Assessment optimization method and device for secondary mass spectrum identification sequence

Abstract

The invention provides an evaluation optimization method and device for a secondary mass spectrometry identification sequence, and belongs to the technical field of detection, and the method comprises the following steps: generating a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced with a random subsequence with the same fragment molecular mass, and a plurality of first candidate sequences corresponding to the first original sequence are obtained; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry; constructing an evaluation sequence set based on the plurality of first original sequences and the plurality of corresponding first candidate sequences, and calculating the matching degree of each sequence in the evaluation sequence set and the secondary mass spectrum; and selecting a first sequence from the evaluation sequence set based on the matching degree, and determining the first sequence as an evaluation optimization result. According to the evaluation and optimization method and device for the secondary mass spectrum identification sequence, the evaluation and optimization effect of the secondary mass spectrum identification sequence can be improved.

Description

Technical Field

[0001] The present disclosure belongs to the field of detection technology, and more specifically, to a method and device for evaluating and optimizing a secondary mass spectrometry identification sequence. Background Art

[0002] De novo sequencing using mass spectrometry data generated by liquid chromatography-mass spectrometry (LC-MS / MS) has become a key method in proteomics research. Dynamic programming is the main method for de novo sequencing. This technology has the disadvantages of high computational time complexity and difficult application of complex scoring functions. Previous optimization directions tended to reduce the accuracy of dynamic programming calculations, such as expanding the calculation unit from 0.01 Dalton to 0.1 Dalton, and then comparing the peptide sequence generated by de novo sequencing with the secondary mass spectrometry database to achieve the purpose of optimization. However, if the database does not contain the corresponding peptide sequence, the credibility of the optimization result is very low. Another optimization direction is to find homologous mass spectra in the secondary mass spectrometry set through mass spectrometry parameters such as retention time to compare the results. The disadvantage of this method is that the mass spectra of the same experimental group use the same dynamic programming method, the homologous mass spectrometry identification results affect each other, and the noise peaks in the mass spectrometry will increase the interference of the identification results. Therefore, there is a possibility that the optimization results will deteriorate. Summary of the invention

[0003] The purpose of the present invention is to provide a method and device for evaluating and optimizing a secondary mass spectrometry identification sequence, so as to improve the evaluation and optimization effect of the secondary mass spectrometry identification sequence.

[0004] In a first aspect of the embodiments of the present disclosure, a method for evaluating and optimizing a secondary mass spectrometry identification sequence is provided, comprising: Generate a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced by a random subsequence with the same molecular mass of the fragment, to obtain a plurality of first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry; Constructing an evaluation sequence set based on the first original sequences and the corresponding first candidate sequences, and calculating the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum; A first sequence is selected from the evaluation sequence set based on the matching degree, and the first sequence is determined as an evaluation optimization result.

[0005] A second aspect of the disclosed embodiments provides an evaluation and optimization device for a secondary mass spectrometry identification sequence, comprising: A first generation module is used to generate a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced by a random subsequence with the same molecular mass of the fragment, to obtain a plurality of first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry; A first calculation module is used to construct an evaluation sequence set based on the first original sequences and the corresponding first candidate sequences, and calculate the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum; The first screening module is used to select a first sequence from the evaluation sequence set based on the matching degree, and determine the first sequence as the evaluation optimization result.

[0006] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned method for evaluating and optimizing secondary mass spectrometry identification sequences when executing the computer program.

[0007] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for evaluating and optimizing the secondary mass spectrometry identification sequence are implemented.

[0008] The beneficial effects of the evaluation and optimization method and device for secondary mass spectrometry identification sequence provided by the embodiments of the present disclosure are: In the disclosed embodiment, each fragment in the original sequence is first replaced with a random subsequence with the same molecular mass of the fragment, and an attempt is made to generate a first candidate sequence that better matches the secondary mass spectrum. Then, an evaluation sequence set is constructed based on multiple first original sequences and corresponding multiple first candidate sequences, and each sequence in the evaluation sequence set is matched with the secondary mass spectrum respectively. For sequences with a high degree of match, it indicates that the secondary mass spectrum contains sufficient and obvious peaks to support the analysis of this fragment portion. Based on this, a first sequence with a high degree of match can be selected from the evaluation sequence set, thereby achieving optimization of the evaluation of the first original sequence.

[0009] The disclosed embodiments can evaluate and optimize the identification results of the sequence without the help of database or other secondary mass spectrometry information, thus avoiding the influence of the database or other secondary mass spectrometry on the optimization results, and is conducive to improving the optimization effect of the secondary mass spectrometry identification sequence. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic diagram of a flow chart of a method for optimizing the evaluation of a secondary mass spectrometry identification sequence provided in an embodiment of the present disclosure; Figure 2 A schematic diagram of a mapping relationship between a first array and a second array provided in an embodiment of the present disclosure; Figure 3 A schematic diagram of a process for generating a first candidate sequence provided in an embodiment of the present disclosure; Figure 4 A schematic diagram of a construction process of an evaluation sequence set provided in an embodiment of the present disclosure; Figure 5 A structural block diagram of an evaluation and optimization device for a secondary mass spectrometry identification sequence provided in one embodiment of the present disclosure; Figure 6 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0013] The technical terms involved in the embodiments of the present disclosure are explained below.

[0014] Secondary mass spectrometry (MS / MS or Tandem MS) sequence identification is an important bioanalysis technology, widely used in proteomics, peptide analysis and other fields. This technology uses a tandem mass spectrometer to perform accurate mass analysis and sequence identification on protein or peptide samples. The generation process of secondary mass spectrometry identification sequence is as follows: Sample processing: First, the protein sample needs to go through extraction, purification and other steps, and then use specific proteases (such as trypsin) to cut the protein into smaller polypeptide fragments.

