JP5181908B2 - Mass spectrometry data analyzer - Google Patents

Description

  The present invention relates to a mass spectrometry data analysis apparatus that identifies a protein by mass-analyzing a test sample containing a protein-derived peptide mixture and estimating the amino acid sequence of the peptide using mass spectrometry data obtained thereby.

In recent years, protein structures and functions have been rapidly analyzed as post-genomic research. As one of such protein structure / function analysis methods (proteome analysis), protein expression analysis and primary structure analysis using mass spectrometers have been widely performed, and quadrupole ion traps have been widely used. So-called MS ⁿ analysis (n is an integer of 2 or more), which captures and cleaves a specific peak by, for example, collision induced decomposition (CID), is effective. In general, in MS ² (= MS / MS) analysis, first, an ion having a specific m / z is selected as a precursor ion from an analysis object, and the precursor ion is cleaved by CID. Then, information on the mass and chemical structure of the target ion can be obtained by mass analysis of ions (product ions) generated by cleavage.

When identifying a protein using MS ⁿ analysis as described above, first, the protein is digested with an appropriate enzyme to obtain a mixture of peptide fragments, and then the peptide mixture is subjected to mass spectrometry to obtain a mass spectrum. Subsequently, from a mass spectrum data of the peptide mixture, for example, a set of isotope peaks derived from a single peptide is selected as a precursor ion, and the ion (product that is generated by cleaving the precursor ion with CID is obtained. Ion) mass analysis, that is, MS / MS analysis. Further, when the cleavage operation is not performed into a sufficiently small fragment by one cleavage operation, the cleavage operation may be performed a plurality of times.

  Based on the mass spectrum pattern of the product ions obtained by one or two or more multi-stage cleavage operations as described above and the mass spectrum pattern of the precursor ions, for example, a mascot (MASCOT) provided by Matrix Science A search engine such as is used to execute a collation process with the amino acid sequence database. Thereby, the amino acid sequence of the test peptide is determined, and the original protein is identified.

  Various database search engines as described above are known and put into practical use, but the mascot described above is one of the most widely used (see Non-Patent Documents 1 and 2). FIG. 4 is an example of a search setting screen for MS / MS ion search by mascot displayed on the monitor screen of the computer.

  The main search items to be set by the user are the database used for matching (Database), the type of digestive enzyme used for protein degradation (Enzyme), and the type of modification (fixed modification) that occurs deterministically. (Fixed modification), types of (non-deterministic) modifications that may occur (variable modification), tolerance of mass spectrometry accuracy (MS / MS tol.), Etc. . Some of these search items are pull-down menus, and the user can appropriately specify from these menus. When the user sets these search conditions as appropriate and clicks the “Start Search” button to instruct the execution of the search, the database is checked under the set search conditions on the computer, and finally Lists peptide candidates with high accuracy in the search. In the case of a mascot, the accuracy of a peptide candidate is called a score.

  However, the user cannot always set each search item correctly. For example, it may frequently occur that the accuracy tolerance “MS / MS tol.” Is estimated to be small or that it is difficult to predict a correct variable modification. In order to solve such a problem, a method called an error tolerant search that allows a search condition setting error after narrowing down the types of proteins in advance has been developed (see Non-Patent Documents 3 and 4).

  The error tolerant search method will be briefly described. First, the user performs an MS / MS ion search under the search conditions set on the search setting screen as shown in FIG. 4, and exceeds a preset threshold called a homology level. Protein candidates containing peptides hit with a score of are extracted. In this MS / MS ion search, a variable set by the user as a variable modification is used. In the peptide candidate protein extracted in this way, database search is attempted under conditions that allow setting errors in the following four search conditions (A), (B), (C), and (D).

(A) The search item of the enzyme is set to “semi-specific”. Here, semi-specific means that specific cleavage by an enzyme occurs only on one side.
(B) Increase the number of “missed cleavage” by one. Here, “missed cribbage” means that the bond is broken by cleavage at a position that should not be cut.
(C) Set all the variable modifications one by one in order.
(D) Consider a single amino acid substitution.
Among the peptide candidates hit by the database search as described above, the score is higher than that at the time of executing the MS / MS ion search, and the threshold value is called a preset identity level (a level higher than the homology level). The peptide hit with the score of is selected, and this is displayed as a search result.

  In this error tolerant search method, the MS / MS ion search is first executed to limit the protein and the search is relaxed. Therefore, the process is more efficient than the normal MS / MS ion search for all proteins. It is possible to shorten the time.

