Q-TOF mass spectrum database system and method for analyzing unknown object of medical instrument

Abstract

The invention discloses a Q-TOF mass spectrum database system and a Q-TOF mass spectrum database method for analyzing unknown substances of medical equipment. According to the system and the method, the traditional positive matching logic of quasi-molecule ion priority is abandoned, and a reverse analysis strategy from a structural unit to a molecular structure is creatively adopted. The core of the method is that: a candidate structural unit is locked preferentially through characteristic fragment ions in a secondary mass spectrum and mass difference matching between the ions; and carrying out intelligent combination calculation by combining information of primary excimer ions (essentially adduct ions), and finally deducing the molecular composition of an unknown compound. The method effectively solves the problems that a traditional method is low in unknown derivative identification success rate and excessively depends on expert experience, minute-level efficient identification is achieved, and the efficiency, accuracy and coverage range of medical instrument leached matter identification are remarkably improved.

Description

Technical Field

[0001] This invention relates to the fields of mass spectrometry analysis and cheminformatics, and more specifically, to a Q-TOF mass spectrometry database system and method for the analysis of unknown leachable substances in medical devices. Background Technology

[0002] In biocompatibility studies of medical devices, research on leachable substances is crucial. Its core lies in the precise identification of unknown leachable substances in the extract to construct a complete profile of leachable substances, providing data support for subsequent toxicological risk assessments.

[0003] Currently, the mainstream research strategy for unknown leachable compounds in the industry is to use high-resolution mass spectrometry (such as Q-TOF) to obtain precise mass spectral information of the compounds, and then identify them by matching with commercial databases. However, existing commercial databases and methods have two significant technical bottlenecks: First, the identification logic is rigid and lacks fault tolerance. Existing databases generally follow a forward matching logic of "from molecule to fragment," that is, they first and forcibly match the quasi-molecular ion peak in the primary mass spectrometer. Only when the quasi-molecular ion match is successful will the system compare secondary fragment ions; if it fails, the identification process terminates. This results in an extremely low success rate for derivatives released from complex material systems in medical devices, where the quasi-molecular ion information is incomplete or easily changeable.

[0004] Second, the over-reliance on expert experience leads to inefficiency. Due to the aforementioned logical flaws, a large number of unknowns must be manually analyzed by analysts, requiring significant time investment. This process is not only time-consuming and labor-intensive (often requiring hours or even days for a single unknown), but its accuracy and efficiency also heavily depend on the individual knowledge and experience of the analysts, constituting a major bottleneck for the popularization and efficiency improvement of this technology.

[0005] The root of the problem lies in the fact that existing technologies have failed to effectively utilize the "structural unit" information contained in secondary mass spectrometry fragments, which originates from finite material monomers and processing aids. Summary of the Invention

[0006] The purpose of this invention is to overcome the aforementioned deficiencies of the prior art and provide a Q-TOF mass spectrometry database system and method for the analysis of unknown substances in medical devices. This invention is based on a core understanding: although the final molecular structure of leachable substances is complex and varied, its basic building blocks all originate from a limited number of material monomers and processing aids.

[0007] In a first aspect, the present invention provides a Q-TOF mass spectrometry database system for the analysis of unknown substances in medical devices.

[0008] The system employs a reverse analytical logic "from structural unit to molecular structure," and its core comprises three functional modules: 1. Unknown compound auxiliary analysis module: As the core functional module of the system, it is used to receive input mass spectrometry data, and by calling the pre-built structural unit database, it prioritizes the intelligent matching and analysis of secondary fragment ions to identify potential structural units. It also performs constrained combination calculations in combination with the mass-charge ratio of quasi-molecular ions, and finally outputs the identification results of unknown compounds or their structural unit composition.

[0009] 2. Single-unit combination calculation module: As the core calculation engine of the system, it provides two calculation modes: forward combination calculation and reverse composition analysis, providing key algorithmic support for the reverse analysis logic of this invention.

[0010] 3. Feature Fragment Query Module: As a query service module, it provides a fast retrieval interface for feature fragment ion information for specific structural units.

[0011] Secondly, the present invention provides a Q-TOF mass spectrometry database method for the analysis of unknown substances in medical devices.

