A method for analyzing the interactions between microscopic states in protein / polypeptide assembly

Abstract

The present invention provides a method for analyzing the interactions between various microscopic states in protein / polypeptide assembly. The method provided by the present invention realizes the structural analysis of multiple microscopic states of proteins / polypeptides, establishes the relative energy relationship of each microscopic state, quantitatively analyzes the selectivity of interactions between various thermodynamic microscopic states in the ensemble, and proves that there are significant differences in the selectivity of interactions between various microscopic states of different protein / polypeptide assemblies. The present invention is of great significance for the development of conformational ensemble characterization technology and the understanding of the interactions between thermodynamic microscopic states.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine, and particularly relates to a method for analyzing the interaction between various microscopic states in protein / polypeptide assembly. Background Art

[0002] Proteins are the basic functional units of most life activities. They regulate many physiological processes such as intracellular material transport, signal transduction, metabolic regulation, catalysis, and modification, and are the main executors of life activities. Amino acids are the basic building blocks of proteins. Amino acids form polypeptide chains through dehydration condensation and finally form proteins with specific structures through spatial folding. Proteins are in a constantly moving state, and there are many different conformational states. The collection of protein conformations is called the conformational ensemble. The conversion between protein conformations affects the function. A slight change in the structure of its key part may lead to a complete loss of its function.

[0003] With the development of molecular biology and structural biology, in the analysis of protein conformational ensembles, the main experimental methods include Nuclear magnetic resonance (NMR) spectroscopy, Small-angle X-ray scattering (SAXS), cryo-electron microscopy, circular dichroism spectroscopy, Fourier transform infrared spectroscopy, etc. Theoretical simulations, especially molecular dynamics simulations, provide important information for revealing protein structural ensembles. Computational research methods include replica exchange molecular dynamics simulations, multiple kinetics, and biased exchange multiple kinetics methods, etc. Currently, different integration methods have been developed to study protein conformation and dynamics. These methods usually use experimental data as structural constraints and combine simulation calculations to map protein conformational ensembles.

[0004] NMR is the most commonly used method for studying protein conformational ensembles. It can analyze the kinetic information of conformational transitions by measuring the structure and accurate dynamic parameters of proteins in solution and identifying microscopic states with relatively small proportions. However, when multiple states coexist in the conformational ensemble, it is usually difficult to characterize them structurally. In addition, it is also extremely challenging to study the conformations of large protein assemblies and proteins in non-solution systems. Studying the multiple microscopic states of proteins by experimental methods remains a research difficulty. Summary of the Invention

[0005] To make up for the deficiencies of the prior art, the present invention provides a method for analyzing the interactions between various microscopic states in protein / polypeptide assembly. The scanning tunneling microscopy (STM) with sub-molecular level spatial resolution ability is applied to conduct research, revealing the polymorphic structures of the thermodynamic microscopic states of the protein / polypeptide assembly, statistically analyzing the distribution probabilities of different microscopic states, and deducing the relative energy relationships of each thermodynamic microscopic state. Further, the selectivity of the interactions between each thermodynamic microscopic state is analyzed, and quantitative analysis of homogeneous and heterogeneous assemblies is carried out.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] The first aspect of the present invention provides a method for analyzing the interactions between various microscopic states of a protein / polypeptide assembly, and the method includes the following steps:

[0008] (1) Analyze the geometric features of the STM image of the protein / polypeptide assembly;

[0009] (2) Analyze the structural polymorphism in the protein / polypeptide assembly;

[0010] (3) Analyze the relative energy relationship of different microscopic states of the protein / polypeptide;

[0011] (4) Analyze the selectivity of the interactions between each microscopic state in the protein / polypeptide assembly.

[0012] Furthermore, the STM image is obtained by scanning with a multi-mode scanning tunneling microscope.

[0013] Furthermore, step (3) includes calculating the relative energy difference between different microscopic states.

