the amino terminus (N-terminus) of the peptide, enhancing electrophoretic mobility. The driving force can be optimized by adjusting the length of the polyaspartic acid. The peptide has cleavage sites specifically recognized by the target protease for selective protease detection. The universal structure of the probe can be D... x M y S, where D x The expression is polyaspartic acid, where x is the quantity of aspartic acid, and M is the amount of aspartic acid. y For the polypeptide, y is the target protease number; S is the steric hindrance tag, and the design logic is D. x Enhanced electrophoretic driving force, S prolongs the residence time of peptides in nanopores, synergistically improving signal stability, M yThis probe is used for selective detection of proteases. For example, D7M2Cz targets matrix metalloproteinase-2 (MMP-2). D7 is a polyaspartic acid with 7 aspartic acid residues, and M2 contains the PLGLAG cleavage site specifically recognized by MMP-2. The steric hindrance tag is Cz (imidazolium). The probe peptides can allow for interchangeable modes (e.g., D7M1Cz, D7M2Cz, D7M9Cz), enabling specific differentiation of homologous proteases (MMP-1, MMP-2, and MMP-9). The probe can achieve translocation dynamics regulation through systematic optimization of the steric hindrance tag size and polyaspartic acid length. The steric hindrance effect of the probe has been verified through molecular dynamics simulations and numerical calculations, ensuring the rationality of the design. The enzyme-controlled signal switching mechanism is as follows: probe integrity is key to signal generation. After the target protease specifically cleaves the peptide, the probe breaks into D2-containing peptides. x The detection mechanism of 'enzyme digestion-signal switching' is achieved by combining the signal fragment of S (which can generate characteristic current blocking) with the signal-free fragment without electrophoretic driving force. For example, after MMP-2 digests the D7K{Cz}M2TPE probe, it generates D7K{Cz}PLG (which can generate a signal) and LAG{TPE} (which does not generate a signal).

[0006] Preferably, the steric hindrance label is a rigid aromatic compound. It should be noted that rigid aromatic compounds can enhance spatial confinement and optimize signal output.

[0007] Preferably, the rigid aromatic compound includes at least one of benzene, carbazole, and tetraphenylethylene. It should be noted that the steric hindrance tag is preferably carbazole, whose size (Cz, diameter 1.1083 nm) is close to the nanopore contraction region, which can balance signal intensity and reversible translocation, producing stable and reversible blocking.

[0008] Preferably, the polyaspartic acid contains 4, 7, or 10 aspartic acid residues. It should be noted that the polyaspartic acid preferably contains 7 aspartic acid residues. Polyaspartic acid with 7 aspartic acid residues (D7) can achieve the highest event capture frequency (50.97 events / minute) for carbazole (sterically hindered tag), i.e., by using D4M2Cz, D7M2Cz, and D... 10 The results are derived by comparing the frequency values ​​measured by the three M2Cz probes under the same conditions.

[0009] Preferably, the target protease is a matrix metalloproteinase.

[0010] Preferably, the matrix metalloproteinase includes matrix metalloproteinase-1, matrix metalloproteinase-2, or matrix metalloproteinase-9.

[0011] Preferably, the steric hindrance tag is attached to the carboxyl terminus of the polypeptide via a click chemistry reaction. It should be noted that the click chemistry reaction can be a copper-catalyzed azido-alkyne cycloaddition (CuAAC) click chemistry reaction.

[0012] Secondly, the present invention also provides an application of the aforementioned nanopore probe in a nanopore sensor for detecting protease activity. It should be noted that the nanopore probe can be used in a nanopore sensor for point-of-care testing (POCT) of protease activity in clinical samples (such as urine); wherein the procedure for POCT of protease activity in clinical samples can be as follows: Incubate clinical samples (such as urine) with a mixture of nanopore probes; After the enzyme reaction, the mixture is analyzed using nanopore sensors (such as portable nanopore devices); The output signal is processed by machine learning algorithms (such as the Bagged Tree model) to achieve disease classification.

[0013] Preferably, the nanopores in the detection cell of the nanopore sensor are biological nanopores.

