Automation-based high-throughput analysis method and system, medium and product

Abstract

The invention discloses a high-throughput analysis method and system based on automation, a medium and a product. The method comprises the following steps: collecting data of a plurality of samples in a preset number of pore plate containers; the abscissa is time, and the ordinate is a mass spectrum detection diagram of ion signal intensity; determining target product mass spectra under different reaction conditions; determining a target product mass spectrum peak area list; selecting the first percentage X in the target product mass spectrum peak area list to obtain a TOPX% target compound reaction condition list; based on preset TopX reaction condition sequence information and a TOPX% target compound reaction condition list, sequentially testing target compounds under different TOPX% reaction conditions to obtain TOPX data; determining an ultraviolet spectrogram according to the TOPX data; and determining the proportion of each target compound according to the area of each ultraviolet peak and the total area of all the ultraviolet peaks, and generating a target compound proportion pie chart. By implementing the method, the sample analysis efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of automation technology, and in particular to a high-throughput analysis method, system, medium and product based on automation. Background Art

[0002] In the field of modern biomedicine and chemical analysis, high-throughput analysis technology plays a vital role. This technology can process large batches of samples and quickly complete data collection, analysis and interpretation, significantly improving the efficiency and accuracy of experiments.

[0003] Currently, liquid chromatography-mass spectrometry (LC-MS) is commonly used for high-throughput analysis. In this technology, samples are first separated by liquid chromatography and then detected and analyzed by mass spectrometry. Chromatographic separation can be based on the hydrophilicity or hydrophobicity of the compound, while mass spectrometry detection depends on the mass-to-charge ratio of the compound and the intensity of the ion signal.

[0004] Although liquid chromatography-mass spectrometry is widely used in multi-sample analysis, it still faces some challenges when processing extremely large samples. For example, when screening samples, it is difficult to automate operations according to screening requirements and analysis scenarios, resulting in low efficiency in the final sample analysis. Summary of the invention

[0005] The present application provides a high-throughput analysis method, system, medium and product based on automation, which are used to improve the efficiency of sample analysis.

[0006] In a first aspect, the present application provides an automated high-throughput analysis method, which is applied to a high-throughput analysis system, the method comprising: collecting multiple sample data in a preset number of orifice plate containers, the preset number of orifice plate containers comprising a preset number of small holes, the small holes being used to load target reactants, the target reactants reacting in the small holes to generate target products, the reaction conditions of the target reactants in each of the small holes being different, the sample data comprising the ion signal intensity and mass-to-charge ratio of the target compounds in each of the small holes, the target compounds comprising the target reactants, the target products and impurities; determining a mass spectrum detection graph with the horizontal axis being time and the vertical axis being the ion signal intensity according to the relationship between the mass-to-charge ratio and time in the sample data; cutting the mass spectrum detection graph based on a preset sample injection time and analysis duration table to obtain target generated mass spectra under different reaction conditions, the preset sample injection time and analysis duration table comprising different injection times and different analysis durations corresponding to the target reactants under different reaction conditions; calculating the target generated mass spectrum peak area according to the target generated mass spectrum, and sorting them from large to small to obtain the target generated mass spectrum. A peak area list; selecting the first X percent in the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, where X is between 0 and 100, and the TOPX% target compound reaction condition list includes the TOPX% reaction conditions corresponding to the target compound; based on the preset TopX reaction condition sequence information and the TOPX% target compound reaction condition list, testing the target compound under different TOPX% reaction conditions in sequence to obtain TOPX data, where the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under different TOPX% reaction conditions, and the TOPX data refers to the chromatographic data obtained by testing the target compound under different TOPX% reaction conditions; determining an ultraviolet spectrum according to the TOPX data, where the ultraviolet spectrum includes multiple ultraviolet peaks, and the ultraviolet peaks correspond to the target compound one by one; determining the proportion of each target compound according to the area of ​​each ultraviolet peak and the total area of ​​all ultraviolet peaks, and generating a target compound proportion pie chart, where the target compound proportion pie chart includes the proportions corresponding to multiple target compounds respectively.

[0007] By adopting the above technical solution, automated analysis from sample data collection to TOPX% reaction condition extraction, TOPX% reaction condition testing and visualization of test results is achieved, which helps to quickly grasp the information of target compounds in the reaction system, greatly improves the accuracy and efficiency of high-throughput analysis methods, and saves time and resources.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the first X percent in the mass spectrum peak area list of the target product is selected to obtain a TOPX% target compound reaction condition list, specifically including: if the target reactant generates multiple sub-target products, then the X percent is equally divided according to the number of the sub-target products to obtain the Y percent corresponding to each sub-target product; the first Y percent in the mass spectrum peak area list of each sub-target product is selected to obtain multiple TOPY% target compound reaction condition lists, the TOPY% target compound reaction condition lists include the TOPY% reaction conditions corresponding to the sub-target reactants, and the number of the TOPY% target compound reaction condition lists is the same as the number of the sub-target products.