  However, both the above-described MS / MS ion search method and error tolerant search method have the following problems. That is, the evaluation of the quality of these search methods is roughly divided into search time and search accuracy. The search accuracy includes a problem of overlooking that the search does not hit and a problem of false positive that a false peptide hits by mistake. Generally speaking, the search accuracy decreases when the search time is shortened, and the search time increases when the search accuracy is increased.

  For example, in the error tolerant search method, the protein to be searched is limited at the beginning, and if the target protein is excluded at that time, it will hit even if the setting error is widened when searching the database according to the above procedure. Cannot be expected. As a result, the search time is short, but overlooked. On the other hand, the MS / MS ion search method does not focus on a specific protein, so detection misses are relatively small, but the search time is long. Further, in the mascot, the number of variable modifications is limited to 9 in order to prevent an increase in search time and false positives, so that some degree of oversight is inevitable.

"Matrix Science-Mascot-MS / MS Ions Search", [online], UK Matrix Science Ltd., [June 2008 Search 24th], Internet <URL: http://www.matrixscience.com/search_form_select.html> Tetsuo Iida and three others, “Application of LCMS-IT-TOF to Proteome Analysis”, Shimazu Critique, Vol.63, No.1, 2, p.19-28 (2006) “Error Tolerant Search”, [online], UK Matrix Science Ltd., [Search June 24, 2008], Internet <URL: hthttp: // www. matrixscience.com/help/error_tolerant_help.html> David M. Creasy and one other, “Error Tolerant Searching of Uninterpreted Tandem Mass Spectrometry Data”, Proteomics ), Volume 2, Issue 10, p.1426-1434 (2002)

  As described above, when the MS / MS ion search method and the error tolerant search method are compared, the latter is advantageous in terms of search time, but inferior in accuracy, while the former is advantageous in terms of accuracy, It can be said that the search time is inferior. However, the MS / MS ion search method has a relatively high probability of being overlooked, and the problem that unidentified proteins remain has become apparent. According to the study by the present inventor, the main cause is that the number of variable modification, which is one of the search conditions, is 9 or more but is limited to a certain value. It was. At the same time, if the variable modification is expanded, the probability of missing will be reduced, but the search time will not only increase, but false positives will increase and it will be difficult to improve the search accuracy as a whole.

  The present invention has been made in view of these points, and an object of the present invention is to find in the conventional MS / MS ion search method and error tolerant search method while suppressing an increase in processing time for search as much as possible. An object of the present invention is to provide a mass spectrometric data analysis apparatus that can identify peptides and proteins that could not be identified, and that can reduce erroneous identification.

  The inventor of the present application provides the number of variable modification (that is, non-deterministic modification) and the search condition when executing the search as the search condition setting for the database search including the MS / MS ion search method. Focused on the direction. That is, as described above, in the conventional method, a maximum of nine types of non-deterministic modifications can be set, but a plurality of non-deterministic modifications are allowed to coexist in the search. That is, the fact that one type of non-deterministic modification and another type of non-deterministic modification can occur simultaneously is also incorporated into the search conditions. However, in general, it is not at all unlikely that modification occurs simultaneously at a plurality of positions in the amino acid sequence of a certain peptide, but it is considered that the probability is considerably low.

  On the other hand, according to the study of the present inventor, when modification / mutation occurs simultaneously in multiple locations of an amino acid sequence, the probability of hitting with a high score in the search despite being different from the actual amino acid sequence In other words, it was found that the probability of false positives was greatly increased. In addition, the condition setting that modification / mutation occurs simultaneously at a plurality of positions in the amino acid sequence leads to a significant increase in the number of searches, particularly when the number of non-deterministic modifications / mutations is increased, which is also disadvantageous in terms of search time. Considering all such factors, it is assumed that multiple coexistence of non-deterministic modifications / mutations is not allowed, that is, modification / mutation occurs only in one place at the maximum, and non-deterministic modifications that can be selected instead. Significantly increasing the number of mutations is considered effective in reducing missed observations while reducing or suppressing false positives. Also, it can be considered that an extreme increase in search time can be suppressed. The present invention has been made based on these findings.