[0014] Preferably, the bio-nanopore comprises an M2 MspA nanopore. It should be noted that the M2Mycobacterium smegmatis porin A (M2 MspA) nanopore is used as the sensing element. Its contraction region has a diameter of approximately 1.2 nm, and its near-neutral charge distribution reduces electroosmotic interference, enabling electrophoretic-driven controllable translocation. The nanopore is prepared through bacterial expression and purification, and its structural integrity is verified by SDS-PAGE and electrophysiological testing.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) In the nanopore probe provided by the present invention, the steric hindrance tag (such as imidazole) can prolong the residence time of the probe in the nanopore (from <0.1 ms to 0.1120 ms), reduce signal fluctuations, significantly improve signal stability, and improve detection reproducibility; in addition, by optimizing the tag size, a balance between high signal intensity and reversible translocation can be achieved.

[0016] (2) The nanopore probe provided by the present invention is used in a nanopore detection platform with a dynamic range of up to 6 orders of magnitude (0.001~1000 ng / mL) and a detection limit as low as 0.033 ng / mL (MMP-1), which is better than the 3 orders of magnitude range of ELISA, and has a wide dynamic range and high sensitivity.

[0017] (3) The nanopore probe provided by the present invention has strong clinical applicability. In 231 clinical urine samples, it was highly consistent with the ELISA results (Bland-Altman analysis bias was close to zero) and has robustness in complex biological matrices.

[0018] (4) The nanopore probe provided by the present invention has multiple detection capabilities and can replace peptides to achieve specific differentiation of homologous proteases.

[0019] (5) The nanopore probe provided by the present invention can be intelligently integrated into the nanopore detection platform, combined with machine learning, to achieve automatic classification, and can be made portable through mobile applications to promote point-of-care testing (POCT) applications. Attached Figure Description

[0020] Figure 1 The Cz-N3 in deuterated chloroform in Example 1 of this invention 1 H NMR spectrum; Figure 2 The Cz-N3 in deuterated chloroform in Example 1 of this invention 13 C NMR spectrum; Figure 3 The HPLC chromatogram and HRMS chromatogram of probe D7M1Cz in Example 1 of this invention are shown below. Figure 4 The HPLC chromatogram and HRMS chromatogram of probe D7M2Cz in Example 1 of this invention are shown below. Figure 5 The HPLC chromatogram and HRMS chromatogram of probe D7M9Cz in Example 1 of this invention are shown below. Figure 6 This is a representative current trajectory recording diagram of the probe D7M2 nanopore translocation event in Embodiment 1 of the present invention; Figure 7 This is a representative current trajectory recording of the nanopore translocation event of probe D7M2Cz in Embodiment 1 of the present invention; Figure 8 This is a diagram showing the single-molecule translocation characteristics of probe D7M1Cz in Example 1 of this invention; Figure 9 This is a diagram showing the single-molecule translocation characteristics of probe D7M2Cz in Example 1 of this invention; Figure 10 This is a diagram showing the single-molecule translocation characteristics of probe D7M9Cz in Example 1 of the present invention; Figure 11 This is a standard curve of the event frequency reduction rate of the probe versus the concentration of the target protease in Example 2 of the present invention; Figure 12 This is a heatmap showing the specificity of the probe with the target protease and non-target protease in Example 2 of the present invention; Figure 13 This is a diagram showing the workflow and test results of the clinical validation in Embodiment 3 of the present invention. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to specific embodiments, so that those skilled in the art can more clearly understand the present invention.

[0022] Example 1: Synthesis and Characterization of Probes Probe D7M y Cz synthesis: Carbazole (Cz) is attached to the C-terminus of the polypeptide via a copper-catalyzed azido-alkyne cycloaddition (CuAAC) click chemistry reaction, with polyaspartic acid (D7) located at the N-terminus of the polypeptide (D7M1, D7M). 2、 (D7M9), probe purity was verified by HPLC and mass spectrometry.

[0023] The synthetic route of Cz-N3 is as follows: .