[0009] By adopting the above technical solution, when the target reactant may generate multiple sub-target products, first, the high-throughput analysis system divides the percentage X equally according to the number of sub-target products to obtain the percentage Y corresponding to each sub-target product, and then the high-throughput analysis system performs TOPY% identification on each sub-target product. This method ensures that each sub-target product can be accurately and fully analyzed, avoiding the situation where some sub-target products are ignored. At the same time, due to the reasonable distribution of the analysis ratio, the entire analysis process is comprehensive and efficient, thereby accurately reflecting the generation of each sub-target product under different reaction conditions.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the step of selecting the top Y percent in the list of peak areas of each sub-target generated material spectrum to obtain multiple TOPY% target compound reaction condition lists, the method also includes: if there are repeated reaction conditions in any TOPY% target compound reaction condition list, then selecting the reaction condition with the highest corresponding mass spectrum peak value in the repeated reaction conditions; if the number of sub-target generated material spectra selected from the sub-target generated material spectrum peak area list does not reach the top Y percent, then selecting the sub-target generated material spectrum with the largest sub-target generated material spectrum peak area from the sub-target generated material spectrum peak area list to fill the gap, and the sub-target generated material spectrum corresponds one-to-one to the reaction condition.

[0011] By adopting the above technical solution, the high-throughput analysis system sets up a processing mechanism for repeated reaction conditions and a data completion mechanism, which further improves the accuracy and completeness of the analysis. That is, when there are repeated reaction conditions in any TOPY% target compound reaction condition list, the high-throughput analysis system selects the reaction condition with the highest mass spectrum peak value to avoid data redundancy; when the number of sub-target generated mass spectra in the sub-target generated mass spectrum peak area list is insufficient, the high-throughput analysis system selects the sub-target generated mass spectrum with the largest sub-target generated mass spectrum peak area in the remaining data for completion, ensuring the integrity of the data analysis. This method not only ensures the reliability of the analysis results, but also improves the analysis efficiency. At the same time, by establishing a one-to-one correspondence between the reaction conditions and the sub-target generated mass spectra, the analysis results are clearer and more intuitive, which is convenient for subsequent data processing and result interpretation.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of selecting the top X percent in the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, the method further includes: obtaining relevant information of the preset number of well plate containers, the relevant information including the sample position corresponding to each different reaction condition, the sample name corresponding to the target compound, the molecular weight of the target reactant and the molecular weight of the target product; based on the sample position corresponding to each different reaction condition, determining the TOP sample position under different TOPX% reaction conditions; according to the TOP sample position under different TOPX% reaction conditions, determining the preset TopX reaction condition sequence information, the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under different TOPX% reaction conditions.

[0013] By adopting the above technical solution, the high-throughput analysis system obtains relevant information of the preset number of well plate containers, and determines the TOP sample position and test order based on this relevant information, achieving accurate positioning and orderly progress of the analysis process. This method avoids sample confusion or positioning errors that may occur during the analysis process, allowing subsequent testing work to be carried out accurately and efficiently. At the same time, testing in accordance with the test order can make the entire analysis process more standardized and systematic, improving analysis efficiency and accuracy.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining relevant information of the preset number of well plate containers, the relevant information including the sample position corresponding to each different reaction condition, the sample name corresponding to the target compound, the molecular weight of the target reactant and the molecular weight of the target product, the method further includes: setting a database based on the molecular weight of chemical compounds, determining the molecular weight identification parameters of the target reactant and the molecular weight identification parameters of the target product; determining the final molecular weight of the target reactant and the final molecular weight of the target product according to the molecular weight and molecular weight identification parameters of the target reactant, and the molecular weight and molecular weight identification parameters of the target product; determining the ultraviolet peak corresponding to the target compound based on the final molecular weight of the target reactant and the final molecular weight of the target product.

[0015] By adopting the above technical solution, the high-throughput analysis method can accurately identify the target reactants and target products through the chemical compound molecular weight database, so that the UV peak corresponding to each target compound can be determined. This method improves the accuracy of the analysis results, makes the analysis process more standardized and automated, and at the same time, through the accurate correspondence of the UV peak, it provides a reliable data basis for subsequent quantitative analysis.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of calculating the peak area of ​​the target generated mass spectrum based on the target generated mass spectrum and sorting them from large to small to obtain a target generated mass spectrum peak area list, the method also includes: according to the target generated mass spectrum peak area list, converting the target generated mass spectrum area under different reaction conditions into a visual heat map, and the display method in the visual heat map is determined by the target generated mass spectrum area.

[0017] By adopting the above technical solution, the high-throughput analysis method introduces the visualization heat map technology, which converts the mass spectrum area of ​​the target product under different reaction conditions into an intuitive visualization heat map for display. This method can intuitively reflect the difference in the amount of target product generated under different reaction conditions, making it easier for researchers to quickly identify the optimal reaction conditions and key influencing factors, and significantly improving the intuitiveness and practicality of data analysis.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining an ultraviolet spectrum according to the TOPX data, wherein the ultraviolet spectrum includes multiple ultraviolet peaks, and the ultraviolet peaks correspond one-to-one to the target compound, the method further includes: if a target compound corresponds to multiple ultraviolet peaks, determining multiple ultraviolet peak areas of a target compound; determining the diastereomeric excess percentage of the target compound based on the multiple ultraviolet peak areas, and the diastereomeric excess percentage is used to quantitatively evaluate the degree of asymmetry of the diastereomeric mixture generated in the reaction to optimize the reaction conditions.

