Method for measuring high-order structure forming ability, etc.

Abstract

The present invention addresses the problem of providing a method that is for analyzing interaction by using a cell system, is simpler than a cell-free measurement system, is applicable regardless of the kind of protein, and is usable for analysis of immune molecules and an MHC.　Provided is a method for measuring multimer-forming abilities for a test polypeptide and a target polypeptide in cells, the method including: an expression step for expressing the test polypeptide and the target polypeptide in a plurality of cells; a reference range setting step for analyzing a reference amount obtained from a cell group that is separated for reference and setting a reference range for an expression amount of the test polypeptide; a measurement step for measuring a test expression amount and a test presentation amount of the test polypeptide in a cell group that is separated for measurement; an extraction step for extracting information regarding test expression amounts and test presentation amounts of cells of which the test expression amounts are within the reference range; a relational expression derivation step for deriving a relational expression between the test expression amount and the test presentation amount on the basis of the extracted information; and a multimer formation value acquisition step for acquiring a multimer formation value on the basis of the relational expression.

Description

Method for measuring higher-order structure formation ability, etc.

[0001] The present invention relates to a method for measuring the ability of a cell to form a multimer containing multiple polypeptides, a method for measuring the ability of a polypeptide to form a three-dimensional structure, a method for measuring the ability of a polypeptide to maintain its localization at the cell membrane, and a method for screening conditions for forming a higher-order structure or conditions for maintaining its localization at the cell membrane using these methods.

[0002] In biological research, it is important to analyze the ability of proteins and other molecules to form higher-order structures. This is because these biomolecules are responsible for all biological functions, and all reactions in the body are based on intermolecular bonds. Therefore, clarifying the contribution of biomolecules and their higher-order structures to biological functions is directly linked to understanding those biological functions.

[0003] Methods for analyzing the ability of proteins and other proteins to form higher-order structures include, for example, analytical methods using electrophoresis, spectroscopic analysis of purified proteins, and analytical methods based on protein structural analysis. Analytical methods using electrophoresis, such as immunoprecipitation and Western blotting, quantitatively detect the presence of proteins in cell lysates using binding molecules such as antibodies. However, analytical methods using electrophoresis require the preparation of proteins from cell lysates, which must often be denatured. Analytical methods based on structural analysis can analyze the structure of proteins in detail based on the crystal structure of the protein. However, crystallization and structural analysis of proteins require a great deal of effort.

[0004] On the other hand, in the development of drugs, etc., it is important not only to analyze biomolecules such as proteins themselves, but also to analyze the interactions between biomolecules and other molecules (e.g., candidate drugs and other proteins). This is because all reactions in the body are based on intermolecular bonds, and their promotion, modification, and / or inhibition result in medicinal effects and side effects.

[0005] In particular, to compare multiple molecules such as candidate drugs and ligands, numerical values ​​for the strength of interaction are used. 50 Value and IC 50 value, dissociation constant (KD ) values ​​are widely used and are measured by methods such as ELISA, fluorescence polarization, surface plasmon resonance, and near-field light (evanescent light). These analyses require highly purified proteins, which often necessitate the large-scale preparation of recombinant proteins. Furthermore, these values ​​are calculated by analyzing the amount of effect of a drug or other substance when applied at a given concentration, based on an index that can quantitatively evaluate the effect of the drug or other substance. Many constraints exist, including the need to identify an appropriate index, the need for multiple experiments under different conditions, and the need to ensure that conditions other than the drug or other substance concentration are as close to physiological conditions as possible. Furthermore, depending on the index and experimental system used, many factors are involved in the measurement and calculation of the index, which means that the index does not necessarily directly reflect the strength of the interaction, the potential for differences in values ​​when measured in different facilities, and the difficulty of quantifying weak binding (Non-Patent Document 1).

[0006] Markossian S et al., Assay Guidance Manual [Internet]. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences; Last Updated: March 15, 2023

[0007] To obtain values ​​that directly reflect the strength of interactions, it is usually necessary to purify the target proteins and construct a cell-free measurement system. However, because changes in the effective concentration of proteins due to the properties of each protein, the solvent used, and protein adsorption to the container cannot be ignored, strictly speaking, an experimental system must be constructed that is tailored to the properties of each protein. However, the interactions of proteins and other biomolecules in living organisms are also affected by the intracellular environment, such as the presence of cell membranes, pH, ion concentration, and other coexisting substances, and these cannot be completely reproduced in a cell-free measurement system.

[0008] Analysis of interactions using cell systems allows us to understand the function of proteins and other molecules in an environment that is closer to their native physiological conditions than cell-free assays. It also allows us to observe the effects of interaction strength on protein and cellular functionality. However, this requires normalization of cell-to-cell variability and quantitative analysis of intact proteins, and no analytical method is readily available for such analysis. Several methods for detecting biomolecular interactions using cell systems are known. These include Förster resonance energy transfer (FRET) and proximity ligation assay (PLA), which fluorescently label two different proteins expressed in cells and detect their proximity under a fluorescence microscope. Other methods, such as the two-hybrid assay, detect the interaction of two different proteins using reporter gene expression. However, while these methods can determine whether molecules are in close proximity and whether an intermolecular interaction exists, they cannot measure the strength of the intermolecular interaction. Furthermore, drug screening using cell systems allows for the observation of changes in cell phenotype (growth, shape, etc.) and the enhancement or inhibition of specific enzyme reactions, but does not provide information on the site of action of the drug within the cell or the strength of the interaction between the drug and proteins.

[0009] Analytical methods using flow cytometry and image cytometry are known as methods that can detect the presence of proteins at the cell level without denaturing them. However, flow cytometry and image cytometry were developed for the qualitative analysis of immunophenotypes, cell cycles, etc., and are not necessarily suitable for quantitative analysis due to differences in detection sensitivity between instruments (models) and variations in measurement values ​​caused by differences in cell state and reagent products.

[0010] For these reasons, even when using cell systems, it is necessary to devise an experimental system, and it is difficult to select an indicator that directly reflects the interaction. Therefore, it has been thought that it would be difficult to develop a method for analyzing the strength of protein interactions using cell systems more easily than cell-free measurement systems.

[0011] In recent years, personalized medicine, which diagnoses and treats diseases based on individual characteristics, has been gaining attention, and there is an increasing need for functional analysis of immune molecules related to individual differences in immune responses. In particular, the function of the major histocompatibility complex (MHC), a molecule deeply involved in susceptibility to immune diseases, vaccine efficacy, and transplant immunity, is considered important for elucidating pathology and developing vaccines by quantifying the interactions between its subunits and between MHC and antigenic peptides, and by comparative analysis between different alleles and antigenic peptides. However, there has been no analytical method that can accurately measure such interaction indicators and provide them in a comparable form.

[0012] Therefore, an objective of the present invention is to provide a method for analyzing interactions using a cell system that is simpler than cell-free measurement systems, can be applied regardless of the type of protein, and can also be used to analyze immune molecules and MHC.

[0013] As a result of intensive research conducted by the present inventors to solve the above problems, they have found that by utilizing the relationship between protein translocation to the cell membrane and the strength of interaction and by devising methods for acquiring and analyzing data, it is possible to calculate comparable numerical values ​​that reflect the strength of interaction, regardless of experimental conditions such as the type of protein and the measuring equipment used. The present invention is based on these novel findings and provides the following.

[0014] [1] A method for measuring the ability of a test polypeptide and a target polypeptide to form multimers in cells, the cells being capable of transiently expressing the test polypeptide as a cell membrane protein and the target polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide and the target polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells whose test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a multimerization value acquisition step of acquiring a multimerization value from the relational equation, wherein the reference range setting step is [2] The method according to [1], wherein the multimer formation value is a derivative of the test expression value. [3] The method according to [1] or [2], wherein the relational expression is a linear expression with the test expression level as a variable, and the multimer formation value is a coefficient of the test expression level. [4] The method according to any one of [1] to [3], wherein the test polypeptide is a membrane protein.[5] The method according to [4], wherein the membrane protein is a subunit of MHC. [6] The method according to any one of [1] to [5], wherein the expression level of the test polypeptide is measured based on the expression level of a labeled protein coupled to the expression of the test polypeptide. [7] The method according to any one of [1] to [6], wherein the measurement is performed by any one or more methods selected from the group consisting of flow cytometry, image cytometry, and mass cytometry. [8] The method according to any one of [1] to [7], wherein the membrane protein is a subunit of MHC, and wherein the measurement of the expression level of the test polypeptide is performed by measuring the expression level of a labeled protein coupled to the expression of the test polypeptide by flow cytometry. [9] A method for measuring fluctuations in multimerization ability under target conditions, comprising: a control value measurement step of measuring a multimerization value under control conditions according to the method of [1] to obtain a control value; a treatment value measurement step of measuring a multimerization value under the target conditions according to the method of [1] to obtain a treatment value; and a calculation step of calculating a fluctuation value based on the obtained control value and treatment value.

[10] A method for measuring the binding affinity of a multimeric receptor to a test ligand on a cell membrane, comprising: a control value measurement step of measuring a multimerization value according to the method of [1] to obtain a control value; a test value measurement step of measuring a multimerization value according to the method of [1] to obtain a test value; and a calculation step of calculating a ligand binding value of the test ligand based on the obtained control value and test value, wherein the control value measurement step uses a fusion protein of a subunit of the multimeric receptor and a control ligand and another subunit of the multimeric receptor as the test polypeptide and the target polypeptide, respectively; and the test value measurement step uses a fusion protein of a subunit of the multimeric receptor and the test ligand and another subunit of the multimeric receptor as the test polypeptide and the target polypeptide, respectively.

[11] The method of

[10] , wherein the ligand binding value is based on the ratio of the test value to the control value.

[12] The method of

[10] , wherein the ligand binding value is based on the difference between the test value and the control value.

[13] A method for screening multimer formation conditions in cells, comprising: a control value measurement step of measuring a multimer formation value under control conditions according to the method described in [1] to obtain a control value; a candidate value measurement step of measuring a multimer formation value under candidate conditions according to the method described in [1] to obtain a candidate value; and a determination step of determining that the candidate conditions are suitable for multimer formation if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for multimer formation if the candidate value is lower than the control value.

[14] The method described in

[13] , wherein the multimer formation condition is the type of drug to which the cells are exposed.

[15] The method described in

[13] , wherein the multimer formation condition is the type of ligand.

[16] A method for measuring the three-dimensional structure formation ability of a test polypeptide in a cell, wherein the cell is capable of transiently expressing the test polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells whose test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a three-dimensional structure formation value acquisition step of acquiring a three-dimensional structure formation value from the relational equation, wherein the reference range setting step is the method includes a confirmation step of confirming the presence or absence of the test polypeptide, a reference cell sorting step of sorting a plurality of cells including cells expressing the test polypeptide as a reference cell group, a reference amount acquisition step of measuring the expression level of the test polypeptide in the reference cell group and obtaining it as a reference amount, a reference amount analysis step of analyzing the reference amount for its expression amount, and a setting step of setting the reference range based on the results of the analysis, wherein the measurement process includes a measurement cell sorting step of sorting a plurality of the cells as a measurement cell group, an expression amount measurement step of measuring the expression level of the test polypeptide in the measurement cell group and obtaining it as a test expression amount, and a presentation amount measurement step of measuring the amount of the test polypeptide present on the cell membrane in the measurement cell group and obtaining it as a test presentation amount, wherein the test presentation amount changes according to the structural stability of the test polypeptide.[16-1] A method for measuring the ability of a test polypeptide to maintain cell membrane localization in cells, wherein the cells are capable of transiently expressing the test polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells where the test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a cell membrane localization value acquisition step of acquiring a cell membrane localization value from the relational equation, wherein the reference range setting step is [16-2] The method according to [16-1], wherein the expression step further comprises expressing a target polypeptide that can be expressed as a cell membrane protein in the plurality of cells.

[17] A method for measuring a change in the ability to form a three-dimensional structure under target conditions, the method comprising: a control value measurement step of measuring a three-dimensional structure formation value under control conditions according to the method described in

[16] to obtain a control value; a treatment value measurement step of measuring a three-dimensional structure formation value under the target conditions according to the method described in

[16] to obtain a treatment value; and a calculation step of calculating a change in the ability to maintain cell membrane localization under target conditions. [17-1] A method for measuring a change in the ability to maintain cell membrane localization under target conditions, the method comprising: a control value measurement step of measuring a cell membrane localization value under control conditions according to the method described in [16-1] or [16-2] to obtain a control value; a treatment value measurement step of measuring a cell membrane localization value under the target conditions according to the method described in [16-1] or [16-2] to obtain a treatment value; and a calculation step of calculating a change in the ability to maintain cell membrane localization under target conditions.

[18] A method for screening conditions for the formation of a three-dimensional structure of a test polypeptide in a cell, comprising: a control value measurement step of measuring a three-dimensional structure formation value under control conditions according to the method described in

[16] to obtain a control value; a candidate value measurement step of measuring a three-dimensional structure formation value under candidate conditions according to the method described in

[16] to obtain a candidate value; and a determination step of determining that the candidate conditions are suitable for the formation of a three-dimensional structure of the test polypeptide if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for the formation of a three-dimensional structure of the test polypeptide if the candidate value is lower than the control value. [18-1] A method for screening conditions for maintaining the cell membrane localization of a test polypeptide in a cell, comprising: a control value measurement step of measuring a cell membrane localization value under control conditions according to the method described in [16-1] or [16-2] to obtain a control value; a candidate value measurement step of measuring a cell membrane localization value under candidate conditions according to the method described in [16-1] or [16-2] to obtain a candidate value; and a determination step of determining that the candidate conditions are suitable for maintaining the cell membrane localization of the test polypeptide if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for maintaining the cell membrane localization of the test polypeptide if the candidate value is lower than the control value.[18-2] The method according to any one of [16-1], [16-2], [17-1], or [18-1], wherein the test polypeptide is a G protein-coupled receptor.

[19] A program for calculating a higher-order structure formation value or a cell membrane localization value of a test polypeptide in a cell, comprising: a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; an extraction step of extracting information on the test expression amount and the test presentation amount for cells where the test expression amount is within the reference range, based on the test expression amount and the test presentation amount of the test polypeptide measured in a cell population sorted for measurement; and an extraction step of extracting information on the test expression amount and the test presentation amount for cells where the test expression amount is within the reference range, based on the extracted information.

[20] The program according to

[19] , wherein the reference range setting step further comprises a confirmation step of confirming the presence or absence of expression of the test polypeptide for each cell based on the expression level of the test polypeptide in the cells, and a reference cell separation step of obtaining data for a cell population containing cells expressing the test polypeptide as a reference. This specification incorporates the disclosure of Japanese Patent Application No. 2024-101522, from which the present application claims priority.

[0015] According to the method of the present invention for measuring the ability to form multimers, the ability of a test polypeptide and a target polypeptide to form multimers can be quantitatively measured.

[0016] According to the method of the present invention for measuring the binding affinity between a multimeric receptor and a test ligand, the binding affinity between a multimeric receptor and a test ligand can be quantitatively measured.

[0017] According to the method of the present invention for measuring the ability to form a three-dimensional structure and / or the ability to maintain localization at the cell membrane, the ability of a test polypeptide to form a three-dimensional structure and / or the ability to maintain localization at the cell membrane can be quantitatively measured.

[0018] According to the method of the present invention for measuring changes in the ability to form higher-order structures and / or the ability to maintain localization at the cell membrane, it is possible to measure changes in the ability to form multimers and / or the ability to form three-dimensional structures and / or the ability to maintain localization at the cell membrane under target conditions.

[0019] According to the method of the present invention for screening conditions for forming higher-order structures and / or conditions for maintaining cell membrane localization, candidate conditions can be screened for conditions that are suitable and / or unsuitable for forming multimers and / or forming three-dimensional structures and / or maintaining cell membrane localization.

[0020] According to the program of the present invention, the method of the present invention can be automatically executed by a computer or the like.

[0021]

[0023] Figure 1A is a schematic diagram showing an exemplary relationship between test expression level, test presentation level, and multimerization ability in a method for measuring multimerization ability. Figures 1A and 1B exemplarily show states in which the expression level (test expression level) and the abundance on the cell membrane (test presentation level) of a test polypeptide are different. In the figures, the gene and polypeptide of the test polypeptide are indicated in black, and the gene and polypeptide of the target polypeptide are indicated in white.

[0024] Figure 1B is a schematic diagram showing an exemplary outline of the reference range setting step S0102.

[0025] Figure 1C is a schematic diagram showing an exemplary outline of the reference range setting step S0102. In the figures, black circles represent cells expressing the test polypeptide, and white circles represent cells not expressing the test polypeptide. FIG. 6 is a schematic diagram illustrating an example of an outline of the steps of a method for measuring multimer formation ability. FIG. 6A shows an outline of the measuring step S0103, FIG. 6B shows the extraction step S0104, and FIG. 6C shows the relational equation deriving step S0105. In FIGS. 6A and 6B, black circles indicate cells expressing the test polypeptide, and white circles indicate cells not expressing the test polypeptide. In FIG. 6C, black circles correspond to data for each cell. It is a schematic diagram showing the structure of the plasmid vector for expressing the α subunit of MHC class II used in Example 1. In the figure, "Amp r " represents the ampicillin resistance gene, "5'LTR" and "3'LTR" represent the 5' and 3' retroviral LTRs (Long Terminal Repeats), "Ψ" represents the retroviral packaging signal, "SV40" represents the SV40 (Simian Virus 40) promoter, and "Puro" represents the r " indicates a puromycin resistance gene. It is a schematic diagram showing the structure of the plasmid vector for expressing the β subunit of MHC class II used in Example 1. In the figure, "Amp r" indicates the ampicillin resistance gene, "5'LTR," "3'LTR" indicate the 5' and 3' retroviral LTRs, "Ψ" indicates the retroviral packaging signal, "IRES" indicates the IRES (internal ribosome entry site), and "GFP" indicates the GFP gene. Furthermore, in the figure, "peptide" indicates a ligand, "linker 1" indicates a linker consisting of the amino acid sequence SGG, and "linker 2" indicates a linker consisting of the amino acid sequence GGGGSIEGRGGGSGSA. Figures 9A and 9B show cell density plots illustrating the gate setting used in Example 1. Figure 9A shows how gate 1 is set, and Figure 9B shows how gate 2 is set using gate 1 as the population. Figures 9A and 9B show how gate 3 and gate 4 are set using gate 2 as the population. Figures 9A and 9B show cell density plots illustrating the gate setting used in Example 1. Figures 9A and 9B show how gate 3 and gate 4 are set using gate 2 as the population. Figures 9A and 9B show cell density plots (color-coded by percentile) illustrating the gate setting used in Example 1. FIG. 11A shows how gate 5 is set for data separated by gate 4, FIG. 11B shows the setting criteria for a and b in FIG. 11A when setting gate 5, and FIG. 11C shows how gates 6 to 9 that divide gate 5 are set. Cell density plots show examples of gate positions used in Example 1. FIG. 12A shows the distribution of fluorescence intensity for each cell in a cell sample in which cells for measuring test expression levels and test presentation levels are treated with an isotype control antibody, and the positions of gates 5 and 6 to 9. FIG. 12B shows the distribution of fluorescence intensity for each cell in a group in which cells for measuring test expression levels and test presentation levels are treated with an anti-HLA antibody, and the positions of gates 5 and 6 to 9. DQA1, the MHC measured in Example 1, * 01:02 and DQB1 * This figure shows the derivation of the relational equation for the heterodimer at 06:02. In the figure, "isotype control" and "α-HLA antibody" indicate data from cell samples treated with an isotype control antibody and an anti-HLA antibody, respectively. Each data point indicates the median value of GFP fluorescence intensity and PE fluorescence intensity in gates 7, 8, and 9, starting from the low value side. In the figure, the equation indicates an approximation, and R 2The values ​​indicate the coefficient of determination. * 03:01 and DQB1 * This figure shows how the relational equation for the heterodimer at 03:02 was derived. In the figure, "isotype control" and "α-HLA antibody" indicate data from cell samples treated with an isotype control antibody and an anti-HLA antibody, respectively. Each data point indicates the median value of GFP fluorescence intensity and PE fluorescence intensity in gates 6 and 7, starting from the low value side. In the figure, the equation indicates an approximation, and R 2 The values ​​indicate the coefficient of determination. Figure 1 shows the results of comparing ligand binding values ​​depending on the type of ligand in Example 3. For each β subunit, the ligand binding value is shown, with the control value when G15 is used as the ligand being set at 1. In the figure, "peptide 1a," "peptide 2a," and "peptide 2d" indicate the results when each peptide was used as a ligand, while "G9" and "G12" indicate the results when peptides consisting of 9 and 12 glycine amino acids were used as ligands, respectively, and "GGS12" indicates the results when peptides consisting of 12 glycine and serine amino acids were used as ligands. Error bars indicate standard deviation. Predicted IC in Example 4 50 1 shows the results of comparison with the values ​​obtained using DRA as the α subunit. * Figure 16A shows the results when 01:01 was used. * 16B shows the results when 04:01 was used, and FIG. 16C shows the results when DRB1 was used as the β subunit. * The results are shown for the case of using 04:05. In the figure, the formula is an approximation, and R 2 The values ​​indicate the coefficient of determination. Predicted IC in Example 4 50 1 shows the results of comparison with the values ​​obtained using DRA as the α subunit. * Figure 17A shows the results when 01:01 was used. * Figure 17B shows the results when 15:02 was used, and Figure 17C shows the results when DRB3 was used as the β subunit. * The results are shown for the case where 01:01 was used. In the figure, the formula indicates an approximation, and R 2The values ​​indicate the coefficient of determination. Predicted IC in Example 4 50 FIG. 18A is a diagram showing the results of comparison with the DQA1 value. * 03:01 and DQB1 * 18B shows the results when using DQA1. * 01:03 and DQB1 * The results are shown for the case where 06:01 was used. In the figure, the formula indicates an approximation, and R 2 The values ​​indicate the coefficient of determination. Figure 1 shows the results of verifying compatibility between measurement models in Example 5. The figures show the ligand binding values ​​when G15 was used as the ligand, with the control value taken as 1. In the figure, "G9" shows the results when a peptide consisting of nine glycine amino acids was used as the ligand, "pep. 1a" shows the results when peptide 1a, "pep. 1b" shows peptide 1b, "pep. 1c" shows peptide 1c, "pep. 2b" shows peptide 2b, "pep. 2c" shows peptide 2c, and "pep. 2d" shows the results when peptide 2d was used as the ligand. Error bars for the "SA3800" data indicate the standard deviation. Figure 1 shows the results of verifying compatibility between measurement models in Example 5. The figures show the ligand binding values ​​when G15 was used as the ligand, with the control value taken as 1. In the figure, "G9" and "G12" indicate the results when peptides consisting of 9 and 12 glycine amino acids were used as ligands, respectively; "pep. 1d" indicates the results when peptide 1d, "pep. 1e" indicates the results when peptide 1e, "pep. 2a" indicates the results when peptide 2a, and "pep. 2b" indicates the results when peptide 2b were used as ligands. The error bars for the "SA3800" data indicate the standard deviation. This figure shows the results of verifying the sensitivity of the method of the present invention in Example 6. Figure 21A shows the values ​​of each index of ligand binding strength ("Rank" and "Rank_BA" values ​​by NetMHCIIpan-4.0, as well as predicted IC) predicted in silico using a known method when each peptide was used as a ligand. 50Figure 21B shows the ligand binding values ​​calculated from the measurement results using the method of the present invention. Figure 21C shows the results of comparing flow cytometry measurements ("Flow Cytometry") and image cytometry measurements ("Imaging Cytometry") in Example 7. The ligand binding values ​​are shown with the results when G15 was used as the ligand taken as 1. In the figure, "G15" shows the results when a peptide consisting of 15 glycine amino acids was used as the ligand; "pep. 1a" shows the results when peptide 1a, "pep. 1b" shows the results when peptide 1b, "pep. 1c" shows the results when peptide 1c was used, and "pep. 2d" shows the results when peptide 2d was used as the ligand. Figure 21D shows the difference in variation depending on the type of HLA class I allele when abacavir sulfate was used in Example 8. The variation values ​​are shown with the result when only PBS solvent was added without adding any drug (control value) taken as 1. In the figure, the concentration indicates the concentration of added abacavir sulfate, and the allele type indicates the type of α-subunit used. Error bars indicate standard deviation. This figure shows the difference in variation when abacavir sulfate and carbamazepine-related compounds were used in Example 8. Figure 24A shows the variation calculated as a ratio to the results when no drug was added and only DMSO or PBS solvent was added. Figure 24B shows the variation calculated as the difference from the results when no drug was added and only DMSO or PBS solvent was added. In the figure, each series indicates the type of drug added. In the figure, "Compound 1" indicates oxcarbazepine, "Compound 2" indicates carbamazepine 10,11-epoxide, "Compound 3" indicates eslicarbazepine acetate, and "Compound 4" indicates the results when carbamazepine was added. Error bars indicate standard deviation. This figure shows the results when a cytokine receptor (mouse IL-2 receptor α) was used as the membrane protein in Example 9. In the figure, each series indicates the type of mouse IL-2 receptor α used. In the figure, "IL2Ra wild type" indicates the results for mouse IL-2 receptor α (wild type), and "IL2Ra mutant type" indicates the results for mouse IL-2 receptor α (Y129H mutant type). Error bars indicate standard deviation.10 shows the difference in results when a ligand and an antagonist were added when orexin receptor 1 (OX1R) was used in Example 10. The values ​​shown are the variation of the results when only DMSO solvent was added without adding any ligand or drug, with the value set to 1. In the figure, "ligand" indicates the type of ligand added, and "antagonist" indicates the type of antagonist added. In the figure, "-" indicates that no antagonist was added, "pep. 3a" indicates the results when peptide 3a, "pep. 3b" indicates peptide 3b, and "pep. 3c" indicates the results when peptide 3c was used as the ligand. Error bars indicate standard deviation. In Example 10, the values ​​shown are the variation of the results when a ligand and an antagonist were added when orexin receptor 2 (OX2R) was used in Example 10. The values ​​shown are the variation of the results when only DMSO solvent was added without adding any ligand or drug, with the value set to 1. In the figure, "ligand" indicates the type of ligand added, and "antagonist" indicates the type of antagonist added. In the figure, "-" indicates that no antagonist was added, "pep. 3a" indicates the results when peptide 3a, "pep. 3b" indicates peptide 3b, and "pep. 3c" indicates the results when peptide 3c was used as the ligand. Error bars indicate standard deviation.