[0014] Furthermore, the calculation formula for the relative energy difference is:

[0015]

[0016] where k B is the Boltzmann constant, T is the absolute temperature, E i and P i are the energy and distribution probability of state i respectively, and E j and P j are the energy and distribution probability of state j respectively.

[0017] Furthermore, cluster analysis is performed on the microscopic states according to the relative energy difference data of different microscopic states.

[0018] Furthermore, the method of cluster analysis is selected from the k-means clustering method.

[0019] Furthermore, the k-means clustering method analysis includes screening the cluster S that satisfies the following formula i:

[0020]

[0021] where μ i is the average value of all points in cluster S i .

[0022] Furthermore, the cluster analysis also includes evaluating the clustering results of the k-means clustering method.

[0023] Furthermore, the elbow method in R language is used to evaluate the clustering results of the k-means clustering method.

[0024] Furthermore, the factoextra package in R language is used to evaluate the clustering results of the k-means clustering method.

[0025] Furthermore, the selectivity of the interactions between the microscopic states in step (4) of protein / polypeptide assembly includes homogeneous assembly or heterogeneous assembly.

[0026] Furthermore, in step (4), the selectivity of the interactions between the microscopic states in protein / polypeptide assembly is quantitatively analyzed by the sum P(homo) value of the probabilities of homogeneous assembly through the interactions between the respective microscopic states.

[0027] Furthermore, the closer the P(homo) value is to 1, the higher the tendency of homogeneous assembly; on the contrary, the higher the tendency of heterogeneous assembly.

[0028] The second aspect of the present invention provides an analysis device for protein / polypeptide microscopic states, the device includes a memory and a processor, the memory is used for storing program instructions, and the processor is used for calling the program instructions, and the program instructions execute the method described in the first aspect of the present invention.

[0029] The third aspect of the present invention provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method described in the first aspect of the present invention.

[0030] The fourth aspect of the present invention provides a system for analyzing the interactions between the microscopic states in protein / polypeptide assembly, the system includes:

[0031] An acquisition unit, configured to acquire the STM image of the protein / polypeptide;

[0032] A processing unit, configured to analyze and process the acquired STM image according to the method described in the first aspect of the present invention;

[0033] A result output unit, configured to display the selectivity of the interactions between the microscopic states in protein / polypeptide assembly according to the analysis result.

[0034] Further, the STM image is obtained by scanning with a multi-mode scanning tunneling microscope.

[0035] The fifth aspect of the present invention provides an analysis device for the microscopic states of proteins / polypeptides, the device comprising a microscopic scanning device and a calculation and output device; the calculation and output device is selected from the analysis equipment described in the second aspect of the present invention, the computer-readable storage medium described in the third aspect of the present invention, or the system described in the fourth aspect of the present invention.

[0036] Further, the analysis device further comprises an assembly formation device.

[0037] Advantages and beneficial effects of the present invention:

[0038] The analysis method for the interactions between microscopic states in the protein / polypeptide assembly provided by the present application can analyze the selectivity of the interactions between microscopic states in different protein / polypeptide assemblies, which is of great significance for the development of conformational ensemble characterization techniques and the understanding of the interactions between microscopic states. Description of the Drawings

[0039] Figure 1 is the assembly structure diagram of hIAPP(8-37), where 1A is the STM image of the hIAPP(8-37) assembly, and 1B is the polypeptide chain spacing diagram;

[0040] Figure 2 is the polymorphism analysis diagram in the molecular assembly structure of hIAPP(8-37);

[0041] Figure 3 is the k-means clustering analysis diagram of the energy values of each thermodynamic microscopic state of the hIAPP(8-37) assembly structure, where 3A is the k-means clustering analysis diagram using the elbow method, and 3B is the analysis diagram with two clusters marked in different colors;

[0042] Figure 4 is the analysis diagram of each thermodynamic microscopic state of the hIAPP(8-37) assembly structure;