[0024] The preparation method of Cz-N3 is as follows: 9-(6-bromohexyl)-9H-carbazole (0.330 g, 1 mmol) and NaN3 (0.065 g, 1 mmol) were added to a 5 mL double-necked round-bottom flask containing 2 mL of N,N-dimethylacetamide (DMF). The mixture was stirred at room temperature for 12 hours. After the reaction was complete, the crude product was purified by silica gel column chromatography using a gradient elution of dichloromethane (DCM) and petroleum ether to give 0.175 g of Cz-N3 as a white powder with a purity of 88.0%. 1 ¹H NMR (400 MHz, chloroform-d) δ 8.10 (dt, J = 7.8, 0.9 Hz, 2H), 7.47 (ddd, J = 8.2, 7.0, 1.2 Hz, 2H), 7.40 (d, J = 8.1 Hz, 2H), 7.23 (ddd, J = 8.0, 7.0, 1.1 Hz, 2H), 4.31 (t, J = 7.1 Hz, 2H), 3.21 (t, J = 6.8 Hz, 2H), 1.94 - 1.85 (m, 2H), 1.54 (q, J = 6.8 Hz, 2H), 1.43- 1.37 (m, 4H); Cz-N3 in deuterated chloroform 1 The H NMR spectrum is shown in [reference]. Figure 1 . 13Cz NMR (101 MHz, chloroform-d) δ 139.39, 124.59, 121.84, 119.34, 117.77, 107.57, 50.29, 41.84, 30.40, 28.68, 27.83, 27.68; Cz-N3 in deuterated chloroform 13 The C NMR spectrum is shown below. Figure 2 .

[0025] The synthetic route for D7M1Cz is as follows: ; The preparation method of D7M1Cz is as follows: Cz-N3 (4.09 mg, 14.00 μmol), peptide D7M1 (10.00 mg, 7.00 μmol), sodium ascorbate (6.93 mg, 35.00 μmol), and CuBr (5.02 mg, 35.00 μmol) were dissolved in a DMSO / H2O mixture (v / v = 1:1, total volume 4 mL). The reaction was stirred under a nitrogen atmosphere at room temperature and monitored by analytical HPLC until completion. The crude product was purified by semi-preparative reversed-phase HPLC, and the collected fraction was lyophilized to give 9.05 mg of D7M1Cz as a white powder, with a yield of 75% and chemical formula: C 75 H 107 N 19 O 28 , m / z: 1721.7527 (100.0%), D7M1C z The HPLC chromatogram is shown below. Figure 3 (a) High-resolution mass spectrometry (ESI) m / z: [M-6H] 2- Calculated value: 857.8545; Measured value: 857.8560; [M-7H] 3- Calculated value: 571.5673; Measured value: 571.5682; D7M2C z The HRMS spectrum is shown below. Figure 3 (b).

[0026] The synthetic route of D7M2Cz is as follows: ; The preparation method of D7M2Cz is as follows: Cz-N3 (4.09 mg, 14.00 μmol), peptide D7M2 (10.00 mg, 7.00 μmol), sodium ascorbate (6.93 mg, 35.00 μmol), and CuBr (5.02 mg, 35.00 μmol) were dissolved in a DMSO / H2O mixture (v / v = 1:1, total volume 4 mL). The reaction was stirred under a nitrogen atmosphere at room temperature and monitored by analytical HPLC until completion. The crude product was purified by semi-preparative reversed-phase HPLC, and the collected fraction was lyophilized to give 7.58 mg of D7M2Cz as a white powder, with a yield of 63% and chemical formula: C 75 H 103 N 19 O 28 , m / z: 1717.7214 (100.0%), D7M2C z The HPLC chromatogram is shown below. Figure 4 (a) High-resolution mass spectrometry (ESI) m / z: [MH] - Calculated value: 1716.7142; Measured value: 1716.7109; [M-2H] 2- Calculated value: 857.8534; Measured value: 857.8524; D7M2C z The HRMS spectrum is shown below. Figure 4 (b).