[0022] 1. Method for Measuring Multimer Formation Ability 1-1. Overview A first aspect of the present invention is a method for measuring multimer formation ability. The method of this aspect includes, as essential steps, an expression step, a reference range setting step, a measurement step, an extraction step, a relational equation deriving step, and a multimer formation value acquisition step. According to the method of this aspect, the multimer formation ability of a test polypeptide and a target polypeptide in a cell can be measured.

[0023] 1-2. Definitions The terms used herein are defined below. A "cell" refers to a structural unit of an organism. As used herein, a cell includes any cell, and the species from which it originates is not particularly limited. For example, it may be a cell derived from a unicellular organism or a multicellular organism. Preferably, it is a cell derived from a multicellular organism such as a eukaryote. The type of multicellular organism is not particularly limited, and it may be an animal or a plant. As used herein, a cell is, for example, an animal-derived cell. Examples of animals include mammals, including primates (including humans, chimpanzees, marmosets, etc.), companion animals (including dogs, cats, etc.), livestock (including pigs, cows, sheep, goats, etc.), and laboratory animals (including rodents such as mice, rats, and guinea pigs), as well as birds, amphibians, reptiles, insects, etc. Furthermore, the type of tissue from which the cells originate is not particularly limited. For example, any cell that constitutes a multicellular organism may be used, and specifically, in the case of cells derived from a multicellular organism, the cells include endoderm-derived cells, mesoderm-derived cells, ectoderm-derived cells, or combinations thereof.

[0024] The term "cell population" refers to a group containing multiple cells. As used herein, the term "cell population" includes both those in which the cells that make up the population have some kind of relationship with each other and those in which the cells are unrelated to each other.

[0025] The term "polypeptide" refers to two or more amino acids linked by peptide bonds. In particular, the term "polypeptide" as used herein broadly encompasses not only proteins but also short chains known as peptides and oligopeptides.

[0026] "Higher-order structure" refers to the secondary, tertiary, and quaternary structures that a polypeptide adopts. In this specification, higher-order structure particularly refers to tertiary and quaternary structures, and includes multimers and three-dimensional structures. Furthermore, "ability to form a higher-order structure" includes the ability to form a three-dimensional structure and the ability to form a multimer.

[0027] "Conformation" refers to the three-dimensional structure of the entire molecule. As used herein, the term "conformation" is synonymous with the tertiary structure of a polypeptide.

[0028] As used herein, the term "structural ability" refers to the ability of a polypeptide to maintain a steric structure in the environment it is in. The steric structure-forming ability as used herein encompasses both the influence of the steric structure-forming (folding) reaction of a polypeptide and the influence of both the steric structure-forming reaction and the steric structure-unfolding (unfolding) reaction of a polypeptide.

[0029] "Multimer" refers to a complex formed by the association of multiple molecules. As used herein, "multimer" particularly refers to a set of polypeptides that have a quaternary structure. In contrast, as used herein, "complex" refers not only to polypeptides but also to structures formed by the association of multiple molecules, and includes multimers.

[0030] The term "subunit" refers to one molecule that constitutes a multimer. As used herein, the term "multimer" broadly encompasses any multimer containing multiple subunits. For example, it includes both homomultimers formed only by the same type of subunits and heteromultimers containing different types of subunits.

[0031] As used herein, the term "multimerization ability" refers to the ability of subunits constituting a multimer to maintain a multimeric state in the environment they are in. The multimerization ability used herein encompasses both the effects of the multimerization reaction of subunits and the effects of both the multimerization reaction of subunits and the dissociation reaction from the multimeric state into subunits.

[0032] "Association" refers to the binding of multiple molecules through intermolecular interactions to form a complex. In this context, the intermolecular forces include any forces that act between molecules to form non-covalent bonds, such as hydrophobic interactions, van der Waals forces, Coulomb forces, and hydrogen bonds. The associated molecules may be of the same type or different types.

[0033] The term "membrane protein" refers to a protein present on a biological membrane. The biological membrane here includes any membrane structure formed by a lipid bilayer present in a living organism, such as the cell membrane, nuclear membrane, Golgi apparatus membrane, endoplasmic reticulum membrane, mitochondrial membrane (including inner and outer membranes), chloroplast membrane (including inner and outer membranes), and other vesicles.

[0034] "Cell membrane protein" refers to a protein present on a cell membrane. As used herein, "cell membrane protein" includes transmembrane proteins, cell membrane surface proteins, and lipid-modified proteins. Cell membrane surface proteins and lipid-modified proteins are proteins that do not have a transmembrane domain.

[0035] A "transmembrane domain" is a protein domain that has affinity for the lipid bilayer that constitutes the cell membrane and penetrates the lipid bilayer. In contrast, among cell membrane proteins, a protein domain exposed on the outside of the cell is called an extracellular domain, and a protein domain exposed on the inside of the cell is called an intracellular domain. For example, some lipid-modified proteins and surface cell membrane proteins are not entirely embedded in the cell membrane, and the entire protein can be called an extracellular domain or an intracellular domain.

[0036] "MHC (major histocompatibility complex)" refers to a membrane-spanning glycoprotein complex present on the cell membrane, which forms a heterodimer and expresses itself on the cell surface in a state where it binds to an antigen peptide. In this specification, MHC is used synonymously with MHC antigen. In this specification, MHC is treated as a receptor protein that binds to an antigen peptide (ligand). MHC is broadly classified into class I and class II.

[0037] As used herein, "displayed" when used in reference to a cell membrane protein refers broadly to the presence of the protein on the cell membrane.

[0038] "On the cell membrane" means being in contact with the cell membrane. In this specification, the state of being "on the cell membrane" broadly includes a state of being in direct or indirect contact with the cell membrane. For example, a state of being in direct contact with the cell membrane includes a state in which a part of the molecule (a transmembrane domain of a protein or a covalently bound lipid moiety) is present in the lipid bilayer of the cell membrane, as well as a state in which the surface of the molecule is in contact with the cell membrane through electrostatic interaction or the like. Furthermore, a state of being in indirect contact with the cell membrane refers to a state in which the molecule is in contact with a molecule that is in direct contact with the cell membrane or a state in which the molecule is associated with a molecule that is in direct contact with the cell membrane.

[0039] As used herein, the term "receptor" refers to a protein that specifically recognizes a particular substance. Receptors as used herein include both proteins that recognize substances endogenous to cells and proteins that recognize substances exogenous to cells. Receptors as used herein also include proteins that bind to a ligand to form a stable higher-order structure.

[0040] The term "multimeric receptor" refers to a receptor protein that forms a multimer.

[0041] "Ligand" refers to a substance that specifically binds to a receptor protein. As used herein, the term "ligand" broadly refers to a substance that can bind to a receptor protein and a substance that can contact the ligand-binding site of a receptor protein.

[0042] In this specification, "sorting" refers to separating cells. "Sorting" broadly includes not only the operation of moving cells from a container, but also the operation of measuring or observing a portion of the cells without moving them from the container.

[0043] In this specification, "separation" broadly includes not only aspects such as fractionation but also aspects such as handling certain information separately from other information.

[0044] A "relational expression" refers to an expression that expresses the relationship between multiple phenomena. The relational expression in this specification is not particularly limited, but is preferably an equation, and is also preferably a mathematical expression. The relational expression in this specification is, for example, a functional expression.

[0045] As used herein, the term "binding molecule" refers to any molecule capable of binding to a target molecule. Binding molecules include antibodies, their antigen-binding fragments, antigen-binding derivatives, aptamers, and the like. For example, antibodies include both monoclonal and polyclonal antibodies, such as IgG antibody molecules and IgM antibody molecules. Antibodies include complete antibodies, Fab, Fab', and F(ab')2 fragments, and single-chain antibody (scFv) fragments in which the heavy chain variable region (VH) and light chain variable region (VL) are linked via a linker.

[0046] As used herein, "maintenance on the cell membrane" or "maintenance of localization on the cell membrane" refers to the maintenance of the amount of a certain protein on the cell membrane within a certain range. There are no particular limitations on the causes of a change in the amount of a certain protein on the cell membrane due to loss of maintenance on the cell membrane. Examples include destabilization of the three-dimensional structure of the protein, dissociation of a protein complex, and / or internalization due to protein activation.

[0047] 1-3. Steps The method of this embodiment includes, as essential steps, an expression step, a reference range setting step, a measurement step, an extraction step, a relational equation deriving step, and a multimer formation value obtaining step.

[0048] An overview of this method will be described with reference to FIG. 1. For example, consider cells expressing a test polypeptide (black in the figure) and a target polypeptide (white in the figure) as shown in FIG. 1. If the amount of dimers of the test polypeptide and target polypeptide present on the cell surface (test presentation amount) alone is used as an indicator of the dimer formation ability of the test polypeptide and target polypeptide, the amount of dimers on the cell membrane of the cell in FIG. 1A is two, and the amount of dimers on the cell membrane of the cell in FIG. 1B is four. Therefore, at first glance, the dimer formation ability of the test polypeptide in cell B appears to be twice that of cell A. However, the intracellular expression level of the test polypeptide is higher in cell B than in cell A. For example, when examining the amount of test polypeptide in the endoplasmic reticulum, cell B expresses more than twice the test polypeptide as cell A. Therefore, by correcting the test presentation amount using the expression level of the test polypeptide in the cells (test expression level), it can be determined that the test polypeptide in cells A has a higher ability to form multimers than the test polypeptide in cells B, and the dimer formation ability of each test polypeptide of A and B can be properly evaluated. Each step is explained below.

[0049] 1-3-1. Expression Step S0101 The "expression step" is an essential step in which the test polypeptide and the target polypeptide are expressed in a plurality of cells.

[0050] <Test Polypeptide> As used herein, the terms "test polypeptide" and "subject polypeptide" both refer to polypeptides that constitute the multimer to be measured. The names test polypeptide and subject polypeptide are used for convenience, and which polypeptide in a given multimer is the test polypeptide can be determined arbitrarily.

[0051] The multimer formed by the test polypeptide is not particularly limited as long as it is a complex formed by the association of multiple polypeptides. For example, the multimer herein includes any of enzyme-substrate complexes, ligand-receptor complexes, antigen-antibody complexes, and complexes of multiple proteins that function in cooperation (including enzyme complexes, immune receptor complexes, etc.).

[0052] The multimer may be one that is known to actually form a multimer with the test polypeptide, or it may not be one that is known to form a multimer. For example, if the main purpose is to quantitatively measure the ability to form multimers, the method of this embodiment can be used with known multimers, but if the main purpose is to measure the presence or absence of multimer formation, the multimer formed by the test polypeptide and the target polypeptide is unknown.

[0053] The multimer may have a stable structure, or may have a structure that is stable only under specific conditions. For example, both multimers that have a stable structure in the extracellular environment and multimers that have a stable structure in the intracellular environment can be used. When using a multimer that has a stable structure in the extracellular environment, it can be used in the method of this embodiment by expressing it as a cell membrane protein so that at least a portion of the test polypeptide is located extracellularly. On the other hand, when using a multimer that has a stable structure in the intracellular environment, it can be used in the method of this embodiment by expressing it as a cell membrane protein so that at least a portion of the test polypeptide is located extracellularly. Furthermore, in the multimer, further covalent bonds may be formed after association by intermolecular interactions.

[0054] The number of molecules constituting the multimer is not particularly limited, as long as it is plural. For example, the multimer may be composed of two or more, three or more, four or more, five or more, or more molecules. Furthermore, the multimer may be composed of, for example, 20 or fewer, 18 or fewer, 17 or fewer, 16 or fewer, 15 or fewer, 14 or fewer, 13 or fewer, 12 or fewer, 11 or fewer, 10 or fewer, 8 or fewer, 7 or fewer, 6 or fewer, 5 or fewer, 4 or fewer, or 3 or fewer molecules. When it is unknown whether the test polypeptide forms a multimer, the method of this embodiment may be carried out without specifically determining the number of molecules constituting the multimer.

[0055] A multimer may be composed of all identical molecules (i.e., a homomultimer), or may contain some different molecules (i.e., a heteromultimer). The number of test polypeptide molecules contained in one multimer is not particularly limited, and may be, for example, 18 or fewer, 16 or fewer, 14 or fewer, 12 or fewer, 11 or fewer, 10 or fewer, 8 or fewer, 7 or fewer, 6 or fewer, 5 or fewer, 4 or fewer, 3 or fewer, or 2 or fewer, and preferably 2 or fewer or 1 molecule.

[0056] The test polypeptide may be a membrane protein or a non-membrane protein as long as it can be expressed as a membrane protein in the cells described below. When the test polypeptide is a membrane protein, its specific type is not particularly limited. For example, the test polypeptide may be a membrane protein. Test polypeptides that are not membrane proteins include, for example, receptor ligands and antigen peptides that bind to MHC. Furthermore, exogenous polypeptides can be suitably used as the test polypeptide, but endogenous polypeptides may also be used as long as the timing of their expression can be controlled. Exogenous polypeptides include polypeptides derived from the same individual organism as the cell, polypeptides derived from the same species as the cell, and polypeptides derived from a different species from the cell. The polypeptide may be artificial or natural.

[0057] The test polypeptide and / or the target polypeptide may be linked to a tag. Examples of tags include epitope tags. Examples of epitope tags include, but are not limited to, His tags, Strep-tag (registered trademark) II, FLAG (registered trademark) tags, and Myc tags. The test polypeptide and / or the target polypeptide may be linked to the tag directly or indirectly. For example, the polypeptide and the tag may be linked via an artificial sequence directly linking the polypeptide and the tag, or via a linker, a protease cleavage sequence, a restriction enzyme recognition sequence, or the like.

[0058] The type of cell membrane protein used in this embodiment is not particularly limited, as long as the formation of multimers is a protein necessary for migration to the cell membrane and / or maintenance on the cell membrane. Note that the cell membrane protein used in other embodiments can be any cell membrane protein suitable for that purpose. For example, when measuring the ability to form a three-dimensional structure, the protein is not particularly limited, as long as it is necessary for the formation of a three-dimensional structure to migrate to the cell membrane and / or maintenance on the cell membrane. For example, when measuring the ability to maintain cell membrane localization, the protein is not particularly limited, as long as it is capable of migrating to the cell membrane and the ease of maintenance on the cell membrane is affected by conditions such as the state of the protein or the presence or absence of a ligand. Note that "necessary" for migration to the cell membrane and / or maintenance on the cell membrane means that satisfying the conditions makes it easier to migrate to the cell membrane and / or maintain on the cell membrane.

[0059] The protein may be any of transmembrane proteins, surface membrane proteins, and lipid-modified proteins, or may be a protein that localizes on the cell membrane under specific conditions. Examples of cell membrane proteins include transporter proteins (including channel proteins such as ion channels, selective channels such as aquaporins, and non-selective channels such as connexins; pump proteins including proteins that use ion movement as energy, such as sodium ion pumps, proton pumps, and ATPases; as well as symporters and antiporters), cell membrane protein receptors (including enzyme-linked receptors, ion channel receptors, and G protein-coupled receptors), cell adhesion molecules, membrane-bound ligands, and membrane antigens. Cell membrane protein receptors, cell adhesion molecules, membrane-bound ligands, and membrane antigens (e.g., MHC) are suitable for use. Preferably, membrane-bound ligands and membrane antigens can be used; specifically, MHC can be used.

[0060] Enzyme-linked receptors (e.g., receptor tyrosine kinases) undergo dimerization or multimerization upon ligand binding, activating the receptor-bound enzyme and initiating signal transduction based on the enzymatic reaction. It has been suggested that the stability of the three-dimensional structure of enzyme-linked receptors, such as cytokine receptors (e.g., interleukin receptors such as IL-2 receptor), affects their expression on the cell membrane.

[0061] Ionotropic receptors are often heteropolymers that change their conformation upon ligand binding, thereby functioning as channels that regulate membrane permeability of ions. Examples of ionotropic receptors include glutamate receptors, nicotinic receptors, GABA receptors, serotonin receptors, and glycine receptors.

[0062] When the cell membrane protein is a G protein-coupled receptor, the specific type is not particularly limited. G protein-coupled receptors initiate signal transduction by, for example, structural changes upon ligand binding or activation of G proteins present in the cytoplasm. It is known that some receptors, such as G protein-coupled receptors, are internalized into cells through interactions with β-arrestins in the cytoplasm upon ligand binding. This internalization phenomenon is known to occur in G protein-coupled receptors, such as orexin receptor 1 (OX1R), orexin receptor 2 (OX2R), and dopamine receptors.

[0063] When the multimer is an MHC, the specific type is not particularly limited, and may be, for example, either MHC class I or MHC class II.

[0064] MHC class I is composed of a dimer of an α subunit and β2 microglobulin, is present in all nucleated cells and platelets, and activates CD8+ cytotoxic T cells. On the other hand, MHC class II is composed of a dimer of an α subunit and β subunit, is expressed on antigen-presenting cells, and activates CD4+ helper T cells. When the multimer is an MHC, either subunit can be used as the test polypeptide.