[0043] Figure 5 is the interaction diagram between each thermodynamic microscopic state in the hIAPP(8-37) assembly structure;

[0044] Figure 6 is the heat map of the interaction between each thermodynamic microscopic state in the hIAPP(8-37) assembly structure;

[0045] Figure 7 is the single-molecule imaging diagram of different protein / polypeptide assemblies, where 7A is the single-molecule imaging diagram of the hIAPP(8-37) assembly, and 7B is the single-molecule imaging diagram of the Abeta42 assembly;

[0046] Figure 8 It is a heat map of the interactions between various micro-thermodynamic microstates in different protein / polypeptide assemblies. Among them, 8A is the heat map of the interaction of hIAPP(8 - 37), and 8B is the heat map of the interaction of Abeta42. Detailed implementation mode

[0047] The present invention provides a method for analyzing the interactions between various microstates of a protein / polypeptide assembly, and the method includes the following steps:

[0048] (1) Analyze the geometric features of the STM image of the protein / polypeptide assembly;

[0049] (2) Analyze the structural polymorphism in the protein / polypeptide assembly;

[0050] (3) Analyze the relative energy relationship of different microstates of the protein / polypeptide;

[0051] (4) Analyze the selectivity of the interactions between various microstates in the protein / polypeptide assembly.

[0052] Among them, the STM image is obtained by scanning with a multi-mode scanning tunneling microscope.

[0053] In the present invention, the terms "protein", "polypeptide", "peptide" or "oligopeptide" refer to any composition comprising two or more amino acids linked together by peptide bonds. It should be understood that polypeptides often contain amino acids different from the 20 naturally occurring amino acids, and many amino acids, including terminal amino acids, can be modified in a specific polypeptide either by natural processes such as glycosylation and other post-translational modifications, or by chemical modification techniques well-known in the art. Known modifications that may be present in the polypeptides of the present invention include, but are not limited to, acetylation, acylation, ADP-ribosylation, amidation, covalent attachment of flavonoid or heme moieties, covalent attachment of polynucleotides or polynucleotide derivatives, covalent attachment of lipids or lipid derivatives, covalent attachment of phosphatidylinositol, cross-linking, cyclization, disulfide bond formation, demethylation, formation of covalent cross-links, cystine formation, pyroglutamate formation, formylation, γ-carboxylation, glycosylation, formation of glycosylphosphatidylinositol (GPI) membrane anchors, hydroxylation, iodination, methylation, myristoylation, oxidation, proteolysis, phosphorylation, prenylation, racemization, selenoylation, sulfation.

[0054] In some embodiments of the present invention, the multi-mode scanning tunneling microscope is also referred to as a "scanning tunneling microscope" or a "tunneling scanning microscope", and is an instrument for detecting the surface structure of a substance by using the tunneling effect in quantum theory.

[0055] As a scanning probe microscopy tool, the scanning tunneling microscope allows scientists to observe and position individual atoms, with a higher resolution than other similar atomic force microscopes. In addition, the scanning tunneling microscope can precisely manipulate atoms using the probe tip at low temperatures (4K), so it is both an important measurement tool and a processing tool in nanotechnology.

[0056] Step (3) includes performing cluster analysis on the microstates based on the energy data between the microstates.

[0057] In some embodiments of the present invention, cluster analysis or clustering is the task of assigning a collection of objects to groups, also called clusters, such that objects within the same cluster are more similar to each other than those in other clusters. Cluster analysis groups objects based on the information found in the data that describes the objects or their relationships. The aim is that the objects in a group will be similar to each other and different from the objects in other groups. The greater the similarity within the groups and the greater the differences between the groups, the "better" or clearer the clustering.

[0058] Appropriate clustering algorithms and parameter settings (including values such as the distance function to be used, density thresholds, or the number of expected clusters) depend on the individual data set and the intended use of the results. Cluster analysis is typically an iterative process of interactive multi-objective optimization or knowledge discovery involving trial and error. It is usually necessary to modify the data preprocessing and model parameters until the results achieve the desired properties.