[0019] By adopting the above technical solution, when a target compound may correspond to multiple UV peaks, the diastereomeric excess percentage can be determined by calculating the areas of multiple UV peaks, which provides an important basis for optimizing the reaction conditions. This method provides more comprehensive compound characteristic information, so that the stereoselectivity of the reaction can be accurately evaluated.

[0020] In a second aspect, an embodiment of the present application provides a high-throughput analysis system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the high-throughput analysis system to perform the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on a high-throughput analysis system, enables the high-throughput analysis system to perform the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a high-throughput analysis system, the high-throughput analysis system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0023] It is understandable that the high-throughput analysis system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By adopting the above technical solution, automated analysis from sample data collection to TOPX% reaction condition extraction, TOPX% reaction condition testing and visualization of test results is realized, which helps to quickly grasp the information of target compounds in the reaction system, greatly improves the accuracy and efficiency of high-throughput analysis methods, and saves time and resources.

[0025] 2. By adopting the above technical solution, the high-throughput analysis system sets up a processing mechanism for repeated reaction conditions and a data completion mechanism, which further improves the accuracy and completeness of the analysis. That is, when there are repeated reaction conditions in any TOPY% target compound reaction condition list, the high-throughput analysis system selects the reaction condition with the highest mass spectrum peak value to avoid data redundancy; when the number of sub-target generated mass spectra in the sub-target generated mass spectrum peak area list is insufficient, the high-throughput analysis system selects the sub-target generated mass spectrum with the largest sub-target generated mass spectrum peak area in the remaining data for completion, ensuring the integrity of the data analysis. This method not only ensures the reliability of the analysis results, but also improves the analysis efficiency. At the same time, by establishing a one-to-one correspondence between the reaction conditions and the sub-target generated mass spectra, the analysis results are clearer and more intuitive, which is convenient for subsequent data processing and result interpretation.

[0026] 3. By adopting the above technical solution, when a target compound may correspond to multiple UV peaks, the diastereomeric excess percentage can be determined by calculating the areas of multiple UV peaks, which provides an important basis for optimizing the reaction conditions. This method provides more comprehensive compound characteristic information, so that the stereoselectivity of the reaction can be accurately evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of a process of a high-throughput analysis method based on automation in an embodiment of the present application; Figure 2 is another schematic diagram of the process of the high-throughput analysis method based on automation in the embodiment of the present application; Figure 3 It is a schematic diagram of a physical device structure of a high-throughput analysis system in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , is a flow chart of a high-throughput analysis method based on automation in an embodiment of the present application.

[0031] S101, collecting a plurality of sample data in a preset number of orifice plate containers, wherein the preset number of orifice plate containers includes a preset number of small holes, wherein the small holes are used to load target reactants, wherein the target reactants react in the small holes to generate target products, wherein the reaction conditions of the target reactants in each of the small holes are different, and wherein the sample data includes the ion signal intensity and mass-to-charge ratio of the target compounds in each of the small holes, wherein the target compounds include the target reactants, the target products, and impurities; Among them, a preset number of well plate containers refers to a multi-well plate device for placing samples, including a preset number of small holes, for example, a 96-well plate; a small hole refers to a sample placement space unit on a preset number of well plate containers, and each hole is used to load a target reactant; a target reactant refers to a substance that needs to react; a target product refers to a product generated after the reaction; reaction conditions refer to various parameters affecting the reaction, such as temperature, pressure, catalyst, etc.; sample data refers to experimental data obtained through mass spectrometry detection; ion signal intensity refers to the abundance of ions in mass spectrometry detection; mass-to-charge ratio refers to the ratio of ion mass to charge; target compounds refer to all related compounds in the reaction system; impurities refer to non-target substances produced in the reaction.

[0032] Specifically, first, the high-throughput analysis system confirms the position information and corresponding reaction conditions of each small hole in the preset number of well plate containers. Then, the high-throughput analysis system scans and detects the samples in each small hole through a mass spectrometer to obtain ion signal intensity and mass-to-charge ratio data. During the detection process, the high-throughput analysis system will scan the samples in each small hole multiple times to ensure the accuracy of the data, and record the data changes at different time points. The high-throughput analysis system will preliminarily screen and organize all the collected sample data to form a complete target compound data set containing target reactants, target products, and impurities.

[0033] S102, determining a mass spectrum detection graph with the horizontal axis being time and the vertical axis being ion signal intensity according to the relationship between the mass-to-charge ratio and time in the sample data; Among them, the mass spectrum detection diagram is a two-dimensional graph used to reflect the changes of mass spectrum data over time; the horizontal axis represents the time axis during the detection process; the vertical axis represents the detected ion signal intensity value; the change relationship refers to the corresponding relationship between mass-to-charge ratio and time.