[0065] In particular, human MHC is called human leukocyte antigen (HLA). HLA, classified as MHC class I (HLA class I), has many polymorphisms in the HLA-A, -B, and -C loci encoding the α subunit, with over 4,000 alleles registered for each. β2 microglobulin is less polymorphic. HLA class I is further classified into isotypes such as HLA-A, HLA-B, HLA-C, HLA-E, HLA-F, and HLA-G, and each isotype is further classified into several serological types. HLA-A serological types include, for example, HLA-A1, -A2, -A3, -A9, -A10, -A11, -A19, -A28, -A36, -A43, and -A80. HLA-A genes include, for example, HLA-A ＊ 01:01, -A ＊ 02:01, -A ＊ 03:01, -A ＊ 24:02, etc. Examples of serological types of HLA-B include HLA-B5, -B7, -B8, -B12, -B13, -B14, -B15, -B16, -B17, -B18, -B21, -B22, -B27, -B35, -B37, -B40, -B41, -B42, -B46, -B47, -B48, -B53, -B57, -B59, -B67, -B70, -B73, -B78, and -B81. Examples of HLA-B genes include HLA-B ＊ 07:02, -B ＊ 08:01, -B * 15:02, -B ＊ 44:02, -B ＊ 51:01, -B ＊ 52:01, -B * 57:01, -B * 57:02, -B * Examples of the serological types of HLA-C include HLA-Cw1, -Cw2, -Cw3, -Cw4, -Cw5, -Cw6, -Cw7, and -Cw8. Examples of the HLA-C gene include HLA-C ＊ 01:02, -C ＊ 03:03, -C ＊04:01, -C ＊ 07:01, -C ＊ Examples include 07:02.

[0066] While there are relatively few polymorphisms in the genes encoding the α subunit of HLA (HLA class II), which is classified as MHC class II, there are many polymorphisms in the genes encoding the β subunit, with over 1,000 alleles registered for each of the HLA-DRB1, -DQB1, and -DPB1 loci. HLA class II is further classified into isotypes such as HLA-DR, HLA-DQ, and HLA-DP. Each isotype is further classified into several serological or cytological types. Serological types of HLA-DR include HLA-DR1, -DR2, -DR3, -DR4, -DR5, -DR6, -DR7, -DR8, -DR9, -DR10, -DR51, -DR52, and -DR53. Examples of genes encoding the α subunit of HLA-DR include HLA-DRA, -DR51, -DR52, and -DR53. ＊ 01:01, etc. Examples of the gene encoding the β subunit of HLA-DR include HLA-DRB1 ＊ 03:01, -DRB1 ＊ 04:05,-DRB1*07:01,-DRB1 ＊ 09:01, -DRB1 ＊ 15:01, -DRB1 ＊ 15:02, -DRB3 ＊ 01:01, -DRB3 ＊ 02:02, -DRB3 ＊ 03:01, -DRB4 ＊ 01:03, -DRB5 ＊ 01:01, -DRB5 ＊ Examples of the cytological types of HLA-DP include HLA-DPw1, -DPw2, -DPw3, -DPw4, -DPw5, and -DPw6. Examples of the genes encoding the α subunit of HLA-DP include HLA-DPPA1, ＊ 01:03, -DPA1 ＊ 02:02, etc. Examples of the gene encoding the β subunit of HLA-DP include HLA-DPB1 ＊ 02:01, -DPB1＊ 04:01, -DPB1 ＊ 04:02, -DPB1 ＊ 05:01, -DPB1 ＊ Examples of the serological types of HLA-DQ include HLA-DQ1, -DQ2, -DQ3, and -DQ4. Examples of the α subunit gene of HLA-DQ include HLA-DQA1, ＊ 01:02, -DQA1 ＊ 02:01, -DQA1*03:01, -DQA1 ＊ 05:01, etc. Examples of the HLA-DQ β subunit gene include HLA-DQB1 ＊ 02:01, -DQB1 ＊ 03:01, -DQB1 ＊ 03:03, -DQB1 ＊ 04:01, -DQB1 ＊ 06:01, -DQB1 ＊ Examples include 06:02.

[0067] <Target Polypeptide> The target polypeptide is a polypeptide whose ability to form a multimer with a test polypeptide is measured by the method of this embodiment.

[0068] As mentioned above, the distinction between the target polypeptide and the test polypeptide is for convenience. Therefore, the basic content of the target polypeptide is the same as that of the test polypeptide. Here, only the differences from the test polypeptide will be described.

[0069] The type of target polypeptide is not particularly limited as long as it has the potential to form a multimer with the test polypeptide. For example, the target polypeptide may be a polypeptide known to associate with the test polypeptide, or a polypeptide unknown to associate with the test polypeptide. Furthermore, the target polypeptide may be an endogenous polypeptide or an exogenous polypeptide.

[0070] The number of target polypeptides is not particularly limited as long as it is one or more types. For example, the number of target polypeptides may be two or more types, three or more types, four or more types, or five or more types, or may be, for example, 20 or less types, 18 or less types, 16 or less types, 14 or less types, 12 or less types, 10 or less types, 8 or less types, 6 or less types, 5 or less types, 4 or less types, 3 or less types, or 2 or less types.

[0071] The number of molecules of each target polypeptide contained in one multimer is not particularly limited, and may be, for example, 10 or less, 8 or less, 4 or less, 3 or less, 2 or less, or 1 molecule.

[0072] <Cells> The cells used in the method of this embodiment are capable of transiently expressing a test polypeptide as a cell membrane protein, and are capable of expressing a target polypeptide as a cell membrane protein.

[0073] The type of cell used is not particularly limited as long as it is capable of expressing the test polypeptide and the target polypeptide. For example, any of the cells described above in the definition section can be used. Furthermore, the cells used may be cells that normally express the test polypeptide and / or the target polypeptide, or may be cells that have been modified by specific manipulation to express these polypeptides.

[0074] The specific type of cell is not particularly limited, and examples include animal-derived cells, vertebrate-derived cells, mammalian-derived cells, and human-derived cells. The cells may be derived from the same or different organisms as those from which the test polypeptide and target polypeptide are derived. Cultured cells can also be used. In this case, the cultured cells may be primary cultured cells, subcultured cells, or established cell lines. For example, tumor-derived cells, immortalized cells, antigen-presenting cells (B cells, dendritic cells, macrophages, etc.), cells differentiated from pluripotent stem cells such as ES cells and iPS cells, and established cell lines thereof can be used.

[0075] Cells into which at least one gene for a test polypeptide and / or a target polypeptide has been introduced can be used. Any known method can be used for gene introduction, and is not particularly limited. For example, the gene may be integrated into genomic DNA, or may be introduced into cells as a nucleic acid molecule independent of genomic DNA. Any known vector can be used for gene introduction, and is not particularly limited. For example, viruses, plasmids, cosmids, artificial chromosomes, etc. can be used as vectors. Viruses include various vectors derived from retroviruses, adenoviruses, adeno-associated viruses, lentiviruses, etc. Plasmids include pKA1, pCDM8, pSVK3, pMSG, pSVL, pBK-CMV, pBK-RSV, pEBV, pRS, pcDNA3, pMSG, pYES2, pMXs-puro, pMXs-IB, pMXs-IRES-GFP, etc.

[0076] When genes for both a test polypeptide and a target polypeptide are introduced, the genes for both polypeptides may be contained in the same vector or in separate vectors, and the introduction method used in this case may be a common method or separate methods.

[0077] The cells are capable of expressing the test polypeptide and the polypeptide of interest as cell membrane proteins.

[0078] As used herein, the phrase "capable of being expressed as a cell membrane protein" refers to the ability to be expressed in the form of a cell membrane protein when used in the method of this embodiment. When the test polypeptide and the target polypeptide themselves are cell membrane proteins or parts thereof, they can be expressed as cell membrane proteins by expressing the test polypeptide and the target polypeptide as they are. Furthermore, when at least one of the test polypeptide and the target polypeptide is a membrane protein other than a cell membrane protein, it can be expressed as a cell membrane protein, for example, by substituting a localization signal sequence for another organelle with an endoplasmic reticulum localization signal sequence. Furthermore, when at least one of the test polypeptide and the target polypeptide is not a membrane protein, it can be expressed as a cell membrane protein, for example, by expressing the test polypeptide as a fusion protein with a cell membrane protein (including membrane proteins modified into cell membrane proteins as described above) or a part thereof. In this case, any of the cell membrane proteins described above for the test polypeptide can be used as the cell membrane protein.

[0079] The test polypeptide presentation amount, described below, changes depending on the association between the test polypeptide and the target polypeptide. Therefore, the cells used in this embodiment express both polypeptides in such a manner that the translocation of the multimer to the cell membrane changes depending on the association between the test polypeptide and the target polypeptide. For example, the cells express both polypeptides in such a manner that the association between the test polypeptide and the target polypeptide is essential for the translocation of the multimer to the cell membrane. Specifically, for example, if the test polypeptide and / or the target polypeptide are cell membrane proteins and it is known that the formation of multimers is essential for the translocation to the cell membrane, the method of this embodiment can be carried out by expressing them as they are. Furthermore, for example, if the test polypeptide and / or the target polypeptide form homomultimers or the like and are capable of translocation to the cell membrane, the method of this embodiment can be carried out by detecting an indicator that reflects the abundance of multimers containing the test polypeptide and / or the target polypeptide on the cell membrane when measuring the test polypeptide presentation amount. If the test polypeptide and / or the target polypeptide is not a cell membrane protein, the method of this embodiment can be carried out by expressing them as cell membrane proteins that can be expressed in the manner described above.

[0080] The cells are capable of transiently expressing a test polypeptide. As used herein, "transiently expressible" refers to the fact that the test polypeptide is not present in the cells as a cell membrane protein at the start of the expression step, but that the test polypeptide can be expressed as a cell membrane protein after the start of the expression step. That is, the test polypeptide has never been expressed as a cell membrane protein in the cells before the expression step, or even if it has been expressed, the expression level is low or depleted at the start of the expression step.

[0081] The end of expression of the test polypeptide is not particularly limited as long as it continues to be expressed until the end of this step. For example, the expression may be stopped simultaneously with the end of this step, or may be continued even after the end of this step.

[0082] The cells are capable of expressing the target polypeptide. The manner of expression of the target polypeptide is not particularly limited as long as the timing and amount of expression of the target polypeptide in this step are not rate-limiting for the transfer of the multimer to the cell membrane or the maintenance of the expression state on the membrane. For example, the target polypeptide may be constitutively expressed or may be conditionally expressible. Preferably, the target polypeptide is expressed before the start of the expression step.

[0083] The type of promoter that controls the expression of these polypeptides is not particularly limited. As used herein, a "promoter" refers to a gene expression regulatory region that can control the expression of a gene, etc., located downstream (3' end) of the promoter. Based on the location at which a gene, etc., under its expression control is expressed, promoters can be divided into ubiquitous promoters (systemic promoters) and site-specific promoters. A ubiquitous promoter is a promoter that controls the expression of a target gene, etc. (referred to as a "target gene, etc.") in all cells, i.e., the entire host organism. A site-specific promoter is a promoter that controls the expression of a target gene, etc., only in specific cells or tissues. The promoters that control the test polypeptide and target polypeptide of the present invention may be either ubiquitous promoters or site-specific promoters.

[0084] When classified based on the timing of expression, promoters are classified into constitutively active promoters, inducible promoters, and stage-specific active promoters. Constitutively active promoters can constitutively express a target gene, etc. in cells. Inducible promoters can induce the expression of a target gene, etc. in cells at any time based on an inductive stimulus. Stage-specific active promoters can induce the expression of a target gene, etc. in cells only at a specific stage of development. A promoter that controls the expression of a test polypeptide or target polypeptide may be any of a constitutively active promoter, an inducible promoter, and a stage-specific active promoter. In particular, the target polypeptide may be an endogenous polypeptide, and its promoter may be an endogenous promoter.

[0085] The duration of this step is not particularly limited as long as it allows sufficient expression of the test polypeptide. For example, the step can be carried out for 1 hour or more, 2 hours or more, 3 hours or more, 5 hours or more, 6 hours or more, 9 hours or more, 12 hours or more, 18 hours or more, 24 hours or more, 30 hours or more, 36 hours or more, 42 hours or more, 48 hours or more, 50 hours or more, 55 hours or more, 60 hours or more, 70 hours or more, 72 hours or more, 80 hours or more, 84 hours or more, 90 hours or more, or 96 hours or more.

[0086] The conditions for this step are not particularly limited and can be set appropriately depending on the cells used. Culture methods for different cell types are well known in the art, and any of these can be used. For example, various media, additives, etc. are commercially available, and these may also be used. The culture environment is not particularly limited. Culture can be performed in a commonly used environment, for example, at 37°C and 5% CO2.

[0087] 1-3-2. Reference Range Setting Step S0102 The "reference range setting step" is an essential step in which a reference amount obtained from a cell population sorted for reference is analyzed to set a reference range for the expression amount of the test polypeptide. This step can be performed simultaneously with or after the expression step.

[0088] This process includes a confirmation step, a reference cell sorting step, a reference amount acquisition step, a reference amount analysis step, and a setting step.

[0089] First, an overview of this step will be described with reference to Figure 5. In this step, the presence or absence of expression of the test polypeptide in the cells is first confirmed ((1) in Figure 5). Then, a plurality of cells including cells expressing the test polypeptide are sorted as a reference cell group ((2) in Figure 5). The expression level of the test polypeptide in the sorted cell group is measured, and this expression level is obtained as a reference level ((3) in Figure 5). The expression level of the test polypeptide obtained is analyzed and tabulated in any format, such as a graph ((4) in Figure 5), and a reference range is set based on the results of the analysis ((5) in Figure 5). The reference range set in this step is used in the subsequent extraction step. Each step is described below.

[0090] (1) Confirmation Step S0110 This step is a step for confirming whether or not a test polypeptide is expressed in a cell ((1) in FIG. 5).

[0091] The indicator for determining the presence or absence of expression is not particularly limited as long as it reflects the expression of the test polypeptide. For example, the amount of the transcription product of the test polypeptide, the amount of the translation product, the amount of the label bound to the test polypeptide, the amount of the transcription product coupled with the expression of the test polypeptide, the expression amount of the labeled protein coupled with the expression of the test polypeptide, the amount of the label coupled with the function of the test polypeptide, etc. can be used.

[0092] The type of label is not particularly limited. For example, a low-molecular-weight label, a labeled peptide, a labeled protein, etc. can be used. Specific types of labels include, for example, luminescent substances, fluorescent substances, enzymes, radioactive substances, metal isotopes, quantum dots, enzyme substrates, enzyme cofactors, enzyme inhibitors, dyes, metal ions, and combinations thereof.

[0093] Examples of luminescent substances include acridinium esters, 3-(2'-spiroadamantane)-4-methoxy-4-(3"-phosphoryloxy)phenyl-1,2-dioxetane (AMPPD), luminol and its modified forms, 4-aminophthalhydrazide, various coelenterazines, and luciferin.

[0094] Examples of fluorescent substances include FITC, Texas Red, PE, PerCP, APC, Cy3, Cy5, Cy7, FAM, HEX, VIC, JOE, Rox, TET, Bodipy493, NBD, TAMRA, Qdot (registered trademark), DAPI, DyLight (registered trademark), and Pacific Blue. TM , eFluor TM , Brilliant Violet TM ,BD Horizon TM , Alexa-Fluor (registered trademark) dyes, and tandem dyes thereof; fluorescent proteins such as GFP, EGFP, BFP, CFP, YFP, and mCHERRY.

[0095] Examples of enzymes include proteases, peroxidases, phosphatases (eg, alkaline phosphatase), sulfatases, peptidases, glycosidases, hydrolases, oxidoreductases, lyases, transferases, isomerases, ligases, and synthetases.

[0096] Examples of radioactive materials include: 14 C. 123 I, 124 I, 125 I, 131 I, Tc99m, 32 P, 35 S and 3 H, etc. In addition, metal isotopes include: 169 Tm, 167 Er, 144 Nd, etc.

[0097] When a label is bound to the test polypeptide, the label may be bound directly to the test polypeptide or indirectly via a linker, etc. In addition to labels that are directly detectable, labels that become detectable after additional treatment, such as the enzyme substrates described above, can also be used.

[0098] As used herein, the term "labeled protein coupled to the expression of a test polypeptide" refers to a labeled protein whose expression level correlates with that of the test polypeptide. Examples of such proteins include labeled proteins whose genes are under the control of the same promoter as the test polypeptide and are expressed simultaneously with the test polypeptide (polycistronic expression), and labeled proteins whose genes are under the control of a promoter that competes with the promoter of the test polypeptide and whose expression level decreases in accordance with the expression level of the test polypeptide. Examples of polycistronic expression include IRES, IGR-IRES, and self-cleaving peptides such as 2A peptides (P2A, T2A, E2A, F2A).

[0099] Furthermore, if the labels used for the confirmation in this step and the measurement in the reference amount acquisition step are different, a labeled protein having a gene under the control of the same promoter in the same vector or in a different vector can be used to confirm the expression of the test polypeptide in this step. Even in such cases, if there is a clear correlation between the expression level of the test polypeptide and the expression level of the labeled protein, such a labeled protein can also be used in the measurement in the reference amount acquisition step by correcting based on that information, for example.

[0100] In this case, the labeled protein includes not only a protein whose presence can be directly detected, but also a protein whose presence can be indirectly detected. Examples of proteins whose presence can be directly detected include the various fluorescent proteins described above. Furthermore, examples of proteins whose presence can be indirectly detected include enzymes that become detectable in the presence of a specific substrate, and proteins that migrate onto the cell membrane and can be detected by the method described below in the step of measuring the amount of presentation.

[0101] A label conjugated to the function of a test polypeptide refers to a label that becomes detectable based on the function of the test polypeptide. For example, if part of the test polypeptide is an enzyme, the expression of the test polypeptide can be detected based on the enzymatic reaction by using its substrate as a label.

[0102] The method for determining the presence or absence of expression is not particularly limited as long as it can detect the expression of biomolecules in individual cells. The biomolecules to be detected are not limited to polypeptides, but may also be proteins or nucleic acids. Preferably, the method does not disrupt the cell structure and can measure the intracellular localization and amount. For example, the presence or absence of expression can be determined visually, using a microscope (e.g., a stereomicroscope, a confocal microscope, a fluorescence microscope, etc.), by detecting the presence or absence of detection using a detection device, or by measuring the expression level. In the case of a method using a detection device, the specific method is not particularly limited. For example, a method for detecting the amount of biomolecules in each cell can be used. Examples of such methods include methods using instruments such as a microscope image analyzer or a plate image analyzer, flow cytometry, image cytometry, and mass cytometry. In the case of a detection method based on fluorescence detection, the specific method is not particularly limited. For example, methods using fluorescently labeled antibodies or Förster resonance energy transfer (FRET), bimolecular fluorescence complementation assay (BiFc), proximity ligation assay (PLA), single-molecule fluorescence detection methods, spectroscopy, etc. can be used. Methods that can be used to quantify nucleic acids include, but are not limited to, detection methods using nucleic acid staining reagents and methods that count the number of reads per cell using a next-generation sequencer.

[0103] When the level of expression can be detected as a continuous value, the level of expression used to determine whether a test polypeptide is expressed is not particularly limited. For example, it may be sufficient that the expression is greater than that in cells that do not express the test polypeptide (control cells), or may be significantly greater than that in the control cells.

[0104] The cells used in this step may be live cells or fixed cells.

[0105] (2) Reference Cell Sorting Step S0111 This step is a step of sorting a cell population containing cells expressing a test polypeptide as a reference cell population ((2) in Figure 5). This step can be performed simultaneously with or after the confirmation step.

[0106] The method of sorting is not particularly limited. For example, a desired number of cells may be selected from a cell population that has already been separated (e.g., a cell population separated into small compartments in a culture vessel), or cells from multiple arbitrary positions may be sorted from a cell population in one compartment, or multiple previously separated cell populations may be sorted together as a single cell group. When using image cytometry for measurement, the cells in the culture vessel can be used as the measurement target.

[0107] The number of cells in the cell population to be sorted for reference is not particularly limited. For example, a cell population consisting of 600 cells or more, 1,000 cells or more, 2,000 cells or more, 3,000 cells or more, 5,000 cells or more, 7,000 cells or more, 10,000 cells or more, 20,000 cells or more, 30,000 cells or more, 40,000 cells or more, or 50,000 cells or more can be sorted.

[0108] The number of cell populations to be sorted is not particularly limited, as long as it is 1 or more. For example, 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, or 6 or more cell populations can be sorted. The number of cell populations can be increased or decreased depending on, for example, the number of types of test polypeptides and the number of types of experimental conditions in the expression step.

[0109] Furthermore, in this step, any additional processing can be performed for processing in the reference amount acquisition step, etc. For example, if the reference cell population is cultured in an adherent culture and flow cytometry is used in the reference amount acquisition step, the cell population can be detached from the culture vessel, etc., and suspended in a liquid such as a medium, in this step.

[0110] (3) Reference Amount Acquisition Step S0112 This step is a step of measuring the expression level of the test polypeptide in the sorted cell population and acquiring the reference amount ((3) in Figure 5). This step can be performed simultaneously with or separately from the confirmation step.

[0111] In this step, the expression level of the test polypeptide is measured and obtained as a reference level. The expression level of the test polypeptide broadly includes the amount of transcription product and the amount of translation product, and is not particularly limited. For example, the expression level of the test polypeptide can be measured using the indicators described in the confirmation step. Specifically, for example, the expression level of the test polypeptide can be measured by the expression level of a labeled protein conjugated to the expression of the test polypeptide.

[0112] The indicator for measuring the expression level may be the same as or different from the indicator used in the confirmation step. Preferably, the same indicator is used in the confirmation step and this step.

[0113] The method for measuring the expression level of a test polypeptide is not particularly limited. For example, the methods described in the confirmation step can be used. Specifically, for example, a method for detecting the amount of a biomolecule per cell can be used. Techniques for detecting the amount of a biomolecule per cell include a microscope image analyzer, a plate image analyzer, flow cytometry, image cytometry, and mass cytometry. The biomolecule to be detected is not limited to a polypeptide, and may be a protein or a nucleic acid.

[0114] When flow cytometry is used for the measurement, there are no particular limitations on the light source irradiation method, wavelength adjustment (detection) method (e.g., spectral type, filter method, etc.), the presence or absence of a cell sorting device, and the sorting method, etc. When image cytometry is used for the measurement, examples include analysis using laser scanning cytometry and confocal laser microscopes.