[0059] Any standard clustering technique such as Agglomerative, Single-Pass, or K-Means can be used for the analysis of the present invention.

[0060] In a specific embodiment of the present invention, the method of cluster analysis is selected from the k-means clustering method. The k-means clustering algorithm is an iterative clustering analysis algorithm. Its steps are as follows: initially divide the data into k groups, then randomly select k objects as the initial cluster centers, and then calculate the distance between each object and each seed cluster center, and assign each object to the cluster center closest to it. The cluster centers and the objects assigned to them represent a cluster. Each time a sample is assigned, the cluster centers of the clusters will be recalculated based on the existing objects in the cluster. This process will be repeated continuously until a certain termination condition is met. The termination condition can be that no (or the minimum number of) objects are reassigned to different clusters, no (or the minimum number of) cluster centers change anymore, or the sum of squared errors is locally minimized.

[0061] Cluster analysis also includes evaluating the clustering results of the k-means clustering method; using the elbow method in the R language to evaluate the clustering results of the k-means clustering method.

[0062] R is a complete software system for data processing, computing, and mapping. Its functions include: a data storage and processing system; array operation tools (especially powerful in vector and matrix operations); a complete and coherent statistical analysis tool; excellent statistical mapping capabilities; a simple and powerful programming language: capable of manipulating data input and output, implementing branching and looping, and allowing users to customize functions.

[0063] In the present invention, the elbow method is used to reflect the true number of data clusters. Generally, as the number of clusters k increases, the sample division will be more refined, and the aggregation degree of each cluster will gradually increase. Then, the sum of the squared errors (SSE) will naturally gradually decrease. When k is less than the true number of clusters, the decline rate of SSE will be large. When k reaches the true number of clusters, the return of the aggregation degree obtained by increasing k will rapidly become smaller. Therefore, the decline rate of SSE will suddenly decrease and then level off as the value of k continues to increase. That is to say, the relationship graph between SSE and k is in the shape of an elbow, and the k value corresponding to this elbow is the true number of data clusters.

[0064] The selectivity of the interactions between the microscopic states in step (4) of protein / polypeptide assembly includes homogeneous assembly or heterogeneous assembly.

[0065] In some embodiments of the present invention, homogeneous or heterogeneous assemblies are formed between the thermodynamic microscopic states of proteins / polypeptides through intermolecular interactions. Among them, homogeneous assembly refers to the self-assembly of the same thermodynamic microscopic states, and heterogeneous assembly refers to the co-assembly of different thermodynamic microscopic states.

[0066] The present invention provides an analysis device for protein / polypeptide microscopic states. The device includes a memory and a processor. The memory is used to store program instructions, and the processor is used to call the program instructions to execute the above method.

[0067] In some embodiments of the present invention, any device capable of implementing the method and / or recording the results can be used to implement the method described in the present invention and / or record the results. Examples of devices that can be used include, but are not limited to, electronic computing devices, including all types of computers. When the method described in the present invention is implemented and / or recorded on a computer, the computer program that can be used to configure the computer to implement the steps of the method can be included in any computer-readable medium capable of containing the computer program. Examples of computer-readable media that can be used include, but are not limited to, magnetic disks, CD-ROMs, DVDs, ROMs, RAMs, or other memories and computer storage devices. The computer program that can be used to configure the computer to implement the steps of the method and / or record the results can also be provided on an electronic network, such as the Internet, an intranet, or other networks.

[0068] The present invention also provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the above method.

[0069] Those skilled in the art of the present technology should understand that the present invention can be implemented as a device, a method, or a computer program product. Therefore, the present invention can be specifically implemented in the following forms: it can be completely hardware, can also be completely software (including firmware, resident software, microcode, etc.), or can also be a combination of hardware and software. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, which contain computer-readable program codes.