That is, the present invention made to solve the above-mentioned problems is to identify peptides and proteins in a test sample based on spectrum data collected by a mass spectrometer capable of MS ⁿ analysis (n ≧ 2). In the mass spectrometry data analysis device that performs database search,
a) Peak list creation means for creating a peak list that collects peak information of peaks derived from the test sample based on the spectral data;
b) a first condition specifying means for the user to specify an arbitrary number of conditions relating to modifications / mutations that can occur in the amino acid sequence;
a second condition setting means for a user to specify a search condition for the data base search beyond the conditions specified by c) said first condition designating means,
d) Each of the peak lists under a condition obtained by combining the conditions selected by the first condition designating unit and the search conditions designated by the second condition designating unit while sequentially selecting the conditions designated by the first condition designating unit. The process of extracting peptide / protein candidates by collating the peak list created by the creation means with the database is performed until all of the conditions designated by the first condition designation means are completed or a predetermined termination condition Database search execution means that repeats until
e) output means for outputting information based on the accuracy of each peptide / protein candidate extracted by the database search execution means;
And the limitation on the number of types of non-deterministic modification / mutation that can be specified by the first condition specifying means under an exclusive condition that non-deterministic modification / mutation occurs at only one place at the maximum By eliminating or broadening, both the reduction of false positives when identifying peptides and proteins in a test sample, or the suppression of the increase, and the reduction of missed identification, and the increase in search time are suppressed. It is characterized in that the.

  Since the total number of types of non-deterministic modification / mutation currently known is about 600, it is not practical to specify whether or not to include them in the search target by key operation or mouse operation. Therefore, as an aspect of the mass spectrometry data analysis apparatus according to the present invention, preferably, the modification / mutation database storing all known conditions for modification / mutation of the amino acid sequence is provided, and the first condition specifying means The configuration may be such that any number of conditions can be specified using a modification / mutation database.

  In this configuration, as an example, the first condition designating means can designate all non-deterministic modifications / mutations registered in the modification / mutation database as search conditions. In addition, priorities based on the probability of occurrence of all non-deterministic modifications / mutations in the database are determined, and an appropriate number, for example, “100 in descending order of priority” is set. The conditions for non-deterministic modification / mutation can be set simply.

  The search condition specified by the second condition setting means can be items other than the variable modification that can be set in the above-described conventional MS / MS ion search. -Includes modification, missed cribage, etc.

  The database search execution means may repeat the search until all of the non-deterministic modification / mutation conditions specified by the first condition specifying means are completed, but a peptide / protein having a considerably high accuracy is hit. If the search is terminated at the time, a great effect of shortening the search time can be expected. Therefore, as one aspect of the mass spectrometry data analysis apparatus according to the present invention, the database search execution means repeats the database search at the time when the extracted peptide / protein candidate with a certain probability is more than a predetermined threshold is searched. It does not matter if you cancel

  According to the mass spectrometric data analysis apparatus of the present invention, it is possible to greatly reduce the number of cases in which proteins and peptides cannot be identified, as compared to a database search using a mascot MS / MS ion search method, etc. (False positives) can also be reduced. On the other hand, although the search time is generally longer, an increase in the search time can be suppressed as compared with the case where the limitation of variable modification is simply expanded by the conventional mascot MS / MS ion search method. It becomes possible to keep the search time within an allowable time by using a normal computer. Furthermore, the search time can be shortened by performing a process that terminates the search when a suitable search result is obtained.

  Hereinafter, an embodiment of a protein identification system using a mass spectrometry data analysis apparatus according to the present invention will be described with reference to the accompanying drawings. FIG. 1 is an overall configuration diagram of the protein identification system of this embodiment, and FIG. 2 is a flowchart showing a protein identification procedure using this system.

  The protein identification system according to the present embodiment is roughly divided into a mass analysis unit 1 and a control / processing unit 2 configured mainly by a computer. The mass analyzer 1 is an ion trap time-of-flight mass spectrometer, which ionizes a molecule or atom in a target sample and temporarily captures the generated ions, and according to m / z as necessary. A three-dimensional quadrupole ion trap 11 that performs selective ion selection and ion cleavage by CID, and a time-of-flight type that separates and detects various ions emitted from the ion trap 11 according to m / z A mass spectrometer (TOFMS) 12.

  The ionization unit 10 that performs ionization on a biological sample is generally based on a matrix-assisted laser desorption ionization method (MALDI), but the ionization method is not limited to this. For example, a combination of a high-speed liquid chromatograph (HPLC) with a micro flow rate of less than 1 μm / min and nano-ESI (electrospray ionization) corresponding to the ionization unit 10 is useful (see Non-Patent Document 2).

  The TOFMS 12 includes a flight space 13 in which ions are turned back by an electric field generated by a reflectron electrode, and a detector 14 that sequentially detects ions temporally separated according to m / z while flying in the flight space 13. And including.