[0027] The synthetic route for D7M9Cz is as follows: ; The preparation method of D7M9Cz is as follows: Cz-N3 (3.33 mg, 11.42 μmol), peptide D7M9 (10.00 mg, 5.71 μmol), sodium ascorbate (5.66 mg, 28.55 μmol), and CuBr (4.09 mg, 28.55 μmol) were dissolved in a DMSO / H2O mixture (v / v = 1:1, total volume 4 mL). The reaction was stirred under a nitrogen atmosphere at room temperature and monitored by analytical HPLC until completion. The crude product was purified by semi-preparative reversed-phase HPLC, and the collected fraction was lyophilized to give 9 mg of D7M2Cz as a white powder, with a yield of 77%. Chemical formula: C 89 H 126 N 24 O 32 , m / z: 2042.8965 (100.0%), D7M9C z The HPLC chromatogram is shown below. Figure 5 (a) High-resolution mass spectrometry (ESI) m / z: [MH] 2-Calculated value: 1020.9446; Measured value: 1020.9440; [M-2H] 3- Calculated value: 680.2940; Measured value: 680.2927; D7M2C z The HRMS spectrum is shown below. Figure 5 (b).

[0028] Nanopore characterization: All nanopore current measurements were performed on an Orbit 16 (Nanion) instrument using a MECA-16 microfluidic chip (Ionera). The test conditions were as follows: current sampling frequency 20 kHz, filtering frequency 2.5 kHz, working buffer 1 MKCl solution (containing 10 mM HEPES, pH 7.4), and applied voltage +50 mV. The experiments were conducted as follows: First, current compensation calibration was performed using a standard calibration chip, and the system accuracy was verified by monitoring the chip's conductivity. Buffer solution was added to the MECA-16 microfluidic chip reaction cell, and mechanical pressurization was applied to ensure a stable conduction path was formed inside the chip. Subsequently, 0.2 μL of lipid solution (solvent: n-octane, solute: DPhPC, final concentration: 5 mg / mL) was added to the bottom of the chip. -1 When the lipid solution comes into contact with the microporous array, a lipid bilayer can be automatically formed. Then, 2 μL of M2 MspA protein solution pre-diluted with buffer is added to the buffer interface. Finally, a constant voltage of +50 mV is applied to drive the insertion of individual nanoporous proteins into the lipid bilayer.

[0029] Representative current trajectory recordings of nanopore translocation events of probe D7M2 are shown below. Figure 6 Probe D7M2C z Representative current trajectory recordings of nanopore translocation events are shown in the figure. Figure 7 Probe D7M1C z The unimolecular translocation characteristics are shown in Figure 8 ,in, Figure 8 (a) is relative current blocking ( I / I0) distribution map, Figure 8 (b) shows the blocking time distribution diagram for probe D7M2C. z The unimolecular translocation characteristics are shown in Figure 9 ,in, Figure 9 (a) is relative current blocking ( I / I0) distribution map, Figure 9 (b) shows the blocking time distribution; probe D7M9C z The unimolecular translocation characteristics are shown in Figure 10 ,in, Figure 10 (a) is relative current blocking ( I / I0) distribution map, Figure 10 (b) shows the blocking time distribution; probe D7M9C z .

[0030] Depend on Figure 6 It can be seen that the probe with the unmodified steric tether tag (D7M2) did not detect any blocking signal. Given the instrument's sampling rate of 20 kHz (i.e., a sampling interval of 0.05 ms), the minimum detectable residence time for a single event is 0.1 ms. Therefore, it can be inferred that the residence time of the probe with the unmodified steric tether tag in the nanopore is less than 0.1 ms. Figures 7 to 10 It can be seen that probe D7M1C z Stable blocking events occur ( I / I0 = 10.26 ± 0.11%, t = 0.0555 ms), probe D7M2C z Stable blocking events occur ( I / I0 = 13.67 ± 0.09%, t = 0.1120 ms), the event frequency is 50.97 events / minute, probe D7M9C z Stable blocking events occur ( I / I0=10.47±0.17%, t=0.0765 ms).