[0070] The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0071] A computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0072] The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination of the foregoing.

[0073] The computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0074] The present invention also provides a system for analyzing the interactions between microscopic states in protein / polypeptide assembly, the system comprising: an acquisition unit for acquiring the STM image of the protein / polypeptide; a processing unit for analyzing and processing the acquired STM image according to the above method; and a result output unit for displaying the selectivity of the interactions between microscopic states in protein / polypeptide assembly according to the analysis result.

[0075] In some embodiments of the present invention, "system" is a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other words can achieve the same purpose, the said words may be replaced by other expressions, such as "device", "unit".

[0076] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. The following embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. Any simple improvement made according to the essence of the present invention falls within the scope of the present invention claimed.

[0077] Example 1 Selective Analysis of Interactions between Protein Microstates

[0078] 1.1 Experimental Materials

[0079] The hIAPP(8-37) polypeptide was purchased from GuoPeptide Biotechnology Co., Ltd. The sample was a white powdery solid, verified by high performance liquid chromatography (HPLC) and mass spectrometry, with a purity > 98%.

[0080] 1,1,1,3,3,3-Hexafluoro-2-propanol was purchased from Beijing Innochem Science & Technology Co., Ltd.

[0081] 1.2 Experimental Methods

[0082] (1) STM Single-Molecule Imaging of hIAPP(8-37) Assemblies

[0083] For hIAPP(8-37) that has reached a thermodynamic equilibrium state under solution conditions, with STM having ultra-high spatial resolution as the characterization means, the structure of hIAPP(8-37) in the assembly was characterized at the single-molecule level. The multi-mode scanning tunneling microscope detected the local electron state density of hIAPP(8-37) adsorbed on the surface of highly oriented pyrolytic graphite in constant current mode at room temperature in an atmospheric environment. The atomically sharp STM tip was prepared by mechanical force processing combined with current pulses. The geometric features of hIAPP(8-37) single molecules in the STM image were measured and statistically analyzed. The spacing between adjacent peptide chains in the single-molecule image was statistically analyzed to reveal the periodic law of the structural changes in the assembly. The distance between adjacent molecular chains was in line with the peptide chain spacing characteristics of the β-sheet structure, indicating that hIAPP(8-37) formed a β-sheet assembly structure.

[0084] (2) Structural Polymorphism Analysis of the Thermodynamic Microstates of hIAPP(8-37) in the Assembly

[0085] Measure and statistically analyze the hIAPP(8-37) assembly structure obtained in STM imaging. Measure the peptide chain length in the β-sheet (counting the number of peptide chains > 500), and obtain the length distribution of the peptide chains in the β-sheet structure. Based on the geometric morphology of the peptide chains in the STM single-molecule image and combined with the literature reports, confirm whether hIAPP(8-37) has a parallel β-sheet structure. Taking the distance between two adjacent residues on a peptide chain in the parallel β-sheet structure as 0.325 nm as the calculation basis, calculate the number and distribution of amino acid residues constituting the β-sheet domain of the peptide chain. Different lengths of the β-sheet domain represent different thermodynamic microstates of hIAPP(8-37). Thus, obtain the microstate ensemble and probability distribution characteristics of the β-sheet structure of the hIAPP(8-37) assembly. The hIAPP(8-37) ensemble contains n kinds of thermodynamic microstates, and this value is an important quantitative index of the structural polymorphism of hIAPP(8-37).

[0086] (3) Analysis of the relative energy relationship of different thermodynamic microstates of hIAPP(8-37) in the assembly

[0087] According to the β-sheet domain ensemble and probability distribution obtained in step (2), analyze the relative energy relationship of different thermodynamic microstates. The analysis method is as follows:

[0088] A molecule in a thermodynamic equilibrium state has n possible thermodynamic microstates, and the energy (E i ) of each thermodynamic microstate and the occurrence probability (P i ) follow the Maxwell-Boltzmann equation:

[0089]

[0090] where k B is the Boltzmann constant and T is the absolute temperature. Then the energy difference ΔE i and E j ) of any two states i and j is: i,j :

[0091]

[0092] Calculate the relative energy difference between any two thermodynamic microstates of hIAPP(8-37) in the assembly structure through the above formula.

