WO2023125751A1 - 基于dia的定量化学蛋白质组学筛选靶标的方法 - Google Patents

基于dia的定量化学蛋白质组学筛选靶标的方法 Download PDF

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WO2023125751A1
WO2023125751A1 PCT/CN2022/143156 CN2022143156W WO2023125751A1 WO 2023125751 A1 WO2023125751 A1 WO 2023125751A1 CN 2022143156 W CN2022143156 W CN 2022143156W WO 2023125751 A1 WO2023125751 A1 WO 2023125751A1
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dia
abpp
electrophilic
samples
chemical proteomics
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王初
杨帆
陈南
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北京大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
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    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids

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  • the present application relates to the field of chemical proteomics, in particular to a method for screening targets by quantitative chemical proteomics based on DIA.
  • Chemical proteomics is one of the hot topics in current chemical biology research. By combining active molecular probes and quantitative mass spectrometry methods, it can be used for the analysis of proteins with specific functions or modifications in complex proteomes, as well as with The discovery of target proteins with which specific active compound molecules interact.
  • ABPP activity-based protein profiling
  • the structure of small molecule probes generally has three parts: a reactive group, which can specifically recognize certain amino acid sites, such as cysteine.
  • the linker in the middle usually a carbon chain or a polyethylene glycol chain, is used to connect the reactive group and the reporter tag behind it.
  • reporter groups There are two types of reporter groups, one is a fluorescent group, which is used for gel electrophoresis detection; the other is biotin, which is used for affinity enrichment by streptavidin resin.
  • Mass spectrometry identifies proteins bound by active molecular probes.
  • ABPP is considered to be a promising new generation of function-based proteomics technology, and it is a bridge and link between proteome and drug target research.
  • the DIA-based quantitative chemical proteomics screening method applied the DIA-based quantitative omics technology to ABPP to form DIA-ABPP, which can achieve high coverage, high reproducibility and high precision.
  • Target screening can meet the needs of large-scale high-throughput detection.
  • This application provides a method for screening targets based on DIA-based quantitative chemical proteomics, including:
  • Active molecular probes are used to covalently modify specific active amino acids in the proteome.
  • the active amino acid is cysteine, lysine, tyrosine, methionine, glutamic acid or aspartic acid.
  • the active amino acids involved in this application can also be other modification sites that can be enriched by chemical probes.
  • This embodiment still belongs to the protection scope of this application, such as: related to rheumatoid arthritis
  • guanidinylation modification see the literature for details: Ronak Tilvawala, Son Hong Nguyen, Aaron J. Maurais, Venkatesh V. Nemmara, Mitesh Nagar, Ari J. Salinger, Sunil Nagpal, Eranthie Weerapana, Paul R. Thompson. The Rheumatoid Arthritis-Associated Citrullinome[J].Cell Chemical Biology,2018,25(6)
  • the active amino acid is cysteine.
  • the iodoacetamide-alkyne (IA-alkyne) probe can be used for quantitative cysteine-reactivity analysis (cysteine-reactivity).
  • the active molecular probe corresponding to the active amino acid is: the cysteine is covalently modified by the iodoacetamide-alkyne probe, the lysine is modified by the sulfotetrafluorobenzene- covalent modification of the alkynyl probe, the covalent modification of the tyrosine with a sulfonyltriazole substituted alkynyl probe, the covalent modification of the methionine with an oxazinidine-alkynyl probe, the Acid and aspartic acid are covalently modified with 3-phenyl-2H-aziridine-alkynyl probes.
  • the active molecular probe corresponding to the active amino acid is: cysteine is covalently modified by an iodoacetamide-alkynyl probe.
  • cleavable tag in the process of covalently modifying specific active amino acids in the proteome using active molecular probes, a cleavable tag is used, specifically:
  • proteome samples use active molecular probes to protect from light, use cleavable labels to undergo click chemistry reaction, enrich until overnight enzyme digestion, wash away non-specifically adsorbed peptides and urea, and finally use cleavable label reagents corresponding to Cutting method to cut.
  • an acid-cleavage tag is used, specifically:
  • proteome samples protect from light with iodoacetamide-alkyne probes, use acid-cleaved tags to undergo click chemistry reactions, enrich until tryptic digestion overnight, wash away non-specifically adsorbed peptides and urea, and finally use acid
  • the cleavage method corresponding to the cleavage labeling reagent is used for cleavage.
  • the process of quantitatively analyzing the covalently modified sites of the probes through DIA-based quantitative omics technology includes: performing mass spectrometry analysis, collecting in DDA mode, and the obtained data results are analyzed by Pulsar software Create a spectral library, set the number of windows and the window interval, reserve 1.0Da overlap between two adjacent isolation windows, use the same chromatographic method to collect samples in DIA mode, and finally use Spectronaut to analyze the DIA data results.
  • it also includes: establishing a molecular library of electrophilic fragments, and the electrophilic fragments include: acrylamide, chloroacetamide, ethylene oxide, acrylonitrile or ethyl vinyl sulfone as reactive groups.
  • the electrophilic fragment molecular library is:
  • This application has constructed an electrophilic fragment molecular library.
  • the numbers of acrylamide as a reactive group are: F5, F14, F23, F31, F38, F56, and the numbers of chloroacetamide as a reactive group are: F2, F3, F4, F7, F8 , F9, F10, F11, F12, F13, F20, F21, F27, F28, F30, F32, F33, F52. See Figure 4 for details.
  • it also includes: after treating the proteome sample with an electrophilic fragment, adding an active molecular probe to protect it from light, and then using a cleavable labeling reagent to perform a click chemical reaction, enrichment, enzyme cleavage and acid cleavage, and prepare The electrophilic fragment was replaced with the control sample of dimethyl sulfoxide, and the sample labeled with the active molecular probe was prepared for DDA analysis to establish a spectral library. After the window setting was completed, the DIA collection and analysis of the electrophilic fragment sample was performed.
  • the sample comprises Ramos (human B lymphocytoma cells) cells, a tissue sample or a blood sample.
  • Ramos human B lymphocytoma cells
  • the sample is human B lymphoma cells.
  • it also includes: after the proteome sample is treated with the electrophilic fragment, the iodoacetamide-alkyne probe is added to protect from light, and then the acid cleavage labeling reagent is used to perform click chemistry reaction, enrichment, enzyme digestion and Acid cutting, preparation of control samples with electrophilic fragments replaced with dimethyl sulfoxide, preparation of iodoacetamide-alkyne probe-labeled samples of human B lymphocytoma cells for DDA analysis and establishment of a spectral library, after completing the window setting , DIA acquisition and analysis of electrophilic fragment samples.
  • analyzing the electrophilic fragment sample comprises: for each active amino acid, the ratio of the peptide intensity in the control sample to the peptide intensity in the electrophilic fragment treated sample is the target for binding of the electrophilic fragment to the active amino acid. To the ratio, and report the median ratio of two repetitions as the final ratio, screen and remove active amino acids with less than 3 final ratio values, and obtain the final quantitative information of active amino acids, screen for at least two fragments with a final ratio value greater than 4, at least Active amino acid sites with a final ratio value between 0.5 and 2 in a fragment are targetable active amino acid sites.
  • analyzing the electrophilic fragment sample comprises: for each cysteine, the ratio of the peptide intensity in the control sample to the peptide intensity in the electrophilic fragment-treated sample is the ratio of the electrophilic fragment-bound cysteine amino acid target ratio, and report the median ratio of two replicates as the final ratio, and filter out cysteines with less than 3 final ratio values to obtain the final cysteine quantitative information. Screening contains at least two Fragments with a final ratio value greater than 4 and at least one cysteine site with a final ratio value between 0.5 and 2 in the fragment are targetable cysteine sites.