[0115] The expression level of the test polypeptide may be measured for all cells in the cell population sorted in the reference cell sorting step, or may be measured for only a portion of cells that meet specific criteria.

[0116] It is possible to separate the data of some cells from the data of each cell group and exclude them from subsequent analysis (exclusion processing). The criteria for performing exclusion processing are not particularly limited. For example, data derived from dead cells, cell debris, and aggregated cells can be separated and excluded.

[0117] For example, if flow cytometry is used in this step, data near the origin showing low values ​​for both forward scatter (FSC) and side scatter (SSC) can be considered as data on dead cells or cell debris and can be excluded. Alternatively, dead cells can be labeled with any reagent that stains dead cells, and data on dead cells can be excluded based on the labeling.

[0118] Furthermore, for example, when flow cytometry is used in this step, a two-dimensional expanded surface for a combination of SSC-Area (or SSC-Width) and SSC-Height, FSC-Area (or FSC-Width) and FSC-Height, etc. can be used to exclude data on aggregated cells that deviate from the distribution of single cells based on methods commonly used in the art.

[0119] In this step, any additional treatment can be performed as long as it does not interfere with the measurement of the expression level of the test polypeptide. For example, when using a lymphocyte-derived cell type, a treatment to prevent nonspecific binding of antibodies to Fc receptors on the cell surface may be performed. Furthermore, a control treatment (such as application of a negative control reagent) can be performed to control the measurement conditions used in the measurement step. When using an isotype control antibody or the like as a negative control reagent, the binding molecule used, such as an antibody, is not particularly limited as long as it is a binding molecule prepared against an antigen not present in the cell type and cell sample used in this step. For example, a commercially available antibody can be used as an isotype control antibody. When using an isotype control antibody, it is preferable to match one or more of the immune organism species, immunoglobulin subclass, and type (and / or number) of label on the primary antibody with the antibody used in the expression level measurement step.

[0120] The staining conditions for the isotype control antibody are not particularly limited, and are preferably the same as the staining conditions when applying the antibody used in the step of measuring the amount of expression in the measurement process described below.

[0121] (4) Reference Amount Analysis Step S0113 This step is a step of analyzing the reference amount data with respect to the expression amount of the test polypeptide ((4) in FIG. 5).

[0122] Here, "analysis" refers to a process of aggregating and / or organizing the data of the reference amounts to obtain analysis data to be used in the setting step.

[0123] The specific analysis content is not particularly limited as long as the method can aggregate and / or organize the reference amount data in relation to the magnitude of the expression level values. For example, the method may include organizing the reference amount in relation to the expression level values ​​of the test polypeptide in any format, such as a table or graph. In particular, the setting step utilizes information on the expression level of the test polypeptide and the cell count. Therefore, it is preferable that the analysis in this step be performed so that the distribution of cells in relation to the magnitude of the expression level values ​​of the test polypeptide can be analyzed. For example, the data may be sorted according to the magnitude of the expression level values ​​of the test polypeptide, or the relationship between the expression level of the test polypeptide and the cell count may be organized in the form of a graph. When a graph format is used, it may be a histogram in which the expression level of the test polypeptide and the cell count are plotted on the horizontal and vertical axes, or a density plot or contour plot of cells in which data is displayed on two axes using two different parameters.

[0124] For example, the distribution of cells with respect to the expression level of a test polypeptide (e.g., a histogram with the expression level of the test polypeptide on the horizontal axis and the number of cells on the vertical axis, or a two-dimensional dot plot, density plot, or contour plot developed using the expression level of the test polypeptide and another index) can be used to determine the distribution of cells with low expression levels of the test polypeptide (non-expressing cell group) and cells with high expression levels of the test polypeptide (expressing cell group). If the distributions of these groups overlap, a level for distinguishing between the non-expressing cell group and the expressing cell group can be set at the overlapping portion of these groups, or at the boundary between them if they do not overlap. The method for estimating the level position is not particularly limited. An appropriate known estimation method can be selected depending on the degree of overlap between the two groups. For example, any known method for separating a multimodal distribution into a unimodal distribution can be used. For example, a method based on cluster analysis, a method assuming that each unimodal distribution follows a known probability distribution (including a normal distribution, a chi-squared distribution, etc.), a method based on percentiles (e.g., percentile contours, etc.), a known method that can be used with any software, or a combination of these can be used. Furthermore, for example, each cell group can be distinguished using a gate that encompasses either the non-expressing cell group or the expressing cell group, or both groups.

[0125] The position of the level or gate for distinguishing between the non-expressing cell group and the expressing cell group is not particularly limited. Preferably, the level can be set so that the proportion of test polypeptide-expressing cells among the total number of cells contained in the expressing cell group is 40% or more. For example, the level can be set so that the proportion of test polypeptide-expressing cells among the cells contained in the expressing cell group is 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 85% or more, 95% or more, or 99% or more.

[0126] If the exclusion process was not performed or was insufficient in the reference amount acquisition step, the exclusion process can be performed in this step. The specific content of the exclusion process is not particularly limited. For example, the exclusion process can be performed based on the criteria described in the reference amount acquisition step. Furthermore, for example, the exclusion process may be performed based on criteria other than the correspondence between the expression level of the test polypeptide and the number of cells.

[0127] Furthermore, for example, data from cells (e.g., overexpressing cells) whose expression levels of the test polypeptide deviate from the expression level distribution in the expressing cell population can be excluded. The degree of deviation in this case is not particularly limited, but it is preferable not to excessively exclude data from cells expressing the test polypeptide. In this case, for example, data from deviating cells is excluded so that data from 70% or more, 80% or more, 85% or more, 90% or more, 95% or more, or 99% or more of the expressing cells before exclusion is retained. The exclusion method is not particularly limited, and exclusion can be performed based on methods commonly used in the art.

[0128] The analysis can be performed using any software. For example, analytical software such as Excel, programs running on R or Python, or any known software for flow cytometry when flow cytometry is used for the measurement, can be used. Any software normally used in the selected measurement method can be used. Specific examples of flow cytometry software include FCS Express (De Novo Software) and BD FACSDiva. TM (Becton Dickinson), BD Accuri TM (Becton Dickinson), FlowJo TM (Becton Dickinson), Kaluza (Beckman Coulter), NovoExpress (Agilent), Forecyt® (Saltorius), Attune NxT (Thermo Fisher), etc., but are not limited to these. These software can also be used in the confirmation step, reference amount acquisition step, setting step, measurement step, extraction step, etc. Gates can be set using these software when performing data exclusion processing or extraction, which will be described later, but the criteria for setting the gates at that time are not particularly limited.

[0129] (5) Setting Step S0114 This step is a step of setting a reference range for the expression level of the test polypeptide based on the result of the reference level analysis step ((5) in FIG. 5).

[0130] The "reference range" herein refers to the range of expression levels of the test polypeptide used in the extraction step described below, and is set for the expression level of the test polypeptide in this step. The expression level of the test polypeptide can be, for example, the expression level of the labeled protein conjugated to the expression of the test polypeptide described above in the confirmation step.

[0131] The reference range is set within the distribution range of expression level values ​​of the test polypeptide in the expressing cell population based on the data (analysis data) obtained from the reference amount analysis step. The specific range to be set is not particularly limited, and can be set at any position within the above-mentioned distribution range. The expression level values ​​of the test polypeptide included in the reference range are expression level values ​​that can be used to calculate the higher-order structure formation value in the relational equation derivation step described below (for example, a range in which the relationship between the test expression level and the test presentation amount in the measurement step described below follows a predetermined relational equation (including a linear equation or a higher-order equation), a range in which a certain degree of quantitativeness is observed in the measured value (such as the detectable range of the instrument)), etc., and the criteria to be set are not particularly limited. The method for processing the analysis data in this case is not particularly limited, and can be performed, for example, using the various software described above in the reference amount analysis step.

[0132] The method for setting the reference range is not particularly limited. For example, the reference range can be set using a specific value of the expression level of the test polypeptide. The specific value used in this case can be appropriately selected based on experimental findings, the results of the measurement step, etc.

[0133] The number of analytical data used to set the reference range is not particularly limited. For example, it may be one or more. Furthermore, the analytical data may be data on cells, data using non-cellular particles such as labeled particles or other labeling reagents, or a combination thereof. For example, analytical data on a reference cell group prepared under predetermined experimental conditions may be used to set the reference range. Furthermore, for example, data on non-cellular particles such as labeled particles artificially processed to show expression level values ​​equivalent to those obtained when using cell data may be used to set the reference range.

[0134] The criteria for selecting analytical data used to set the reference range are not particularly limited. Any analytical data that meets any criteria based on the experimental conditions or the results of the measurement process can be used, and the specific criteria used here are not particularly limited.

[0135] As a criterion for selecting analytical data, for example, the expression level of the test polypeptide or any index related thereto can be used. The specific index used in this case is not particularly limited. For example, an index reflecting the difference in the expression level value of the test polypeptide between a non-expressing cell group and an expressing cell group, or an index reflecting the gene introduction efficiency of the test polypeptide, such as the proportion of cells expressing the test polypeptide (proportion of expressing cells), can be used as an index. The proportion of expressing cells can be calculated as the ratio of the number of cells in the expressing cell group to the total number of cells in the analytical data.

[0136] The specific method for using the proportion of expressing cells as a criterion is not particularly limited. For example, analytical data in which this proportion is a predetermined proportion can be selected as analytical data to be used for setting a reference range.

[0137] The specific value of the predetermined ratio is not particularly limited and can be appropriately selected depending on conditions such as the type of cell, the indicator used to determine the presence or absence of expression, and the method of gene transfer. For example, the predetermined ratio can be 1% to 90%, 10% to 90%, 15% to 80%, 15% to 60%, 15% to 50%, 20% to 80%, 20% to 60%, 20% to 50%, 25% to 80%, 25% to 60%, 25% to 50%, 25% to 35%, 27% to 33%, etc.

[0138] The method for setting the predetermined ratio is not particularly limited, and may be set based on information such as the general transfer efficiency of the method used for gene transfer and the characteristics of the cell type used, or based on knowledge obtained through actual experiments.

[0139] For example, reference ranges may be set based on multiple predetermined ratios, and the measurement process and subsequent steps may be performed to obtain results based on the respective reference ranges, from which an appropriate result can be selected.

[0140] When a reference range is set using analytical data selected based on a predetermined ratio as a standard, the specific details of the predetermined setting method are not particularly limited. For example, the lower and upper limits of the expression level of the test polypeptide in the expression cell group in the analytical data can be used as the numerical range of the reference range. In addition, for example, percentile display (color-coded display or contour display, etc.) of the density plot of the expression cell group in the analytical data can be used to set the reference range by using the numerical value of the expression level of the test polypeptide corresponding to the contour line (percentile contour line) of a predetermined percentile value.

[0141] Here, percentile contours are, for example, cell density contours that display the proportion (percentile value) of a cell in a cell distribution diagram relative to the whole. In a setting method based on percentile contours, for example, the lower and upper limits of a reference range can be determined using percentile contours of a predetermined value in a unimodal density plot of an expressing cell group as an index. For example, the unimodal distribution of an expressing cell group is displayed using a density plot (percentile contour display) with the expression level of a test polypeptide on the horizontal axis and the presented amount of the test polypeptide on the vertical axis. A percentile contour (first percentile contour) for defining the lower limit of the reference range and a percentile contour (second percentile contour) for defining the upper limit can be selected, with the lowest value of the expression level of the test polypeptide corresponding to the first percentile contour being the lower limit of the reference range, and the highest value of the expression level of the test polypeptide corresponding to the second percentile contour being the upper limit of the reference range. In this case, the percentile values ​​of the first and second percentile contours may be the same or different, and are not particularly limited. The percentile value of the second percentile contour can be lower than the percentile value of the first percentile contour. The percentile value of the first percentile contour can be, for example, the 1st percentile, the 20th percentile, the 40th percentile, the 50th percentile, the 60th percentile, the 70th percentile, the 75th percentile, the 80th percentile, the 80th percentile, the 60th percentile, the 40th percentile, the 30th percentile, the 20th percentile, the 10th percentile, the 5th percentile, the 1st percentile, etc.Combinations of percentile values ​​of the first and second percentile contour lines can be, for example, the 60th percentile and the 20th percentile, the 60th percentile and the 10th percentile, the 60th percentile and the 1st percentile, the 80th percentile and the 20th percentile, the 80th percentile and the 10th percentile, the 80th percentile and the 1st percentile, etc. However, any combination of percentile values ​​can be used depending on the state of density distribution of the cell population (density of the contour lines), the degree of separation between the expressing cell group and the non-expressing cell group, the specific value of the predetermined ratio, etc.

[0142] A reference range can be set for each experimental condition or each experimental run. For example, when there are multiple experimental conditions, such as the type of cells used or the method for detecting the test polypeptide, when the detection sensitivity of the measuring instrument varies from one experimental run to another, or when the detection sensitivity differs between instruments (models), the range of expression level of the test polypeptide set using a predetermined standard and a predetermined method for each experimental condition, each experimental run, or each measuring instrument (model) can be used as a reference range. In this case, the method for setting the reference range is preferably one that is not affected by factors that may cause differences depending on the experimental conditions, the experimental run, or the measuring instrument (model), such as the detection sensitivity of the measuring instrument. Furthermore, for example, when the same experimental conditions are used and there is no or negligible difference in detection sensitivity between experimental runs or between instruments (models), the reference range previously set for that experimental condition can be directly applied to the extraction process in other experimental runs or measurements using a different measuring instrument (model).

[0143] In the extraction step of the method of the present invention, the reference range set in this step as the numerical range of the expression level of the test polypeptide is applied regardless of the numerical distribution of the test expression level in the cell group sorted and measured in the measurement step described below.

[0144] The reference range established in this step may be used to select a cell sample suitable for subsequent measurements or experiments. In this case, for example, the expression step and the reference range establishment step can be used as part of a method for evaluating the quality of a cell sample. In this case, a detection polypeptide is expressed in a plurality of cells in the expression step, a reference range for the expression level of the detection polypeptide is established in the reference range establishment step, and the expression level of the detection polypeptide expressed in the cell sample is measured. If the proportion of cells whose expression level falls within the reference range is within a certain range, the quality of the cell sample is evaluated as good. In this case, the detection polypeptide is not particularly limited as long as it is a detectable protein that reflects the efficiency of gene transfer. For example, a protein containing the above-mentioned labeled protein can be used. Alternatively, for example, instead of directly measuring the abundance of the detection polypeptide as the expression level, the abundance of a nucleic acid encoding the detection polypeptide may be measured. The evaluation method in this method is not particularly limited, and can be performed, for example, in accordance with the exclusion method using the reference range exemplified in the extraction step.

[0145] 1-3-3. Measurement step S0103 The "measurement step" is an essential step in which the test expression level and test presentation level are measured in a cell population sorted for measurement. This step can be performed simultaneously with or after the expression step. This step can also be performed simultaneously with or separately from the reference range setting step.

[0146] When this step is performed simultaneously with the reference range setting step, for example, the test expression level and test presentation level are measured for all cells, and a portion of the cells can be used as a reference for the reference range setting step. Also, for example, when this step is performed separately from the reference range setting step, this step may be performed after the reference range setting step, or the reference range setting step may be performed after this step, or parts of both steps may be performed simultaneously.

[0147] This process includes a step of sorting measurement cells, a step of measuring expression levels, and a step of measuring presentation levels.

[0148] First, an overview of this step will be explained with reference to Figure 6A. In this step, a plurality of cells are first sorted into a cell population for measurement ((1) in Figure 6A). Then, the expression level of the test polypeptide in the cell population for measurement is measured, and the expression level data is obtained as the "test expression level" ((2) in Figure 6A). At the same time, the amount of the test polypeptide present on the cell membrane is measured, and the amount data is obtained as the "test presentation amount" ((3) in Figure 6A). The test expression level and presentation amount data obtained in this step are used in the extraction step using the reference range set in the reference range setting step. Each step is explained below.

[0149] (1) Measurement Cell Sorting Step S0115 This step is a step of sorting a plurality of cells as a cell group for measurement ((1) in FIG. 6A).

[0150] The basic content of this step is similar to that of the reference cell sorting step in the reference range setting step, so only the differences from the reference cell sorting step will be described here.

[0151] The method and criteria for sorting the cell population for measurement are not particularly limited. Depending on the purpose, only cells that meet specific criteria can be sorted. In this case, the criteria are not particularly limited.

[0152] The culture conditions and gene transfer conditions for the reference cell group and the measurement cell group are preferably the same. For example, the reference cell group and the measurement cell group are composed of cells with the same properties, such as cells of the same type that have been gene transferred under the same conditions and cultured under the same culture conditions. For example, cell groups sorted from the same culture vessel can be used as the reference cell group and the measurement cell group.

[0153] The number of cells to be sorted is not particularly limited. For example, 500 cells or more, 800 cells or more, 1,000 cells or more, 1,500 cells or more, 2,000 cells or more, 3,000 cells or more, 5,000 cells or more, 7,000 cells or more, 10,000 cells or more, 15,000 cells or more, 20,000 cells or more, 25,000 cells or more, 30,000 cells or more, or 50,000 cells or more can be sorted. For example, if the cell line or cell type used is morphologically uniform, 500 cells or more can be sorted. Furthermore, if it is desired to reduce variability in measurement values, 30,000 cells or more can be sorted. Multiple cell populations may also be sorted. In this case, the number of cell populations is not particularly limited.

[0154] (2) Expression level measurement step S0116 This step is a step of measuring the expression level of a test polypeptide in a cell population for measurement and obtaining the test expression level ((2) in FIG. 6A). This step can be performed simultaneously with or after the measurement cell sorting step.

[0155] The content of this step is similar to that of the reference amount acquisition step in the reference range setting process. Therefore, detailed explanations will be omitted here. Unlike the reference amount acquisition step, in this step, the expression level of the test polypeptide is acquired and referred to as the "test expression level." This step is preferably performed using the same method and measuring equipment as the reference amount acquisition step.

[0156] (3) Presentation Amount Measurement Step S0117 This step is a step of measuring the amount of test polypeptide present on the cell membrane in the cell population for measurement and obtaining the test presentation amount ((3) in Figure 6A). This step can be performed simultaneously with or after the measurement cell sorting step. This step can be performed simultaneously with or separately from the expression amount measurement step.

[0157] This step may be performed on all cells measured in the expression level measurement step, or on a portion of the cells. For example, measurement in this step can be performed only when the test expression level measured in the expression level measurement step meets a certain level. In this case, the level is not particularly limited. For example, the determination may be made based on whether the test expression level is within a reference range.

[0158] This step can be performed in the same manner as the expression level measurement step, but in this step, the amount of the test polypeptide present on the cell membrane is quantitatively measured and obtained as a "test presentation amount." Therefore, the measurement method and indicator used are those that can detect the intracellular localization of the polypeptide to an extent that allows determination of whether it is present on the cell membrane.

[0159] The indicator is not particularly limited as long as it can distinguish between polypeptides present on the cell membrane and those present in the cytoplasm. For example, the indicator can be the amount of label on a binding molecule that detects a cell surface antigen, the amount of label on a binding molecule that distinguishes between a test polypeptide present on the cell membrane, the amount of activity (enzyme activity, etc.) of a test polypeptide on the cell membrane, the amount of a test polypeptide in a cell membrane fraction, or the amount of label bound to a target polypeptide that can distinguish between its association with the test polypeptide.

[0160] When a binding molecule is used, the specific binding target is not particularly limited as long as the amount of the binding molecule reflects the amount of the test polypeptide on the cell membrane. Examples include, but are not limited to, a part of the test polypeptide, a part of a multimer, a part of the target polypeptide, etc. For example, a binding molecule that can bind to a part of the test polypeptide (such as the extracellular domain) can be preferably used.

[0161] The label used is not particularly limited. For example, the label described above in relation to the confirmation step can be used. The label detected in this step is preferably a label that can be detected separately from the label detected in the expression level measurement step, for example, a label different from the label detected in the expression level measurement step.

[0162] The detection method may be appropriately selected depending on the label used. For example, any of the methods described in the reference range setting step may be used. Preferably, this step is performed using the same detection method and measuring device as the expression level measurement step.

[0163] For each reference range setting step, one or more of this step, the extraction step, the relational expression deriving step, and the multimer formation value obtaining step may be performed two or more times. In this case, the test polypeptide and / or target polypeptide to be measured may be different each time, or may be the same for multiple times. When this step is performed repeatedly, it is preferable that the gene introduction method and conditions, and expression step conditions are the same for the samples used in the reference range setting step and the repeated this step. When repeated, one or more of this step, the extraction step, and the relational expression deriving step may also be performed on a cell population that has been treated in the same way as the cells measured in the reference amount obtaining step (e.g., treated with an isotype control antibody).

[0164] 1-3-4. Extraction Step S0104 The "extraction step" is a step of extracting information on the test expression level and the test presentation level for cells whose test expression level is within the reference range. This step can be performed simultaneously with or after the measurement step. In this specification, "extraction" refers to the operation of separating a portion of the data and subjecting it to subsequent analysis.

[0165] For example, this step can be performed simultaneously with the measurement step by setting a detection range according to the reference range on the measurement device.

[0166] The extraction method is not particularly limited. For example, information on the test expression level and the test presentation level may be extracted for all cells whose test expression level is within the reference range, or data on only a portion of those cells may be extracted.

[0167] For example, cells from which data are extracted can be determined according to additional arbitrary criteria. The criteria used in this case are not particularly limited. For example, the criteria described for the reference amount acquisition step and the reference amount analysis step can be used. For example, data from cells whose test expression level and / or test display level are dissociated from the distribution area of ​​the expressing cell group can be excluded. When the measurement step is performed repeatedly, it is preferable to use a common criterion for determining cells to be extracted in this step.