[0034] Specifically, first, the high-throughput analysis system arranges the collected mass-to-charge ratios in chronological order to determine the ion signal intensity corresponding to each time point. Then, the high-throughput analysis system establishes a rectangular coordinate system, with time as the horizontal axis and ion signal intensity as the vertical axis, and plots the data points in the rectangular coordinate system. The high-throughput analysis system generates continuous mass spectrometry detection graphs through data smoothing and curve fitting, making the data change trend more clearly visible.

[0035] S103, based on a preset sample injection time and analysis time table, cutting the mass spectrum detection graph to obtain target generated mass spectra under different reaction conditions, wherein the preset sample injection time and analysis time table includes different injection times and different analysis times corresponding to target reactants under different reaction conditions; Among them, the preset sample injection time and analysis duration table refers to the pre-set sample detection time schedule; the injection time refers to the time point when the sample is detected; the analysis duration refers to the detection duration of a single sample; cutting refers to the division of the mass spectrometry detection graph into time intervals; the target generated mass spectrum refers to the mass spectrum of the target product under different reaction conditions.

[0036] Specifically, first, the high-throughput analysis system reads the preset sample injection time and analysis duration table to determine the data collection time interval corresponding to each reaction condition. Then, the high-throughput analysis system accurately cuts the mass spectrometry detection graph according to these data collection time intervals to separate the data under different reaction conditions. For each cut data segment, the high-throughput analysis system performs background noise elimination and baseline correction to obtain a clear target generated mass spectrum.

[0037] S104, calculating the peak area of ​​the target generated mass spectrum according to the target generated mass spectrum, and sorting them from large to small to obtain a target generated mass spectrum peak area list; The target generated mass spectrum peak area refers to the integrated area of ​​the peak in the target generated mass spectrum; the target generated mass spectrum peak area list refers to a data table containing all target generated mass spectrum peak areas and their sorting information.

[0038] Specifically, first, the high-throughput analysis system performs peak detection on each target generated mass spectrum to determine the starting point and end point of each peak. Then, the high-throughput analysis system uses a numerical integration method to calculate the integrated area of ​​the peak in each target generated mass spectrum, while considering the effects of baseline correction and peak overlap. The high-throughput analysis system sorts all the calculated target generated mass spectra peak areas in descending order to obtain a target generated mass spectrum peak area list.

[0039] S105, selecting the top X percent in the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, where X is between 0 and 100, and the TOPX% target compound reaction condition list includes the TOPX% reaction conditions corresponding to the target compound; Among them, the first percent X is used to represent the proportion threshold selected from the target generated mass spectrum peak area list; the TOPX% target compound reaction condition list refers to the set of dominant reaction conditions obtained after screening; X refers to a percentage value between 0 and 100; and the TOPX% reaction condition refers to the screened dominant reaction condition.

[0040] Specifically, first, the high-throughput analysis system determines the appropriate value of X according to the research objectives and analysis requirements, usually selecting values ​​such as 10, 20 or 30. Then, the high-throughput analysis system selects the data with the largest target generated mass spectrum peak area from the sorted target generated mass spectrum peak area list according to the top X percent. For the selected data, the high-throughput analysis system extracts the corresponding reaction conditions, including temperature, pressure, solvent, catalyst and other parameters, to form a TOPX% target compound reaction condition list.

[0041] Optionally, under normal circumstances, selecting the first X percent in the mass spectrum peak area list of the target generation to obtain a TOPX% target compound reaction condition list can be achieved in the following manner, which is not limited here: if the target reactant generates multiple sub-target products, then dividing the X percent equally according to the number of the sub-target products to obtain the Y percent corresponding to each sub-target product; selecting the first Y percent in the mass spectrum peak area list for each sub-target generation to obtain multiple TOPY% target compound reaction condition lists, the TOPY% target compound reaction condition list includes the TOPY% reaction conditions corresponding to the sub-target reactants, and the number of the TOPY% target compound reaction condition lists is the same as the number of the sub-target products.

[0042] Optionally, under normal circumstances, after selecting the top Y percent in the list of peak areas of each sub-target generated mass spectrum to obtain multiple TOPY% target compound reaction condition lists, the following steps can be performed, which are not limited here: if there are repeated reaction conditions in any TOPY% target compound reaction condition list, then the reaction condition with the highest corresponding mass spectrum peak value in the repeated reaction conditions is selected; if the number of sub-target generated mass spectra selected from the sub-target generated mass spectrum peak area list does not reach the top Y percent, then the sub-target generated mass spectrum with the largest sub-target generated mass spectrum peak area is selected from the sub-target generated mass spectrum peak area list to fill the gap, and the sub-target generated mass spectrum corresponds one-to-one to the reaction condition.