  • the Pulsar software parameters are set to: carbamidomethylation variable modification of cysteine + 57.02146 Da, cysteine by iodoacetamide-alkynyl probe Variable modification +280.18993 Da introduced with acid cleavage tag.
  • DIA-ABPP which combines DIA and ABPP, belongs to the standard-free quantification technique, and compared with label quantification, the relative quantification error is larger in theory.
  • the prior art isoTOP-ABPP mainly relies on the first-order spectrum for quantification. During sample collection, the acquisition time of the first-order spectrum generally accounts for less than 20% of the total time, and the spectrum is highly complex and has many interferences.
  • SLC-ABPP belongs to the quantification of the secondary spectrum, and the interference of co-eluting peptides in the quantification of the secondary spectrum will lead to the compression effect of the quantification ratio.
  • Data acquisition mode - data-independent acquisition which can solve the data loss problem existing in the traditional mass spectrometry acquisition mode - data-dependent acquisition (DDA for short).
  • DIA technology can obtain sample information and accurate quantification without omission and difference under label-free conditions.
  • This application combines DIA technology with ABPP technology to form a new method called DIA-ABPP. This method avoids the use of expensive isotope labeling reagents and serious data loss problems in traditional strategies, and is a new method with high coverage, high reproducibility and high precision.
  • this application constructed an electrophilic fragment library containing chloroacetamide and acrylamide, and further used this method to deeply mine targetable cysteine Amino acid sites can be discovered on a large scale among regulated proteins, providing corresponding technical support for subsequent drug development.
  • DIA uses secondary spectrum to quantify, and the scanning time of secondary spectrum generally accounts for about 90% of the total sample collection time, so a large amount of time can provide sufficient data quantitative information.
  • the complexity of the MS signal is reduced through quadrupole isolation.
  • the present application also adds retention time corrected peptides at the chromatographic level, so that the retention time can be corrected and assigned to the correct peptide segment and corresponding fragment ions.
  • DIA-ABPP is a quantitative chemical proteomics strategy with relatively high quantitative accuracy and precision, which is suitable for large-scale high-throughput detection and analysis.
  • the comparative document discloses the chemical proteomics method of screening small molecule targets and discovering small molecule binding targets from complex biological sample systems Target Responsive Accessibility Change Profile Technology (TRAP), which is in In the biological sample (such as cell lysate) containing the target of small molecules, the active molecular probe is used to covalently modify the specific active amino acid (such as lysine) in the protein.
  • TRIP Target Responsive Accessibility Change Profile Technology
  • quantitative proteomics technology is used to Compare the changes in the abundance of each active amino acid modified at the whole proteome level in biological samples in the absence and presence of incubated small molecules, so as to characterize the changes in the accessibility of protein sites, and screen the incubated small molecules according to the change fold and significance.
  • Sites where molecular ligands cause significant changes in chemical accessibility serve as candidate targets as well as sites for potential binding and induction of allosterism by small molecule ligands to targets.
  • the sample preparation method of this application is different from that of the comparative document (CN 112485442 A), and the combined proteomics is also different (this application is the combination of ABPP and DIA, which is different from the chemical proteome based on the comparative document), and the follow-up on specific active amino acids, targets
  • This application is the combination of ABPP and DIA, which is different from the chemical proteome based on the comparative document
  • the follow-up on specific active amino acids, targets The screening process and screening criteria for proteins are different, and the technical problems solved by this application and the reference documents are also different.
  • active probe molecules covalently modify specific active amino acids in the proteome; based on DIA quantitative omics, quantitative analysis is performed on the sites after the covalent modification of the probes to obtain candidate targets.
  • the screening coverage of the present application is wider, the reproducibility is good, and the accuracy is high.
  • Figure 1 is a comparison chart based on DDA collection and DIA collection, wherein, a is the comparison of the number of peptides identified by DDA sample and DIA sample collection, b is the comparison of the reproducibility of DDA sample and DIA sample collection, Mass run ( Mass spectrometry sample needle number), Peptide IDs (peptide type);
  • Figure 2 is the experimental results of the optimization of various parameters in the DIA-ABPP technology, where a is the optimization of the cleavable label, b is the optimization of the chromatographic time, and c is the peak corresponding to the same peptide in the 140min chromatographic method and the 460min chromatographic method , d is the optimization of the chromatographic gradient, e is the optimization of the search software, f is the optimization of the collection of the spectral library, TEV tag (tobacco etch virus protease cutting tag), Diazo tag (azobenzene tag), Photo tag (photocutting label), Acid tag (acid cut label), Chromatographic time (chromatographic time), FWHM (full width at half maximum), Gradient (gradient), Fraction (component), Replicate (repeated sample);
  • a is the optimization of the cleavable label
  • b is the optimization of the chromatographic time
  • c is the peak corresponding to the same peptide in the 140min chromatographic method and the
  • Figure 3 is the identification and quantitative effect evaluation of DIA-ABPP technology, where a is the experimental process of DIA-ABPP technology, b is the comparison between DDA acquisition and DIA acquisition, c is the identification result of DIA-ABPP before and after optimization, and d is the same Evaluation of DIA-ABPP technology under ratio conditions, e is the evaluation of DIA-ABPP technology under different ratio conditions;
  • Figure 4 is a molecular library of electrophilic fragments
  • Figure 5 shows the screening based on electrophilic fragments using DIA-ABPP technology, in which, a is the experimental process, b is the identification result of DIA-ABPP and the functional analysis of targetable cysteine, and c is DIA-ABPP and isoTOP -The coverage of ABPP technology, d is the number of identified cysteines corresponding to each protein, e is the cysteine targeting analysis on protein NUP205, f is the cysteine targeting on protein NUP205 Reactivity analysis, g and h are reactivity analysis of fragments of the same binding fragment with different reactive groups, Chloroacetamide (chloroacetamide), Acrylamide (acrylamide), DMSO (dimethyl sulfoxide), Trypsin digestion (trypsin digestion ), On-beads cleavage (cutting on solid phase), Cysteine sites (cysteine site), Fragment ID (fragment type), Helix (helix), BETA strand ( ⁇ chain), Binding (combination
  • K562 and Ramos cells were cultured in RPMI 1640 medium (Gibco, Life) and DMEM medium (Gibco, Life) containing 10% fetal bovine serum (Thermo Fisher Scientific) and 1% penicillin-streptomycin (Thermo Fisher Scientific), respectively. Cultured at 37°C, 5% CO 2 .
  • Embodiment 2 the establishment of DIA-ABPP technology
  • the peak width (first-order spectrum scanning time + number of windows ⁇ second-order spectrum scanning time) ⁇ 7, the number of windows can be finally calculated, and each The interval of the window. See Table 1 for settings of mass spectrometry parameters.
  • the results of the collection of DIA mode were integrated into Spectronaut by using the software Pulsar to search the database for comparison, and the database used Homo sapiens UniProt database (release-2012_11).
  • Embodiment 3 Optimization of DIA-ABPP technology
  • ProLuCID Use three kinds of search software ProLuCID, Thermo Proteome Discover, Pulsar to search the data of DDA respectively, all three use the same database: Homo sapiens UniProt database (release-2012_11), ProLuCID setting parameter cysteine urea Cysteine fixed modification (+57.02146Da), variable modification introduced by iodoacetamide-alkyne probe on cysteine (+464.28596Da), Thermo Proteome Discover setting parameter Variable modification (+57.02146Da), variable modification on cysteine introduced by iodoacetamide-alkynyl probe (+521.30742Da), Pulsar setting parameter carbamidomethylation variable modification of cysteine (+ 57.02146Da), the variable modification (+521.30742Da) introduced by the iodoacetamide-alkynyl probe on cysteine, the false positive rate of the three softwares is finally controlled to 1%.