[0168] For example, when the relational expression is derived based on the values ​​for each section obtained by dividing the reference range in the relational expression deriving step as described below, cell samples containing a certain number of cells or less in each section can be excluded from the extraction step. The number of cells is not particularly limited, but for example, a cell sample can be excluded when the number of cells contained in each section is less than the number of cells described below.

[0169] When the relational expression is derived based on the values ​​for each compartment obtained by dividing the reference range as described below in the relational expression derivation step, cell samples in which the ratio of the number of cells contained in each compartment does not satisfy certain conditions may be excluded from the extraction step. Specific conditions are not particularly limited. For example, data from cell samples in which cells are distributed so that the number of cells contained in compartments with relatively low test expression levels (low expression compartments) tends to be significantly higher than in compartments with relatively high test expression levels (high expression compartments), or data from cell samples in which cells are distributed so that the number of cells contained in compartments with relatively high test expression levels (high expression compartments) tends to be significantly higher than in compartments with relatively low test expression levels (low expression compartments), can be excluded from the extraction step. The specific value of the ratio is not particularly limited. For example, cell samples in which the number of cells in the low expression compartment is significantly higher than the number of cells in the high expression compartment (e.g., the ratio of the number of cells in the two compartments (low expression compartment / high expression compartment) is greater than 2-fold, greater than 4-fold, greater than 8-fold, greater than 20-fold, greater than 40-fold, etc.) can be excluded. Furthermore, for example, cell samples in which the number of cells in the low-expression compartment is significantly lower than the number of cells in the high-expression compartment (the ratio of the cell numbers in the two compartments (low-expression compartment / high-expression compartment) is 0.3 times or less, 0.4 times or less, 0.5 times or less, 0.6 times or less, 0.9 times or less, etc.) can be excluded. For example, when the reference range is divided into three or more compartments, conditions based on the ratio of the cell numbers in each compartment can be set for all or some combinations of two compartments.

[0170] 1-3-5. Relational Expression Deriving Step S0105 The "relational expression deriving step" is a step of deriving a relational expression between the test expression amount and the test presentation amount from the extracted information. This step can be performed simultaneously with or after the extraction step.

[0171] The type of relational expression is not particularly limited as long as it reflects the relationship between test expression amount and test presentation amount.For example, the relational expression is a relational expression in which test expression amount is one of explanatory variables, and test presentation amount is a target variable.In addition, the relational expression in which the explanatory variable and the target variable are reversed can also be used.

[0172] For example, the degree of the relational expression is not particularly limited. For example, it may be a linear expression, a quadratic expression, a cubic expression, or an expression of a higher degree. Alternatively, it may be an expression of a degree of one or less, including radical roots, or a fractional expression of a negative degree.

[0173] The relational expression may also be formed by a combination of functional expressions, such as a linear function, a quadratic function, a cubic function, a quartic function, a trigonometric function, an exponential function, a logarithmic function, or a combination thereof.

[0174] Preferably, the relational expression is a functional expression, ie, there is at most one value of the response variable corresponding to each value of the explanatory variable.

[0175] The relational expression can be, for example, a known mathematical expression that is widely used. Examples of such mathematical expressions include linear functions, Michaelis-Menten equation, Hill equation, logistic equation, sigmoid function expressions such as hyperbolic tangent function, Gompertz function, arctangent function, and Gudermann function, as well as saturation curve expressions. For example, a linear expression can be used as a suitable relational expression.

[0176] In addition, the relational expression can be expressed by a different formula for each of a plurality of domains within the reference range. For example, in the domain where the test expression level is low, the test expression level is expressed by a formula that monotonically increases, and in the domain where the test expression level is a certain value or more, the test expression level is expressed by a formula that asymptotically approaches a certain value.

[0177] The derivation method is not particularly limited as long as it can derive a relational equation that reflects the relationship between the test expression level and the test presentation level.For example, any method commonly used in simple regression analysis can be used.Specifically, the least squares method, maximum likelihood method, fuzzy robust regression, etc. can be used.

[0178] For example, the derivation method may be such that the type of relational equation is first determined and then its coefficients and constant terms, etc. are confirmed, or the derivation method may be such that the type of relational equation can change depending on the specific data for the test expression amount and the test presentation amount.

[0179] The derivation may be performed by handling all the extracted information at once, or by separating and handling each portion of the information. For example, the reference range is divided into multiple sections for the expression level of the test polypeptide, and the test expression level and test presentation level separated in each section are quantified, and the relationship equation can be derived based on these numerical values. Specifically, for example, the average (or median) of the test expression level and the average (or median) of the test presentation level in each section are calculated, and the calculated values ​​are subjected to regression analysis, thereby easily deriving the relationship equation. The regression analysis can be performed based on data including values ​​where the test expression level and the test presentation level are both 0, in addition to the calculated values.

[0180] In this case, the number of compartments is not particularly limited. For example, separation into two or more, three or more, or four or more compartments is possible. Furthermore, the separation method is not particularly limited. For example, separation may be performed using gates that divide the expression level of the test polypeptide equally, or may be performed using gates that divide the expression level of the test polypeptide unevenly.

[0181] The number of cells contained in each compartment is not particularly limited. For example, each compartment can contain 50 or more cells, 100 or more cells, 500 or more cells, 1,000 or more cells, 2,000 or more cells, 5,000 or more cells, 7,000 or more cells, or 10,000 or more cells. For example, if the cell line or cell type used is morphologically uniform, each compartment can contain 50 or more cells. Furthermore, if it is desired to minimize the variation in the mean (or median) of each compartment, each compartment can contain 10,000 or more cells.

[0182] When the reference range is divided into multiple compartments, all or some of the compartments can be used to derive the relational equation. When some compartments are used to derive the relational equation, the number of compartments to be used can be determined by any method. For example, the selection of compartments to be used can be based on a criterion regarding the number of cells contained in each compartment or a criterion regarding the relationship between the number of cells contained in each compartment. Alternatively, multiple relational equations using combinations of two or more compartments can be derived, and one of these relational equations can be used to calculate the multimer formation value according to a certain criterion. For example, a relational equation can be derived using each of all possible combinations of two or more compartments, and one of these relational equations can be used to calculate the multimer formation value. The criterion in this case is not particularly limited, and for example, the relational equation that results in the largest multimer formation value can be selected from the multiple derived relational equations. When deriving relational equations for combinations of multiple compartments, it is preferable that the derivation methods for each are the same.

[0183] When the measurement step is carried out repeatedly, it is preferable to use the same type of relational expression, the same method of derivation, etc. in this step.

[0184] 1-3-6. Multimer formation value acquisition step S0106 The "multimer formation value acquisition step" is a step of acquiring a multimer formation value from the relational expression. This step can be performed simultaneously with or after the relational expression derivation step.

[0185] The method for obtaining the multimer formation value is based on a relational formula, and is not particularly limited as long as it is possible to obtain a value that correlates with the ease with which the test polypeptide translocates onto the cell membrane.

[0186] For example, the multimer formation value can be calculated based on the derivative of the relational expression. When the relational expression is a polynomial, the multimer formation value can be calculated, for example, based on the coefficients of one or more terms. In this case, the coefficient is preferably the coefficient of a term that uses the test expression level as a variable. When there are multiple terms that use the test expression level as a variable, the coefficient of any one or more of these terms can be used. For example, when the relational expression is a linear expression that uses the test expression level as a variable, the coefficient of the test expression level can be used as the multimer formation value.

[0187] Any arithmetic operation can be performed when calculating the multimer formation value from the coefficients. The arithmetic operation in this case is not particularly limited, but examples include arithmetic operations on the coefficients, exponentiation, radical roots, and combinations thereof.

[0188] For example, if measurements are also performed on cell populations that have been subjected to control treatments (such as treatments performed on the cells measured in the reference amount acquisition step) in the measurement step, the results of comparison with the multimer formation values ​​obtained from those cell populations can be used as the multimer formation value. The comparison method in this case is not particularly limited. Examples include taking the difference or quotient. In this case, it is preferable that the multimer formation values ​​to be compared are calculated using a common method.

[0189] Preferably, the multimerization value correlates with one or more known indices of multimerization ability. Known indices of multimerization ability include, for example, IC 50 Value, EC 50 value, dissociation constant (K D In this case, the degree of correlation is not particularly limited. Specifically, for example, the correlation coefficient may be 0.2 or more, 0.3 or more, 0.4 or more, 0.5 or more, 0.6 or more, 0.7 or more, or 0.8 or more, or the correlation may be significant.

[0190] The method of the present invention can be performed multiple times using different combinations of test polypeptides and target polypeptides. In this case, the combination of test polypeptides and target polypeptides is not particularly limited. For example, when the method of the present invention is performed multiple times under multiple conditions, one or more combinations of test polypeptides and target polypeptides can be common between the conditions.

[0191] 1-4. Effect According to the method of this embodiment, an index reflecting the strength of interaction between multimer subunits (multimer formation value) can be easily obtained with the same amount of effort as performing cell expression analysis by flow cytometry or the like. Furthermore, the multimer formation value can be calculated without performing measurements under multiple conditions, such as repeatedly measuring multiple cell samples with different cell numbers or gene introduction amounts. The multimer formation value calculated by the method of this embodiment provides equivalent values ​​even when different detection instruments (models) are used, and can be compared between instruments (models) and facilities.

[0192] 2. Method for measuring the binding affinity of a test ligand 2-1. Overview A second aspect of the present invention is a method for measuring the binding affinity of a test ligand to a multimeric receptor. The method of this aspect essentially comprises a control value measurement step, a test value measurement step, and a calculation step.

[0193] 2-2. Steps 2-2-1. Control Value Measurement Step The "control value measurement step" is an essential step in which the multimer formation value is measured according to the method described in the first embodiment and obtained as a control value.

[0194] The basic content of this step is the same as that of the first embodiment, so only the differences from the first embodiment will be described here.

[0195] In this step, a fusion protein of a subunit of a multimeric receptor and a control ligand is used as the test polypeptide, and another subunit of the multimeric receptor is used as the target polypeptide, and the multimer formation value is measured as the control value.

[0196] Each polypeptide is described below.

[0197] The basic structure of the test polypeptide is similar to that of the test polypeptide described in the first embodiment. The subunit contained in the test polypeptide may or may not be a membrane protein. Preferably, it is a membrane protein such as a cell membrane protein. Examples of such membrane proteins include subunits of MHC.

[0198] The composition of the control ligand is not particularly limited, but it is typically a polypeptide. When it is a polypeptide, its sequence is not particularly limited. Examples of amino acid sequences that can be used include sequences containing uncharged polar amino acids with low polarity side chains (Asn, Gln, Ser, Thr) and sequences containing neutral amino acids (Gly, Ile, Val, Leu, Ala, Pro). The proportion of these amino acids in the amino acid sequence of the control ligand is not particularly limited, but can be, for example, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more, or 100%. Specific amino acid sequences include polyglycine, a mixed sequence of serine and glycine, a mixed sequence of alanine and glycine, etc.

[0199] The size of the control ligand is not particularly limited, but it is preferably the same size as the test ligand. For example, the number of amino acids in the control ligand may differ from the number of amino acids in the test ligand by 15 or less, 10 or less, 6 or less, 5 or less, 4 or less, 2 or less, or 1, or the control ligand may be composed of the same number of amino acids as the test ligand. Furthermore, for example, when multiple polypeptides are used as test ligands, the control ligand may be composed of the same number of amino acids as the average (or median) number of amino acids of the polypeptides, or may be composed of the same number of amino acids as the average (or median) number of amino acids of the known polypeptides, or may be composed of the same number of amino acids as the average (or median) number of amino acids as ... Furthermore, for example, when the target receptor is MHC class II, the length of the control ligand can be, for example, 8 to 40 amino acids, 8 to 33 amino acids, 8 to 30 amino acids, 8 to 25 amino acids, 8 to 24 amino acids, 8 to 20 amino acids, 8 to 18 amino acids, 8 to 17 amino acids, 8 to 16 amino acids, 9 to 15 amino acids, 11 to 15 amino acids, or 15 amino acids. For example, when the target receptor is MHC class II, a polyglycine or a mixed sequence of serine and glycine with the above-mentioned number of amino acids can be used as the control ligand, specifically, for example, a polyglycine consisting of 9 amino acids (SEQ ID NO: 1), a polyglycine consisting of 12 amino acids (SEQ ID NO: 2), a polyglycine consisting of 15 amino acids (SEQ ID NO: 3), or a mixed sequence of serine and glycine consisting of 12 amino acids (SEQ ID NO: 4).

[0200] Alternatively, a control ligand may be, for example, a ligand with low binding, low functionality, or low activity for the target receptor. For example, when the receptor is an MHC, a peptide derived from any endogenous protein (e.g., when the target receptor is an MHC class II receptor, a peptide derived from the invariant chain (CD74)) can be used as the control ligand.

[0201] In the fusion protein, the control ligand and the subunit may be linked directly or via a linker, preferably via a linker.

[0202] The type of linker used is not particularly limited, and any known linker can be used. For example, linkers that are cleavable in intracellular and / or extracellular environments, linkers that are not cleavable in these environments, and combinations thereof can be used. The linker used herein may be a chemical linker (e.g., a disulfide linker, a maleimide linker, etc.) or a peptide linker, but a peptide linker is preferred. Specifically, peptide linkers consisting of, for example, 1 to 50, 5 to 40, 5 to 30, 5 to 25, or preferably 10 to 20 amino acid residues, such as a GS linker or a GGS linker consisting of glycine and serine, can be used. A GS linker contains one or more, for example, 2 to 8 or 3 to 6, amino acid residues represented by GGGGS. On the other hand, a GGS linker contains one or more, for example, 2 to 6 or 2 to 4 GGS residues. The linker may contain amino acid residues other than glycine and serine. When a cleavable linker is used, its type is not particularly limited. For example, any linker known to be cleavable may be used, or the linker moiety may be designed to be cleavable by combining a protease cleavage site such as LVGRPS (SEQ ID NO: 5) and / or IEGR (SEQ ID NO: 6) with any known linker.

[0203] The fusion protein can be encoded by a fusion gene in which a gene encoding a control ligand and a gene encoding a subunit contained in a test polypeptide are fused together. The specific structure of the fusion protein is not particularly limited.

[0204] The target polypeptide used in this step contains subunits that constitute a multimeric receptor together with the subunits contained in the test polypeptide. Other configurations of the target polypeptide are as described in the first embodiment.

[0205] When the method of this embodiment is performed multiple times to calculate ligand binding values ​​for multiple types of ligands for the same multimeric receptor, the control ligand and linker used for each calculation may be different each time, or the same for multiple calculations. Preferably, the same control ligand and linker are used.

[0206] The "test value measurement step" is an essential step in which the multimer formation level is measured according to the method described in the first aspect and obtained as a test value. This step can be performed simultaneously with or separately from the control value measurement step.

[0207] In this step, a fusion protein of a subunit of a multimeric receptor and a test ligand is used as the test polypeptide, and another subunit of the multimeric receptor is used as the target polypeptide, and the multimer formation value is measured as the test value.

[0208] This step can be performed in the same manner as the control value measurement step, except that the test polypeptide used is a fusion protein containing a test ligand as a ligand. This step is preferably performed under the same conditions as the control value measurement step (including the subunits contained in the test polypeptide and the target polypeptide, the type of cell, etc.), except for the ligand used.

[0209] The test ligand is a ligand whose binding ability to a multimeric receptor is measured by the method of this embodiment. Therefore, the type of test ligand is not particularly limited and can be selected appropriately depending on the purpose. The test ligand may be a molecule known to bind to a multimeric receptor, or a molecule whose binding to a multimeric receptor is unknown. For example, a peptide ligand may be used.

[0210] The "calculation step" is an essential step in which the ligand binding value of the test ligand is calculated based on the obtained control value and test value. This step can be performed simultaneously with or separately from the test value measurement step.

[0211] The ligand binding value is a numerical value indicating the binding ability of the test ligand to the multimeric receptor. The specific method for calculating the ligand binding value is not particularly limited as long as it is based on the test value and the control value. For example, the ligand binding value can be calculated by performing any arithmetic operation on the test value and the control value, similar to the multimer formation value obtaining step.

[0212] For example, the ligand binding value may be a value based on the ratio of the test value to the control value or a value based on the difference between the test value and the control value. Further calculations may be performed as necessary.

[0213] 2-3. Effect According to the method of this embodiment, an index (ligand binding value) relating to the binding ability between a multimeric receptor and a ligand can be calculated with high accuracy in a manner that is highly compatible between measuring devices (models) and facilities.

[0214] For example, a value based on the ratio of a test value to a control value can provide an index of binding ability as a ratio that is less susceptible to the influence of variation in the measured values, even when such variation is likely to occur.Furthermore, for example, a value based on the difference between a test value and a control value can provide an index of binding ability that clearly distinguishes the difference, even when the amount of change in cell membrane migration associated with binding ability is small.

[0215] 3. Method for measuring three-dimensional structure forming ability, etc. 3-1. Overview A third aspect of the present invention is a method for measuring three-dimensional structure forming ability, etc. When implemented as a method for measuring three-dimensional structure forming ability, the method of this aspect includes, as essential steps, an expression step, a reference range setting step, a measurement step, an extraction step, a relational formula deriving step, and a three-dimensional structure forming value obtaining step. Furthermore, when implemented as a method for measuring the ability to maintain cell membrane localization, the method of this aspect includes, as essential steps, an expression step, a reference range setting step, a measurement step, an extraction step, a relational formula deriving step, and a cell membrane localization value obtaining step. According to the method of this aspect, the three-dimensional structure forming ability and the ability to maintain cell membrane localization of a test polypeptide in a cell can be measured.

[0216] 3-2. Steps 3-2-1. Expression Step The "expression step" is an essential step in which a test polypeptide is expressed in multiple cells. This step is essential in both the method for measuring the ability to form a three-dimensional structure and the method for measuring the ability to maintain cell membrane localization.

[0217] The basic content of this step is similar to that of the expression step of the first embodiment, so only the differences from the first embodiment will be described here.

[0218] In this step, the test polypeptide is expressed in a plurality of cells, where the test polypeptide can be transiently expressed as a cell membrane protein in the cells.

[0219] The test polypeptide in this embodiment is a polypeptide whose ability to form a three-dimensional structure or maintain its localization at the cell membrane is measured by the method of this embodiment.

[0220] The type of test polypeptide is not particularly limited. It may be a polypeptide that can associate with other polypeptides expressed in the cells used, but it is preferable that the test polypeptide does not associate with other cell membrane proteins expressed in the cells used, or that the amount present on the cell membrane does not change from a constant value due to association with other cell membrane proteins.

[0221] The test polypeptide presentation amount in the method of this embodiment varies depending on the structural stability and cell membrane localization of the test polypeptide. Therefore, typically, cells express the test polypeptide in such a manner that translocation to the cell membrane occurs as a result of the formation of a three-dimensional structure of the test polypeptide. For example, if the test polypeptide is a cell membrane protein, the test polypeptide can be expressed as a cell membrane protein by expressing it as is. Alternatively, if the test polypeptide is a membrane protein other than a cell membrane protein, it can be expressed as a cell membrane protein, for example, by substituting a localization signal sequence for another organelle with an endoplasmic reticulum localization signal sequence. Alternatively, if the test polypeptide is not a membrane protein, it can be expressed as a cell membrane protein by, for example, expressing the test polypeptide as a fusion protein with a cell membrane protein or a portion thereof, as described in the first embodiment. In this case, when measuring the three-dimensional structure formation ability using the method of this embodiment, since the three-dimensional structure formation ability is detected as the amount of translocation to the cell membrane, it is preferable that the cell membrane protein obtained by modifying the test polypeptide is configured so that the formation of a three-dimensional structure of the test polypeptide is essential for its translocation to the cell membrane. On the other hand, when measuring the ability to maintain cell membrane localization using the method of this embodiment, the likelihood of the test polypeptide being maintained on the cell membrane after translocation of the test polypeptide onto the cell membrane is measured. Therefore, it is preferable that a sufficient amount of the test polypeptide is configured to be capable of translocation to the membrane. For example, the test polypeptide can be configured to consist of the full-length sequence of the protein to be measured, have an endoplasmic reticulum targeting signal sequence, and be capable of sufficient expression, e.g., overexpression.

[0222] When measuring the ability of a multimer to maintain its cell membrane localization using the method of this embodiment, a target polypeptide that can be expressed as a cell membrane protein can be expressed in the plurality of cells in this step. In this case, the content of the target polypeptide and its handling in the subsequent steps are as described in the first embodiment.

[0223] 3-2-2. Reference Range Setting Step The "reference range setting step" is an essential step in which a reference amount obtained from a cell population sorted for reference is analyzed to set a reference range for the expression level of a test polypeptide. This step is essential in both the method for measuring the ability to form a three-dimensional structure and the method for measuring the ability to maintain cell membrane localization. This step can be performed simultaneously with or after the expression step.

[0224] This process includes a confirmation step, a reference cell sorting step, a reference amount acquisition step, a reference amount analysis step, and a setting step.

[0225] The content of this step is similar to the description of the reference range setting step of the first embodiment, and therefore a detailed description thereof will be omitted here.

[0226] 3-2-3. Measurement step The "measurement step" is an essential step in which the test expression level and test presentation level of the test polypeptide are measured in a cell population sorted for measurement. This step is essential in both the method for measuring the ability to form a three-dimensional structure and the method for measuring the ability to maintain cell membrane localization. This step can be performed simultaneously with or separately from the reference range setting step.

[0227] This step includes a step of sorting measurement cells, a step of measuring expression levels, and a step of measuring presentation levels. The content of this step is similar to the description of the measurement step of the first aspect, so detailed description here will be omitted.

[0228] 3-2-4. Extraction step The "extraction step" is an essential step in which information on the test expression level and test presentation level is extracted for cells whose test expression level is within the reference range. This step is essential in both the method for measuring the ability to form a three-dimensional structure and the method for measuring the ability to maintain cell membrane localization. This step can be performed simultaneously with or after the measurement step.

[0229] The content of this step is similar to that of the extraction step of the first embodiment, and therefore, a detailed description thereof will be omitted here.