[0015] Primary mass spectrometry analysis: After the peptide sample is ionized, a primary mass spectrometer is used to perform preliminary mass analysis to obtain the mass-to-charge ratio (m / z) and relative abundance information of the peptide fragments.

[0016] Ion fragmentation: The specific peptide fragments selected in the primary mass spectrometry are further fragmented to produce fragment ions.

[0017] Secondary mass spectrometry analysis: The fragmented ions enter the mass spectrometer again for a more detailed mass analysis to obtain the mass-to-charge ratio and relative abundance information of the fragment ions.

[0018] Sequence identification: By comparing the secondary mass spectrometry data with the known protein database, bioinformatics tools are used to infer the amino acid sequence of the polypeptide fragment. Each amino acid sequence includes multiple sequentially arranged amino acid residues.

[0019] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , Figure 1 A schematic diagram of a flow chart of a method for evaluating and optimizing a secondary mass spectrometry identification sequence provided in an embodiment of the present disclosure, the method comprising: S101: Generate a first candidate sequence corresponding to each original sequence; wherein, each fragment in the first original sequence is replaced by a random subsequence with the same molecular mass of the fragment, to obtain multiple first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry.

[0021] In this embodiment, multiple protein identification sequences (or polypeptide sequences) can be obtained based on the secondary mass spectrometry data. By evaluating and optimizing the multiple protein identification sequences, a more accurate protein identification sequence can be obtained. Taking the first original sequence (that is, any protein identification sequence) as an example, the first original sequence usually contains multiple fragments, each of which is a short peptide consisting of several to dozens of amino acid residues, and each fragment is supported by a corresponding peak in the secondary mass spectrometry. By replacing each fragment with a random subsequence with the same molecular mass of the fragment, multiple first candidate sequences can be obtained.

[0022] For example, the first original sequence contains the first segment " ", the molecular weight of the first fragment is c1, and a random subsequence with a molecular weight of c1 can be constructed according to the molecular weight of each amino acid residue. The construction results include , , ..., By replacing the first fragment with the above 6 random subsequences respectively, 6 first candidate sequences can be obtained.

[0023] S102: constructing an evaluation sequence set based on the multiple first original sequences and the corresponding multiple first candidate sequences, and calculating the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum.

[0024] In this embodiment, based on the above method, multiple first candidate sequences corresponding to the multiple first original sequences can be obtained, an evaluation sequence set is constructed based on the multiple first original sequences and the corresponding multiple first candidate sequences, and each sequence in the evaluation sequence set is matched with the secondary mass spectrum respectively. For sequences with a high degree of matching, it indicates that the secondary mass spectrum contains sufficient and obvious peaks to support the analysis of this fragment portion.

[0025] Specifically, the same scoring function can be used to match multiple first candidate sequences with the secondary mass spectra to obtain the scores (i.e., matching degrees) of the first candidate sequences. Compared with the original sequence: If the score of the generated first candidate sequence drops significantly, it means that the original fragment (the corresponding fragment in the first original sequence) matches the secondary mass spectrum more closely than the random subsequence, and a slight change can greatly affect the score of the entire sequence.

[0026] If the scores are roughly the same, it means that the contribution of the random subsequence to the score of the first original sequence is similar to that of the original fragment, that is, the original fragment and the random subsequence are roughly equivalent, indicating that the fragment does not match the secondary mass spectrum well or the secondary mass spectrum does not contain enough obvious peaks to support the analysis of this fragment.

[0027] If the score of the generated first candidate sequence is higher than that of the first original sequence, it proves that the first original sequence can be optimized into the first candidate sequence.

[0028] Among them, the scoring function is a mathematical function used in multiple fields such as bioinformatics, machine learning, and statistics to evaluate the degree of match between an object (such as protein sequence, gene expression data, prediction model, etc.) and a certain standard or target. In proteomics or mass spectrometry data analysis, the scoring function is specifically used to evaluate the match between the predicted peptide sequence and the secondary mass spectrometry (MS / MS) data obtained from the experiment. Those skilled in the art can design the specific form of the scoring function according to actual needs, which will not be elaborated here.

[0029] S103: Selecting a first sequence from the evaluation sequence set based on the matching degree, and determining the first sequence as the evaluation optimization result.

[0030] In this embodiment, a first threshold can be set, and a sequence with a matching degree higher than the first threshold can be determined as a first sequence. For a sequence with a high matching degree, it indicates that the secondary mass spectrum contains sufficient and obvious peaks to support the analysis of this fragment part, and accordingly, a first sequence with a high matching degree can be selected from the evaluation sequence set, thereby realizing the evaluation optimization of the first original sequence.

[0031] It can be concluded from the above that this embodiment first replaces each fragment in the original sequence with a random subsequence with the same molecular mass of the fragment, thereby generating a new first candidate sequence, and then constructs an evaluation sequence set based on multiple first original sequences and corresponding multiple first candidate sequences, and matches each sequence in the evaluation sequence set with the secondary mass spectrum respectively. For sequences with a high degree of match, it indicates that the secondary mass spectrum contains sufficient and obvious peaks to support the analysis of this fragment part. Based on this, a first sequence with a high degree of match can be selected from the evaluation sequence set, thereby achieving optimization of the evaluation of the first original sequence.

[0032] This embodiment can evaluate and optimize the identification results of the sequence without the help of database or other secondary mass spectrometry information, avoiding the influence of the database or other secondary mass spectrometry on the optimization results, which is conducive to improving the accuracy of secondary mass spectrometry identification of the sequence.