  • the edge of the isolation window is accompanied by signal attenuation, and it is necessary to reserve 1Da overlap between every two adjacent isolation windows to alleviate the decline in identification ability caused by the edge effect.
  • the prepared 2 TOP-ABPP samples are pre-graded into 6 components, and the spectral library is established.
  • the same 2 TOP-ABPP samples are directly analyzed by mass spectrometry without classification, and then the spectral library is established. Set up according to the results of the two spectral libraries.
  • the DIA method was used for acquisition and subsequent Spectronaut analysis.
  • the collected supernatants were combined and spin-dried, desalted, added the reagent for retention time correction (indexed retention time kit, iRT kit) and re-spun, sent to the mass spectrometer and used the chromatographic conditions of 140min gradient 1 for DDA mode acquisition, the obtained data results
  • reagent for retention time correction indexed retention time kit, iRT kit
  • iRT kit indexed retention time kit
  • Pulsar software builds the spectral library, sets the number of windows and the window interval, uses the same chromatographic method to collect samples in DIA mode, and finally uses Spectronaut to analyze the DIA data results.
  • room temperature involved in the examples of the present application is 29°C.
  • Embodiment 5 DIA-ABPP technology is used for the screening based on electrophilic fragment
  • iodoacetamide-alkyne probe-labeled samples of Ramos cells were prepared for DDA analysis to establish a spectral library. After the window setting was completed, DIA collection and analysis of 6 control samples and 48 electrophilic fragment samples were performed. For each cysteine, the ratio of the peptide intensity in the control sample to the peptide intensity in the electrophilic fragment-treated sample is the targeting ratio of the electrophilic fragment to that cysteine, and the two replicates Median ratios are reported as final ratios (R). Cysteine with less than 3 R values was screened out to obtain the final cysteine quantitative information list. Further screening contains at least two fragments with an R value greater than 4, and at least one cysteine site with an R value between 0.5 and 2 is the targetable cysteine site.
  • Example 6 Comparison of identification results obtained after collecting mass spectrometry data in DDA and DIA modes
  • the horizontal axis is the experimental number of the three samples, and the vertical axis is the intersection of the number of peptides modified by the iodoacetamide-alkyne probe identified in this sample and the number of modified peptides identified in the previous one or two samples, It is used to reflect the overall level and reproducibility of the method for the identification of modified peptides.
  • Embodiment 7 the effect of optimizing experimental parameters
  • the DIA-ABPP process is systematically optimized, and the optimization mainly starts from the optimization of sample preparation, chromatographic conditions, database search software, mass spectrometry conditions, and collection of spectral libraries.
  • Figure 2 shows the experimental results of parameter optimization in each aspect.
  • Mass spectrometry analysis was performed under the conditions of chromatographic gradient of acid-cut tag (Acid tag) and 140min high acetonitrile phase, and the spectral library was established by using the library search software Pulsar for DIA data analysis. Alignment has the best results.
  • this application reserves an overlap of 1.0 Da between each two adjacent isolation windows, so as to compensate for the decline in identification ability caused by the edge effect .
  • a Comparison of the effects of four cleavable labeling reagents commonly used in chemical proteome analysis on identification using TOP-ABPP.
  • the acid cleavage label is convenient for sample preparation, and the performance of the acid cleavage label is the best, which is convenient for sample preparation and is conducive to mass spectrometry detection;
  • b Use TOP-ABPP to compare the number of identified peptides corresponding to the three liquid chromatography times;
  • c Analysis 140min and the chromatographic peak width of the same peptide in 460min chromatographic time; although longer elution time will identify more peptides, the chromatographic peak of 460min chromatographic peak is significantly broadened, which will interfere with downstream DIA analysis; d.
  • a sample of TOP-ABPP modified with iodoacetamide-alkyne probe was prepared for quantitative effect evaluation.
  • three identical samples were used for analysis using the DIA-ABPP technique, and a good correlation was found between the samples (Fig. 3d).
  • the applicant prepared 7 identical samples, 3 of which first completed the data acquisition in DDA mode for the establishment of the spectral library, and then the other 4 samples according to the sample The content ratio is 1:2:5:10 and divided into 4 samples, and then use DIA mode for mass spectrometry data collection, comparison, extraction and subsequent quantification.
  • Figure 3 is the identification and quantitative effect evaluation of DIA-ABPP technology.
  • a DIA-ABPP scheme, including TOP-ABPP sample preparation, spectral library generation and DIA analysis (optimized conditions: use acid cleavage tag for release of labeled peptide, use high acetonitrile gradient 140min chromatographic time, use Spectronaut to process and generate based on Pulsar The DIA data of the spectral library);
  • b. The number of peptide ends identified by the TOP-ABPP experiment before and after optimization;
  • c The number of peptide ends identified by the samples collected by DDA and DIA;
  • d Correlation analysis between DIA-ABPP samples . Calculation of Pearson correlation(r) between samples;
  • e Quantitative performance analysis of DIA-ABPP; DIA analysis of samples at a specified ratio of 1:2:5:10, plotting the results of the measured ratio of DIA-ABPP.
  • the boxplot shows the median, 10th percentile, and 90th percent
  • Example 9 Screening based on electrophilic fragments using DIA-ABPP technology
  • the screening based on electrophilic fragments is performed using DIA-ABPP technology.
  • Figure 4 shows the chemical structures of the 24 fragment electrophilic fragments used in this study. These fragments contain acrylamide or chloroacetamide as reactive groups.
  • Figure 5 Electrophilic fragment-based screening using DIA-ABPP. a. Schematic diagram of the reactive groups of covalent fragments and the application process for screening by DIA-ABPP; b. The proportion of targetable cysteine and protein obtained by DIA-ABPP strategy analysis. Use the DrugBank database to further search for the corresponding protein, and classify it according to the corresponding functional category; c. compare the quantitative distribution of the cysteine quantified by the electrophilic fragment when using isoTOP-ABPP and DIA-ABPP technology analysis (listed Cysteines with quantitative results for at least three fragments); d.
  • Violin plots showing the distribution of the number of quantitative cysteines for each protein when analyzed by isoTOP-ABPP and DIA-ABPP techniques. (***p ⁇ 0.001, t test); e. Using DIA-ABPP technology to analyze the targetability of cysteine in protein NUP205, two targetable cysteine sites are represented by color depth 8.0 and 6.0 show; f. heat map showing the targetability of four cysteine sites in VDAC2 to 24 electrophilic fragments; g–h. volcano plot comparing electrophiles with the same binding fragment but different reactive groups Differences in the targetability of fragments to cysteines.
  • DIA-ABPP can obtain more quantitative information on cysteine (Fig. 5d), so that the selective targeting position of the electrophilic fragment can be better determined.
  • NUP205 acts as an endocyclic nucleoporin that functions in nuclear pore complex (NPC) assembly and/or maintenance.
  • DIA-ABPP can quantify 16 cysteines in the protein, two of which are considered to be cysteine sites that can be targeted by different kinds of electrophilic probes, while for isoTOP-ABPP, only Information was obtained for an inactive cysteine (C1662) (Fig. 5e).