  The control / processing unit 2 includes an analysis control unit 20 that controls each unit of the mass analysis unit 1, an MSn data processing unit 21 that creates a mass spectrum, an MS / MS spectrum, and the like based on a detection signal obtained from the detector 14, and A peak list creation unit 22 for extracting a peak appearing in the mass spectrum and MS / MS spectrum and creating a peak list including information such as m / z and intensity of each peak, and non-deterministic modification of the amino acid sequence Modification / mutation database (DB) 24 storing mutation information, identification database (DB) 25 for estimating peptide amino acid sequences, and searching for proteins / peptides that hit the peak list using these databases The sequence identification processing unit 23 to be performed is included as a functional block. In the modification / mutation database 24, information on all modifications / mutations known at the time, that is, names of modifications / mutations, types of amino acids to be changed, peptide sites, change mass (m / z), etc. It shall be registered.

  The entity of the control / processing unit 2 is a computer, and the above-described various functions are achieved by the operation of dedicated control / processing software installed in the computer. The search condition input unit 28 connected to the sequence identification processing unit 23 is for inputting and setting search conditions. Specifically, the search condition input unit 28 is a keyboard or a pointing device connected to a computer. The display unit 29 is for displaying a search condition input setting screen by the search condition input unit 28 or displaying an identification result.

  Next, protein identification work using the protein identification system of the present embodiment will be described with reference to FIG. In the following description, a case where the same database search engine as the mascot MS / MS ion search method is used is taken as an example, but the database search method is not limited to this, and other well-known methods are used. It is easy to understand.

  The user prepares a test sample containing the peptide mixture by digesting the target protein with an appropriate enzyme. This test sample is subjected to mass analysis by the mass analyzer 1, and a peak appearing on the mass spectrum obtained thereby is selected as a precursor to perform MS / MS analysis (step S1). The method of selecting a precursor is not directly related to the present invention, and thus the details are omitted. For example, for a peak appearing in a mass spectrum, an isotope peak is determined, a multivalent ion peak is determined, and the like. After removing the overlap, ions to be used as a precursor are determined by determining the peak intensity or the like.

  Next, the peak list creation unit 22 collects information on peaks appearing in the obtained mass spectrum and MS / MS spectrum and creates a peak list (step S2). The peak information listed in the peak list includes the peak m / z and intensity.

  Next, before executing the database search, the user sets other search condition items excluding non-deterministic modification and substitution from the search condition input unit 28 (step S3). That is, the search condition setting screen as shown in FIG. 4 is displayed on the screen of the display unit 29, and the database type (Database), biological classification (Taxonomy), enzyme type (Enzyme), allowable number of mis-cleavages. (Missed cleavage), definite modification and substitution (indicated as “Fixed modifications” in FIG. 4), allowable m / z range of peptide (Peptide tol.), Allowable m at MS / MS analysis For each item such as / z range (MS / MS tol.), peptide valence (Peptide charge), measuring device type (Instrument), select from the pull-down menu, enter numerical values or direct key input, or check box Fill in the check. These search conditions mainly depend on the type of sample to be measured, the performance of the measurement apparatus (mass analyzer 1), etc., and are known to the user or can be easily predicted.

  Next, the user designates the non-deterministic modification / mutation (item described as “Variable modifications” in FIG. 4) that was not set (cannot be set) in step S3 by the search condition input unit 28. (Step S4). At this time, the sequence identification processing unit 23 can display a list of registration information read from the modification / mutation database 24 on the screen of the display unit 29, and the user can make a selection based on the list. Here, since the number of nondeterministic modifications / mutations that can be specified is not limited, all non-deterministic modifications / mutations registered in the database 24 can be specified as search conditions. In that case, the user may instruct the search condition input unit 28 to select all non-deterministic modifications / mutations on the list.

  In other cases, it is possible to select non-deterministic modifications / mutations listed in the list one by one and specify them as search conditions, but such work is troublesome. As described above, the total number of modifications / mutations is about 600, but many modifications / mutations that actually occur with a very low probability are included. Therefore, the priority and importance based on the high possibility of occurrence are registered in the database 24 for each modification / mutation, and for example, a predetermined number of modifications / mutations are selected in descending order of priority and used as search conditions. A simple designation method such as designation may be employed.