[0033] In one embodiment of the present disclosure, the evaluation and optimization method of the secondary mass spectrometry identification sequence further includes: All fragment molecular masses between the first value and the second value are traversed with the first step length, a plurality of first subsequences corresponding to each fragment molecular mass are determined, and a plurality of first subsequences corresponding to the fragment molecular masses are obtained.

[0034] The sum of the molecular masses of the amino acid residues in the plurality of first subsequences corresponding to the molecular mass of any fragment is equal to the molecular mass of the fragment.

[0035] In this embodiment, a total of 20 basic amino acid residues are included, as well as amino acid residues with post-translational modifications and other marker modifications. Common amino acid residues include: glycine (Gly), alanine (Ala), valine (Val), leucine (Leu), etc.

[0036] The first value can be a smaller number, such as 0, 1, 2, etc. The second value is the upper limit of the molecular weight of the first subsequence fragment. The length of the first subsequence (that is, the number of amino acid residues contained) will increase exponentially with the size of the second value. In order to balance the time cost of the calculation and the length of the first subsequence, while considering the scheme of dividing the first original sequence fragments, the second value should be sufficient to contain at least three amino acid residue combinations, which is about 700 Daltons. With an accuracy of 0.01 Dalton as 1 calculation unit, the second value can be 70000 (700 / 0.01), and the first step length can be set to 0.01 Dalton, that is, 1 calculation unit.

[0037] For each fragment molecular mass between the first value and the second value, determine which amino acids the fragment molecular mass can be composed of. If a fragment molecular mass can be composed of one or more amino acids, the one or more amino acid combinations are used as multiple first subsequences corresponding to the fragment molecular mass. Otherwise, if a fragment molecular mass cannot be composed of one or more amino acids, the multiple first subsequences corresponding to the fragment molecular mass are empty (NULL).

[0038] The molecular weight of each fragment and the corresponding multiple first subsequences are saved accordingly, so that when a fragment (such as the first fragment) in the first original sequence is replaced, the first subsequence with the same molecular weight as the first fragment can be quickly found.

[0039] It can be concluded from the above that this embodiment pre-constructs a mapping relationship between the molecular mass of the fragment and the first subsequence, so that when a fragment (for example, the first fragment) in the first original sequence is replaced, the first subsequence with the same molecular mass as the first fragment can be quickly found, and the first subsequence is randomly arranged to obtain a random subsequence with the same molecular mass as the first fragment.

[0040] In one embodiment of the present disclosure, determining a plurality of first subsequences corresponding to the molecular mass of each fragment includes: For the molecular mass of the first fragment, traverse all the amino acid residues, If the molecular mass of the first fragment is equal to the molecular mass of the first amino acid residue, the first amino acid residue is determined as the first subsequence corresponding to the molecular mass of the first fragment; the molecular mass of the first fragment is the molecular mass of any fragment; If the molecular mass of the first fragment is greater than the molecular mass of the second amino acid residue, and there is a corresponding first subsequence for the molecular mass of the second fragment, the first subsequence corresponding to the molecular mass of the second fragment is combined with the second amino acid residue to obtain a second subsequence corresponding to the molecular mass of the first fragment; all second subsequences corresponding to the molecular mass of the first fragment are deduplicated to obtain all first subsequences corresponding to the molecular mass of the first fragment; The first amino acid residue and the second amino acid residue are any two amino acid residues; the molecular mass of the second fragment is the difference between the molecular mass of the first fragment and the molecular mass of the second amino acid residue.

[0041] In this embodiment, a specific implementation method for determining multiple first subsequences corresponding to the molecular mass of each fragment is provided. For any fragment molecular mass (e.g., the first fragment molecular mass), when determining multiple first subsequences corresponding to the first fragment molecular mass, all amino acid residues are traversed. If the first fragment molecular mass is equal to the molecular mass of a certain amino acid residue (e.g., the first amino acid residue), the first amino acid residue is determined as the first subsequence corresponding to the first fragment molecular mass; if the first fragment molecular mass is greater than the molecular mass of a certain amino acid residue (e.g., the second amino acid residue), the molecular mass of the second fragment is obtained by subtracting the molecular mass of the second amino acid residue from the molecular mass of the first fragment. If the second fragment molecular mass has a corresponding first subsequence, the first subsequence corresponding to the second fragment molecular mass is combined with the second amino acid residue to obtain the second subsequence corresponding to the first fragment molecular mass; if the second fragment molecular mass does not have a corresponding first subsequence, it indicates that the second fragment molecular mass cannot form any reasonable amino acid residue combination. If all amino acid residues are traversed and the corresponding second fragment molecular mass does not have a corresponding first subsequence, it indicates that the first fragment molecular mass cannot form any reasonable amino acid residue combination, that is, the first fragment molecular mass does not have a corresponding first subsequence.