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Abstract

基于数据非依赖型采集（DIA）的定量化学蛋白质组学筛选靶标的方法，包括采用活性分子探针，共价修饰蛋白质组中特定的活性氨基酸；通过基于DIA的定量组学方法，对探针共价修饰后的位点进行定量分析，得到候选靶标。基于DIA的定量化学蛋白质组学筛选靶标的方法是将基于DIA的定量组学技术应用到基于活性的蛋白质分析（ABPP）中，形成DIA-ABPP，可实现高覆盖度、高重现性以及高精确度的靶标筛选，为后续药物开发提供相应的技术支持。

Description

基于DIA的定量化学蛋白质组学筛选靶标的方法
本发明要求2021年12月31日向中国国家知识产权局提交的，专利申请号为202111665395.3，发明名称为“基于DIA的定量化学蛋白质组学筛选靶标的方法”的在先申请的优先权。上述在先申请的全文通过引用的方式结合于本发明中。
技术领域
本申请涉及化学蛋白质组领域，尤其涉及基于DIA的定量化学蛋白质组学筛选靶标的方法。
背景技术
化学蛋白质组学是当前化学生物学研究的热点方向之一，通过将活性分子探针和定量质谱组学方法相结合，以用于复杂蛋白质组中具有特定功能或修饰的蛋白质的分析，以及与特定活性化合物分子存在相互作用的靶蛋白的发现。
目前最常用的化学蛋白质组学策略是基于活性的蛋白质分析(Activity-based protein profiling，简称ABPP)，ABPP技术的原理是通过设计一种可以共价地结合活性蛋白质中某些氨基酸的活性分子探针，从而可以在蛋白质组中获得具有某种特定活性的蛋白其对应的活性状态。小分子探针的结构一般具有三部分：反应基团(reactive group)，可以特定地识别某些氨基酸位点，例如半胱氨酸。中间连接部分(linker)，通常为碳链或聚乙二醇链，用于连接反应基团以及后面的报告基团(reporter tags)。报告基团有两种类型，一种是荧光基团，用于凝胶电泳检测；另一类为生物素(biotin)，通过链霉亲和素(streptavidin)树脂进行亲和富集，用于质谱对活性分子探针结合的蛋白进行鉴定。目前，ABPP被认为是很有前景的新一代基于功能的蛋白质组学技术，是联系蛋白质组和药物靶点研究的桥梁和纽带。
而随着研究领域的不断发展和定量组学方法的不断开发，基于定量的化学蛋白质组学已经越来越多的应用于未知蛋白功能的解析，活性小分子靶标蛋白的鉴定，翻译后修饰位点的发现以及小分子抑制剂的筛选等众多方向。为了进一步实现化学蛋白质组学的精准定量分析，科学家们开发了基于同位素标记的定量化学蛋白质组学技术，包括基于一级谱定量的isoTOP(基于同位素的串联正交蛋白水解)-ABPP技术和rdTOP(基于还原二甲基化的串联正交蛋白水解)-ABPP技术以及基于二级谱定量的MTRP(多通道活性巯基筛选)技术和SLC(流线型的半胱氨酸)-ABPP技术。
2016年美国Scripps研究所的Cravatt课题组将定量化学蛋白质组学技术(isoTOP-ABPP)与基于亲电小分子片段的药物发现相结合，通过制备数百个样品，数月的质谱采集，数据的整合和分析，他们发现七百多个此前被认为是无法通过小分子进行功能调控的蛋白中含有活性半胱氨酸位点能够被特定的亲电片段共价修饰，使这些蛋白重新成为可被调控的靶标。然而该技术只能进行二重定量分析，策略较为繁杂冗长，重现性差，鉴定数目少，灵敏度低；2020年哈佛大学的Gygi课题组开发了基于等压标签的多重定量化学蛋白质组学技术(SLC-ABPP)用于共价片段筛选，虽然能 够实现多个样品的平行定量分析，但是标签试剂非常昂贵，算法复杂，可操作性差，无法满足化学生物学家们大规模高通量的检测需求。因此迫切需要新的优化的化学蛋白质组学技术，以满足大规模高通量检测的需求。
发明内容
本申请提供的基于DIA的定量化学蛋白质组学筛选靶标的方法，将基于DIA的定量组学技术应用到ABPP当中，形成DIA-ABPP，可实现高覆盖度、高重现性以及高精确度的靶标筛选，可满足大规模高通量检测需求。
本申请提供基于DIA的定量化学蛋白质组学筛选靶标的方法，包括：
采用活性分子探针，共价修饰蛋白质组中的特定的活性氨基酸。
通过基于DIA的定量组学技术，对探针共价修饰后的位点进行定量分析，得到候选靶标。
在一个实施方案中，所述活性氨基酸为半胱氨酸、赖氨酸、酪氨酸、甲硫氨酸、谷氨酸或天冬氨酸。
另外需要说明的是，本申请涉及的活性氨基酸，也可为其它有化学探针可以富集的修饰位点，该实施方式仍属于本申请的保护范围，比如：与类风湿性关节炎相关的胍基化修饰，具体参见文献：Ronak Tilvawala,Son Hong Nguyen,Aaron J.Maurais,Venkatesh V.Nemmara,Mitesh Nagar,Ari J.Salinger,Sunil Nagpal,Eranthie Weerapana,Paul R.Thompson.The Rheumatoid Arthritis-Associated Citrullinome[J].Cell Chemical Biology,2018,25(6)
在一个实施方案中，所述活性氨基酸为半胱氨酸。
碘乙酰胺-炔基(IA-alkyne)探针作为一种广谱的反应性探针，其可用于定量的半胱氨酸反应分析(cysteine-reactivity)。
在一个实施方案中，与所述活性氨基酸对应的活性分子探针为：所述半胱氨酸由碘乙酰胺-炔基探针共价修饰、所述赖氨酸由磺基四氟苯-炔基探针共价修饰、所述酪氨酸由磺酰三唑取代的炔基探针共价修饰、所述甲硫氨酸由恶嗪啶-炔基探针共价修饰、所述谷氨酸和天冬氨酸由3-苯-2H-氮丙啶-炔基探针共价修饰。
在一个实施方案中，与所述活性氨基酸对应的活性分子探针为：半胱氨酸由碘乙酰胺-炔基探针共价修饰。
在一个实施方案中，在所述采用活性分子探针，共价修饰蛋白质组中的特定的活性氨基酸的过程中，采用可切割标签，具体为：
获取蛋白质组样品，用活性分子探针避光处理，使用可切割标签发生点击化学反应，富集至酶切过夜后，洗去非特异性吸附的肽段和尿素，最后用可切割标签试剂对应的切割方法进行切割。
在一个实施方案中，在所述采用活性分子探针，共价修饰蛋白质组中的特定的活性氨基酸的过程中，采用酸切标签，具体为：
获取蛋白质组样品，用碘乙酰胺-炔基探针避光处理，使用酸切标签发生点击化学反应，富集至胰酶切过夜后，洗去非特异性吸附的肽段和尿素，最后用酸切标签试剂对应的切割方法进行切割。
在一个实施方案中，所述通过基于DIA的定量组学技术，对探针共价修饰后的位 点进行定量分析的过程包括：进行质谱分析，用DDA模式采集，得到的数据结果由Pulsar软件进行谱图库建立，设置窗口数目和窗口区间，每邻近的两个隔离窗口中间预留1.0Da的重叠，利用相同色谱方法进行样品在DIA模式下的采集，最后利用Spectronaut对DIA数据结果进行分析。
在一个实施方案中，还包括：建立亲电片段分子库，所述亲电片段包括：丙烯酰胺、氯乙酰胺、环氧乙烷、丙烯腈或乙基乙烯基砜作为反应基团。
在一个实施方案中，所述亲电片段分子库为：
Figure PCTCN2022143156-appb-000001
本申请构建了亲电片段分子库，丙烯酰胺作为反应基团编号为：F5、F14、F23、F31、F38、F56，氯乙酰胺作为反应基团编号为：F2、F3、F4、F7、F8、F9、F10、F11、F12、F13、F20、F21、F27、F28、F30、F32、F33、F52。具体参见图4。