[0043] S106. Based on the preset TopX reaction condition sequence information and the TOPX% target compound reaction condition list, the target compound under different TOPX% reaction conditions is tested in sequence to obtain TOPX data, wherein the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under different TOPX% reaction conditions, and the TOPX data refers to chromatographic data obtained by testing the target compound under different TOPX% reaction conditions; Among them, the preset TopX reaction condition sequence information refers to the sequential arrangement of testing the screened superior reaction conditions; the test sequence refers to the order in which the tests are performed; TOPX data refers to the chromatographic data obtained after the test; and chromatographic data refers to the separation detection results obtained through chromatographic analysis.

[0044] Specifically, first, the high-throughput analysis system formulates the optimal test sequence according to the experimental equipment status and sample characteristics, that is, the preset TopX reaction condition sequence information. Then, the high-throughput analysis system tests each TOPX% reaction condition in turn according to the preset TopX reaction condition sequence information. In each test, the high-throughput analysis system controls the precise setting of the reaction conditions, and separates and detects the reactants and products through chromatographic instruments to obtain TOPX data.

[0045] S107, determining an ultraviolet spectrum according to the TOPX data, wherein the ultraviolet spectrum includes a plurality of ultraviolet peaks, and the ultraviolet peaks correspond one to one to the target compound; Among them, the ultraviolet spectrum refers to the spectrum reflecting the ultraviolet absorption characteristics of the target compound; the ultraviolet peak refers to the absorption peak in the ultraviolet spectrum.

[0046] Specifically, first, the high-throughput analysis system extracts and processes the UV detector response of the chromatographic data to obtain a complete UV spectrum that reflects the UV absorption characteristics of the sample. Then, the high-throughput analysis system determines the target compound corresponding to each UV peak through peak shape analysis and spectral feature matching. The high-throughput analysis system simultaneously considers the structural characteristics and functional group information of the target compound to ensure the accuracy of the attribution of the UV peak. For possible overlapping peaks, the high-throughput analysis system uses a peak separation algorithm to process them to ensure accurate single peak information.

[0047] S108. Determine the proportion of each target compound according to the area of ​​each ultraviolet peak and the total area of ​​all ultraviolet peaks, and generate a target compound proportion pie chart, wherein the target compound proportion pie chart includes proportions corresponding to a plurality of target compounds.

[0048] Among them, the area of ​​the UV peak refers to the integrated area of ​​a peak in the UV spectrum; the total area of ​​all UV peaks refers to the sum of the integrated areas of all peaks in the UV spectrum; the target compound proportion represents the relative content of a target compound in the mixture; the target compound proportion pie chart is used to visualize the distribution of the content of each target compound.

[0049] Specifically, first, the high-throughput analysis system performs accurate area integration calculations for each UV peak, taking into account the effects of baseline correction and peak overlap. Then, the high-throughput analysis system calculates the sum of the areas of all UV peaks as a normalized reference value. The high-throughput analysis system calculates the relative content percentage of each target compound by the ratio of the area of ​​a single UV peak to the total area of ​​all UV peaks. Finally, the high-throughput analysis system converts the calculation results into an intuitive target compound proportion pie chart, in which the angle and area of ​​the sector in the target compound proportion pie chart are proportional to the relative content percentage of the target compound. The high-throughput analysis system also marks the specific percentage values ​​and the name of the target compound in the target compound proportion pie chart, and distinguishes them through different colors and legends, making the results clearer and easier to read.

[0050] By adopting the above technical solution, automated analysis from sample data collection to TOPX% reaction condition extraction, TOPX% reaction condition testing and visualization of test results is achieved, which helps to quickly grasp the information of target compounds in the reaction system, greatly improves the accuracy and efficiency of high-throughput analysis methods, and saves time and resources.

[0051] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the automated high-throughput analysis method in the embodiments of the present application.

[0052] After step S104, the following steps may be performed, which are not limited here: S201, according to the target generated mass spectrum peak area list, converting the target generated mass spectrum area under different reaction conditions into a visualized heat map, wherein the display mode in the visualized heat map is determined by the target generated mass spectrum area; Among them, the visualization heat map refers to a two-dimensional graph that uses different color depths or brightness to display data distribution; the display method refers to the color mapping rules and display format in the visualization heat map; the target product mass spectrum area refers to the amount of target product generated under each reaction condition.

[0053] Specifically, first, the high-throughput analysis system organizes the target generated mass spectrum area into a standardized two-dimensional data matrix according to the reaction conditions (such as temperature, pressure, time, etc.). Then, the high-throughput analysis system determines the appropriate color mapping rules and display format, usually selecting a gradient color system from cold to warm tones, such as from dark blue to dark red, to intuitively reflect the size changes of the data. Next, the high-throughput analysis system maps the numerical value of the target generated mass spectrum peak area to the selected color space according to the target generated mass spectrum peak area list.

[0054] S202, selecting the top X percent in the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, where X is between 0 and 100, and the TOPX% target compound reaction condition list includes the TOPX% reaction conditions corresponding to the target compound; For details, please refer to step S105, which will not be described in detail here.