[0042] For example, in a certain identification sequence, the molecular masses corresponding to amino acid residue a1, amino acid residue a2, and amino acid residue a3 are c1, c2, and c3, respectively. Amino acid residue a1 can be first used as the first subsequence corresponding to the fragment molecular mass c1, amino acid residue a2 can be used as the first subsequence corresponding to the fragment molecular mass c2, and amino acid residue a3 can be used as the first subsequence corresponding to the fragment molecular mass c3. When determining the first subsequence corresponding to the molecular mass of the fragment c4, if the molecular mass of the fragment c4 is greater than the molecular mass of the amino acid residue a3, and the molecular mass of the fragment (c4-||a3||) has a corresponding first subsequence (for example, amino acid residue a1), the first subsequence a1 and the amino acid residue a3 corresponding to the molecular mass of the fragment (c4-||a3||) are combined together to obtain the subsequence a1a3, and the subsequence a1a3 is used as the second subsequence corresponding to the molecular mass of the fragment c4; if the molecular mass of the fragment c4 is greater than the molecular mass of the amino acid residue a2, and the molecular mass of the fragment (c4-||a2||) does not have a corresponding first subsequence, it indicates that the second subsequence corresponding to the molecular mass of the fragment c4 is not added in this operation; it can continue to determine whether the molecular mass of the fragment (c4-||a1||) has a corresponding second subsequence, ..., and repeat this process until all amino acid residues are traversed to obtain the second subsequence corresponding to the molecular mass of the fragment c4. Using the same method, multiple second subsequences corresponding to other molecular masses of the fragment can be obtained.

[0043] After obtaining all the second subsequences corresponding to the molecular mass of the first fragment, considering that some second subsequences are mutually arranged and combined, it is necessary to perform deduplication processing on these mutually arranged and combined second subsequences. Specifically, all the second subsequences can be rearranged in alphabetical order. After the rearrangement, multiple second subsequences that are mutually arranged and combined become the same subsequence, and only one of the same subsequences is retained. For example, the second subsequence a1a3 and the second subsequence a3a1 are the same sequence after being arranged in alphabetical order, and only the sequence arranged in alphabetical order can be saved.

[0044] In one embodiment of the present disclosure, the evaluation and optimization method of the secondary mass spectrometry identification sequence further includes: storing a plurality of first subsequences in ascending order of fragment molecular weight into a first array, determining the fragment molecular weight as an index of a second array, performing multiple pointer storage operations, and storing a pointer of a third subsequence corresponding to each fragment molecular weight into a corresponding index position in the second array; the third subsequence is the first subsequence among a plurality of first subsequences corresponding to the same fragment molecular weight; If the number of the first subsequence corresponding to the molecular mass m of the fragment is greater than 0, the pointer corresponding to the molecular mass m of the fragment is increased by n+1 to obtain the pointer corresponding to the molecular mass m+1 of the fragment; If the number of the first subsequences corresponding to the fragment molecular mass m is equal to 0, determine the pointer corresponding to the fragment molecular mass m as the pointer corresponding to the molecular mass m + 1; n represents the number of the first subsequences corresponding to the fragment molecular mass m; when the fragment molecular mass m = 0, the corresponding pointer points to the starting position of the first array.

[0045] In this embodiment, the evaluation and optimization of the secondary mass spectrometry identification sequence are realized through a computer program. Multiple first subsequences can be stored in the first array A in advance. The multiple fragment molecular masses between the first value and the second value are used as the indexes of the second array M, and the second array M stores the pointers of the first subsequences corresponding to the multiple fragment molecular masses, which is convenient for the program to call the first subsequences.

[0046] Please refer to Figure 2 , first, in the order of increasing fragment molecular mass, store the multiple first subsequences corresponding to the multiple fragment molecular masses into the first array in sequence. For example, if the fragment molecular masses are c1 < c2, first store the first subsequences A 11 , A 12 ,..., A 1n into the first array, and then store the first subsequences A 21 , A 22 ,..., A 2u into the first array.

[0047] Then, store the pointer p of the first subsequence A 11 among the multiple first subsequences corresponding to the fragment molecular mass c1 into the c1 position of the second array, that is, M[c1] = p; assuming that in the previous embodiment, the number of the first subsequences corresponding to the fragment molecular mass c1 is n, and the fragment molecular mass c1 + 1 = c x , then increase the pointer corresponding to the fragment molecular mass c1 by n + 1 to obtain the pointer corresponding to the fragment molecular mass c x , that is, M[c x = p + n + 1; for another example, in the previous embodiment, it is obtained that there is no corresponding first subsequence for the fragment molecular mass c x , that is, the number of the first subsequences corresponding to the fragment molecular mass c x is 0, and the fragment molecular mass c x + 1 = c2, then use the pointer corresponding to the fragment molecular mass c x as the pointer corresponding to the fragment molecular mass c2. And so on, store the multiple fragment molecular masses and their corresponding multiple first subsequences in one-to-one correspondence.

[0048] It can be concluded from the above that in this embodiment, multiple first subsequences are stored in the first array A, multiple fragment molecular masses are used as indexes of the second array M, and the second array M stores pointers to the first subsequences corresponding to the multiple fragment molecular masses, so as to facilitate the computer program to call the first subsequence.

[0049] In one embodiment of the present disclosure, each fragment in the first original sequence is replaced with a random subsequence with the same molecular mass of the fragments, including: The first molecular mass of the first fragment is calculated based on the molecular masses of the amino acid residues in the first fragment; the first fragment is any fragment in the first original sequence.

[0050] A first pointer is searched from the second array based on the first molecular mass of the first fragment.

[0051] A second pointer is searched from the second array based on the second molecular mass; the second molecular mass is obtained by adding the first step length to the first molecular mass.

[0052] If the address pointed to by the second pointer is greater than the address pointed to by the first pointer, the first subsequence between the address pointed to by the first pointer and the address pointed to by the second pointer is determined as the fourth subsequence.

[0053] Randomly sorting the fourth subsequence to obtain a random subsequence having the same molecular mass as the first fragment; The first fragment is replaced by a random subsequence of fragments with the same molecular mass.

[0054] In this embodiment, a specific implementation method of replacing each fragment in the first original sequence with a random subsequence with the same molecular mass of the fragments is provided.