[0230] 3-2-5. Relational Equation Deriving Step The "relational equation deriving step" is an essential step in which a relational equation between the test expression level and the test presentation level is derived from the extracted information. This step is essential in both the method for measuring the ability to form a three-dimensional structure and the method for measuring the ability to maintain cell membrane localization. This step can be performed simultaneously with or after the extraction step.

[0231] The content of this step is similar to the description of the relational equation deriving step of the first embodiment, and therefore, a detailed description thereof will be omitted here.

[0232] 3-2-6. Step of Obtaining a Three-Dimensional Structure Formation Value The "step of obtaining a three-dimensional structure formation value" is an essential step in the method for measuring three-dimensional structure formation ability, and is a step of obtaining a three-dimensional structure formation value from a relational equation. In the method for measuring the ability to maintain cell membrane localization, a step of obtaining a cell membrane localization value is performed as an essential step instead of this step. The "step of obtaining a cell membrane localization value" is a step of obtaining a cell membrane localization value from a relational equation. This step can be performed simultaneously with or after the step of deriving the relational equation.

[0233] The basic content of this step is similar to that of the step of obtaining a multimer formation value in the first embodiment. Therefore, detailed explanations will be omitted here. In the method for measuring the ability to form a three-dimensional structure, a value is obtained as a three-dimensional structure formation value rather than a multimer formation value, and in the method for measuring the ability to maintain cell membrane localization, a value is obtained as a cell membrane localization value rather than a multimer formation value.

[0234] 3-3. Effect According to the method of this embodiment, an index reflecting the ease of formation of a three-dimensional structure (three-dimensional structure formation value or cell membrane localization value) can be easily obtained with the same amount of effort as performing expression analysis of cells by flow cytometry or the like.

[0235] Furthermore, it is possible to calculate the three-dimensional structure formation value and the cell membrane localization value without performing measurements under multiple conditions, such as by repeatedly measuring multiple cell samples with different cell numbers or gene introduction amounts. The three-dimensional structure formation value and the cell membrane localization value calculated by the method of this embodiment are equivalent even when different detection instruments (models) are used, and can be compared between instruments (models).

[0236] When the method of this embodiment is applied to a polypeptide that forms a homomultimer, the ability to form a three-dimensional structure and the ability to form a homomultimer can be examined simultaneously. Furthermore, when the method of this embodiment is applied to a fusion protein of a monomeric receptor subunit and a test ligand, it can be used to calculate an index (ligand binding value) relating to the ligand binding ability of the monomeric receptor and the ligand. The processing performed in this case is similar to that described in the second embodiment.

[0237] 4. Method for Measuring Changes in Higher-Order Structure Formation Ability, etc. 4-1. Overview A fourth aspect of the present invention is a method for measuring changes in higher-order structure formation ability, etc., due to target conditions. The method of this aspect includes, as essential steps, a control value measurement step, a treatment value measurement step, and a calculation step. By using the method of this aspect, it is possible to measure changes in multimer formation ability, three-dimensional structure formation ability, and / or cell membrane localization maintenance ability due to target conditions.

[0238] 4-2. Steps 4-2-1. Control Value Measurement Step The "control value measurement step" is an essential step in which the higher-order structure-forming ability (multimer formation value, tertiary structure formation value) and the ability to maintain cell membrane localization (cell membrane localization value) are measured under control conditions according to the method described in the first or third aspect, and the results are obtained as control values.

[0239] The basic content of this step is similar to that of the first and third embodiments, so only the differences from the first and third embodiments will be described here.

[0240] The control conditions are conditions under which the influence of the test polypeptide on the formation of higher-order structures (multimer formation and / or three-dimensional structure formation) and on the ability to maintain its localization at the cell membrane is measured as a control value.

[0241] The specific content of the control conditions is not particularly limited, as long as they are conditions that allow the influence of the target conditions described below to be determined. Preferably, the control conditions share many conditions with the target conditions, and differ only in the target conditions for which the influence is measured using the method of this embodiment. For example, when the influence of the medium composition is measured as a fluctuation in a value using the method of this embodiment, it is preferable that other conditions (e.g., cell density, etc.) are common. As will be clear to those skilled in the art, differences in conditions other than the target conditions are acceptable to the extent that they do not affect the measurement results.

[0242] The "treatment value measurement step" is an essential step in which a multimer formation value, a three-dimensional structure formation value, or a cell membrane localization value is measured under target conditions according to the method described in the first or third aspect, and is obtained as a treatment value. This step can be performed simultaneously with or separately from the control value measurement step.

[0243] In this embodiment, the target condition is a condition for which the influence on the formation of a higher-order structure (multimer formation and / or three-dimensional structure) of a test polypeptide or the maintenance of its localization at the cell membrane is measured as a variation. The target condition may be any condition that can affect the formation of a higher-order structure or the maintenance of its localization at the cell membrane of a test polypeptide, and the specific type of the target condition is not particularly limited. Examples of the target condition include exposure to a substance and exposure to the environment.

[0244] When the effect of exposure to a substance is measured in this embodiment, the type of substance used is not particularly limited. Examples include medium additives, drugs, ligands, etc. In this case, the substance may be a biological substance, an artificially synthesized compound, a low molecular weight substance, or a high molecular weight substance. When the effect of exposure to a substance is measured, the parameter of interest is not particularly limited. For example, such parameters include the type of substance, its concentration, and the timing of its addition. For example, when the substance is a drug, the effect of the type of drug to which the cells are exposed can be measured as a variation value, and when the substance is a ligand, the effect of the type of ligand to which the cells are exposed can be measured as a variation value.

[0245] When the effect of exposure to an environment is measured in this embodiment, the type of environment used is not particularly limited. Examples include the composition of the atmosphere (e.g., the gas aerated into the culture medium), the composition of the culture medium, cell density, pH, etc. When the effect of exposure to an environment is measured, the parameter of interest is not particularly limited. For example, such parameters include the type and concentration of components, the timing of exposure, etc. For example, when the environment is the composition of the atmosphere, the effect of the type of components contained in the atmosphere to which the cells are exposed can be measured as a variation.

[0246] The specific conditions are not particularly limited and can be appropriately set depending on the type of condition, and may be, for example, conditions known to affect the formation of higher-order structures or the maintenance of cell membrane localization, or conditions unknown to have such effects.

[0247] 4-2-3. Calculation step The "calculation step" is an essential step in which a variation value is calculated based on the obtained control value and treatment value. This step can be performed simultaneously with or separately from the treatment value measurement step.

[0248] Specifically, when the control and treatment values ​​are measured by the method described in the first aspect, the influence of the target conditions on multimer formation is calculated as a variation value in this step, whereas when the control and treatment values ​​are measured by the method described in the third aspect, the influence of the target conditions on the formation of a three-dimensional structure or the maintenance of cell membrane localization is calculated as a variation value in this step.

[0249] The "variation value" refers to a numerical value that indicates the degree of influence that the difference between the control conditions and the target conditions has on the formation of higher-order structures and the maintenance of cell membrane localization.

[0250] The basic content of this step is similar to the calculation step of the second embodiment, so only the differences from the second embodiment will be described here.

[0251] The control value and the treatment value are used in the calculation in this step, and therefore this step can be carried out by replacing the test value in the calculation step of the second embodiment with the treatment value.

[0252] The method for calculating the variation value (for example, a relational expression) can be changed depending on the type of target condition and the purpose of performing the method of this embodiment.

[0253] 4-3. Effects According to the method of this embodiment, the variation of the ability to form higher-order structures or maintain cell membrane localization due to the influence of exposure to substances or the environment can be calculated in a manner that is highly compatible between instruments (models) and facilities. For example, by obtaining a value based on the ratio of the treatment value to the control value as the variation, even when the individual measurements are prone to variability, it is possible to obtain an index showing the variation of the ability to form higher-order structures or maintain cell membrane localization under the target conditions as a ratio that is less susceptible to such variability. Furthermore, for example, by using a value based on the difference between the treatment value and the control value, it is possible to obtain an index that clearly distinguishes the difference even when the amount of change in the variation due to the target conditions is small. Furthermore, by applying the method of this embodiment using a fusion protein of a receptor subunit and a test ligand as the test polypeptide, it is possible to calculate the variation of the influence of exposure to substances or the environment on the formation of higher-order structures or the maintenance of cell membrane localization due to the interaction between the receptor and the ligand.

[0254] 5. Method for screening conditions for higher-order structure formation, etc. 5-1. Overview A fifth aspect of the present invention is a method for screening conditions for higher-order structure formation, etc. The method of this aspect includes, as essential steps, a control value measurement step, a candidate value measurement step, and a determination step. The method of this aspect makes it possible to screen for the ability to form higher-order structures (multimer formation conditions and / or three-dimensional structure formation conditions) and the ability to maintain cell membrane localization.

[0255] 5-2. Steps 5-2-1. Control Value Measurement Step The "control value measurement step" is an essential step in which the ability to form higher-order structures (multimer formation value and / or three-dimensional structure formation value) and the ability to maintain cell membrane localization (cell membrane localization value) are measured under control conditions according to the method described in the first or third aspect, and the results are obtained as control values.

[0256] The basic content of this step is similar to that of the reference value measurement step of the fourth embodiment, so only the differences from the fourth embodiment will be described here.

[0257] The control conditions used in this step are conditions that, by comparison, enable one to determine whether the candidate conditions are suitable for the formation of a higher-order structure or for maintaining localization at the cell membrane. The specific content of such control conditions is not particularly limited. For example, any conditions that are generally used as comparison targets in screening candidate conditions can be used. Specific examples include conditions that are known to have neither a favorable nor a detrimental effect on the formation of a higher-order structure and / or the maintenance of localization at the cell membrane, conditions that are known to be unsuitable for the formation of a higher-order structure and / or the maintenance of localization at the cell membrane, and conditions that are known to be suitable for the formation of a higher-order structure and / or the maintenance of localization at the cell membrane.

[0258] The "candidate value measurement step" is an essential step in which the higher-order structure formation ability (multimer formation value and / or three-dimensional structure formation value) and the ability to maintain cell membrane localization (cell membrane localization value) are measured under candidate conditions according to the method described in the first or third embodiment, and the results are obtained as candidate values. This step can be performed simultaneously with or separately from the control value measurement step.

[0259] The content of this step is similar to the description of the process value measurement step of the fourth embodiment, so only the differences from the fourth embodiment will be described here.

[0260] It should be noted that the terms "processing value" and "target condition" in the description of the fourth embodiment are to be read as "candidate value" and "candidate condition", respectively, in this step.

[0261] Typically, the candidate conditions in the method of this embodiment can include multiple conditions. In this case, the type of each condition is not particularly limited. For example, the multiple conditions may include conditions of the same type but with different magnitudes (e.g., the amount of drug to which the cells are exposed), or may include conditions of different types (e.g., the type of drug to which the cells are exposed, exposure of the cells to the drug, and exposure of the cells to the atmosphere, etc.).

[0262] The "determination step" is an essential step in which, if the candidate value is higher than the control value, it is determined that the candidate conditions are suitable for the formation of a higher-order structure and / or the maintenance of cell membrane localization, and / or, if the candidate value is lower than the control value, it is determined that the candidate conditions are not suitable for the formation of a higher-order structure and / or the maintenance of cell membrane localization. This step can be performed simultaneously with or after the candidate value measurement step.

[0263] Specifically, when the control value and candidate value are measured by the method described in the first aspect, this step determines whether the candidate conditions are suitable for multimer formation, whereas when the control value and candidate value are measured by the method described in the third aspect, this step determines whether the candidate conditions are suitable for three-dimensional structure formation.

[0264] For example, when conditions known to have no advantageous or adverse effect on the formation of higher-order structures and / or the maintenance of cell membrane localization are used as control conditions, if the candidate value is higher than the control value, it can be determined that the candidate conditions are suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization, and if the candidate value is lower than the control value, it can be determined that the candidate conditions are not suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization.

[0265] Furthermore, for example, when conditions known to be unsuitable for the formation of higher-order structures and / or the maintenance of cell membrane localization are used as control conditions, if the candidate value is lower than the control value, it can be determined that the candidate conditions are unsuitable for the formation of higher-order structures and / or the maintenance of cell membrane localization.On the other hand, when conditions known to be suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization are used as control conditions, if the candidate value is higher than the control value, it can be determined that the candidate conditions are suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization.

[0266] For example, when measuring the fluctuations based on the internalization of a G protein-coupled receptor as the ability to maintain plasma membrane localization, conditions that are not suitable for maintaining plasma membrane localization are conditions that activate the G protein-coupled receptor, and conditions that are suitable for maintaining plasma membrane localization are conditions that do not activate or inactivate the G protein-coupled receptor.

[0267] The control value and candidate value may be subjected to any processing before being subjected to the determination in this step. The processing in this case is not particularly limited, but for example, the control value and candidate value may be converted into the ligand binding value described in the second aspect or the variable value described in the fourth aspect. The processing performed in this case is in accordance with the descriptions of the second and fourth aspects, respectively.

[0268] The method for comparing the candidate value and the control value is not particularly limited, and any known method that can be used for comparing multiple types of numerical values ​​can be used. For example, the determination can be based on a simple comparison between numerical values, based on a cutoff value, or based on the presence or absence of a statistically significant difference between the candidate value and the control value.

[0269] (i) Determination Method Based on Cutoff Value The "determination method based on cutoff value" is a method in which a candidate value is compared with a predetermined cutoff value and a determination is made based on the comparison result.

[0270] As used herein, the term "cutoff value" refers to a boundary value for determining whether a candidate value is positive or negative. Here, "positive" indicates that the candidate conditions are suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization, and "negative" indicates that the candidate conditions are not suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization. The method for setting the cutoff value may follow methods known in the field of statistics and is not particularly limited. For example, a numerical value corresponding to a specific percentile value in a population of normally distributed values ​​including a control value and values ​​(multimerization value, three-dimensional structure formation value, or cell membrane localization value) measured under conditions known to be suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization can be used as the cutoff value. For example, if almost all of the values ​​measured under conditions known to be suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization are higher than the 90th percentile value in the group of values, the numerical value corresponding to the 90th percentile value can be used as the cutoff value. In this case, if the candidate value is higher than the cutoff value, the candidate condition is judged to be positive, i.e., the candidate condition is suitable for forming a higher-order structure and / or maintaining cell membrane localization; conversely, if the candidate value is equal to or lower than the cutoff value, the candidate condition is judged to be negative, i.e., the candidate condition is not suitable for forming a higher-order structure and / or maintaining cell membrane localization.

[0271] (ii) Determination method based on statistical test Determination method based on statistical test determines whether the candidate conditions are suitable for the formation of higher-order structures and / or the maintenance of cell membrane localization based on whether the candidate value is statistically significantly higher than the control value.

[0272] As used herein, "significant" refers to statistical significance. The significance level in this case is not particularly limited. For example, 5%, 1%, 0.1%, etc. can be used as the significance level. The statistical processing test method is not particularly limited, and any known test method capable of determining the presence or absence of a significant difference can be used as appropriate. For example, Student's t-test, paired Student's t-test, Welch's t-test, Wilcoxon rank sum test, analysis of variance, Tukey post-hoc test, etc. can be used, but are not particularly limited.

[0273] When determining whether a candidate condition is suitable for the formation of a higher-order structure and / or the maintenance of cell membrane localization based on a statistical test, if the candidate value is significantly greater than the control value, the candidate condition is determined to be suitable for the formation of a higher-order structure and / or the maintenance of cell membrane localization. On the other hand, if there is no significant difference between the candidate value and the control value or if the candidate value is significantly smaller than the control value, the candidate condition can be determined to be unsuitable for the formation of a higher-order structure and / or the maintenance of cell membrane localization. Alternatively, if there is no significant difference between the candidate value and the control value, it can be determined that the candidate condition does not affect the formation of a higher-order structure and / or the maintenance of cell membrane localization.

[0274] 5-3. Effects According to the method of this embodiment, it is possible to screen for suitable and / or unsuitable conditions for multimer formation, formation of a three-dimensional structure, and / or maintenance of cell membrane localization. For example, by performing the method of this embodiment using MHC as a multimeric receptor and the type of peptide ligand as a candidate condition, it is possible to simply and accurately screen for peptide ligands that are promising as vaccines (e.g., vaccines against cancer and / or infectious diseases).

[0275] 6. Program for Calculating Higher-Order Structure Formation Value 6-1. Overview A sixth aspect of the present invention is a program for calculating the higher-order structure formation value and / or cell membrane localization value of a test polypeptide in a cell.

[0276] This program is configured to cause a computer to execute a reference range setting step, an extraction step, a relational expression deriving step, and a higher-order structure formation value acquisition step or a cell membrane localization value acquisition step, and this program enables information processing in the method according to the first aspect and / or the method according to the third aspect.

[0277] The details of each step executed by the program of the present invention are as described in detail in the first and third embodiments.

[0278] This program is configured to execute a reference amount obtaining step, a reference amount analyzing step, and a setting step as a reference range setting process.

[0279] If the user requests separation of data of an appropriate cell group, the computer is further configured to execute a confirmation step and a reference cell separation step, the details of which are essentially as described in detail as the confirmation step and the reference cell sorting step in the first and third aspects, respectively.

[0280] The reference cell separation step is a step of obtaining data of a cell population containing cells expressing a test polypeptide as a reference. In this step, unlike the reference cell sorting step, data of an appropriate cell population is separated on the data or dataset.

[0281] Here, whether or not to perform the confirmation step and the reference cell separation step is selected depending on whether or not the user has already performed the confirmation step and / or the reference cell sorting step described in the first or third aspect. The necessity of the confirmation step and / or the reference cell separation step depends, for example, on whether or not the user requests them. Alternatively, the method may be configured to select the steps according to the type of data to be processed. Furthermore, parameters such as the necessity of the reference amount acquisition step, the reference amount analysis step, and / or the setting step, and the criteria to be used may also be configured to be selected according to the type of data to be processed. For example, if the data to be processed is data from a cell sample containing cells expressing a test polypeptide at a predetermined ratio, all or some of these steps may be omitted, or the criteria used in each step may be changed; otherwise, these steps may be performed.

[0282] The program of the present invention may be configured to prompt the user for further instructions, such as one or more of the criteria for determining whether a cell is expressing (e.g., thresholds for test expression level or test presentation level), the criteria for setting a reference range (e.g., the proportion of expressing cells), the relational equation to be used and the method for deriving it, and the method for calculating the higher-order structure formation value from the relational equation.

[0283] The timing and number of times that instructions are requested from the user are not particularly limited. For example, all instructions may be requested at once at the beginning, or instructions may be requested multiple times each time instructions are needed.

[0284] The program of the present invention can be further configured to include, as appropriate, the additional steps detailed in the first to fifth aspects.

[0285] The program may be stored on a recording medium, such as an optical recording medium such as a CD-ROM or DVD, or an information storage medium such as a semiconductor memory, a flexible disk, or a hard disk.

[0286] 6-2. Effect By using the program of this embodiment, it is possible to automatically execute the information processing required for the methods of the first to fifth embodiments. Furthermore, by incorporating the program of this embodiment into a measurement and / or analysis program for image cytometry, flow cytometry, or the like, it is possible to perform measurement, analysis, and information processing of a cell sample using a single device and obtain desired indicators.

[0287] Example 1 Measurement of multimer formation ability (Purpose) The multimer formation ability of MHC subunits associated with each other is measured.

[0288] (Method) 1. Plasmid Design The α subunit of MHC class II was used as the target polypeptide, and the β subunit was used as the test polypeptide. A plasmid vector for stable expression of the MHC class II α subunit was designed using pMXs-puro (Cell Biolabs). A schematic diagram of the structure of the stable expression plasmid vector is shown in Figure 7. On the other hand, a plasmid vector for transient expression of the MHC class II β subunit was designed using pMXs-IRES-GFP (Cell Biolabs). A schematic diagram of the structure of the transient expression plasmid vector is shown in Figure 8.

[0289] The gene sequence of the α subunit is DQA1 having the amino acid sequence shown in SEQ ID NO: 7. * The base sequence encoding 01:02 (SEQ ID NO: 8) was used.

[0290] The gene sequence of the β subunit is DQB1 having the amino acid sequence shown in SEQ ID NO: 9. *The nucleotide sequence encoding 06:02 (SEQ ID NO: 10) was used. Here, a fusion protein was used in which a 15-mer polyglycine (G15: SEQ ID NO: 3) sequence was fused to the N-terminal signal sequence of the β subunit via a linker (Linker 2) (SEQ ID NO: 11). The amino acid sequence of the fusion protein is shown in SEQ ID NO: 12, and the nucleotide sequence encoding it is shown in SEQ ID NO: 13.

[0291] 2. Preparation of viral particles. Retrovirus packaging cells (PLAT-E (Morita et al., Gene Ther., 2000. 7:1063-1066.)) maintained in antibiotic-containing medium (DMEM (Sigma-Aldrich) supplemented with 10% FBS, L-glutamine (2 mM), and antibiotic antimycotic solution (1x) (Sigma-Aldrich)) in the presence of puromycin (1 μg / mL) and blasticidin S (10 μg / mL) were introduced with the plasmid as follows to prepare viral particles.

[0292] PLAT-E cells were seeded in 2 mL of antibiotic-containing medium at a cell density of 1E6 cells / well in a 6-well dish. After overnight culture, the medium was replaced with 1 mL of antibiotic-free DMEM supplemented with 10% FBS and 2 mM L-glutamine.

[0293] 1.5 μg of plasmid DNA was placed in 50 μL of Opti-MEMI (Thermo Fisher Scientific), and the plasmid DNA was transfected into PLAT-E cells after medium replacement using 4.5 μL of FuGene (Promega; product number: E2311) according to the manufacturer's recommended protocol.

[0294] 24 hours after transfection, the medium was replaced with 1 mL / well of antibiotic-containing medium. 24 hours after the medium replacement, the culture supernatant was collected as a virus solution, and PLAT-E cells were removed by filtration using a 0.45 μm pore size filter or centrifugation.