[0012] This method is based on a reverse parsing strategy and includes the following steps: 1. Construct a structural unit information database containing structural unit names, element composition, feature fragment information, and feature differences; 2. Import the primary and secondary mass spectrometry data of the target compound; 3. Prioritize characteristic ion matching and characteristic difference matching of fragment ions in secondary mass spectrometry to identify candidate structural units; 4. Based on the identified structural units, and combined with the quasi-molecular ion mass-charge ratio provided by the first-level mass spectrometer, the final compound molecular formula, structure, or structural unit composition information is automatically derived through constraint and combination calculations.

[0013] The beneficial effects of this invention are as follows: 1. Revolutionary Improvement in Identification Efficiency and Success Rate: By employing a "fragment-first" reverse matching strategy, this method effectively overcomes the identification impasse caused by the failure of quasi-molecular ion matching in traditional databases. Practice has shown that this method achieves highly efficient identification at the minute level, significantly improving the success rate of identifying unknown derivatives.

[0014] 2. Significantly reduces technical barriers and operational difficulty: The system transforms the complex analysis process that relies on expert experience into a standardized and intelligent calculation process, reducing the professional skill requirements for analysis personnel and effectively promoting the popularization and application of this technology.

[0015] 3. Enhanced identification capabilities and coverage: Particularly suitable for identifying new compounds derived from basic material units, expanding the range of identifiable leachable substances and providing more comprehensive and reliable protection for the chemical safety of medical devices. Attached Figure Description

[0016] Figure 1 This is the core method flowchart of the unknown object auxiliary analysis module of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] 1. System Foundation: Continuously Updating Structural Unit Information Database The foundation of this invention's system lies in a dynamically expandable structural unit information database. This database is initialized and updated manually and employs a continuously open architecture, allowing users to add new structural units and their mass spectrometry behavior data at any time based on actual research needs and accumulated knowledge, ensuring the continuous evolution of the system's identification capabilities and the constant expansion of its coverage. The input content includes at least: structural unit name, elemental composition, characteristic ion mass-to-charge ratio, elemental composition and structural formula, and structural unit difference characteristics.

[0019] 2. Core analysis process (combined with...) Figure 1 ) The core analysis process of this invention follows Figure 1 The logic block diagram shown specifically includes the following steps: S1. Mass Spectrometry Data Import: The system receives and imports raw data files acquired by high-resolution mass spectrometers such as Q-TOF.

[0020] S2. Characteristic Ion Matching and Initial Screening of Structural Units: The system automatically identifies secondary mass spectrometry fragment peaks and matches them with the characteristic fragment library of structural units. It outputs a list of successfully matched structural units and the matching degree K, where K = (n / m) × 100% (n is the number of matches, and m is the total number of characteristic fragments of that unit in the library).

[0021] S3. Feature Difference Matching and Structural Unit Verification: The system calculates the mass-to-charge ratio difference between secondary fragment ions and matches it with feature differences in the library. The system outputs the number of matches, which indicates the frequency of recurrence of structural units.

[0022] S4. Combinatorial Calculation Trigger: The system decides whether to execute subsequent combination calculations based on user instructions.

[0023] S5. Modification Item Selection: When performing combined calculations, users can choose to introduce modification items (such as +H2O, -H2O, +O, etc.) to simulate chemical modifications.

[0024] S6. Charge state determination: The charge number is determined by analyzing the isotope peak distribution and using the formula z=1 / Δ(m / z).

[0025] S7. Determination of adduct ion type: Diagnostic mass difference (such as H+) is determined by scanning near the quasi-molecular ion peak. + with Na + (Difference -21.9819 Da), determine the type of adduct ion (e.g., [M+H)). + [M+Na] + ), and estimate the neutral molecular weight M.

[0026] S8. Structural Unit Combination Calculation: Based on the mathematical model a×[mass1]+b×[mass2]+....+[modifier mass]=M, iterative calculations are performed to solve for the stoichiometric coefficients a,b,... . The exact solution is output first; if no exact solution is found, the optimal approximate solution and the elemental composition of the remaining mass difference are output.

[0027] S9. Comprehensive Analysis Result Output: The system generates and outputs a structured comprehensive evaluation report.

[0028] 3. Example Example 1: Target Ion m / z The parsing process for = 558.2810 The library information involving this ion is as follows:

[0029] S1, Data Import The mass spectrometry data obtained from Q-TOF will be imported into the system.