[0055] Taking the first fragment as an example, the molecular weights of the amino acid residues in the first fragment are added to obtain the first molecular weight of the first fragment (i.e., the molecular weight of the first fragment); then the first pointer stored in the index position corresponding to the first molecular weight is searched from the second array, the first molecular weight is increased by the first step length to obtain the second molecular weight, and the second pointer stored in the index position corresponding to the second molecular weight is searched from the second array. If the address pointed to by the second pointer is equal to the address pointed to by the first pointer, it indicates that the first molecular weight does not have a corresponding first subsequence, and the replacement of the first fragment can be stopped at this time. Otherwise, if the address pointed to by the second pointer is greater than the address pointed to by the first pointer, it indicates that the first molecular weight has a corresponding first subsequence, and the first subsequence corresponding to the first molecular weight is stored between the address pointed to by the first pointer and the address pointed to by the second pointer, the fourth subsequence (i.e., the first subsequence between the address pointed to by the first pointer and the address pointed to by the second pointer) is read, and the fourth subsequence is randomly sorted to obtain multiple random subsequences, and then the first fragment is replaced with multiple random subsequences respectively.

[0056] Please refer to Figure 2 , if the first molecular mass of the first fragment is c1, the first pointer stored in the index position corresponding to the first molecular mass c1 is searched from the second array to obtain M[c1]=p, and the second pointer stored in the index position corresponding to the second molecular mass is searched from the second array to obtain M[c1+1]=p+n+1, p+n+1>p, indicating that the first molecular mass c1 has a corresponding first subsequence, and the first subsequence A between the address pointed to by the first pointer p and the address pointed to by the second address p+n+1 is converted to 11 , A 12 , ..., A 1n As the first subsequence corresponding to the first molecular mass c1, the first subsequence A 11 , A 12 , ..., A 1n By performing random sorting, a plurality of random subsequences can be obtained, and then the first fragment can be replaced with the plurality of random subsequences respectively.

[0057] For example, the first molecular mass of the first fragment is c x , find the first molecular mass c from the second array x The first pointer stored in the corresponding index position is obtained by M[c x ]=p+n+1, find the second pointer stored in the index position corresponding to the second molecular mass from the second array to obtain M[c x +1]=p+n+1,M[c x ]=M[c x +1], indicating the first molecular mass c x There is no corresponding first subsequence, and the replacement of the first segment can be stopped at this time.

[0058] It should be noted that Figure 2 Here, max mass represents the upper limit of the molecular mass of the fragment, that is, the second value. When the first molecular mass is max mass, the corresponding second molecular mass is max mass+1.

[0059] It can be concluded from the above that, in this embodiment, by setting the first pointer and the second pointer, the first subsequence corresponding to the first molecular mass can be quickly found to replace the first fragment.

[0060] In one embodiment of the present disclosure, the evaluation and optimization method of the secondary mass spectrometry identification sequence further includes: A plurality of fragments in the first original sequence are intercepted according to a specified rule; the specified rule is: the molecular weight of each fragment is less than a second value and contains a maximum number of amino acid residues.

[0061] In this embodiment, a specific implementation method for cutting multiple fragments of the first original sequence is provided. During the cutting process, under the condition that the molecular weight of each fragment is less than a second value (for example, 70,000), the length of the fragment is required to be the largest, that is, the number of amino acid residues contained in each fragment is the largest.

[0062] Assume that the first original sequence is P=a1a2…a K , any segment P'=a i a i+1 …a k Should satisfy: ||a i a i+1 …a k ||<=c, and ||a i a i+1 …a k+1 ||>c, a represents the amino acid residue, || || represents the molecular mass of the amino acid residue, the subscript i represents the serial number of any amino acid residue, K and k are both natural numbers, K represents the total number of amino acid residues in the first original sequence, and k is less than or equal to K. For example, the first original sequence P = a1a2…a K In the above, the molecular weight of fragment a1a2a3 is 50000, which is less than 70000; the molecular weight of fragment a1a2a3a4 is 65000, which is less than 70000; the molecular weight of fragment a1a2a3a4a5 is 70050, which is greater than 70000. Then a1a2a3a4 is taken as a fragment of the first original sequence P. Other fragments in the first original sequence P can be obtained by the same method, including a1a2a3a4, a2a3a4, a3a4a5a6a7, etc.

[0063] It can be concluded from the above that this embodiment extracts multiple fragments in the first original sequence based on the molecular mass of the fragments, which can take into account both the time cost and the length of the fragments, thereby improving the calculation speed.

[0064] Please refer to Figure 3 Assuming that the first original sequence P = a1a2…a9, the above method can be used to intercept multiple fragments in the first original sequence to obtain the first fragment a1a2a3a4, the second fragment a2a3a4a5a6, ..., the Zth fragment a7a8a9. Taking the first fragment as an example, its corresponding first molecular mass is , by searching the first array and the second array, we can get the first molecular mass The corresponding first subsequence includes: , , Wait, will Random sorting can be obtained , , ...,Will Random sorting can be obtained , , ...,Will Random sorting can be obtained , , , ..., replace the first fragment with , , ..., , , ..., , , , ..., we can get the corresponding multiple first candidate sequences , ..., ....

[0065] In one embodiment of the present disclosure, constructing an evaluation sequence set based on a plurality of first original sequences and a corresponding plurality of first candidate sequences includes: Using the same scoring function, the first original sequence is compared and scored with the secondary mass spectrum, and the corresponding multiple first candidate sequences are compared and scored with the secondary mass spectrum. Based on the results of the comparison and scoring, multiple second candidate sequences are screened from the first original sequence and the multiple first candidate sequences.

[0066] An evaluation sequence set is constructed based on a plurality of first original sequences and a corresponding plurality of second candidate sequences.