[0295] 3. Transduction of Expression Cells NIH3T3 cells (mouse fibroblast cell line) were used as expression cells. NIH3T3 cells were seeded in 1 mL of DMEM in a 12-well dish at a cell density of 0.5E5–2E5 cells / well and cultured overnight. The next day, immediately before transduction, the medium was replaced with 0.35 mL / well of antibiotic-containing medium.

[0296] In a 1.5 mL tube, 900 μL of virus solution was mixed with 11.2 μL of polybrene (1 μg / μL; Sigma-Aldrich) to prepare the virus solution for transduction. The virus solution for transduction was used directly after collection or stored at -80°C before use.

[0297] After medium replacement, the virus solution for transduction was added to the NIH3T3 cells and incubated at 37°C for at least 3 hours. The volume of virus solution added was 15-50 μL / well for stable expression plasmid vectors and 5-50 μL / well for transient expression plasmid vectors. Then, 1 mL / well of antibiotic-containing medium was added, and the cells were cultured for 48 hours after virus infection.

[0298] 4. Antibody staining: The medium was removed and 1 mL of FCM buffer (PBS containing 0.1% BSA) was added instead. The cells were then detached from the container and placed in a 1.5 mL tube. The collected cell suspension was centrifuged at 300-500 x g for 2 minutes, the supernatant was discarded, and 100-300 μL of FCM buffer was added to prepare a cell suspension for antibody reaction.

[0299] 100 μL of the cell suspension for antibody reaction was added to a 1.5 mL tube into which 0.1 μg of primary antibody had been dispensed in advance for each cell sample, and the mixture was incubated at 4° C. for 15 minutes in the dark.

[0300] After washing the cells with FCM buffer, 0.2 μg of secondary antibody solution (0.2 μg in 25 μL of FCM buffer) was added to each cell sample, and the mixture was incubated at 4° C. for 15 minutes in the dark.

[0301] After incubation, the washed cells were suspended in 600 μL of FCM buffer to prepare a cell suspension for flow cytometry, which was filtered through a nylon mesh (pore size 40 μm) immediately before measurement to remove aggregated cells.

[0302] The following antibodies were used: Primary antibody: Antibody for measuring the amount of HLA-DP DQ DR presented to the subject, Mouse Anti-Human HLA-DP DQ DR Monoclonal antibody, Unconjugated (Bio-Rad Laboratories; clone name: WR18); Isotype control antibody: Mouse IgG2a Isotype Control antibody, Unconjugated (Medical & Biological Laboratories; clone name: 6H3); Secondary antibody: Goat F(ab')2 Anti-Mouse Ig, Human ads-PE antibody (Southern Biotechnology Associates; catalog number: 1012-09).

[0303] Measurement by flow cytometry was carried out as follows: A Spectral Cell Analyzer SA3800 (Sony) was used as the flow cytometer.

[0304] The measurement parameters were as follows: Excitation: 488 nm, Window extension: Wide, Threshold CH: FSC, Threshold Value: 16.0%, FSC Gain: 17, SSC voltage: 25.8%, Fluorescence PMT voltage: 38.0%, Flow rate: 500-1,000 events / second, Fluorescence compensation: None

[0305] Data acquisition was performed using SA3800 software, and the data obtained from the measurements was analyzed using FCS Express ver. 6.06.00336 (De Novo Software).

[0306] 5. Confirmation of the Proportion of GFP-Expressing Cells In this example, the expression level of the β subunit was determined based on the GFP expression level (measured value of GFP fluorescence intensity).

[0307] The proportion of GFP-expressing cells was confirmed by flow cytometry. Specifically, the presence or absence of GFP expression was determined as follows.

[0308] First, GFP and PE fluorescence intensities were measured by flow cytometry using non-GFP-expressing cells, and the maximum GFP fluorescence intensity of the non-GFP-expressing cells on the GFP and PE fluorescence intensity distribution plane was determined as a threshold. Next, a cell population containing GFP-expressing cells was measured, and cells showing GFP fluorescence intensity above the threshold were determined to be GFP-expressing cells.

[0309] A reference range was established using a cell sample in which the proportion of GFP-expressing cells was approximately 30% when Gate 2 described below was used as the population, and an isotype control antibody was applied to the sample.

[0310] 6. Setting the reference range First, the measured data for each cell was expanded using FSC-Area and SSC-Area, and Gate 1 was set to include the target cell population. Gate 1 was set to exclude particles with low FSC-Area and SSC-Area values ​​(particles, dead cells, cell debris, etc.) and cells with high FSC-Area and / or SSC-Area values ​​(aggregated cells, cells with changes in cell diameter or internal structure after gene transfer, etc.) (Figure 9A).

[0311] Next, the data extracted by Gate 1 were expanded using FSC-Area and FSC-Height, and a rectangular Gate 2 was set to extract data derived from single cells (Figure 9B). Cells not included in Gate 2 were considered to be data on aggregated cells and were therefore excluded.

[0312] Next, the data of the cells extracted by gate 2 was expanded by GFP fluorescence intensity and PE fluorescence intensity, and gate 3 was set at a position that included more than 90% of the GFP non-expressing cells, and the cell group included in gate 3 was designated as the non-expressing cell group (Figure 10). In the same two-dimensional expansion, gate 4 was set, which included GFP-expressing cells, and the cell group included in gate 4 was designated as the expressing cell group (Figure 10).

[0313] Next, the data from cells extracted by gate 4 were plotted as a density plot (color-coded by percentile) of GFP and PE fluorescence intensities, and a reference range was set for GFP fluorescence intensity based on the percentile contours (color-coded boundaries) (Figure 11A). In the density plot, the total number of cells extracted by gate 4 was used as the parameter. The lowest GFP fluorescence intensity value within the 80th percentile ("a" in Figures 11A and 11B: the value corresponding to the boundary between the 80th and 60th percentiles) was defined as the lower limit of the reference range. Meanwhile, the highest GFP expression level within the 20th percentile ("b" in Figures 11A and 11B: the value corresponding to the boundary between the 20th and 1st percentiles) was defined as the upper limit of the reference range. Gate 5 was set so that data from cells whose GFP fluorescence intensity fell within the reference range were extracted regardless of PE fluorescence intensity (Figure 11A). Furthermore, gates 6 to 9 were set to divide gate 5 into four equal sections based on the logarithmic scale of GFP fluorescence intensity (Figure 11C). Gate 5 extracts data from cells extracted by gate 4 whose GFP fluorescence intensity falls within the reference range, and gates 6 to 9 divide gate 5.

[0314] 7. Measurement of Test Expression Levels and Test Presentation Levels Cell samples to which antibodies for measuring test presentation levels had been applied were measured by flow cytometry. The measurement method and setting of gates 1 to 3 were the same as when determining the reference range. Gate 4 was set at a position encompassing the GFP-positive, PE-positive population in each cell sample. Gate 5, which had been previously set as the reference range, was applied to the data of cells extracted by gate 4 without changing its position, and data for cells encompassed by gate 5 was extracted.

[0315] Furthermore, the data of cells extracted by gate 5 was applied without changing the positions of the gates dividing gate 5 (gates 6 to 9) (Fig. 12B).

[0316] Next, cell samples suitable for calculating higher-order structure formation values ​​were selected based on the cell counts contained in gates 6–9. Specifically, data from cell samples that met any of the following conditions were excluded from the extraction process: the number of cells contained in each gate (gates 6–9) was less than 100; or the cell count ratio was outside the following (lower limit | upper limit) reference value range (half-open interval at the lower limit): Gate 6 / Gate 7 cell count ratio (0.5 | 2), Gate 6 / Gate 8 cell count ratio (0.4 | 8), Gate 6 / Gate 9 cell count ratio (0.3 | 40), Gate 7 / Gate 8 cell count ratio (0.6 | 4), Gate 7 / Gate 9 cell count ratio (0.5 | 20), Gate 8 / Gate 9 cell count ratio (0.9 | 8). For data from cell samples that were not excluded, the median GFP fluorescence intensity (test expression level) and PE fluorescence intensity (test presentation level) were calculated for each of gates 6–9.

[0317] Similarly, measurements were performed using an isotype control antibody for each cell sample (FIG. 12A), and the median values ​​of GFP and PE fluorescence intensities in each of the sections of gates 6 to 9 were calculated.

[0318] 8. Derivation of the relational equation For each cell sample, the relationship between the median GFP fluorescence intensity and the median PE fluorescence intensity in each section for gates 6, 7, 8, and 9 was plotted on a graph.

[0319] The equation of the regression line was derived by the least squares method using all combinations of 2, 3, or 4 data points from gates 6, 7, 8, and 9 and the origin. Excel was used to derive the equation of the regression line. The equation of the regression line showing the largest regression coefficient was used to calculate the multimer formation value. The data points from the same gate as those used for the equation of the regression line showing the largest regression coefficient (here, the slope) were used to calculate the regression coefficient for the cell sample to which the isotype control antibody was applied (Figure 13).

[0320] 9. Calculation of multimer formation value The multimer formation value was calculated by subtracting the regression coefficient for the cell sample to which the isotype control antibody was applied from the regression coefficient in the equation (regression line) relating GFP fluorescence intensity to PE fluorescence intensity derived for the cell sample to which the antibody for measuring the display amount to be tested was applied.

[0321] (Results) The results are shown in Figure 13. The regression coefficient of the regression line of the cell sample to which the test antibody for measuring the presentation amount (in the figure, "α-HLA antibody") was applied was 1.35, which was larger than the regression coefficient of the regression line of the cell sample to which the isotype control antibody (in the figure, "isotype control") was applied, which was 0.16. From these results, it can be seen that the DQA1 in which G15 was fused to the β chain * 01:02 and DQB1 * The multimer formation value of the heterodimer at 06:02 was calculated to be 1.19 (= 1.35 - 0.16).

[0322] Example 2: Changes in multimer formation value depending on the type of subunit (Objective) To investigate the effect of the type of subunit (HLA allele) on the multimer formation value.

[0323] (Method) The same procedure as in Example 1 was carried out except for the type of subunit used. * 03:01 (SEQ ID NO: 14), DQB1 as the β subunit * As in Example 1, a fusion protein was used in which a 15-mer polyglycine (G15: SEQ ID NO: 3) sequence was fused to the N-terminal signal sequence of the β subunit via a linker (Linker 2) (SEQ ID NO: 11).

[0324] The relational equation was derived in the same manner as in Example 1, using the values ​​of gates 6 and 7, which had the largest regression coefficient values.

[0325] (Results) The results are shown in Figure 14 and Table 1. DQA1 * 03:01 and DQB1 * By comparing the regression coefficient value when the test antibody for measuring the presentation amount was applied to the 03:02 heterodimer with the regression coefficient value of the cell sample when the isotype control antibody was applied, the multimer formation value was calculated to be 0.11 (= 0.29 - 0.18) (Figure 14).

[0326] Even when MHC fused with G15 was used as in Example 1, differences in the multimer formation value were observed depending on the type of subunit, which is thought to reflect differences in binding strength between the α and β subunits depending on the type (allele) of HLA.

[0327] As shown in Table 1, the results of this example and Example 1 are consistent with the results of the heterodimer binding strength evaluated based on the stability in the presence of the surfactant SDS, as reported in a previous study (Ettinger et al., J. Immunol., 1998, 161:6439-6445.). Furthermore, this method allows the measurement of DQA1, which was difficult in the previous study. * 03:01 and DQB1 * The multimer formation value of the 03:02 heterodimer could be quantified.

[0328]

[0329] This demonstrates that the method of the present invention makes it possible to easily and accurately quantify the ability to form multimers without performing electrophoresis, Western blotting, treatment with detergents, etc., and that it is also possible to quantify the ability to form multimers with low structural stability.

[0330] Example 3: Changes in ligand binding value depending on the type of ligand (Objective) To investigate the effect of the type of ligand on the ligand binding value.

[0331] (Method) DRA as the α subunit * 01:01 (SEQ ID NO: 16) was used, and DRB1 was used as the β subunit. * 04:01 (SEQ ID NO: 17), DRB1 * 04:05 (SEQ ID NO: 18), DRB1 * 09:01 (SEQ ID NO: 19) and DRB3 *01:01 (SEQ ID NO: 20) was used. Furthermore, peptides derived from the CFP-10 and ESAT-6 proteins of Mycobacterium tuberculosis H37Rv shown in Table 2 below were used as ligands. Experiments were carried out in the same manner as in Example 1, except that the subunit type and ligand sequence were different. The value based on the ratio of the test value to the control value (the multimer formation value when the control ligand G15 was used) was calculated as the ligand binding value. The ligand binding value was calculated as the average of 3 to 8 trials.

[0332]

[0333] (Results) The results are shown in Figure 15. The ligand binding value differed depending on the type of ligand. Based on the ligand binding value, for example, the β subunit binds to DRB1. * In the case of 09:01, it is easy to form a multimer with peptides derived from ESAT-6 (peptide 2a, peptide 2d), while the β subunit is easily integrated with DRB3. * In the case of 01:01, it was found that it easily formed a multimer with a peptide derived from CFP-10 (peptide 1a). * In the case of 04:05, it was found that among the peptides derived from ESAT-6, peptide 2a was relatively likely to form a multimer.

[0334] From the above, it was demonstrated that the method of the present invention makes it possible to find peptide ligands that readily form multimers depending on the type of MHC, such as HLA alleles, without purifying the MHC protein. Note that the control values ​​and test values ​​in this Example and Example 4 can be used as control values ​​and candidate values, respectively, and can be applied to screening for candidate peptide ligands that bind to MHC.

[0335] Example 4. IC 50 (Purpose) Comparing the ligand binding values ​​obtained by the method of the present invention with predicted IC values 50 Compare with the value.

[0336] (Method) DRA as HLA allele * 01:01 (SEQ ID NO: 16) and DRB1* 04:01 (SEQ ID NO: 17) (Figure 16A), DRA * 01:01 and DRB1 * 04:05 (SEQ ID NO: 18) (Figure 16B), DRA * 01:01 and DRB1 * 15:02 (SEQ ID NO: 30) (Figure 17A), DRA * 01:01 and DRB3 * 01:01 (SEQ ID NO: 20) (Figure 17B), DQA1 * 03:01 and DQB1 * 03:01 (SEQ ID NO: 31) (Figure 18A), DQA1 * 01:03 (SEQ ID NO: 32) and DQB1 * The combination 06:01 (SEQ ID NO: 33) (Figure 18B) was used.

[0337] Measurement of the multimer formation values ​​for these and the ligands shown in Table 3 below was carried out in the same manner as in Examples 1 and 3, except that the subunit types and ligand sequences were different. The value based on the ratio of the test value to the control value (the multimer formation value when the control ligand G15 was used) was calculated as the ligand binding value.

[0338]

[0339] Predicted IC 50 The IC values ​​were predicted using NetMHCIIpan-4.0 (Reynisson et al., J. Proteome. Res., 2020, 19: 2304-2315). NetMHCIIpan-4.0 is a server that predicts the binding affinity of MHC class II peptides. It provides Rank values ​​(percentile rankings predicted based on the binding affinity dataset and peptide elution dataset), Rank_BA values ​​(percentile rankings predicted based on the binding affinity dataset), and IC values. 50 The value is output as a predicted value. Enter the amino acid sequence of the peptide shown in Table 3 into NetMHCIIpan-4.0 and select the target HLA allele to calculate the predicted IC value output as "nM". 50 taken as a value.

[0340] Ligand binding values ​​and predicted IC 50The correlation between the values ​​was verified by calculating the Pearson correlation coefficient, which was calculated using Excel.

[0341] (Results) The results are shown in Figures 16 to 18. For each combination of HLA and peptide measured, the ligand binding value and predicted IC 50 A positive correlation was observed between the α and β subunit values, and the correlation coefficient was high, at 0.8 or higher, for a wide variety of allele combinations of α and β subunits (Figures 16 to 18). This indicates that the multimer formation values ​​obtained by the method of the present invention reflect the ligand binding ability. In addition, the weak binding affinity (IC 50 This method was also capable of quantifying the concentration of α-glucan in the range of 1E4 nM to 1E5 nM.

[0342] This confirmed that the method of the present invention allows for simple and accurate measurement of ligand binding levels.

[0343] Example 5. Compatibility between measurement models (Purpose) To check the compatibility between the models of flow cytometers used.

[0344] (Method) The multimer formation value was measured and the ligand binding value was calculated in the same manner as in Examples 1 and 3. As a flow cytometer, Epics-XL (Beckman Coulter) (a filter-type cell analyzer) or FACSCanto TM The values ​​were measured using a filter-type cell analyzer (Becton Dickinson) II and compared with the ligand binding values ​​calculated from measurements using a spectral cell analyzer (SA3800) (Sony).

[0345] In comparing Epics-XL and SA3800, DRA * 01:01 (SEQ ID NO: 16) and DRB1 * The combination of 08:03 (SEQ ID NO: 34) was used. TM In comparing the DRA II and SA3800, * 01:01 (SEQ ID NO: 16) and DRB3 *The combination 01:01 (SEQ ID NO: 20) was used. The peptides shown in Table 3 were used as ligands.

[0346] Measurements using the Epics-XL were performed using the following parameters: excitation: 488 nm, forward scatter (FS): 30, side scatter (SS): 400, first fluorescence (FL1): 620 V, second fluorescence (FL2): 680 V, fluorescence compensation: FL1 (vs. FL2): 10%, FL2 (vs. FL1): 0%, flow rate: 300–1,000 events / s. Data acquisition was performed using EXPO32 software.

[0347] FACSCanto TM The following parameters were used for measurements using II: excitation: 488 nm, FSC: 216 V, SSC: 390 V, FITC: 390 V, PE: 340 V, fluorescence compensation: FL1 (vs. FL2): 23%, FL2 (vs. FL1): 4.0%, flow rate: 300–1,000 events / sec, Area Scaling Factor: Blue: 0.83, FSC: 0.77. Data acquisition was performed using FACSDiva. TM This was done using software.

[0348] Gate setting was performed using analysis software (FCS Express ver. 6.06.00336 (De Novo Software)) in accordance with Example 1. TM Measurements using II were performed in one to two replicates. Measurements using SA3800 were performed in one to four replicates. Ligand binding values ​​were calculated as the ratio of the test value to the control value at G15. The number of cells used as the cell population for measurement in each run was 11,000 to 26,000 (Gate 1), and the number of cells within the reference range used to calculate the multimer formation value was 860 to 6,800 (Gate 5).

[0349] (Results) The results are shown in Figures 19 and 20. Even when different models of flow cytometers were used, the trends in ligand binding values ​​depending on the type of ligand were in good agreement between the models. In addition, it was found that not only the trends but also the numerical values ​​were highly consistent between different models regardless of the ligand used. This demonstrates that the ligand binding values ​​calculated by the method of the present invention have very high compatibility between measurement models.

[0350] Example 6: Verification of the sensitivity of the method of the present invention (Objective) To verify the sensitivity of the ligand binding value calculated by the present invention using predicted binding rank values ​​(Rank value and Rank_BA value) and predicted IC 50 Compare with the sensitivity of the value.

[0351] (Method) Measurement of the ligand binding value by the method of the present invention was carried out in the same manner as in Examples 1 and 3, except that the ligand and subunit used were different. * 01:01 (SEQ ID NO: 16) and DRB1 * The combination of 08:03 (SEQ ID NO: 34) was used. The peptides shown in Table 4 were used as ligands, and the ligand binding value was calculated as the ratio of the test value to the control value in G9.

[0352]

[0353] The peptides shown in Table 4 are peptides in which one amino acid each from the N-terminus or C-terminus of a partial peptide (peptide 1c) in the region of positions 49 to 63 of the ESAT-6 protein of Mycobacterium tuberculosis has been substituted with glycine.

[0354] As described in Example 4, the predicted binding value was determined by inputting the amino acid sequence of each peptide into NetMHCIIpan-4.0, selecting the target HLA allele, and outputting the predicted binding rank ("Rank" or "Rank_BA"). 50 The value output as "nM" was used.

[0355] (Results) The results are shown in Figure 21B. According to the results of the ligand binding value calculated by the method of the present invention, when the fourth residue (glutamine) in addition to the first three residues from the N-terminus of peptide 1c was substituted with glycine (1c 5-15), and when the fourth residue (glutamic acid) in addition to the first three residues from the C-terminus was substituted with glycine (1c 1-11), the ligand binding value dropped sharply (Figure 21B). In general, it is known that the side chains of both glutamine and glutamic acid contribute significantly to intermolecular interactions. In particular, DRB1 * From the results of structural analysis of HLA, which has a common polymorphism with 08:03, DRB1 * This result is considered plausible because it is predicted that acidic amino acids are accommodated as anchor residues in the binding pocket on the C-terminal side of the antigen peptide of 08:03 (Jones et al., Nat. Rev. Immunol., 2006, 6:271-282).

[0356] Predicted binding rank ("Rank", "Rank_BA") and predicted IC 50 The trend of the values ​​was generally consistent with the ligand binding values ​​(Figure 21A). However, since the predicted binding rank ("Rank") did not decrease monotonically, it was not possible to clearly determine which residues were important for ligand binding. In addition, the predicted binding rank ("Rank_BA") and predicted IC 50 Even based on the values, it was difficult to identify residues involved in the strength of binding to MHC (Figure 21A).

[0357] From the above, the ligand binding value obtained by the method of the present invention is calculated based on the predicted binding rank and predicted IC 50 It was shown to be an excellent indicator with extremely high sensitivity compared to the values.

[0358] Example 7 Measurement by Image Cytometry (Purpose) To investigate whether it is possible to measure ligand binding values ​​using image cytometry in the same way as flow cytometry.