[0055] S203, obtaining relevant information of the preset number of well plate containers, the relevant information including the sample position corresponding to each different reaction condition, the sample name corresponding to the target compound, the molecular weight of the target reactant, and the molecular weight of the target product; Among them, relevant information refers to the basic data set directly related to sample analysis; sample position refers to the specific spatial coordinates of the sample corresponding to each different reaction condition in the preset number of well plate containers, usually expressed as row and column numbers; sample name refers to the standard name or number of the target compound; molecular weight refers to the relative molecular mass value of the target compound.

[0056] Specifically, first, the high-throughput analysis system reads the electronic configuration file of the preset number of well plate containers, which contains complete sample layout information. Then, the high-throughput analysis system establishes a multidimensional data table to associate the physical location of each sample well (such as A1, B2, etc.) with its corresponding reaction conditions (such as temperature, pressure, time, etc.). At the same time, the high-throughput analysis system extracts the standard name (sample name) and theoretical molecular weight information of each target compound from the compound database, and establishes a mapping relationship between this information and the physical location of the well where the sample is located.

[0057] S204, determining a molecular weight identification parameter of the target reactant and a molecular weight identification parameter of the target product based on a database of molecular weights of chemical compounds; The chemical compound molecular weight setting database is a structured data system that contains molecular weight information of standard compounds; the molecular weight identification parameter is used to determine the tolerance range of the molecular weight of the target compound.

[0058] Specifically, first, the high-throughput analysis system is connected to the chemical compound molecular weight setting database, which contains the standard molecular weight information and isotope distribution patterns of common compounds. Then, the high-throughput analysis system sets appropriate molecular weight recognition parameters according to the performance parameters of the mass spectrometer and experimental requirements, including mass deviation tolerance (usually ±0.1 to ±0.5Da), isotope peak intensity ratio requirements, ionization mode determination rules, etc.

[0059] S205, determining the final molecular weight of the target reactant and the final molecular weight of the target product according to the molecular weight and molecular weight identification parameter of the target reactant, and the molecular weight and molecular weight identification parameter of the target product; The final molecular weight refers to the molecular weight value determined after parameter correction and verification; the combination of molecular weight and molecular weight identification parameter refers to the process of combining the standard molecular weight with possible mass deviation.

[0060] Specifically, first, the high-throughput analysis system adds or subtracts the molecular weight of the target reactant from the molecular weight identification parameter to determine the final molecular weight of the target reactant. The same method is applied to the target product, and the high-throughput analysis system adds or subtracts the molecular weight of the target product from the molecular weight identification parameter to determine the final molecular weight of the target product.

[0061] S206, determining the ultraviolet peak corresponding to the target compound based on the final molecular weight of the target reactant and the final molecular weight of the target product; Among them, the ultraviolet peak corresponding to the target compound refers to the characteristic absorption peak of the specific compound in the ultraviolet spectrum; the final molecular weight refers to the molecular weight value of the compound after calibration and confirmation.

[0062] Specifically, first, the high-throughput analysis system retrieves the standard UV spectra of the target reactants and target products from the spectral database according to the final molecular weight of the target reactants and the final molecular weight of the target products. Then, the high-throughput analysis system intelligently matches the measured UV spectra with the standard UV spectra, and performs a comprehensive score based on multiple parameters such as wavelength position, peak shape characteristics, and relative intensity. The high-throughput analysis system simultaneously considers the structural characteristics and chromophore information of the target compound, establishes strict peak attribution rules, and ensures that the correspondence between the UV peaks and the target compounds is accurate and reliable.

[0063] S207, based on the sample position corresponding to each different reaction condition, determining the TOP sample position under different TOPX% reaction conditions; Among them, TOP sample position refers to the specific spatial coordinates of the sample corresponding to the dominant reaction condition; TOPX% reaction condition refers to the screened dominant reaction condition.

[0064] Specifically, first, the high-throughput analysis system establishes a complete TOPX% reaction condition-TOP sample position correspondence table, and associates each TOPX% reaction condition with its specific spatial coordinates in a preset number of well plate containers. Then, the high-throughput analysis system uses an intelligent positioning algorithm to quickly locate the sample positions corresponding to these advantageous conditions.

[0065] S208, determining preset TopX reaction condition sequence information according to the TOP sample positions under the different TOPX% reaction conditions, where the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under the different TOPX% reaction conditions; Specifically, first, the high-throughput analysis system determines the TOP sample positions corresponding to the TOPX% reaction conditions in the preset number of well plate containers. Then, the high-throughput analysis method plans a shortest path based on all TOP sample positions, and based on the shortest path, determines the preset TopX reaction condition sequence information, wherein the preset TopX reaction condition sequence information refers to the test order arrangement of the samples under the dominant reaction conditions.

[0066] S209, based on the preset TopX reaction condition sequence information and the TOPX% target compound reaction condition list, sequentially test the target compound under different TOPX% reaction conditions to obtain TOPX data, wherein the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under different TOPX% reaction conditions, and the TOPX data refers to the chromatographic data obtained by testing the target compound under different TOPX% reaction conditions; For details, please refer to step S106, which will not be described in detail here.