[0067] In this embodiment, the same scoring function can be used to compare and score multiple first candidate sequences and the first original sequence with the secondary mass spectrum, set a percentage threshold (for example, 90%), and remove the first candidate sequence with a score less than the original sequence score multiplied by the threshold. The second candidate sequences screened by the threshold are all high-scoring sequences. For each original sequence, if some changes to some parts of the sequence will greatly affect the score of the entire sequence, the first candidate sequence with this part of the change will be eliminated. The more eliminated, the more the remaining second candidate sequences match the secondary mass spectrum. The fewer the remaining second candidate sequences, the more the original sequence matches the secondary mass spectrum. In the statistical evaluation, the screened second candidate sequence set generated by all the original sequences is combined into an evaluation sequence set, and the first sequence with a higher degree of match with the secondary mass spectrum is further screened. In order to ensure that the second candidate sequence set generated by each original sequence has the same statistical weight, multiple original sequences are added to each candidate sequence set to ensure that each candidate sequence set contains the same number of sequences.

[0068] It can be concluded from the above that this embodiment performs a preliminary screening of the first candidate sequence based on the scoring function, and screens the second candidate sequence with a higher score to construct an evaluation sequence set, which is conducive to reducing the amount of calculation.

[0069] In one embodiment of the present disclosure, calculating the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum includes: Calculate theoretical peaks for all sequences in the evaluation sequence set.

[0070] The confidence score for each theoretical peak is determined based on the ratio of the number of times each theoretical peak occurs in the evaluation sequence set to the total number of sequences in the evaluation sequence set.

[0071] The confidence score for each sequence was determined based on the confidence scores and molecular masses of multiple theoretical peaks in each sequence.

[0072] The confidence score for each sequence was determined as the match of each sequence to the MS / MS spectrum.

[0073] In this embodiment, given a sequence, the theoretical peaks of the sequence can be calculated, and for each theoretical peak, the confidence score of the theoretical peak can be obtained based on the ratio of the number of times the peak appears in the evaluation sequence set to the total number of sequences in the evaluation sequence set. Then, the confidence score of each peak in each sequence is weighted and summed with the molecular weight it represents, and then divided by the ratio of the molecular weight of the entire sequence to obtain the confidence score of each sequence.

[0074] set up is the confidence score of sequence seq; is the molecular mass of the sequence; j is the number of amino acids contained in the sequence; is the molecular mass of the theoretical peak of the ith amino acid, is the molecular mass of the i-1th amino acid theoretical peak; is the confidence score of the theoretical peak. The confidence score of the sequence is calculated as

[0075] According to actual data testing, the confidence score of the best matching sequence of high-quality secondary mass spectrometry is often greater than 0.8 (the full score is 1), and the confidence score of the best matching sequence of low-quality secondary mass spectrometry is often around 0.4. The confidence score calculation method of the sequence can be adjusted according to demand, for example, only the theoretical peak representation area with a confidence score greater than a certain threshold (such as 0.9) is counted and then weighted summed. The calculated confidence score of the sequence represents the proportion of the most confident subsequence in the sequence.

[0076] It can be concluded from the above that this embodiment quantifies the matching degree between each sequence and the secondary mass spectrum by calculating the confidence score, which is conducive to screening out a more optimized identification sequence.

[0077] Please refer to Figure 4 Assuming that the original sequence includes the first original sequence OS1, the second original sequence OS2, the third original sequence OS3, and the fourth original sequence OS4, by replacing the fragments in the first original sequence OS1 with random subsequences with the same molecular mass of the fragments, multiple corresponding first candidate sequences can be obtained, and the second candidate sequence NS 11 NS 12 、...、NS 1N By replacing the fragments in the second original sequence OS2 with random subsequences with the same molecular mass of the fragments, multiple corresponding first candidate sequences can be obtained, and the second candidate sequences NS 21 NS 22 、...、NS 2N 、...、NS 2M By replacing the fragments in the third original sequence OS3 with random subsequences with the same molecular mass of the fragments, multiple corresponding first candidate sequences can be obtained, and the second candidate sequences NS 31 NS 32 、...、NS 3N By replacing the fragments in the fourth original sequence OS4 with random subsequences with the same molecular mass of the fragments, multiple corresponding first candidate sequences can be obtained, and the second candidate sequence NS 41 NS 42 、...、NS 4NAn evaluation sequence set is constructed based on the first original sequence OS1, the second original sequence OS2, the third original sequence OS3, the fourth original sequence OS4, and their corresponding second candidate sequences. The confidence score of each theoretical peak and the confidence score of each sequence are calculated based on the evaluation sequence set. The matching degree of each sequence with the secondary mass spectrometry sequence is determined based on the confidence score.

[0078] In summary, this embodiment proposes an evaluation optimization algorithm for secondary mass spectrometry identification sequences. The core of the algorithm is to process multiple original sequences generated from scratch, and try to generate a polypeptide sequence that better matches the secondary mass spectrum. Through screening statistics, a confidence score is designed for each theoretical peak of the polypeptide sequence to indicate the proportion of each theoretical peak in the sequence that appears in the generated high-scoring sequence set. The scores of these theoretical peaks are weighted and summed with the molecular weight of the sequence they represent, and then divided by the molecular mass of the sequence to obtain a confidence score for each sequence, which is used to indicate the degree of match of the sequence with the secondary mass spectrum.

[0079] This embodiment is applied without reducing the calculation accuracy of dynamic programming. By "shuffling" each part of the sequence, a new sequence set is generated and function scores are assigned to the sequences in the sequence set. The high-scoring sequences in the sequence set are used for evaluation and optimization of the secondary mass spectrometry identification sequence.