[0359] (Method) The method was basically the same as in Examples 1 and 3, except that the detection equipment was different. *01:02 (SEQ ID NO: 7) was used, and DQB1 was used as the β subunit. * 06:02 (SEQ ID NO: 9) was used. Furthermore, peptides derived from the CFP-10 and ESAT-6 proteins of Mycobacterium tuberculosis H37Rv shown in Table 2 were used as ligands. A 24-well plastic plate was coated with 2% gelatin and cells were seeded on it. Antibody staining was performed on the plate using the same antibody as in Example 1, and then the cells were fixed with 4% paraformaldehyde / PBS. The fixative was replaced with PBS and the cells were stored at 4°C for 18 hours in the dark before being photographed using a confocal quantitative image cytometer, CellVoyager CQ1 (Yokogawa Electric Corporation). Photography was performed under the following conditions: GFP detection: excitation 488 nm, fluorescence BP 525 / 50 nm PE (MHC) detection: excitation 561 nm, fluorescence BP 617 / 713 nm

[0360] Ten fields of view (objective: ×10) were photographed for each specimen. Image data were analyzed using CellPathfinder (Yokogawa Electric Corporation), and the fluorescence intensity value for each cell was calculated. The average value of the boundary line (GFP fluorescence intensity: 10,738) determined by assuming that each cell population follows a normal distribution in samples using isotype control antibodies was used as the threshold for separation of GFP-negative and positive cell populations. As in Example 1, the lower and upper limits of the GFP fluorescence intensity of Gate 5 were set at the 60th and 20th percentiles of the cell density distribution of the GFP-positive cell population (GFP fluorescence intensity: 24,044 to 61,802), respectively.

[0361] Gates 6 to 9 were set in the region that divides the GFP fluorescence intensity in gate 5 into four equal parts. The median values ​​of the GFP and PE fluorescence intensities in each of gates 6 to 9 were calculated. The derivation of the relational equation and calculation of the multimer formation value were performed in the same manner as in Example 1.

[0362] The ligand binding value was calculated based on the ratio of the multimer formation value (test value) when each ligand was used to the multimer formation value (control value) when the control ligand G15 was used. Samples prepared simultaneously with the image cytometry samples were analyzed by flow cytometry in the same manner as in Example 1, and the results were compared with those obtained by image cytometry.

[0363] (Results) The results are shown in Figure 22. The ligand binding value differed depending on the type of ligand, and for each, comparable results were obtained in measurements by flow cytometry and image cytometry.

[0364] From the above, it was demonstrated that even when image cytometry is used, the method of the present invention makes it possible to measure ligand binding values ​​with the same accuracy as flow cytometry.

[0365] Example 8 Measurement of Changes in Higher-Order Conformation Ability Due to Drugs or Compounds (Purpose) The change in higher-order conformation ability due to binding between HLA class I and a drug is measured.

[0366] (Method) HLA class I α subunit (HLA-B) was used as a test polypeptide. * 57:01 (SEQ ID NO: 55), HLA-B * 57:03 (SEQ ID NO: 56) and HLA-B * The target polypeptides used were abacavir sulfate (Fujifilm Wako Pure Chemical Industries, Ltd.; product number: 017-26393) and carbamazepine-related compounds, oxcarbazepine (Tokyo Chemical Industry Co., Ltd.; product number: O0363) (Compound 1), carbamazepine 10,11-epoxide (Tokyo Chemical Industry Co., Ltd.; product number: D5982) (Compound 2), eslicarbazepine acetate (Tokyo Chemical Industry Co., Ltd.; product number: E1046) (Compound 3), and carbamazepine (Fujifilm Wako Pure Chemical Industries, Ltd.; product number: 034-23701) (Compound 4).

[0367] Preparation of viral particles and transduction of expression cells were performed in the same manner as in Example 1. However, expression cells were seeded 3 hours before transduction, and 0.5 mL / well of antibiotic-containing medium was added 2 hours after transduction (viral infection). Drugs were added by dissolving the drug in DMSO or PBS and adding the solution to the medium 24 hours after viral infection (final concentration 700 μM).

[0368] The following antibodies were used as different antibodies from those described in Example 1: Primary antibody; Antibody for measuring the amount of HLA-A, B, C presented to the subject: Anti-human HLA-A, B, C Antibody (Biolegend; clone name: W6 / 32)

[0369] The variability was calculated as the ratio or difference between the higher-order structure formation value of the drug-treated sample (treated value) and the higher-order structure formation value of the DMSO- or PBS-treated sample (control value). The variability was calculated as the average of three trials.

[0370] (Results) The results are shown in Figures 23 and 24. Figure 23 shows the difference in fluctuation values ​​depending on the type of allele when abacavir sulfate was used. HLA-B * In the case of 57:01, the fluctuation value increased in a concentration-dependent manner, and abacavir sulfate was associated with HLA-B * It was suggested that the drug rash caused by abacavir is linked to HLA-B 57:01. * It is known that there is a strong association with the 57:01 genotype. * 57:03 and HLA-B * The addition of abacavir sulfate did not affect the variation of alleles such as 15:02, which have not been reported to be associated with abacavir-induced drug rash.

[0371] Abacavir is a HLA-B * Structural analysis and analysis of T cell responses suggest that it acts specifically on the 57:01 allele (Illing et al. Nature, 2012, 486: 554-558.), and the measurement results shown in Figure 23 are in good agreement with this report.

[0372] Figure 24 shows the alleles of HLA-B* 24 shows the fluctuation values ​​when abacavir sulfate and carbamazepine-related compounds were used in the case of using 57:01. When abacavir sulfate was used as the drug ("Abacavir" in FIG. 24), the fluctuation value was high, and HLA-B * The binding of 57:01 to abacavir sulfate was suggested. HLA-B * When carbamazepine-related compounds known not to bind strongly to 57:01 were used ("Compound 1" to "Compound 4" in Figure 24), the fluctuation values ​​were low, suggesting only weak or no binding. Similar results were obtained when the difference-based values ​​were used (Figure 24B) as when the ratio-based values ​​were used (Figure 24A).

[0373] From the above, it has been demonstrated that the method of the present invention makes it possible to discover differences in the binding ability of specific drugs to HLA and differences in the effects of each drug on specific HLA alleles without performing analyses such as immunoassays or mass spectrometry. Note that by treating the control value and treatment value in this example as the control value and candidate value, respectively, candidate drugs that bind to MHC can be screened.

[0374] Example 9 Measurement of conformational value in membrane proteins other than MHC (Objective) A cytokine receptor (mouse IL-2 receptor α subunit: IL-2Rα) was used as a membrane protein to investigate whether the effect of mutations that affect stability can be measured as a conformational value.

[0375] (Method) Measurements were basically carried out in the same manner as in Example 1, except that the wild-type protein (SEQ ID NO: 59) or the Y129H mutant protein (SEQ ID NO: 60) of mouse IL-2Rα was used as the test polypeptide.

[0376] The following PE-labeled antibodies were used as detection antibodies: Antibody for measuring the amount of CD25 presented to the subject: PE Rat Anti-Mouse CD25 Monoclonal antibody (BD Pharmingen) TM, clone name: PC61) Isotype control antibody PE Rat IgG1, κ Isotype Control (Biolegend; clone name: RTK2071)

[0377] (Results) The results are shown in Figure 25. When mouse IL-2Rα (wild-type) was used, the conformation formation value was 6.04 ("IL2Ra wild-type" in Figure 25). On the other hand, when mouse IL-2Rα (Y129H mutant) was used, the conformation formation value was an extremely low 0.03 ("IL2Ra mutant" in Figure 25).

[0378] Previous research (Permanyer et al. Cell. Mol. Immunol., 2021, 18:398-414) has speculated that the Y129H mutation affects IL-2Rα stabilization, and has reported that forced expression of wild-type and Y129H mutant forms in 293T cell lines results in decreased surface expression of the Y129H mutant form. The results shown in Figure 25 are in good agreement with this report.

[0379] From the above, it was demonstrated that the method of the present invention is also useful for membrane proteins other than MHC and membrane proteins expressed as monomers, and that changes in the amount of receptor on the membrane due to mutations can be accurately detected.

[0380] Example 10 Measurement of the ability of G protein-coupled receptors to maintain their localization at the cell membrane and the effects of drugs (Purpose) To confirm that the method of the present invention can measure the ability of G protein-coupled receptors to maintain their localization at the cell membrane, and to investigate the effects of drugs on the ability to maintain their localization at the cell membrane.

[0381] (Method) Orexin receptor 1 (OX1R) (SEQ ID NO: 61) and orexin receptor 2 (OX2R) (SEQ ID NO: 62) were used as G protein-coupled receptors. The ligands used were the orexin B sequence (Peptide 3b), which is a ligand for these receptors, and two partial sequences of orexin A and orexin B (Peptide 3a and Peptide 3c, respectively) that have been reported to bind strongly to both OX1R and OX2R (Lang, et al., J. Med. Chem. 2004, 47:1153-1160). These peptides (C-terminal amidated, >90% purity, GenScript) (final concentration 10 μM) were synthesized. The sequences used are shown in Table 5.

[0382]

[0383] The antagonists used were Almorexant HCl (AdooQ bioscience; product number: A14286-5; OX1R and OX2R antagonist) and SB-334867 (AdooQ bioscience; product number: A16695-5; OX1R selective antagonist) (final concentration 10 μM). The experiment was carried out in the same manner as in Example 8, except that the types of test polypeptide and drug were different.

[0384] The following antibodies were used as antibodies different from those described in Example 1. OX1R: Primary antibody; Antibody for measuring the amount of presentation to be tested: Anti-Orexin Receptor 1 / HCRTR1 Rabbit mAb (Cell signaling technology; clone name: E5Q8B) Isotype control antibody: Normal rabbit IgG: sc-3888 (Santa Cruz Biotechnology) Secondary antibody; Goat Anti-Rabbit IgG H&L (PE) preadsorbed (Abcam) OX2R: Primary antibody; Antibody for measuring the amount of presentation to be tested: Invitrogen Anti-Orexin Receptor 2 Monoclonal Antibody (Thermo Fisher; clone name: 456738)

[0385] The variation was calculated based on the ratio of the plasma membrane localization value of the sample to which the ligand or the ligand and antagonist was added (treated value) to the plasma membrane localization value of the sample to which DMSO was added (control value). The variation was calculated as the average of three trials.

[0386] (Results) The results are shown in Figures 26 and 27. Figures 26 and 27 are diagrams showing the difference in fluctuation values ​​when a ligand or a ligand and an antagonist were added. Figure 26 shows the results for OX1R, and Figure 27 shows the results for OX2R.

[0387] When no antagonist was used (in Figures 26 and 27, "antagonist" is "-"), the change in the value when only the ligand was added was significantly lower than when only the solvent (DMSO) was added (in Figures 26 and 27, "ligand" is "-"). It is known that when G protein-coupled receptors are activated, they are internalized along with the surrounding cell membrane. As mentioned above, these ligands have been reported to bind with high affinity to OX1R and OX2R. Therefore, the results of adding the ligands in Figures 26 and 27 closely reflect this internalization phenomenon of G protein-coupled receptors.

[0388] On the other hand, when Almorexant HCl, an antagonist acting on both OX1R and OX2R, was added together with the ligand (in Figures 26 and 27, "antagonist" is "Almorexant"), the internalization observed when only the ligand was added was suppressed for both OX1R and OX2R. On the other hand, when SB-334867, an antagonist acting specifically on OX1R, was added together with the ligand (in Figures 26 and 27, "antagonist" is "SB-334867"), the change in OX1R (Figure 26) increased, whereas the change in OX2R (Figure 27) decreased significantly, similar to the change in the absence of the antagonist. This suggests that OX1R-specific internalization was inhibited.

[0389] From the above, according to the method of the present invention, Ca 2+It was suggested that the internalization phenomenon associated with ligand binding to a G protein-coupled receptor can be measured without performing analyses such as intracellular assays to detect G protein-coupled receptors, and that the inhibitory effect of an antagonist can be detected. Furthermore, by treating the control value and treatment value in this example as the control value and candidate value, respectively, this method can be applied to the search for ligands of G protein-coupled receptors and the screening of agonists and antagonists. All publications, patents, and patent applications cited herein are incorporated herein by reference in their entirety.

[0390] S0101 Expression step S0102 Reference range setting step S0103 Measurement step S0104 Extraction step S0105 Relational equation derivation step S0106 Multimer formation value acquisition step S0110 Confirmation step S0111 Reference cell sorting step S0112 Reference amount acquisition step S0113 Reference amount analysis step S0114 Setting step S0115 Measurement cell sorting step S0116 Expression amount measurement step S0117 Presentation amount measurement step

Claims

1. A method for measuring the ability of a test polypeptide and a target polypeptide to form multimers in cells, wherein the cells are capable of transiently expressing the test polypeptide as a cell membrane protein and are capable of expressing the target polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide and the target polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells whose test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a multimerization value acquisition step of acquiring a multimerization value from the relational equation, wherein the reference range setting step comprises: a confirmation step of confirming whether or not the test polypeptide is expressed in the cells; the method comprising: a reference cell sorting step of sorting a plurality of cells, including cells expressing the test polypeptide, as a reference cell group; a reference amount obtaining step of measuring the expression level of the test polypeptide in the reference cell group and obtaining the reference amount; a reference amount analysis step of analyzing the reference amount for the expression level of the test polypeptide; and a setting step of setting the reference range based on the results of the analysis, wherein the measurement process comprises: a measurement cell sorting step of sorting a plurality of the cells as a measurement cell group; an expression amount measuring step of measuring the expression level of the test polypeptide in the measurement cell group and obtaining the result as a test expression amount; and a presentation amount measuring step of measuring the amount of the test polypeptide present on the cell membrane in the measurement cell group and obtaining the result as a test presentation amount, wherein the test presentation amount changes according to the association between the test polypeptide and the target polypeptide.

2. The method according to claim 1, wherein the relationship is a linear equation with the test expression level as a variable, and the multimer formation value is a coefficient of the test expression level.

3. The method of claim 1, wherein the test polypeptide is a membrane protein.

4. The method of claim 3, wherein the membrane protein is a subunit of MHC.

5. The method of claim 1, wherein the expression level of the test polypeptide is measured by the expression level of a labeled protein coupled to the expression of the test polypeptide.

6. The method of claim 1, wherein the measurement is performed by any one or more selected from the group consisting of flow cytometry, image cytometry, and mass cytometry.

7. The method of claim 4, wherein the membrane protein is a subunit of MHC, and the measurement of the expression level of the test polypeptide is carried out by measuring the expression level of a labeled protein coupled to the expression of the test polypeptide by flow cytometry.

8. A method for measuring fluctuations in multimer formation ability under target conditions, comprising: a control value measurement step of measuring a multimer formation value under control conditions according to the method of claim 1 and obtaining a control value; a treatment value measurement step of measuring a multimer formation value under the target conditions according to the method of claim 1 and obtaining a treatment value; and a calculation step of calculating a fluctuation value based on the obtained control value and treatment value.

9. A method for measuring the binding ability of a multimeric receptor to a test ligand on a cell membrane, comprising: a control value measurement step of measuring a multimer formation value according to the method of claim 1 and obtaining a control value; a test value measurement step of measuring a multimer formation value according to the method of claim 1 and obtaining a test value; and a calculation step of calculating a ligand binding value of the test ligand based on the obtained control value and test value, wherein the control value measurement step uses a fusion protein of a subunit of the multimeric receptor and a control ligand and another subunit of the multimeric receptor as the test polypeptide and the target polypeptide, and the test value measurement step uses a fusion protein of a subunit of the multimeric receptor and a test ligand and another subunit of the multimeric receptor as the test polypeptide and the target polypeptide.

10. The method of claim 9, wherein the ligand binding value is based on a ratio of the test value to the control value.

11. The method of claim 9, wherein the ligand binding value is based on the difference between the test value and the control value.

12. A method for screening conditions for multimer formation in cells, comprising: a control value measurement step of measuring a multimer formation value under control conditions according to the method of claim 1 and obtaining a control value; a candidate value measurement step of measuring a multimer formation value under candidate conditions according to the method of claim 1 and obtaining a candidate value; and a determination step of determining that the candidate conditions are suitable for multimer formation if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for multimer formation if the candidate value is lower than the control value.

13. The method of claim 12, wherein the multimerization conditions are the type of agent to which the cells are exposed.

14. The method of claim 12, wherein the multimerization condition is the type of ligand.

15. A method for measuring the ability of a test polypeptide to form a three-dimensional structure in cells, wherein the cells are capable of transiently expressing the test polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells whose test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a three-dimensional structure formation value acquisition step of acquiring a three-dimensional structure formation value from the relational equation, wherein the reference range setting step comprises: a confirmation step of confirming whether or not the test polypeptide is expressed in the cells; a reference cell sorting step of sorting a plurality of the cells including cells expressing the test polypeptide as a reference cell population; the method comprising: a reference amount obtaining step of measuring the expression amount of the test polypeptide in the reference cell group and obtaining it as a reference amount; a reference amount analyzing step of analyzing the reference amount for its expression amount; and a setting step of setting the reference range based on the results of the analysis, wherein the measurement process comprises: a measurement cell sorting step of sorting a plurality of the cells into a cell group for measurement; an expression amount measuring step of measuring the expression amount of the test polypeptide in the cell group for measurement and obtaining it as a test expression amount; and a presentation amount measuring step of measuring the amount of the test polypeptide present on the cell membrane in the cell group for measurement and obtaining it as a test presentation amount, wherein the test presentation amount changes according to the structural stability of the test polypeptide.

16. A method for measuring fluctuations in three-dimensional structure formation ability under target conditions, comprising: a control value measurement step of measuring a three-dimensional structure formation value under control conditions according to the method of claim 15 and obtaining a control value; a treatment value measurement step of measuring a three-dimensional structure formation value under the target conditions according to the method of claim 15 and obtaining a treatment value; and a calculation step of calculating a fluctuation value based on the obtained control value and treatment value.

17. A method for screening conditions for the formation of a three-dimensional structure of a test polypeptide in a cell, comprising: a control value measurement step of measuring a three-dimensional structure formation value under control conditions according to the method of claim 15 and obtaining a control value; a candidate value measurement step of measuring a three-dimensional structure formation value under candidate conditions according to the method of claim 15 and obtaining a candidate value; and a determination step of determining that the candidate conditions are suitable for the formation of a three-dimensional structure of the test polypeptide if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for the formation of a three-dimensional structure of the test polypeptide if the candidate value is lower than the control value.

18. A method for measuring the ability of a test polypeptide to maintain cell membrane localization in cells, wherein the cells are capable of transiently expressing the test polypeptide as a cell membrane protein, the method comprising: an expression step of expressing the test polypeptide in a plurality of the cells; a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; a measurement step of measuring a test expression amount and a test presentation amount of the test polypeptide in a cell population sorted for measurement; an extraction step of extracting information on the test expression amount and the test presentation amount for cells whose test expression amount is within the reference range; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a cell membrane localization value acquisition step of acquiring a cell membrane localization value from the relational equation, wherein the reference range setting step comprises: a confirmation step of confirming whether or not the test polypeptide is expressed in the cells; a reference cell sorting step of sorting a plurality of the cells including cells expressing the test polypeptide as a reference cell population; the method comprising: a reference amount obtaining step of measuring the expression amount of the test polypeptide in the reference cell group and obtaining the amount as a reference amount; a reference amount analyzing step of analyzing the reference amount for its expression amount; and a setting step of setting the reference range based on the results of the analysis, wherein the measurement process comprises: a measurement cell sorting step of sorting a plurality of the cells into a cell group for measurement; an expression amount measuring step of measuring the expression amount of the test polypeptide in the cell group for measurement and obtaining the amount as a test expression amount; and a presentation amount measuring step of measuring the amount of the test polypeptide present on the cell membrane in the cell group for measurement and obtaining the amount as a test presentation amount, wherein the test presentation amount varies according to the cell membrane localization of the test polypeptide.

19. A method for measuring fluctuations in the ability to maintain cell membrane localization under target conditions, comprising: a control value measurement step of measuring a cell membrane localization value under control conditions according to the method of claim 18 and obtaining a control value; a treatment value measurement step of measuring a cell membrane localization value under the target conditions according to the method of claim 18 and obtaining a treatment value; and a calculation step of calculating a fluctuation value based on the obtained control value and treatment value.

20. A method for screening conditions for maintaining the cell membrane localization of a test polypeptide in a cell, comprising: a control value measurement step of measuring a cell membrane localization value under control conditions according to the method of claim 18 and obtaining a control value; a candidate value measurement step of measuring a cell membrane localization value under candidate conditions according to the method of claim 18 and obtaining a candidate value; and a determination step of determining that the candidate conditions are suitable for maintaining the cell membrane localization of the test polypeptide if the candidate value is higher than the control value, and / or determining that the candidate conditions are not suitable for maintaining the cell membrane localization of the test polypeptide if the candidate value is lower than the control value.

21. The method of any one of claims 18 to 20, wherein the test polypeptide is a G protein-coupled receptor.

22. A program for calculating a higher-order structure formation value or a cell membrane localization value of a test polypeptide in a cell, the program being configured to cause a computer to execute: a reference range setting step of analyzing a reference amount obtained from a cell population sorted for reference and setting a reference range for the expression amount of the test polypeptide; an extraction step of extracting information on the test expression amount and the test presentation amount of the test polypeptide for cells whose test expression amount is within the reference range, based on the test expression amount and the test presentation amount of the test polypeptide measured in a cell population sorted for measurement; a relational equation derivation step of deriving a relational equation between the test expression amount and the test presentation amount from the extracted information; and a higher-order structure formation value acquisition step of acquiring a higher-order structure formation value from the relational equation or a cell membrane localization value acquisition step of acquiring a cell membrane localization value from the relational equation, wherein the reference range setting step includes: a reference amount acquisition step of acquiring the expression amount of the test polypeptide measured in the sorted reference cell population as a reference amount; a reference amount analysis step of analyzing the reference amount for its expression amount; the program further comprising a setting step of setting the reference range based on the result of the analysis.

23. The program described in claim 22, wherein the reference range setting process further includes a confirmation step of confirming whether or not the test polypeptide is expressed in each cell based on the expression level of the test polypeptide in the cell, and a reference cell separation step of obtaining data for reference from a cell group containing cells expressing the test polypeptide.

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