[0093] Based on the energy analysis data among thermodynamic microstates, the k-means clustering method is used to perform clustering analysis on each microstate of hIAPP(8-37). The purpose of this analysis is to divide n points (i.e., n kinds of thermodynamic microstates) into k clusters, so that each point belongs to the cluster corresponding to the mean value (i.e., the cluster center) closest to it. Specifically, k-means clustering divides n observations into k sets, so that the sum of squared errors within the group is minimized, that is, to find the cluster S that satisfies the following formula i :

[0094]

[0095] where μ i is the average value of all points in cluster S i . The number of clusters k is another important indicator reflecting the structural polymorphism of the microstates of hIAPP(8-37).

[0096] The elbow method in R language is used to evaluate the clustering results of the k-means clustering method. The inflection point with the largest slope in the result graph is the true number of clusters of the data set. R language program:

[0097] install.packages("factoextra")

[0098] library(factoextra)

[0099] hIAPP<-as.matrix(c(4.595098426,2.515679609,1.417064796,0.766478108,0.405464802,0.095309629,0,0.084260229,0.467985544,0.744971454,0.984201805,1.76190647,2.985684753,3.208819215,3.496506337,3.496506337,3.901981545,4.595098426))# Enter n energy values in the parentheses#

[0100] fviz_nbclust(hIAPP,FUNcluster=kmeans,method="wss",k.max=16)

[0101] h1=kmeans(hIAPP,2)

[0102] plot(hIAPP,col=h1$cluster)

[0103] (4) Homogeneity and heterogeneity analysis of the interactions between the thermodynamic microstates of hIAPP(8 - 37) in the assembly The thermodynamic microstates of hIAPP(8 - 37) form homogeneous (self - assembly of the same thermodynamic microstates) or heterogeneous (co - assembly of different thermodynamic microstates) structures through intermolecular interactions. To reveal the homogeneous / heterogeneous assembly trend between the thermodynamic microstates of hIAPP(8 - 37), the structures and distribution probabilities of the adjacent microstates of each thermodynamic microstate are statistically analyzed. Using R language, a heatmap is used to display the probability distribution of the interaction between each thermodynamic microstate and other thermodynamic microstates in the hIAPP(8 - 37) assembly structure.

[0104] R language program:

[0105] install.packages("pheatmap")

[0106] library("pheatmap")

[0107] exp<-read.table("D: / R / hIAPP.new.txt",sep="\t",header=TRUE,row.names=1)

[0108] colnames(exp)<-c("7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25")

[0109] pheatmap(exp,cellwidth=11,cellheight=11,cluster_cols=F,cluster_rows=F,color=colorRampPalette(colors=c("white","red"))(1000),angle_col=0,display_numbers=F)

[0110] Statistically analyze the adjacent thermodynamic microstates of each thermodynamic microstate in the STM single - molecule image, calculate the sum of the probabilities of homogeneous assembly of the interactions between each thermodynamic microstate, P(homo), and quantitatively describe the tendency of homogeneous assembly of each thermodynamic microstate in the protein assembly. The closer the value of P(homo) is to 1, the higher the tendency of homogeneous assembly, and vice versa, the higher the tendency of heterogeneous assembly.

[0111] The diagonal region of the heat map represents homogeneous assembly, and the non-diagonal region represents heterogeneous assembly. The more concentrated in the diagonal region of the figure, the higher the tendency of homogeneity, and the more dispersed, the higher the tendency of heterogeneity.