  When all of the search conditions necessary for the search are specified as described above and the user instructs the start of the search (step S5), the sequence identification processing unit 23 first determines the nondeterministic modification / mutation specified in step S4. One of them is selected and combined with the other search conditions set in step S3 as a search condition (step S6). When selecting a modification / mutation one by one from a large number of non-deterministic modifications / mutations, for example, the order of priority given to each modification / mutation may be set as described above. Then, under this search condition, an amino acid sequence that matches the peak information included in the peak list created by the peak list creation unit 22 is searched by collating with the identification database 25 (step S7).

  If any amino acid sequence is hit by the database search, the search result information, for example, the amino acid sequence of the hit peptide, protein name, score (reliability index value), and the like are stored in a storage unit (not shown) (step S8). . Subsequently, it is determined whether or not a search using all non-deterministic modifications / mutations specified in step S4 has been executed (step S9). If there is an unsearched item, the process returns to step S6. Then, after selecting another non-deterministic modification / mutation that has not yet been selected, the process proceeds to step S7 and subsequent steps. By repeating steps S6 to S9, a database search is performed using all nondeterministic modifications / mutations specified in step S4 as search conditions. If there is a hit in each search, the result is stored in the storage unit. Saved in. Therefore, for example, when 200 pieces (types) are designated as non-deterministic modifications / mutations, the database search is repeated 200 times.

  When the database search using all the non-deterministic modifications / mutations as search conditions is completed, the sequence identification processing unit 23 reads all the search results from the storage unit and evaluates the validity of the results with reference to the scores and the like. (Step S10). For example, a predetermined number of results are extracted in a descending order of results having a score of a certain value or higher. Then, the extracted result, that is, the validity evaluation result is displayed on the screen of the display unit 29 (step S11). The user sees this, and finally determines, for example, that the result with the highest score is the peptide / protein identification result.

  As described above, in the protein identification system according to the present embodiment, the number of possible nondeterministic modifications / mutations is limited to one instead of eliminating the restriction on the designated number of search conditions for non-deterministic modifications / mutations. In other words, the case where two or more non-deterministic modifications / mutations occur at the same time, which is very unlikely to actually occur, is not considered in the search. As a result, it is possible to exhaustively search for all peptides / proteins with non-deterministic modifications / mutations, so it is difficult for the user to predict, which could not be identified by the conventional MS / MS ion search method. Proteins with modifications and mutations can be identified. In addition, although there are no restrictions on the number of search conditions for non-deterministic modification / mutation, it does not take into account the simultaneous occurrence of two or more non-deterministic modifications / mutations. Search time can be reduced within a sufficiently acceptable time. Furthermore, by not considering the co-occurrence of two or more non-deterministic modifications / mutations, an increase in false positives in the search can be suppressed, and the reliability of the search results can be improved.

  As described above, by registering information such as the frequency of occurrence and importance of non-deterministic modifications and mutations in the modification / mutation database 24, the user in step S4 has a high frequency of occurrence or priority or A modification / mutation with high importance can be selected and specified. At this time, the threshold of occurrence frequency and priority can be set by the user, and a modification / mutation with an occurrence frequency or priority higher than the threshold is automatically selected as a search condition for non-deterministic modification / mutation. It is convenient to do so. In addition, if non-deterministic modifications / mutations with high validity, that is, high scores are found as search results, the frequency of occurrence of non-deterministic modifications / mutations is automatically added or the priority is increased. In other words, a learning function may be added. This makes it possible to add information on non-deterministic modification / mutation specific to the user that occurs with the type of sample to be analyzed, the sample preparation method, the measurement method, etc., so that a more accurate search is possible.

  In the above embodiment, a database search was performed using all specified non-deterministic modifications / mutations as search conditions. However, when a sufficiently reliable result was obtained during the search, May stop the database search at that time. FIG. 3 shows a flowchart when the procedure is changed in this way. As apparent from comparison with FIG. 2, after step S8, it is determined whether or not the score is equal to or greater than the threshold (step S12). If the score is less than the threshold, the process proceeds to step S9, and the score is equal to or greater than the threshold. If so, step S9 is passed and the process proceeds to S10. In the latter case, the subsequent search is not repeated, the validity is evaluated using only the search results obtained so far, and the evaluation result is output to the display unit 29. Thereby, unnecessary search is not performed, and the time required for protein identification can be shortened.

  Even if the score is equal to or greater than the threshold value in step S12, if non-deterministic modification / mutation indicating the same priority or occurrence frequency remains as a search condition (unsearched), the search condition It is preferable to proceed to step S10 after performing the database search. Thereby, it can also be expected to obtain a plurality of results with high scores.