在一个实施方案中，还包括：将蛋白质组样本用亲电片段处理后，加入活性分子探针避光处理，随后利用可切割标签试剂进行点击化学反应，富集，酶切以及酸切，制备将亲电片段换为二甲基亚砜的对照组样品，制备活性分子探针标记的样品用于DDA分析建立谱图库，完成窗口设置后，进行亲电片段样品的DIA采集和分析。
在一个实施方案中，所述样品包括Ramos(人B淋巴细胞瘤细胞)细胞、组织样品或血液样品。
在一个实施方案中，所述样品为人B淋巴细胞瘤细胞。
在一个实施方案中，还包括：将蛋白质组样本用亲电片段处理后，加入碘乙酰胺-炔基探针避光处理，随后利用酸切标签试剂进行点击化学反应，富集，酶切以及酸切，制备将亲电片段换为二甲基亚砜的对照组样品，制备人B淋巴细胞瘤细胞的碘乙酰胺-炔基探针标记样品用于DDA分析建立谱图库，完成窗口设置后，亲电片段样品的DIA采集和分析。
在一个实施方案中，对亲电片段样品分析包括：对于每个活性氨基酸，对照样品的肽段强度与亲电片段处理样品中的肽段强度之比为所述亲电片段结合活性氨基酸的靶向比率，并将两个重复的中值比率报告作为最终比率，筛选剔除不足3个最终比率值的活性氨基酸，得到最终的活性氨基酸定量信息，筛选至少含有两个片段最终比率值大于4，至少一个片段的最终比率值在0.5和2之间的活性氨基酸位点，则为可靶向的活性氨基酸位点。
在一个实施方案中，对亲电片段样品分析包括：对于每个半胱氨酸，对照样品的肽段强度与亲电片段处理样品中的肽段强度之比为所述亲电片段结合半胱氨酸的靶向比率，并将两个重复的中值比率报告作为最终比率，筛选剔除不足3个最终比率值的半胱氨酸，得到最终的半胱氨酸定量信息，筛选至少含有两个片段最终比率值大于4，至少一个片段的最终比率值在0.5和2之间的半胱氨酸位点，则为可靶向的半胱氨酸位点。
在一个实施方案中，在一个实施方案中，所述Pulsar软件参数设置为：半胱氨酸的脲甲基化可变修饰+57.02146Da，半胱氨酸上由碘乙酰胺-炔基探针与酸切标签引入的可变修饰+280.18993Da。
在本申请中，将DIA与ABPP结合的DIA-ABPP属于无标定量技术，与标记定量相比，理论上相对定量误差较大。而现有技术isoTOP-ABPP主要是靠一级谱图定量，在样品采集的时候，一级谱的采集时间一般占总时长的百分之二十以内，且图谱复杂程度高，干扰多。SLC-ABPP属于二级谱定量，二级谱定量存在共流出肽段干扰会导致定量比例的压缩效应。而Gygi课题组开发的基于等压标签的多重定量化学蛋白质组学技术(SLC-ABPP)则不存在此现象，因为其是将高强度的碎片离子隔离进行三级质谱分析，但是需要最新一代的质谱和复杂的参数设置，所以其算法复杂，可操作性差。
数据采集模式——数据非依赖型采集，其可解决传统质谱采集模式——数据依赖型采集(data-dependent acquisition，简称DDA)存在的数据丢失问题。DIA技术能够在无标记的条件下，无遗漏、无差异地获得样本信以及准确定量。本申请将DIA技术与ABPP技术相结合，形成名为DIA-ABPP的新方法。该方法避免了传统策略中昂贵的同位素标签试剂的使用和数据丢失严重的问题，是一种具有高覆盖度、高重现性以及高精确度的新方法。由于不同种类的反应基团对半胱氨酸具有不同的偏好性，本申请构建了一个含有氯乙酰胺和丙烯酰胺的亲电片段库，进一步将该方法用于深度挖掘可靶向的半胱氨酸位点，大规模地发现可调控蛋白之中，为后续药物开发提供相应的技术支持。
而DIA是利用二级谱定量，二级谱的扫描时间一般占总的样品采集时间的百分之九十左右，所以大量的时间可以提供充足的数据定量信息。另外，通过四级杆隔离作用，质谱信号的复杂程度降低。本申请还在色谱层面加入了保留时间校正的多肽，从而可以将保留时间进行校正，从而归属到正确的肽段以及对应的碎片离子进行。综合以上相关因素，从定量而言，DIA-ABPP是一种具有相对高定量准确性和精确度的定量化学蛋白质组学策略，适用于大规模高通量检测分析。
另外，对比文件(CN 112485442 A)公开了筛选小分子靶标，从复杂的生物样品体系中发现小分子结合靶标的化学蛋白质组学方法靶点响应性可及性变化谱技术 (TRAP)，其在包含目标小分子作用靶标的生物样本(如细胞裂解液)中，利用活性分子探针共价修饰蛋白中特定活性氨基酸(如赖氨酸)，在终止标记过程后，利用定量蛋白质组学技术，比较生物样本在缺乏及存在孵育的小分子时其中全蛋白组水平各活性氨基酸被修饰的丰度的变化，以此表征蛋白位点的可及性变化，根据变化的倍数及显著性筛选孵育小分子配体导致化学可及性显著变化的位点作为候选靶标及小分子配体与靶标的潜在结合和诱导变构的位点。
本申请与对比文件(CN 112485442 A)的样本制备方法不同，结合的蛋白质组学也不同(本申请为ABPP与DIA结合，与对比文件基于的化学蛋白质组不同)，后续对特定活性氨基酸，靶标蛋白的筛选过程以及筛选标准不同，本申请与对比文件所解决的技术问题也不相同。本申请通过活性探针分子共价修饰蛋白质组中的特定的活性氨基酸；再基于DIA的定量组学，对探针共价修饰后的位点，进行定量分析，得到候选靶标。并且本申请的筛选覆盖度更广，重现性好，准确度高。
附图说明
为了更清楚地说明本申请的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，对于本领域普通技术人员而言，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为基于DDA采集和基于DIA采集的对比图，其中，a为DDA样品和DIA样品采集鉴定到的肽段数的对比，b为DDA样品和DIA样品采集的重现性的对比，Mass run(质谱采集样品针数)，Peptide IDs(肽段种类)；
图2为DIA-ABPP技术中各项参数优化的实验结果图，其中，a为可切割标签的优化，b为色谱时间的优化，c为140min色谱方法和460min色谱方法中同一肽段对应的峰，d为色谱梯度的优化，e为搜库软件的优化，f为谱图库采集的优化，TEV tag(烟草蚀纹病毒蛋白酶切割标签)，Diazo tag(偶氮苯标签)，Photo tag(光切标签)，Acid tag(酸切标签)，Chromatographic time(色谱时间)，FWHM(半峰全宽)，Gradient(梯度)，Fraction(组分)，Replicate(重复样品)；
图3为DIA-ABPP技术的鉴定和定量效果评估，其中，a为DIA-ABPP技术的实验流程，b为DDA采集与DIA采集的对比，c为优化前后DIA-ABPP的鉴定结果，d为相同比例条件下DIA-ABPP技术的评估，e为不同比例条件下DIA-ABPP技术的评估；
图4为亲电片段的分子库；
图5为利用DIA-ABPP技术进行基于亲电片段的筛选，其中，a为其实验流程，b为DIA-ABPP鉴定结果和可靶向半胱氨酸的功能分析，c为DIA-ABPP和isoTOP-ABPP技术的覆盖度，d为每个蛋白所对应的鉴定的半胱氨酸数目，e为蛋白NUP205上的半胱氨酸靶向性分析，f为蛋白NUP205上的半胱氨酸靶向性分析，g和h为相同结合片段不同反应基团的片段的反应性分析，Chloroacetamide(氯乙酰胺)，Acrylamide(丙烯酰胺)，DMSO(二甲基亚砜)，Trypsin digestion(胰蛋白酶酶切)，On-beads cleavage(在固相上切割)，Cysteine sites(半胱氨酸位点)，Fragment ID(片段种类)，Helix(螺旋)，BETA strand(β链)，Binding(结合)，Catalytic activity(催化活性)，Molecular adaptor activity(分子适配活性)，Molecular function regulator(分子功能调控)，Structural molecule activity(结构分子活性)， Translation regulator activity(翻译调控活性)，Transporter activity(转运活性)，Others(其他)，Sample preparation(样品制备)，CuAAC(基于铜催化的点击化学反应)，Enrichment(富集)，Spectral library generation(谱图库建立)，precursor(母离子)，Retention time(保留时间)，Fragment(碎片离子)，Relative Intensity(相对强度)，DIA analysis(数据非依赖型采集数据分析)，Observed ratio(观测比例)，Expected ratio(理论比例)。