[0067] S210, determining an ultraviolet spectrum according to the TOPX data, wherein the ultraviolet spectrum includes a plurality of ultraviolet peaks, and the ultraviolet peaks correspond one to one to the target compound; For details, please refer to step S107, which will not be described in detail here.

[0068] S211. If a target compound corresponds to multiple UV peaks, determine multiple UV peak areas of the target compound; Specifically, first, the high-throughput analysis system carefully examines the multiple ultraviolet peaks corresponding to the target compound to determine their wavelength positions and peak shape characteristics, where multiple ultraviolet peaks represent absorption peaks of the same target compound at different wavelength positions. Then, the high-throughput analysis system sets a suitable integration interval for each ultraviolet peak, taking into account the effects of baseline drift and peak shape distortion. For overlapping ultraviolet peaks, the high-throughput analysis system uses peak separation algorithms, such as Gaussian distribution fitting or spectrum deconvolution, to separate overlapping peaks into single peaks. The high-throughput analysis system uses numerical integration methods to calculate the area of ​​each single peak, while taking into account the effects of baseline correction. To improve the accuracy of the calculation, the high-throughput analysis system will perform multiple repeated calculations and use statistical methods to evaluate the uncertainty of the calculation results.

[0069] S212, determining the diastereomeric excess percentage of the target compound according to the multiple ultraviolet peak areas, wherein the diastereomeric excess percentage is used to quantitatively evaluate the degree of asymmetry of the diastereoisomer mixture generated in the reaction to optimize the reaction conditions; Among them, diastereomeric excess percentage refers to the relative content of the dominant diastereomer in the reaction product; diastereomers refer to isomers with different spatial configurations but not mirror-image relationships; reaction condition optimization refers to the process of adjusting reaction conditions to improve stereoselectivity.

[0070] Specifically, first, the high-throughput analysis system classifies the calculated multiple UV peak areas according to the attribution of diastereoisomers. Then, the high-throughput analysis system uses a known formula to calculate the diastereomeric excess percentage: ee%=[(AB) / (A+B)]×100%, where A and B represent the UV peak areas of two different isomers, respectively. The high-throughput analysis system takes into account the transmission of measurement errors and calculates the uncertainty of the ee value. For each set of reaction conditions, the high-throughput analysis system will generate a complete stereoselectivity analysis report, including ee value, error range and confidence interval. The high-throughput analysis system will also analyze the relationship between ee value and reaction conditions, and establish a mathematical model to describe the factors affecting stereoselectivity. Based on these analysis results, the high-throughput analysis system can predict the optimal reaction conditions and make suggestions for improving stereoselectivity.

[0071] S213. Determine the proportion of each target compound according to the area of ​​each ultraviolet peak and the total area of ​​all ultraviolet peaks, and generate a target compound proportion pie chart, wherein the target compound proportion pie chart includes proportions corresponding to a plurality of target compounds.

[0072] For details, please refer to step S108, which will not be described in detail here.

[0073] The following describes the high-throughput analysis system in the embodiment of the present invention from the perspective of hardware processing. Figure 3, is a schematic diagram of a physical device structure of a high-throughput analysis system in an embodiment of the present application.

[0074] It should be noted that Figure 3 The structure of the high-throughput analysis system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0075] like Figure 3 As shown, the high-throughput analysis system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0076] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0077] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0078] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0079] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0080] Specifically, the high-throughput analysis system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the automation-based high-throughput analysis method provided in the above embodiment is implemented.

[0081] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the high-throughput analysis system described in the above embodiment; or may exist independently without being assembled into the high-throughput analysis system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the high-throughput analysis system, the high-throughput analysis system implements the automation-based high-throughput analysis method provided in the above embodiment.

[0082] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0083] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0084] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A high-throughput analysis method based on automation, characterized in that: Applied to a high-throughput analysis system, the method comprises: Collecting multiple sample data in a preset number of orifice plate containers, wherein the preset number of orifice plate containers includes a preset number of small holes, wherein the small holes are used to load target reactants, wherein the target reactants react in the small holes to generate target products, wherein the reaction conditions of the target reactants in each of the small holes are different, wherein the sample data includes the ion signal intensity and mass-to-charge ratio of the target compounds in each of the small holes, wherein the target compounds include the target reactants, the target products, and impurities; According to the relationship between the mass-to-charge ratio and time in the sample data, a mass spectrum detection graph is determined with the horizontal axis being time and the vertical axis being ion signal intensity; Based on a preset sample injection time and analysis time table, the mass spectrum detection graph is cut to obtain a target generated mass spectrum under different reaction conditions, wherein the preset sample injection time and analysis time table includes different injection times and different analysis times corresponding to target reactants under different reaction conditions; Calculate the peak areas of the target generated mass spectrum according to the target generated mass spectrum, and sort them from large to small to obtain a target generated mass spectrum peak area list; Select the top X percent in the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, where X is between 0 and 100, and the TOPX% target compound reaction condition list includes the TOPX% reaction conditions corresponding to the target compound; Based on the preset TopX reaction condition sequence information and the TOPX% target compound reaction condition list, the target compound under different TOPX% reaction conditions is tested in sequence to obtain TOPX data, wherein the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under different TOPX% reaction conditions, and the TOPX data refers to the chromatographic data obtained by testing the target compound under different TOPX% reaction conditions; Determine an ultraviolet spectrum according to the TOPX data, wherein the ultraviolet spectrum includes a plurality of ultraviolet peaks, and the ultraviolet peaks correspond one to one to the target compound; According to the area of ​​each ultraviolet peak and the total area of ​​all ultraviolet peaks, the proportion of each target compound is determined, and a pie chart of the target compound proportions is generated, wherein the pie chart of the target compound proportions includes the proportions corresponding to the multiple target compounds.