[0112] 1.3 Experimental Results

[0113] (1) Single-molecule imaging of polypeptide assembly structure

[0114] As can be seen from the STM results, its assembly structure presents a typical lamellar structure ( Figure 1 ). The polypeptide shows a bright chain-like structure on the surface during assembly. The polypeptide chains are arranged parallel to each other and perpendicular to the direction of the stripe axis. The most probable measured value of the spacing between self-assembled polypeptide chains is , which belongs to the polypeptide chain spacing in the typical β-sheet structure. Therefore, the value measured in this experiment indicates that the polypeptide forms an ordered assembly structure in the form of β-sheets on the HOPG surface. In the β-sheet structure, the side chains of amino acid residues are all perpendicular to the plane of the folded sheet and alternately extend to the upper and lower sides of the plane.

[0115] (2) Analysis of structural polymorphism in polypeptide assembly

[0116] The core length distribution range of the polypeptide participating in the assembly is 2.6 - 7.5 nm, with different lengths, that is, the polypeptide assembly structure has polymorphism ( Figure 2 ). The spacing between adjacent two amino acid residues in the parallel β-sheet peptide chain is 0.325 nm. Based on the analysis of the polypeptide chain assembly length in the STM image, the number of residues participating in the assembly in the assembly structure is 7 - 24. The most probable length of the core peptide chain participating in the assembly is 4.2 nm, corresponding to 13 amino acid residues.

[0117] (3) Analysis of multiple thermodynamic microstates in polypeptide assembly structure

[0118] The results show that the energy levels of the thermodynamic microstates of various β-structures of hIAPP(8 - 37) can be divided into two clusters ( Figure 3 ). There are 18 different microstates formed in the self-assembly structure of hIAPP(8 - 37), and the microstate with a β-sheet domain composed of 13 residues has the highest occurrence probability. Specifically, the highest energy difference between different thermodynamic microstates is calculated to be 4.60 k B T. The microstate with a β-sheet domain composed of 13 amino acids is the most optimal in terms of energy ( Figure 4 ).

[0119] (4) Selectivity of the interaction between thermodynamic microstates in polypeptide assembly

[0120] Such as Figure 5As shown, the red represents the interaction between homogeneous thermodynamic microstates, and the gray represents heterogeneous assembly. The calculated P(homo) value of the hIAPP(8-37) assembly structure is 14.8%. This indicates that the hIAPP(8-37) assembly structure has a greater tendency towards heterogeneous assembly.

[0121] The probability distribution of the recognition and assembly between each microstate in the polypeptide assembly structure is shown in a heatmap. The heatmap of hIAPP(8-37) assembly is relatively dispersed, indicating that its assembly structure has a greater tendency towards heterogeneous assembly ( Figure 6 ).

[0122] Example 2 Selectivity Analysis of Interactions between Different Protein Microstates

[0123] 2.1 Experimental Materials

[0124] The Abeta42 polypeptide was purchased from Guopeptide Biotechnology Co., Ltd. The sample was a white powdery solid, and its purity was verified to be >98% by high-performance liquid chromatography (HPLC) and mass spectrometry.

[0125] The remaining experimental materials were the same as those in Example 1

[0126] 2.2 Experimental Methods

[0127] The experimental methods were the same as those in Example 1

[0128] 2.3 Experimental Results

[0129] (1) Single-Molecule Imaging of Different Protein / Polypeptide Assemblies

[0130] The STM images of the molecular assembly structures of hIAPP(8-37) and Abeta42 are as Figure 7 shown.

[0131] (2) Selectivity Differences in Interactions between Thermodynamic Microstates in Different Protein / Polypeptide Assemblies

[0132] Analyze the structures of hIAPP(8-37) and Abeta42 and the relative energy relationships in different microstates. As shown in Table 1 and Figure 8 shown, there are significant differences in the selectivity of interactions between thermodynamic microstates in different protein / polypeptide assemblies. The heatmap of hIAPP(8-37) is relatively dispersed, with a P(homo) value of 14.8%. The heatmap of Abeta42 is concentrated on the diagonal, and the P(homo) value of its assembly structure is 24.8%. Compared with hIAPP(8-37), the Abeta42 assembly structure has a greater tendency towards homogeneous assembly.