[0031] Example 2: Protease Activity Detection Sample processing: Urine samples were incubated with the probes for 30 minutes. The concentration range of protease in the urine samples was 0.001~1000 ng / mL. The probe was D7M1Cz, and the matched protease was MMP-1; the probe was D7M2Cz, and the matched protease was MMP-2; and the probe was D7M9Cz, and the matched protease was MMP-9. The concentrations of the protease were 0.001 ng / mL, 0.01 ng / mL, 0.1 ng / mL, 1 ng / mL, 10 ng / mL, 100 ng / mL, and 1000 ng / mL, respectively.

[0032] Signal Analysis: Decrease in the Frequency of Events Recorded in Nanopores ( f / f0) was linearly correlated with protease concentration, with a LOD of 0.093 ng / mL; probe (D7M1C) z D7M2C z D7M9C z The standard curve of the event frequency reduction rate versus the concentration of target proteases (MMP-1, MMP-2, MMP-9) is shown below. Figure 11 Among them, probe D7M1C z event frequency reduction rate ( The standard curve of f / f0 and target protein (MMP-1) concentrations is shown below. Figure 11 (a) Probe D7M2C z event frequency reduction rate ( The standard curve of f / f0 and the concentration of the target protein (MMP-2) is shown below. Figure 11 (b) Probe D7M9C z event frequency reduction rate ( The standard curve of f / f0 and the concentration of the target protein (MMP-9) is shown below. Figure 11 (c); Probe (D7M1C) z D7M2C z D7M9C z The standard curve of the event frequency reduction rate versus the concentration of target proteases (MMP-1, MMP-2, MMP-9) was used to calculate the quantitative detection of target protease activity.

[0033] Specificity thermogram: probe (D7M1C) z D7M2C z D7M9C z The probe was co-incubated with target proteases (MMP-1, MMP-2, MMP-9) or non-target proteases (α-amylase, trypsin, chymotrypsin, collagenase). The specificity heatmaps of the probe with target and non-target proteases are shown below. Figure 12 The heatmap shows the rate of decrease in event frequency ( f / f0). By Figure 12 It can be seen that the matched probe-protease pair alone can produce an inhibition rate of more than 70%, while the signal changes caused by non-target proteases are negligible, which confirms the high specificity of the probe.

[0034] Example 3: Clinical Validation The nanopore detection platform was used for clinical validation of urinary protease proteomic analysis and machine learning-based urothelial carcinoma diagnosis. Sample set: Urine samples from 231 participants, including 54 healthy controls (HC), 73 with benign disease (BD), and 104 with urothelial carcinoma (UC).

[0035] Nanopore detection platform: probes are D7M1C z D7M2C z D7M9C z The nanopores in the detection cell are M2 MspA nanopores.

[0036] (1) Workflow of point-of-care testing and classification prediction of urine samples The workflow consists of four steps: probe incubation, sample detection, result reading, and classification prediction (scale bar is 2cm). See [link / details]. Figure 13(a) This process demonstrates the complete point-of-care testing (POCT) pathway from sample processing to intelligent diagnostics.

[0037] (2) Comparison of quantitative levels between nanopore detection platform and traditional ELISA method (heatmap) Using 231 urine samples from the sample set, the quantitative detection results of MMP-1, MMP-2, and MMP-9 were compared between the nanopore detection platform (ND) and ELISA (ED) methods. The results are shown in [Figure Number]. Figure 13 (b). By Figure 13 (b) It can be seen that the nanopore detection platform and the ELISA method show a high degree of consistency.

[0038] (3) Bland-Altman analysis was used to evaluate the consistency between the ND and ED methods: The measurement results for MMP-1, MMP-2, and MMP-9 are shown below. Figure 13 (c) Figure 13 (d) and Figure 13 (e) The horizontal axis represents the mean of ND and ED measurements for each sample, and the vertical axis represents the difference between the two methods (ND - ED). The solid horizontal line represents the mean deviation, and the dashed line represents the 95% agreement limit (mean difference ± 1.96 standard deviations). Figure 13 (c) to Figure 13 (e) It can be seen that more than 90% of the data points for the three proteases MMP-1, MMP-2 and MMP-9 are within the agreement limit.