具体实施方式
下面将详细地对实施例进行说明，其示例表示在附图中。下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下实施例中描述的实施方式并不代表与本申请相一致的所有实施方式。仅是与权利要求书中所详述的、本申请的一些方面相一致的系统和方法的示例。
实施例1：细胞培养
K562和Ramos细胞分别用含有10％胎牛血清(Thermo Fisher Scientific)和1％青霉素-链霉素(Thermo Fisher Scientific)的RPMI 1640培养基(Gibco,Life)和DMEM培养基(Gibco,Life)在37℃，5％CO 2的条件下培养。
实施例2：DIA-ABPP技术的建立
申请人利用经典的碘乙酰胺-炔基探针标记的TOP-ABPP样品用于DIA模式的方法建立以及后续条件的优化，具体样品制备方法参见文献:
Weerapana Eranthie,Speers Anna E,Cravatt Benjamin F.Tandem orthogonal proteolysis-activity-based protein profiling(TOP-ABPP)--a general method for mapping sites of probe modification in proteomes.[J].Nature protocols,2007,2(6)，此技术为本领域技术人员所公知。
获取2mg/mL K562细胞蛋白质组样品，每份1mL，用终浓度为100μM的碘乙酰胺-炔基室温避光处理1h，后续利用Tev tag进一步利用点击化学反应偶联，沉淀，富集至胰酶切过夜后，每个样品用600μL PBS洗3次，600μL去离子水洗3次以除去非特异性吸附的肽段和尿素，在链霉亲和素磁珠中加入500μL TEV buffer洗1次后，加入150μL TEV buffer，5μL TEV酶，29℃下酶切16h。每个样品分别用2x 50μL水洗，收集上清合并后旋干，除盐，加入用于保留时间校正的试剂(indexed retention time kit，iRT kit)重旋，三个样品送入质谱进行DDA模式采集，后续分析，ProLuCID搜库，搜库参数设置为：半胱氨酸的脲甲基化固定修饰(+57.02146Da)，半胱氨酸上由碘乙酰胺-炔基探针与TEV tag引入的可变修饰(+464.28596Da)，得到每个对应修饰肽段的母离子对应的质荷比信息。进一步对原始数据进行分析得到母离子的平均峰宽，根据峰宽＝(一级谱扫描时间+窗口数×二级谱扫描时间)×7，即可最终算出窗口数目，根据鉴定结果获得每个窗口的区间。参见表1，为质谱参数的设置。
表-1-质谱参数设置
Figure PCTCN2022143156-appb-000002
Figure PCTCN2022143156-appb-000003
DIA模式的采集的结果利用软件Pulsar搜库的结果整合到Spectronaut中进行比对，数据库使用Homo sapiens UniProt database(release-2012_11)。搜库参数设置为：半胱氨酸的脲甲基化固定修饰(+57.02146Da)，半胱氨酸上由碘乙酰胺-炔基探针与TEV tag引入的可变修饰(+521.30742Da)，蛋白伪发现率(protein FDR)＝1，肽谱匹配(peptide spectrum matching，PSM)伪发现率＝0.01以及肽段伪发现率(peptide FDR)＝0.01，iRT校正R 2大于0.8，搜库，完成谱图库的构建后，进一步使用三针DIA采集的数据进行碎片离子的匹配，抽提以及定量，p值小于0.01，最终定量信息按照母离子的水平进行输出。
实施例3：DIA-ABPP技术的优化
(1)可切割标签试剂：
按照上述实验流程，获取2mg/mL K562蛋白质组样品，每份1mL，分别用终浓度为100μM的碘乙酰胺-炔基探针室温避光处理1h，后续分别与TEV tag、Diazo tag、Photo tag、Acid tag发生点击化学反应，富集至胰酶切过夜后，利用PBS和去离子水洗去非特异性吸附的肽段和尿素，最后分别用不同的tag试剂对应的切割方法进行切割。
(2)优化色谱条件：
参见表2，为优化后的色谱时间；参见表3，为优化后的色谱梯度。
表-2-优化后的色谱时间
Figure PCTCN2022143156-appb-000004
表-3-优化后的色谱梯度
Figure PCTCN2022143156-appb-000005
(3)选择建库使用的搜库软件：
分别利用三种搜库软件ProLuCID，Thermo Proteome Discover，Pulsar对DDA的数据进行搜索，三者都是用相同的数据库：Homo sapiens UniProt database(release-2012_11)，ProLuCID设置参数半胱氨酸的脲甲基化固定修饰(+57.02146Da)，半胱氨酸上由碘乙酰胺-炔基探针引入的可变修饰(+464.28596Da)，Thermo Proteome Discover设置参数半胱氨酸的脲甲基化可变修饰(+57.02146Da)，半胱氨酸上由碘乙酰胺-炔基探针引入的可变修饰(+521.30742Da)，Pulsar设置参数半胱氨酸的脲甲基化可变修饰(+57.02146Da)，半胱氨酸上由碘乙酰胺-炔基探针引入的可变修饰(+521.30742Da)，三种软件最终都控制假阳性率为百分之一。
(4)优化质谱条件：
隔离窗口：
隔离窗口的边缘伴随有信号衰减的情况出现，需要在每邻近的两个隔离窗口中间预留1Da的重叠来缓解边缘效应导致的鉴定能力下降。
(5)谱图库的构建：
制备好的2个TOP-ABPP样品预分级为6个组分，进行谱图库建立，相同的2个 TOP-ABPP样品无需分级直接进行质谱分析后建立谱图库，根据两个谱图库的结果分别设置DIA方法进行采集和后续Spectronaut分析。
(6)优化好的实验流程为：
获取2mg/mL蛋白质组样品，每份1mL，用终浓度为100μM的碘乙酰胺-炔基探针室温避光处理1h，后续利用Acid tag进一步利用点击化学反应偶联，沉淀，富集至胰酶切过夜后，洗去非特异性吸附的肽段和尿素，200μL的2％甲酸的水溶液，29℃下反应1h，重复一次后，利用1％甲酸，50％乙腈的水溶液洗两遍。收集上清合并后旋干，除盐，加入用于保留时间校正的试剂(indexed retention time kit，iRT kit)重旋，送入质谱利用140min梯度1的色谱条件进行DDA模式采集，得到的数据结果理由Pulsar软件进行谱图库建立，设置窗口数目和窗口区间，利用相同色谱方法进行样品在DIA模式下的采集，最后利用Spectronaut对DIA数据结果进行分析。