2. The method according to claim 1, characterized in that The selecting the top X percent of the target generated mass spectrum peak area list to obtain the TOPX% target compound reaction condition list specifically includes: If the target reactant generates multiple sub-target products, then the percentage X is equally divided according to the number of the sub-target products to obtain the percentage Y corresponding to each sub-target product; The first Y percent of the mass spectrum peak area list generated by each sub-target is selected to obtain multiple TOPY% target compound reaction condition lists, wherein the TOPY% target compound reaction condition lists include the TOPY% reaction conditions corresponding to the sub-target reactants, and the number of the TOPY% target compound reaction condition lists is the same as the number of the sub-target products.

3. The method according to claim 2, characterized in that After the step of selecting the top Y percent of each sub-target to generate a mass spectrum peak area list to obtain a plurality of TOPY% target compound reaction condition lists, the method further comprises: If there are repeated reaction conditions in any TOPY% target compound reaction condition list, the reaction condition with the highest mass spectrum peak value among the repeated reaction conditions is selected; If the number of sub-target generated mass spectra selected from the sub-target generated mass spectra peak area list does not reach the top Y percent, then the sub-target generated mass spectra with the largest sub-target generated mass spectra peak area are selected from the sub-target generated mass spectra peak area list to fill the gap, and the sub-target generated mass spectra correspond one-to-one to the reaction conditions.

4. The method according to claim 1, characterized in that: After the step of selecting the top X percent of the target generated mass spectrum peak area list to obtain a TOPX% target compound reaction condition list, the method further comprises: Obtaining relevant information of the preset number of well plate containers, the relevant information including the sample position corresponding to each different reaction condition, the sample name corresponding to the target compound, the molecular weight of the target reactant, and the molecular weight of the target product; Based on the sample position corresponding to each different reaction condition, determining the TOP sample position under different TOPX% reaction conditions; According to the TOP sample positions under the different TOPX% reaction conditions, the preset TopX reaction condition sequence information is determined, and the preset TopX reaction condition sequence information is used to indicate the test order of the target compound under the different TOPX% reaction conditions.

5. The method according to claim 4, characterized in that After the step of obtaining relevant information of the preset number of well plate containers, the relevant information including the sample position corresponding to each different reaction condition, the sample name corresponding to the target compound, the molecular weight of the target reactant and the molecular weight of the target product, the method further includes: Setting a database based on the molecular weight of chemical compounds, determining the molecular weight identification parameters of the target reactant and the molecular weight identification parameters of the target product; Determining the final molecular weight of the target reactant and the final molecular weight of the target product according to the molecular weight and molecular weight identification parameter of the target reactant, and the molecular weight and molecular weight identification parameter of the target product; Based on the final molecular weight of the target reactant and the final molecular weight of the target product, the ultraviolet peak corresponding to the target compound is determined.

6. The method according to claim 1, characterized in that After the step of calculating the target generated mass spectrum peak area according to the target generated mass spectrum and sorting the peak areas from large to small to obtain a target generated mass spectrum peak area list, the method further includes: According to the target generated mass spectrum peak area list, the target generated mass spectrum area under different reaction conditions is converted into a visual heat map, and the display mode in the visual heat map is determined by the target generated mass spectrum area.

7. The method according to claim 1, characterized in that After the step of determining an ultraviolet spectrum according to the TOPX data, wherein the ultraviolet spectrum includes a plurality of ultraviolet peaks, and the ultraviolet peaks correspond one-to-one to the target compounds, the method further includes: If a target compound corresponds to multiple UV peaks, then multiple UV peak areas of a target compound are determined; The diastereomeric excess percentage of the target compound is determined based on the multiple ultraviolet peak areas, and the diastereomeric excess percentage is used to quantitatively evaluate the asymmetry of the diastereoisomer mixture generated in the reaction to optimize the reaction conditions.

8. A high-throughput analysis system, characterized in that: The high-throughput analysis system comprises: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors call the computer instructions so that the high-throughput analysis system executes the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a high-throughput analysis system, the high-throughput analysis system is caused to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a high-throughput analysis system, the high-throughput analysis system is enabled to perform the method according to any one of claims 1 to 7.

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