[0133] The probability of homogeneous assembly of Abeta42 is 24.8%, and the probability of homogeneous assembly of hIAPP is 14.8%.

[0134] Table 1 Statistical analysis of energy of each thermodynamic microstate and interaction selectivity in different protein / polypeptide assemblies

[0135]

[0136] The description of the above embodiments is only used to understand the method and its core idea of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims

1. A method for analyzing the interactions between microscopic states of a protein / polypeptide assembly, characterized in that, The method includes the following steps: (1) Analyze the geometric features of the STM image of the protein / polypeptide assembly; (2) Analyze the structural polymorphism in the protein / polypeptide assembly; (3) Analyze the relative energy relationship of different microscopic states of the protein / polypeptide; (4) Analyze the selectivity of the interaction between different microscopic states in the protein / polypeptide assembly; Perform cluster analysis on the microscopic states based on the relative energy difference data of different microscopic states; The method of cluster analysis is selected from k - k-means clustering method; k - The analysis of the K-means clustering method includes screening clusters that satisfy the following formula S i : Among them μ i is the average value of all points in the clustering S i ; The selectivity of the interaction between different microscopic states in step (4) of the protein / polypeptide assembly includes homogeneous assembly or heterogeneous assembly; The STM image is obtained by scanning with a multi-mode scanning tunneling microscope.

2. The method according to claim 1, characterized in that Step (3) includes the calculation of the relative energy difference between different microscopic states; The calculation formula for the relative energy difference is: Among them, k B is the Boltzmann constant, T is the absolute temperature, E i and P i are the energy and distribution probability of state i respectively, E j and P j are the energy and distribution probability of state j respectively.

3. The method according to claim 1, characterized in that, Cluster analysis also includes evaluating k - the clustering results of the k-means clustering method.

4. The method according to claim 3, characterized in that, Evaluation using the elbow method in R language k - Clustering results of the k-means clustering method.

5. The method according to claim 4, wherein Evaluate the clustering results of the mean clustering method using the factoextra package in R language k - The clustering results of the mean clustering method 6. The method according to claim 1, wherein The probability sum of the homogeneous assembly through the interactions between various microstates in step (4) P(homo) is used to quantitatively analyze the selectivity of the interactions between various microstates in protein / polypeptide assembly.

7. The method according to claim 6, wherein The P(homo) closer the value is to 1, the higher the tendency of homogeneous assembly, and vice versa, the higher the tendency of heterogeneous assembly.

8. An analysis device for the microscopic state of a protein / polypeptide, characterized in that, The device includes a memory and a processor. The memory is used to store program instructions, and the processor is used to call the program instructions. The program instructions execute the method according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method according to any one of claims 1-7.

10. A system for analyzing the interactions between various microscopic states in protein / polypeptide assembly, characterized in that, The system includes: An acquisition unit for acquiring the STM image of the protein / polypeptide; A processing unit for analyzing and processing the acquired STM image according to the method according to any one of claims 1-7; A result output unit for displaying the selectivity of the interaction between different microscopic states in the protein / polypeptide assembly according to the analysis result.

11. The system according to claim 10, wherein The STM image is obtained by scanning with a multi-mode scanning tunneling microscope.

12. An analysis device for the microscopic state of a protein / polypeptide, characterized in that, The device includes a microscopic scanning device and a calculation and output device; the calculation and output device is selected from the analysis device according to claim 8, the computer-readable storage medium according to claim 9, or the system according to claim 10 or 11.

13. The analysis device according to claim 12, characterized in that, The analysis device further includes an assembly formation device.

Images