需要说明的是，本申请实施例涉及的室温，为29℃。
实施例4：DIA-ABPP技术的定量效果评估
按照上述流程完成样品制备，得到TOP-ABPP样品，加入含有iRT kit的0.1％甲酸水溶液溶解3份，用于DDA模式建库，设置inclusion list以及隔离窗口等质谱方法，后续将样品含量按比例分为1：2：5：10，4个样品(其中iRT含量相同)，利用DIA模式进行后续的采集。后续用Spectronaut进行匹配，抽提和定量。
实施例5：DIA-ABPP技术用于基于亲电片段的筛选
获取2mg/mL Ramos细胞蛋白质组样品，每份1mL，利用终浓度为500μM的亲电片段处理1h后，加入终浓度为100μM的碘乙酰胺-炔基探针室温避光处理1h，随后利用Acid tag进行点击化学反应，富集，酶切以及酸切，同时制备将亲电片段换为DMSO(二甲基亚砜)的对照组样品。每个亲电片段制备2个样品，对照样品制备6个。另制备6个Ramos细胞的碘乙酰胺-炔基探针标记样品用于DDA分析建立谱图库，完成窗口设置后，进行6个对照组样品以及48个亲电片段样品的DIA采集和分析。对于每个半胱氨酸，对照样品的肽段强度与亲电片段处理样品中的肽段强度之比即为该亲电片段结合该半胱氨酸的靶向比率，并将两个重复的中值比率报告为最终比率(R)。筛选剔除不足3个R值的半胱氨酸得到最终的半胱氨酸定量信息列表。进一步筛选至少含有两个片段R值大于4，至少一个片段的R值在0.5和2之间的半胱氨酸位点即为可靶向的半胱氨酸位点。
下面将通过对比实验来说明本申请提供的基于DIA的定量化学蛋白质组学筛选靶标的方法有益效果。
实施例6：DDA和DIA模式下采集质谱数据后得到的鉴定结果对比
参见图1，为基于DDA采集和基于DIA采集的对比图。
将6份K562细胞的蛋白质组样品利用100μM的碘乙酰胺-炔基探针标记，通过TOP-ABPP实验流程，制得6份肽段上的半胱氨酸带有碘乙酰胺-炔基探针修饰的位点样品，分别用DDA模式和基于DDA建立谱图库的DIA模式采集。图1中总结了三份样品分别在DDA和DIA模式下采集质谱数据后得到的鉴定结果，a为三个DIA样品和三个DDA样品中分别鉴定的肽的数量；b为三个DIA样品和三个DDA样品中重复鉴定的肽段数量。横轴为三份样品的实验编号，纵轴为在该样品中鉴定到的被碘乙酰胺-炔基 探针修饰肽段的数目与前面一次或两次样品中鉴定到修饰肽段数目的交集，用于反映该方法对修饰肽段鉴定的整体水平高低和重现性好坏。
仅对三份样品进行分析时，DDA方法在三份样品中都鉴定到的肽段种类已经只有单份样品的一半左右。DIA的结果则与DDA的结果形成了鲜明的对比，由于在DIA模式中所有母离子都被分配到不同荷质比窗口进行采集和碎裂，所以修饰肽段的信息都尽可能地被保留下来，在三份样品都鉴定到的肽段数目还能维持在单份样品的90％以上。上述结果表明，通过DIA采集模式可以大大提升化学蛋白质组数据中修饰肽段鉴定的重现性。
实施例7：优化实验参数的效果
参见图2，为DIA-ABPP技术中各项参数优化的实验结果图。
对DIA-ABPP流程进行系统地优化，优化主要从以样品的制备、色谱条件、搜库软件、质谱条件以及谱图库的采集等方面的优化等展开。
图2为每一方面参数优化的实验结果，使用酸切标签(Acid tag)、140min高乙腈相的色谱梯度条件下进行质谱分析，利用搜库软件Pulsar进行谱图库的建立后用于DIA数据的比对具有最好的效果。此外，由于四级杆在隔离窗口的边缘会伴随有信号衰减的情况出现，所以本申请在每邻近的两个隔离窗口中间预留1.0Da的重叠，从而对边缘效应导致的鉴定能力下降进行弥补。
图2中，a.利用TOP-ABPP比较常用于化学蛋白质组分析的四种可切割标签试剂对鉴定的影响。酸裂解标签便于样品制备，酸裂解标签的性能最好，便于样品制备，有利于质谱检测；b.利用TOP-ABPP比较三种液相色谱时间所对应的鉴定的肽的数量；c.分析140min和460min色谱时间中同一肽段的色谱峰宽；虽然更长的洗脱时间将识别更多的肽，但460min色谱的色谱峰显著加宽，这将干扰下游DIA分析；d.比较三种色谱梯度下TOP-ABPP鉴定的肽数。有机相比例越高，梯度效果越好；e.比较三个搜索引擎(包括ProLuCID、Proteome Discoverer和Pulsar)所识别的肽段数量。Pulsar可以生成最大的谱图库。f.比较使用预先采集建立的谱图库(样品是否预先预分级建立谱图库)和directDIA(不预先采集谱图库)鉴定的肽数。虽然未预先分级建立的谱图库比分级建立的谱图库稍微小一些，但具有最好的DIA鉴定效果，可能是由于低强度的肽丢失(值代表三次重复实验的平均值±SD。*p<0.05，**p<0.01，t检验)。
实施例8：DIA-ABPP技术的鉴定和定量效果评估
参见图3，为DIA-ABPP技术的鉴定和定量效果评估。
在完成以上所有条件的优化之后，本申请完成了三针DDA样品的采集，建库后再指导后续三针DIA样品的采集和质谱数据分析(图3a)。通过图3b对比可以看出，优化后的DIA-ABPP技术可以比DDA-ABPP多鉴定50％的修饰位点。DDA采集的样品数据丢失非常严重，而DIA采集时数据保留非常完整，拥有更好的覆盖度以及重现性。
本申请制备了碘乙酰胺-炔基探针修饰的TOP-ABPP样品用于定量效果评估。首先利用3个相同的样品进行利用DIA-ABPP技术的分析，发现样品间具有很好的相关性(图3d)。为了进一步比较不同含量的样品间定量的准确性和精确性，申请人制备了7份相同的样品，其中3份首先完成DDA模式的数据采集用于建立谱图库，然后将另外4份样品按照样品含量比例为1：2：5：10分成4个样品，再利用DIA模式进行质谱数 据采集、比对、抽提以及后续定量。图3e为定量实验结果，其中横纵坐标分别代表理论比例和实验测量比例。本申请提取理论比值和测量比例的中值进行过零点的线性拟合，箱状图结果显示肽段定量的比例比较集中、精确度高，线性拟合的结果为y＝1.0436x，R 2为0.9904，说明新方法准确度高。
图3是DIA-ABPP技术的鉴定和定量效果评估。其中：a.DIA-ABPP方案，包括TOP-ABPP样品制备、谱图库库生成和DIA分析(优化条件：使用酸切割标签进行标记肽释放，使用高乙腈梯度140min色谱时间，使用Spectronaut处理基于Pulsar生成的谱图库的DIA数据)；b.优化前后TOP-ABPP实验鉴定到的肽端数目；c.DDA和DIA采集的样品鉴定到的肽端数量；d.DIA-ABPP样本之间的相关性分析。计算样品之间的Pearson correlation(r)；e.DIA-ABPP的定量性能分析；以1:2:5:10的规定比率对样品进行DIA分析，绘制DIA-ABPP测得比率的结果。方框图展示了中位数、第10百分位和第90百分位。
实施例9：利用DIA-ABPP技术进行基于亲电片段的筛选
参见图4，为亲电片段的分子库。
参见图5，为利用DIA-ABPP技术进行基于亲电片段的筛选。
鉴于DIA-ABPP技术具有高重现性和高覆盖度，申请人建立了24个亲电片段的分子库(图4)，进一步利用Ramos细胞的蛋白质组，对亲电片段结合半胱氨酸的水平进行定量分析(图5a)。在总共54个DIA样本中，申请人鉴定到了3734个蛋白质中的8110个半胱氨酸位点，所用的仪器时间是之前方法(isoTOP-ABPP)的四分之一。值得注意的是，DIA-ABPP鉴定结果中，有67.35％的半胱氨酸具有至少21个片段的定量数据，而isoTOP-ABPP技术的覆盖度仅为5.8％(图5c)。