[0030] Its first-order mass spectrometry (only the target mass-to-charge ratio is listed) m / z The table below shows the fragment ion peaks of the secondary mass spectrometry (within ±22) and the peaks of the highest abundance (only the peaks of the highest abundance are listed, and isotope peaks are omitted).

[0031]

[0032] S2, Characteristic Ion Matching Analysis The system automatically matched the secondary mass spectrometry fragments of the target ion, and the results are as follows: (1) Fragment ions m / z287.1024, 269.0919, 225.1018, 150.0548, and 132.0441 were successfully matched to the MDI structural unit. This structural unit has 6 preset characteristic ions, and 5 were matched, with a matching degree of 83.3%.

[0033] (2) Fragment ions m / z 101.0595, 111.0442, and 129.0544 were successfully matched to the adipic acid structural unit. This structural unit has four predefined characteristic ions, and three were successfully matched, with a matching degree of 75%.

[0034] S3, Feature Difference Matching Analysis The system successfully matched the characteristic difference of the butanediol structural unit to the mass difference between fragment ions through mass difference analysis, with a matching number of 13.

[0035] The following ions were matched to the characteristic difference.

[0036]

[0037] S4 Combination Calculation Trigger Judgment The system provides two resolution paths: (1) If you choose not to perform combination calculations, the system will output the current matching results (including each structural unit and its matching degree and number of matches) for manual analysis. The exported results are shown in the table below.

[0038]

[0039] (2) If you choose to perform combined calculations, then select the modifier (S5) and continue the subsequent automatic calculation process.

[0040] S5 Modification Options Based on the reaction characteristics of the structural unit and the process background, the following possible modification terms are selected for combination calculation: [+H2O], [+CH3OH], [+CH3CH2OH].

[0041] S6, Charge State Confirmation Based on the target peak cluster ( m / z The isotopic spacing of 558.2810, 559.2846, and 560.2868 was calculated, and the charge number = 1 / (558.2810-559.2846) ≈ 1, confirming that it is a single-charged ion.

[0042] S7, confirmation of adduct ions Found within ±22 of the target mass-to-charge ratio. m / z 541.2532 (difference -17.0278, close to H) + With NH4 + (difference) and m / z563.2359 (difference +4.9549, close to Na) + With NH4 + The difference (value) is used to determine that the target ion is [M+NH4]. + The calculated neutral molecular weight M is 540.2472.

[0043] S8, Combined Calculation Execution The system is based on the formula a×[C 15 H 12 [N2O3] + b×[C6H8O3] + c×[C4H8O] + ​​[Modifier] = M Calculate separately: (1) Do not use modifiers (2) Use the modifier [+H2O] (3) Use the modifier [+CH3OH] (4) Use the modifier [+CH3CH2OH] The optimal solution was finally obtained: a=1, b=1, c=2. The target molecular weight could be accurately matched without modification terms (mass difference value is 0), and the composition of the compound was determined to be 1 MDI unit, 1 adipic acid unit and 2 butanediol units.

[0044] S9: Export Results

[0045] Example 2: Target Ion m / z Parsing process for =634.3594 and 618.4014 The library information related to the above target ions is as follows:

[0046] S1, Data Import The mass spectrometry data obtained from Q-TOF will be imported into the system.

[0047] Its first-order mass spectrometry (only the target mass-to-charge ratio is listed) m / z The table below shows the fragment ion peaks of the secondary mass spectrometry (within ±22) and the peaks of the highest abundance (only the peaks of the highest abundance are listed, and isotope peaks are omitted).

[0048]

[0049] S2, Characteristic Ion Matching

[0050] S3, Feature Difference Matching

[0051] S4, Combination Calculation Trigger Judgment Choose to perform combined calculations.

[0052] S5, Modification Options Selection Methyl-hindered phenol is an antioxidant structural unit, and its possible side reaction is oxidation. In addition, considering that the direct combination of structural units may involve shrinkage, the following modifications are selected: [-H2O] and / or [+O] or [+2O] or [-2H] or [+O-2H] or [+2O-2H].

[0053] S6, Charge State Confirmation The results, calculated based on the isotopic spacing of the target peak cluster, are shown in the table below.