  According to the examination by the inventors of the present application, among the 16 data that could not be identified by the normal MS / MS ion search method or error tolerant search method (the high score candidate peptide was not hit), Using such a data processing method as described above, a correct modified peptide could be identified from 12 data. Next, as an example of this identification, an identification example of a peptide of bovine serum albumin (BSA = bovine serum albumin) will be described.

  Nine types of probable probable potentials in MS / MS analysis using a m / z 1910 peak as a precursor in a mass spectrum obtained by mass spectrometry of a sample containing a peptide obtained by digesting BSA with triprin enzyme Variable modification (Acetyl (K), Carbamidomethyl (C), Carboxymethyl (C), Dioxidation (M), Methyl (DE), Oxidation (M), Phospho (ST), Phospho (Y), Propionamide (C )) And MS / MS ion search is performed, the candidate ranked first is the peptide “K.YGVASISTVDATCSTGER.E + Methyl (DE); Phospho (ST)” with a score of 27 and the protein “Oryza sativa Hypothetical protein” Met. In this search, the score of 39 or higher is the homology level, and the score of 64 or higher is the identify level. Therefore, the reliability of the candidate ranked first is low. In addition, the correct protein (BSA) was not hit among candidates up to the 20th rank in the search result.

  On the other hand, when the search according to the method of the present invention is performed on the same MS / MS data by designating 350 types of variable modification, the peptide of protein BSA with a score of 62 is ranked as the first candidate. “K.CCAADDKEACFAVEGPK.L + Ammonia-loss (N-term C)” was a hit. In this search, since the homology level is above 33 and the identity level is above 46, the reliability of this candidate is high. That is, peptides that could not be identified by the conventional method could be identified with high accuracy.

  It should be noted that the above embodiment is merely an example of the present invention, and it will be understood that the present invention is encompassed in the scope of the claims of the present application even if appropriate modifications, corrections, additions, etc. are made within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS The whole block diagram of the protein identification system of one Example of this invention. The flowchart which shows the protein identification procedure using the protein identification system of FIG. The flowchart which shows the protein identification procedure which deform | transformed. The figure which shows an example of the search setting screen of MS / MS ion search by the mascot displayed on the monitor screen of a computer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Mass spectrometry part 10 ... Ionization part 11 ... Ion trap 12 ... TOFMS
13 ... Flight space 14 ... Detector 2 ... Control / processing unit 20 ... Analysis control unit 21 ... MSn data processing unit 22 ... Peak list creation unit 23 ... Sequence identification processing unit 24 ... Modification / mutation database 25 ... Identification database 28 ... Search condition input unit 29 ... display unit

Claims (3)

In a mass spectrometry data analysis apparatus for performing database search to identify peptides and proteins in a test sample based on spectrum data collected by a mass spectrometer capable of MS ⁿ analysis (n ≧ 2),
a) Peak list creation means for creating a peak list that collects peak information of peaks derived from the test sample based on the spectral data;
b) a first condition specifying means for the user to specify an arbitrary number of conditions relating to modifications / mutations that can occur in the amino acid sequence;
a second condition setting means for a user to specify a search condition for the data base search beyond the conditions specified by c) said first condition designating means,
d) Each of the peak lists under a condition obtained by combining the conditions selected by the first condition designating unit and the search conditions designated by the second condition designating unit while sequentially selecting the conditions designated by the first condition designating unit. The process of extracting peptide / protein candidates by collating the peak list created by the creation means with the database is performed until all of the conditions designated by the first condition designation means are completed or a predetermined termination condition Database search execution means that repeats until
e) output means for outputting information based on the accuracy of each peptide / protein candidate extracted by the database search execution means;
And the limitation on the number of types of non-deterministic modification / mutation that can be specified by the first condition specifying means under an exclusive condition that non-deterministic modification / mutation occurs at only one place at the maximum By eliminating or broadening, both the reduction of false positives when identifying peptides and proteins in a test sample, or the suppression of the increase, and the reduction of missed identification, and the increase in search time are suppressed. A mass spectrometry data analysis apparatus characterized by that. The mass spectrometry data analysis device according to claim 1 ,
It is equipped with a modification / mutation database that stores all known conditions for modification / mutation of amino acid sequences, and the first condition designating means can designate any number of conditions using the modification / mutation database. A mass spectrometry data analysis apparatus characterized by that. The mass spectrometry data analysis apparatus according to claim 1 or 2 ,
The mass spectrometry data analysis apparatus, wherein the database search execution means terminates the database search repetition when a search is made for an extracted peptide / protein candidate whose accuracy is a predetermined threshold or more.

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