图4为本研究中使用的24个片段亲电片段的化学结构。这些片段包含有丙烯酰胺或氯乙酰胺作为反应基团。图5利用DIA-ABPP进行基于亲电片段的筛选。a.共价片段的反应基团和利用DIA-ABPP进行筛选的申请流程示意图；b.DIA-ABPP策略分析获得的可靶向半胱氨酸和蛋白质的比例。利用DrugBank数据库进一步搜索对应的蛋白质，并按相应的功能类别进行分类；c.比较利用isoTOP-ABPP与DIA-ABPP技术分析时亲电片段所定量到的半胱氨酸的数量分布(列出了至少三个片段有定量结果的半胱氨酸)；d.小提琴图显示通过isoTOP-ABPP与DIA-ABPP技术分析时，每种蛋白质定量半胱氨酸数目的分布。(***p<0.001，t检验)；e.利用DIA-ABPP技术分析蛋白NUP205中的半胱氨酸的可靶向性，两个可靶向的半胱氨酸位点以颜色深度8.0以及6.0显示；f.热图显示VDAC2中的四个半胱氨酸位点对24个亲电片段的可靶向性；g-h.火山图比较了具有相同结合片段但不同反应基团的亲电片段对于半胱氨酸可靶向性的差异。
需要说明的是申请人沿用之前文章(Backus Keriann M,Correia Bruno E,Lum Ke nneth M.Proteome-wide covalent ligand discovery in native biological syst ems.[J].Nature,2016,534(7608))中定义“可连接半胱氨酸”的相同标准(例如，通过两个或多个配体片段标记，半胱氨酸竞争探针的水平高于75％)，从DIA-ABPP的数据集中鉴定到了563个可靶向的半胱氨酸，与之前技术具有相似的可靶向水平。这些可靶向的半胱氨酸归属于458个蛋白质，其中85％的蛋白质未出现在药物库数据库中，参与到结合，催化，调控以及转运等多种分子功能中(图5b)。
另外，值得注意的是，对于单一蛋白质而言，DIA-ABPP技术可以获得更多的半胱氨酸定量信息(图5d)，从而可以更好的确定亲电片段所选择性靶向的位置，最显著的例子是NUP205，它作为一种内环核孔蛋白，在核孔复合体(NPC)组装和/或维护中发挥作用。DIA-ABPP可以对该蛋白质中的16种半胱氨酸进行定量，其中两种被认为是可被不同种的亲电探针靶向的半胱氨酸位点，而对于isoTOP-ABPP，只得到了一种无活性的半胱氨酸(C1662)的信息(图5e)。与此同时，对不同亲电反应基团的反应性进行分析，选取分子库中具有相同结合片段但是不同反应基团的分子进行了头对头比较。申请人发现它们对半胱氨酸表现出不同的反应性，说明不同的反应基团对半胱氨酸存在偏好(图5g，图5h)。进一步以蛋白质为中心进行分析时发现，在DIA-ABPP技术分析时鉴定到了蛋白VDAC2的四个半胱氨酸，它们对含有不同反应基团的分子具有不同的连接能力，其中对于脂源性亲电小分子HNE超敏感的半胱氨酸之一C210只能被含有丙烯酰胺的片段靶向，这种翻译基团与HNE中的反应性基团类似(图5f)。
本申请提供的实施例之间的相似部分相互参见即可，以上提供的具体实施方式只是本申请总的构思下的几个示例，并不构成本申请保护范围的限定。对于本领域的技术人员而言，在不付出创造性劳动的前提下依据本申请方案所扩展出的任何其他实施方式都属于本申请的保护范围。

Claims (11)

  1. 基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，包括：
    采用活性分子探针，共价修饰蛋白质组中的特定的活性氨基酸；
    通过基于DIA的定量组学技术，对探针共价修饰后的位点进行定量分析，得到候选靶标。
  2. 根据权利要求1所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，所述活性氨基酸为半胱氨酸、赖氨酸、酪氨酸、甲硫氨酸、谷氨酸或天冬氨酸。
  3. 根据权利要求2所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，与所述活性氨基酸对应的活性分子探针为：所述半胱氨酸由碘乙酰胺-炔基探针共价修饰、所述赖氨酸由磺基四氟苯-炔基探针共价修饰、所述酪氨酸由磺酰三唑取代的炔基探针共价修饰、所述甲硫氨酸由恶嗪啶-炔基探针共价修饰、所述谷氨酸和天冬氨酸由3-苯-2H-氮丙啶-炔基探针共价修饰。
  4. 根据权利要求3所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，与所述活性氨基酸对应的活性分子探针为：半胱氨酸由碘乙酰胺-炔基探针共价修饰。
  5. 根据权利要求1所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，在所述采用活性分子探针，共价修饰蛋白质组中的特定的活性氨基酸的过程中，采用可切割标签，具体为：
    获取蛋白质组样品，用活性分子探针避光处理，使用可切割标签发生点击化学反应，富集至酶切过夜后，洗去非特异性吸附的肽段和尿素，最后用可切割标签试剂对应的切割方法进行切割。
  6. 根据权利要求1所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，所述通过基于DIA的定量组学技术，对探针共价修饰后的位点进行定量分析的过程包括：进行质谱分析，用DDA模式采集，得到的数据结果由Pulsar软件进行谱图库建立，设置窗口数目和窗口区间，每邻近的两个隔离窗口中间预留1.0Da的重叠，利用相同色谱方法进行样品在DIA模式下的采集，最后利用Spectronaut对DIA数据结果进行分析。
  7. 根据权利要求1所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，还包括：建立亲电片段分子库，所述亲电片段包括：丙烯酰胺、氯乙酰胺、环氧乙烷、丙烯腈或乙基乙烯基砜作为反应基团。
  8. 根据权利要求7所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，所述亲电片段分子库为：
    Figure PCTCN2022143156-appb-100001
  9. 根据权利要求7所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，还包括：将蛋白质组样品用亲电片段处理后，加入活性分子探针避光处理，随后利用可切割标签试剂进行点击化学反应，富集，酶切以及酸切，制备将亲电片段换为二甲基亚砜的对照组样品，制备活性分子探针标记的样品用于DDA分析建立谱图库，完成窗口设置后，进行亲电片段样品的DIA采集和靶点分析。
  10. 根据权利要求9所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，所述样品包括人B淋巴细胞瘤细胞、组织样品或血液样品。
  11. 根据权利要求9所述的基于DIA的定量化学蛋白质组学筛选靶标的方法，其特征在于，对亲电片段样品分析包括：对于每个活性氨基酸，对照样品的肽段强度与亲电片段处理样品中的肽段强度之比为所述亲电片段结合活性氨基酸的靶向比率，并将两个重复的中值比率报告作为最终比率，筛选剔除不足3个最终比率值的活性氨基酸，得到最终的活性氨基酸定量信息，筛选至少含有两个片段最终比率值大于4，至少一个片段的最终比率值在0.5和2之间的活性氨基酸位点，则为可靶向的活性氨基酸位点。
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