[0080] Corresponding to the evaluation and optimization method of the secondary mass spectrometry identification sequence in the above embodiment, Figure 5 A structural block diagram of a secondary mass spectrometry identification sequence evaluation and optimization device provided in an embodiment of the present disclosure. For ease of description, only the parts related to the embodiment of the present disclosure are shown. Figure 5 The evaluation and optimization device 20 for secondary mass spectrometry identification sequence includes: a first generation module 21, a first calculation module 22 and a first screening module 23. Among them, the first generation module 21 is used to generate a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced with a random subsequence with the same molecular mass of the fragment to obtain multiple first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on the secondary mass spectrometry.

[0081] The first calculation module 22 is used to construct an evaluation sequence set based on the multiple first original sequences and the corresponding multiple first candidate sequences, and calculate the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum.

[0082] The first screening module 23 is used to select a first sequence from the evaluation sequence set based on the matching degree, and determine the first sequence as the evaluation optimization result.

[0083] In one embodiment of the present disclosure, the first generating module 21 is specifically used for: All fragment molecular masses between the first value and the second value are traversed with the first step length, a plurality of first subsequences corresponding to each fragment molecular mass are determined, and a plurality of first subsequences corresponding to the fragment molecular masses are obtained.

[0084] The sum of the molecular masses of the amino acid residues in the plurality of first subsequences corresponding to the molecular mass of any fragment is equal to the molecular mass of the fragment.

[0085] In one embodiment of the present disclosure, the first generating module 21 is further used for: For the molecular mass of the first fragment, traverse all the amino acid residues, If the molecular mass of the first fragment is equal to the molecular mass of the first amino acid residue, the first amino acid residue is determined as the first subsequence corresponding to the molecular mass of the first fragment; the molecular mass of the first fragment is the molecular mass of any fragment; If the molecular mass of the first fragment is greater than the molecular mass of the second amino acid residue, and there is a corresponding first subsequence for the molecular mass of the second fragment, the first subsequence corresponding to the molecular mass of the second fragment is combined with the second amino acid residue to obtain a second subsequence corresponding to the molecular mass of the first fragment; all second subsequences corresponding to the molecular mass of the first fragment are deduplicated to obtain all first subsequences corresponding to the molecular mass of the first fragment; The first amino acid residue and the second amino acid residue are any two amino acid residues; the molecular mass of the second fragment is the difference between the molecular mass of the first fragment and the molecular mass of the second amino acid residue.

[0086] In one embodiment of the present disclosure, the first generating module 21 is specifically used for: storing a plurality of first subsequences in ascending order of fragment molecular weight into a first array, determining the fragment molecular weight as an index of a second array, performing multiple pointer storage operations, and storing a pointer of a third subsequence corresponding to each fragment molecular weight into a corresponding index position in the second array; the third subsequence is the first subsequence among a plurality of first subsequences corresponding to the same fragment molecular weight; If the number of the first subsequence corresponding to the molecular mass m of the fragment is greater than 0, the pointer corresponding to the molecular mass m of the fragment is increased by n+1 to obtain the pointer corresponding to the molecular mass m+1 of the fragment; If the number of the first subsequences corresponding to the molecular mass m of the fragment is equal to 0, the pointer corresponding to the molecular mass m of the fragment is determined as the pointer corresponding to the molecular mass m+1; n represents the number of the first subsequences corresponding to the molecular mass m of the fragment; when the molecular mass m of the fragment is 0, its corresponding pointer points to the starting position of the first array.

[0087] In one embodiment of the present disclosure, the first generating module 21 is further used for: A plurality of fragments in the first original sequence are intercepted according to a specified rule; the specified rule is: the molecular weight of each fragment is less than a second value and contains a maximum number of amino acid residues.

[0088] In one embodiment of the present disclosure, the first calculation module 22 is used to: Using the same scoring function, the first original sequence is compared and scored with the secondary mass spectrum, and the corresponding multiple first candidate sequences are compared and scored with the secondary mass spectrum. Based on the results of the comparison and scoring, multiple second candidate sequences are screened from the first original sequence and the corresponding multiple first candidate sequences.

[0089] An evaluation sequence set is constructed based on a plurality of first original sequences and a corresponding plurality of second candidate sequences.

[0090] In one embodiment of the present disclosure, the first calculation module 22 is used to: Calculate theoretical peaks for all sequences in the evaluation sequence set.

[0091] The confidence score for each theoretical peak is determined based on the ratio of the number of times each theoretical peak occurs in the evaluation sequence set to the total number of sequences in the evaluation sequence set.

[0092] The confidence score for each sequence was determined based on the confidence scores and molecular masses of multiple theoretical peaks in each sequence.

[0093] The confidence score for each sequence was determined as the match of each sequence to the MS / MS spectrum.

[0094] See also Figure 6 , Figure 6 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 6 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processors 301, input devices 302, output devices 303 and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of each module / unit in the above-mentioned device embodiments, such as Figure 5 The functions of modules 21 to 23 are shown.

[0095] It should be understood that in the embodiment of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0096] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0097] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0098] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the evaluation and optimization method of the secondary mass spectrometry identification sequence provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device described in the embodiments of the present disclosure, which will not be repeated here.

[0099] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0100] The computer-readable storage medium may be an internal storage unit of the electronic device of any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0101] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0102] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0103] In the several embodiments provided in the present application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0104] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0105] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0106] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for evaluating and optimizing a secondary mass spectrometry identification sequence, characterized in that: include: Generate a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced by a random subsequence with the same molecular mass of the fragment, to obtain a plurality of first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry; Constructing an evaluation sequence set based on the first original sequences and the corresponding first candidate sequences, and calculating the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum; A first sequence is selected from the evaluation sequence set based on the matching degree, and the first sequence is determined as an evaluation optimization result.

2. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 1, wherein: Also includes: Traversing all fragment molecular masses between the first value and the second value with the first step length, determining a plurality of first subsequences corresponding to each fragment molecular mass, and obtaining a plurality of first subsequences corresponding to the fragment molecular masses; The sum of the molecular masses of the amino acid residues in the plurality of first subsequences corresponding to the molecular mass of any fragment is equal to the molecular mass of the fragment.

3. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 2, wherein: The step of determining a plurality of first subsequences corresponding to the molecular mass of each fragment comprises: For the molecular mass of the first fragment, traverse all the amino acid residues, If the molecular mass of the first fragment is equal to the molecular mass of the first amino acid residue, the first amino acid residue is determined as the first subsequence corresponding to the molecular mass of the first fragment; the molecular mass of the first fragment is the molecular mass of any fragment; If the molecular mass of the first fragment is greater than the molecular mass of the second amino acid residue, and there is a corresponding first subsequence for the molecular mass of the second fragment, the first subsequence corresponding to the molecular mass of the second fragment is combined with the second amino acid residue to obtain a second subsequence corresponding to the molecular mass of the first fragment; all second subsequences corresponding to the molecular mass of the first fragment are deduplicated to obtain all first subsequences corresponding to the molecular mass of the first fragment; The first amino acid residue and the second amino acid residue are any two amino acid residues; the molecular mass of the second fragment is the difference between the molecular mass of the first fragment and the molecular mass of the second amino acid residue.

4. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 2, wherein: Also includes: storing a plurality of first subsequences in ascending order of fragment molecular weight into a first array, determining the fragment molecular weight as an index of a second array, performing multiple pointer storage operations, and storing a pointer of a third subsequence corresponding to each fragment molecular weight into a corresponding index position in the second array; the third subsequence is the first subsequence among a plurality of first subsequences corresponding to the same fragment molecular weight; If the number of the first subsequence corresponding to the molecular mass m of the fragment is greater than 0, the pointer corresponding to the molecular mass m of the fragment is increased by n+1 to obtain the pointer corresponding to the molecular mass m+1 of the fragment; If the number of the first subsequences corresponding to the molecular mass m of the fragment is equal to 0, the pointer corresponding to the molecular mass m of the fragment is determined as the pointer corresponding to the molecular mass m+1; n represents the number of the first subsequences corresponding to the molecular mass m of the fragment; when the molecular mass m of the fragment is 0, its corresponding pointer points to the starting position of the first array.

5. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 4, wherein: The step of replacing each fragment in the first original sequence with a random subsequence having the same molecular mass of the fragments comprises: Calculating a first molecular mass of the first fragment based on the molecular mass of the amino acid residues in the first fragment; the first fragment is any fragment in the first original sequence; searching the second array for a first pointer based on a first molecular mass of the first fragment; Searching for a second pointer from the second array based on a second molecular mass; the second molecular mass is obtained by adding the first step length to the first molecular mass; If the address pointed to by the second pointer is greater than the address pointed to by the first pointer, determine the first subsequence between the address pointed to by the first pointer and the address pointed to by the second pointer as the fourth subsequence; Randomly sorting the fourth subsequence to obtain a random subsequence with the same molecular mass as the first fragment; The first fragment is replaced by a random subsequence of fragments with the same molecular mass.

6. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 2, wherein: Also includes: A plurality of fragments in the first original sequence are intercepted according to a specified rule; the specified rule is: the molecular weight of each fragment is less than the second value and contains a maximum number of amino acid residues.

7. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 1, wherein: The step of constructing an evaluation sequence set based on the plurality of first original sequences and the corresponding plurality of first candidate sequences comprises: Using the same scoring function, the first original sequence is compared and scored with the secondary mass spectrum, and the corresponding multiple first candidate sequences are compared and scored with the secondary mass spectrum, and multiple second candidate sequences are screened from the first original sequence and the corresponding multiple first candidate sequences based on the comparison and scoring results; An evaluation sequence set is constructed based on a plurality of first original sequences and a corresponding plurality of second candidate sequences.

8. The method for evaluating and optimizing a secondary mass spectrometry identification sequence according to claim 1, wherein: The calculating the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum comprises: Calculating theoretical peaks of all sequences in the evaluation sequence set; Determine a confidence score for each theoretical peak based on the ratio of the number of times each theoretical peak appears in the evaluation sequence set to the total number of sequences in the evaluation sequence set; Determining a confidence score for each sequence based on the confidence scores and molecular masses of multiple theoretical peaks in each sequence; The confidence score for each sequence was determined as the match of each sequence to the MS / MS spectrum.

9. A device for evaluating and optimizing a secondary mass spectrometry identification sequence, characterized in that: include: A first generation module is used to generate a first candidate sequence corresponding to each original sequence; wherein each fragment in the first original sequence is replaced by a random subsequence with the same molecular mass of the fragment, to obtain a plurality of first candidate sequences corresponding to the first original sequence; the first original sequence is any original sequence, and the original sequence is an identification sequence obtained based on secondary mass spectrometry; A first calculation module is used to construct an evaluation sequence set based on the first original sequences and the corresponding first candidate sequences, and calculate the matching degree between each sequence in the evaluation sequence set and the secondary mass spectrum; The first screening module is used to select a first sequence from the evaluation sequence set based on the matching degree, and determine the first sequence as the evaluation optimization result.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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