[0039] (4) Box plot analysis of protease activity in different clinical groups The distributions of MMP-1, MMP-2, and MMP-9 in the three clinical groups, as measured by the nanopore detection platform, are shown in the figures below. Figure 13 (f) Figure 13 (g) and Figure 13 (h) Statistical significance was determined by one-way ANOVA and Tukey's post-hoc test, with ns indicating p ≥ 0.05, * indicating p < 0.05, ** indicating p < 0.01, and *** indicating p < 0.001. Figure 13 (f) to Figure 13(h) It can be seen that the activities of the three proteases MMP-1, MMP-2 and MMP-9 in the urothelial carcinoma (UC) group were significantly higher than those in the benign lesion (BD) group and the healthy control (HC) group. Specifically: the activity of MMP-1 in the UC group was significantly higher than that in the BD group (p<0.0001) and the HC group (p<0.0001), while there was no significant difference between the BD group and the HC group (p = 0.967); the activity of MMP-2 in the UC group was significantly higher than that in the BD group (p<0.0001) and the HC group (p<0.0001), while the activity in the BD group was slightly higher than that in the HC group (p = 0.036); the activity of MMP-9 in the UC group was significantly higher than that in the BD group (p<0.0001) and the HC group (p<0.0001), while there was no significant difference between the BD group and the HC group (p = 0.864). This indicates that the urinary MMP activity profile can clearly distinguish between urothelial carcinoma, benign lesions, and healthy states, providing quantitative evidence for the characteristics of disease-specific proteases.

[0040] (5) Three-dimensional scatter plot based on protease activity level Based on the quantitative levels of MMP-1, MMP-2, and MMP-9 measured by the nanopore detection platform, a three-dimensional scatter plot of enzyme activity was plotted for the clinical cohort. The results are shown below. Figure 13 (i). Depend on Figure 13 (i) It can be seen that the HC, BD and UC groups have obvious clustering characteristics.

[0041] (6) Feature importance analysis of the three MMPs in the classification model The feature importance analysis results for the three MMPs, MMP-1, MMP-2, and MMP-9, in the classification model are shown below. Figure 13 (j). By Figure 13 (j) It can be seen that MMP-9 is the most discriminative biomarker and can provide a basis for key feature selection for machine learning models.

[0042] (7) Confusion matrix generated by the Bagged Trees model on the independent test set The confusion matrix generated by the Bagged Trees model on the independent test set is shown below. Figure 13 (k). By Figure 13 (k) shows that the nanopore detection platform, using the Bagged Trees model, achieved a high overall classification accuracy of 96.2% when distinguishing between UC, BD, and HC samples, demonstrating the reliability of the platform in clinical diagnosis.

[0043] Unless otherwise specified, all raw materials used in this invention are existing substances that can be purchased directly from the market.

[0044] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. 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. A nanopore probe, characterized in that, The peptide includes a steric hindrance tag attached to its carboxyl terminus and a polyaspartic acid residue attached to its amino terminus, and the peptide has an enzyme cleavage site that is specifically recognized by a target protease.

2. The nanopore probe according to claim 1, characterized in that, The steric hindrance label is a rigid aromatic compound.

3. The nanopore probe according to claim 2, characterized in that, The rigid aromatic compound includes at least one of benzene, carbazole, and tetraphenylethylene.

4. The nanopore probe according to claim 1, characterized in that, The polyaspartic acid contains 4, 7, or 10 aspartic acid molecules.

5. The nanopore probe according to claim 1, characterized in that, The target protease is a matrix metalloproteinase.

6. The nanopore probe according to claim 5, characterized in that, The matrix metalloproteinases include matrix metalloproteinase-1, matrix metalloproteinase-2, or matrix metalloproteinase-9.

7. The nanopore probe according to claim 1, characterized in that, The steric hindrance tag is attached to the carboxyl terminus of the polypeptide via a click chemical reaction.

8. The application of the nanopore probe according to any one of claims 1 to 7 in a nanopore sensor for detecting protease activity.

9. The application according to claim 8, characterized in that, The nanopores in the detection cell of the nanopore sensor are biological nanopores.

10. The application according to claim 9, characterized in that, The bio-nanopores include M2 ​​MspA nanopores.