[0054]

[0055] S7, confirmation of adduct ions

[0056] S8, Combinatorial Calculation The system is based on the formula a×[C 14 H 20 [O3] + b×[C2H4O] + [modifier] = M Calculate separately: (1) Do not use modifiers (2) Use the modifier [-H2O] (3) Use the modifier [+O] (3) Use the modifier [+2O] (4) Use the modifier [-2H] (5) Use the modifier [+O-2H] (6) Use the modifier [+2O-2H] (7) Use the modifiers [-H2O] [+O] (8) Use the modifiers [-H2O] [+2O] (9) Use the modifiers [-H2O] and [-2H] (10) Use the modifiers [-H2O] and [+O-2H] (11) Use the modifiers [-H2O] [+2O-2H] S9. Export Results

[0057] Example 3: Application example of the single-unit combination calculation module In this embodiment, a systematic prediction of the leachable material is performed for medical devices with a known material composition of polyurethane. Based on the chemical composition of polyurethane, it is speculated that the leachable material may be a polymer product of MDI (diphenylmethane diisocyanate) and butanediol or related derivatives.

[0058] The operation process and parameter settings are as follows: 1. Batch Input: Import a series of target mass-to-charge ratio values ​​of suspected leachable materials obtained by Q-TOF into the system in batches.

[0059] 2. Structural Element Setting: Specify the structural element participating in the calculation as MDI (element composition: C 15 H 12 N2O3) and butanediol (elemental composition: C4H8O).

[0060] 3. Addition ion setting: Based on common ionization behavior, the addition ion type is preset to [H]⁺ or [NH4]⁺ for system matching and calculation.

[0061] 4. Modification term setting: Considering common side reactions such as hydrolysis, the modification term [+H2O] is included in the calculation to cover possible hydration derivatization products.

[0062] The system will perform reverse composition analysis on all input target mass-to-charge ratios based on the above parameters, and the analysis results are shown in the table below.

[0063]

[0064] Example 4: Feature Fragment Query Application Example Enter the structural unit name "MDI" in the query window and click query. The results are shown in the table below.

[0065]

[0066] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A Q-TOF mass spectrometry database system for the analysis of unknown substances in medical devices, characterized in that, The system employs a reverse analytical logic "from structural unit to molecular structure" and includes: The unknown substance-assisted analysis module is used to prioritize matching secondary fragment ions to identify structural units based on the input mass spectrometry data, and combine it with primary quasi-molecular ion information for combined calculations to output identification results; The single-unit combination calculation module is used to perform forward combination calculations and reverse composition analysis of structural units; The feature fragment query module is used to provide query services for feature fragment information of structural units.

2. The system according to claim 1, characterized in that, The system operates based on a dynamically expandable structural unit information database, which stores the names, elemental composition, characteristic fragment information, and characteristic differences of structural units, and supports user updates and additions.

3. The method according to claim 3, characterized in that, The feature ion matching step includes calculating the matching degree K, K=(n / m)×100%, where n is the number of successfully matched fragment ions and m is the total number of feature fragments pre-stored in the structural unit.

4. The method according to claim 3, characterized in that, The feature difference matching step outputs a matching number, which refers to the total number of times that the mass-to-charge ratio difference between fragment ion pairs matches the feature mass difference of the structural unit.

5. The method according to claim 3, characterized in that, The combined calculation steps are based on the mathematical model a×[mass of structural unit 1]+b×[mass of structural unit 2]+....+[mass of modification]=M, which is solved iteratively. Here, a, b,... are non-negative integers to be solved, which represent the number of structural units, and M is the neutral molecular weight calculated from the quasi-molecular ion.

6. The method according to claim 6, characterized in that, When the mathematical model has no exact integer solution, the feasible solution with the theoretical molecular weight closest to M is output as the optimal approximate solution, and the remaining mass difference and its potential elemental composition are calculated.

7. The method according to claim 3, characterized in that, Before the combined calculation, the steps also include determining the charge state of the collimated ion and the type of adduct ion.

8. The method according to claim 3, characterized in that, The method allows users to introduce one or more modification terms representing chemical modifications in combinatorial calculations.

9. The method according to claim 3, characterized in that, The method is applicable to the analysis of mass spectrometry data in both ESI positive ion mode and ESI negative ion mode.

10. The method according to claim 3, characterized in that, Throughout the entire calculation process described in the method, the system has a preset configurable tolerance range for quality errors. Users can adjust this parameter according to the instrument's accuracy and analytical needs to control the error tolerance and matching accuracy of the system calculation, effectively balancing the comprehensiveness and accuracy of the identification results.

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