JP4490302B2 - Prediction program for heat-resistant protein and recording medium thereof - Google Patents

Description

  The present invention focuses on a protein produced by an organism, and determines whether or not the protein has heat resistance by calculating a characteristic value related to heat resistance from the amino acid sequence or base sequence data. The present invention relates to a program and a recording medium on which the program is recorded. More specifically, the present invention is a program for determining whether or not a test protein has heat resistance, and is a program specific to the test protein by principal component analysis based on the amino acid composition of the protein. An analysis value is calculated, and the analysis value is compared with an analysis value of a protein corresponding to the test protein of the thermotolerant organism to cause the computer to execute a process for determining the heat resistance of the protein. The present invention relates to a program and a computer-readable recording medium on which the program is recorded.

Thermostable enzymes are widely used in industry, R & D fields and the like as enzymes that do not lose enzyme activity even at high temperatures. For example, an enzyme used in an enzyme reaction step in hydrolysis of saccharides such as starch (see Patent Documents 1 and 2), an enzyme in an enzyme reaction when processing garbage or compost from them (Patent Documents 3 and 2) 4), enzymes in enzyme reactions when producing useful substances such as trehalose (see Patent Documents 5 and 6), and the like.
Thus, thermostable enzymes are very important industrially, but in recent years, they have been used in PCR methods (see Patent Document 7) and replication RNA-based amplification systems (see Patent Documents 8 and 9). Development of thermostable DNA polymerases has been regarded as important, and a large number of thermostable DNA polymerases have been isolated mainly from thermophilic microorganisms. DNA polymerase has become one of the important tools in gene manipulation technology. It is important not only for gene cloning and sequencing, but also as a tool for detecting and identifying trace amounts of genes and as an enzyme for gene amplification. It has become.

  Currently, thermophilic DNA polymerases primarily used for these purposes are T.I. It is derived from the genus Thermus such as Taq polymerase derived from T. aquaticus. There is a growing interest in the discovery of novel polymerases with more appropriate properties and activities. Examples of those other than those belonging to the genus Thermus include a method using a DNA polymerase from Anaerocellum thermophilum (see Patent Document 10). In addition, a method using a sulfur metabolism thermophilic archaeon Pyrococcus horikoshi (see Patent Document 11) has been reported.

In this way, the importance of thermostable enzymes is increasing, but in many cases, thermostable enzymes are searched for thermophilic bacteria and thermostable bacteria, and the target enzyme-producing bacteria are selected. Since the heat resistance of the enzyme produced by screening from the natural world and examining the culture conditions must be confirmed by heat treatment one by one, it not only requires enormous labor and time, but is often accidental. It was often influenced by. In addition, the target of screening is limited to thermophilic bacteria, heat-resistant bacteria, or mesophilic bacteria, and thermophilic bacteria and heat-resistant bacteria are only limited species in terms of the overall types of microorganisms. Enzyme diversity was limited.
In addition to expectation of accidental discovery, establishment of a systematic and labor-saving method for searching industrially useful thermostable enzymes is required, and the present inventors have filed a patent application for the method. (See Patent Document 12).
There has been a demand for the development of a computer-processable program for easily doing this.

Special table hei 10-506524 JP 2000-50870 JP 2001-61474 A JP2003-2119864 JP 08-336388 A JP 08-149980 A No. 04-67957 Japanese Patent Laid-Open No. 02-5864 Japanese Patent Laid-Open No. 02-500565 Special table 2001-502169 JP 2000-41668 A Japanese Patent Application No. 2004-046880

Conventionally, in many cases of searching for thermostable proteins such as thermostable enzymes, thermophilic bacteria have been the target of screening. However, thermophilic bacteria are only a limited species when considered from the total types of microorganisms. The diversity of thermostable enzymes could not be expected so much. On the other hand, many industrially used thermostable enzymes have been isolated from so-called mesophilic bacteria, but the enzyme produced by screening the target enzyme-producing bacteria from nature and examining the culture conditions. Since heat resistance had to be confirmed one by one by experiment, enormous effort and time were required.
In order to improve the conventional method of searching for thermostable enzymes by trial and error, the present inventors have made it possible to heat the protein with a simple method based on data such as the amino acid sequence or base sequence of the protein. A novel method has been provided that can determine whether or not there is a property (Japanese Patent Application No. 2004-046880). However, this requires complicated statistical processing and computerization has been required.
The present invention aims to improve the conventional method of searching for thermostable enzymes by such trial and error, and is a simple method based on data such as amino acid sequences or base sequences of proteins. The present invention provides a computer program for determining whether or not the protein has heat resistance, data for the computer program, and a recording medium for the computer program.

  The present inventors conducted a principal component analysis using the amino acid composition of the protein predicted in the genomes of 120 types of microorganisms whose whole genome sequences have been known so far. The principal component score of each individual protein is calculated from the weighting factor), and the correlation between this value and the heat resistance of the protein has been studied, and this value and the value in the protein calculated by the thermophile corresponding to the protein Has been found to have a very strong correlation and has already filed a patent application (Japanese Patent Application No. 2004-046880). However, since this method requires a large amount of data processing such as search for ortholog-related proteins, calculation of unique analysis values (vector values) by principal component analysis of test proteins, and comparison with known proteins, Computerization for data processing such as calculation and search was desired, but this was completed.

That is, the present invention is a program executed by a computer for determining whether or not a test protein has heat resistance, and is specific to the test protein by principal component analysis based on the amino acid composition of the protein. In order to cause a computer to execute a process for discriminating the heat resistance of a protein, which comprises calculating the analysis value of the protein and comparing the analysis value with the analysis value of the test protein of the thermostable organism and the corresponding protein. Related to the program.
Further, the present invention is a program for causing a computer to execute the following steps to determine whether or not a test protein has heat resistance,
(1) inputting an amino acid sequence of a protein to be tested;
(2) a protein search step for searching for a known protein in a relationship with a corresponding protein (hereinafter referred to as a “corresponding protein”) produced by a biological species different from the test protein in another organism,
(3) calculating a specific analysis value by principal component analysis based on the amino acid composition of the protein to be tested;
(4) The unique analysis value of the corresponding protein searched in the step (2) and the unique analysis value of the test protein calculated in the step (3) are calculated, and the difference between them is calculated. Step,
(5) Based on the difference calculated in (4), determining whether or not the protein to be tested is similar to the corresponding protein searched in the step (2); and
(6) a step of displaying the corresponding protein searched in the step (2) and the result determined in the step (5);
By comparing the specific analysis value based on the amino acid composition of the test protein with the specific analysis value of the known corresponding protein, it is determined whether or not the test protein has heat resistance. Related to the program.
Furthermore, the present invention relates to a computer-readable recording medium that records a program for causing the computer of the present invention to be executed.

First, a method for determining whether the test protein of the present invention has heat resistance, which is the basis of the program of the present invention, will be described.
It is known that there is a correlation between the amino acid composition of all proteins inferred from the genome sequence of the microorganism for which the entire nucleotide sequence has been determined and the growth temperature of the microorganism. In particular, it is known that there is a significant correlation between hyperthermophilic archaea (Archia) exceeding 80 ° C. and some bacteria. However, since most of the hyperthermophilic bacteria whose whole genome sequence has been determined so far are archaea, detailed investigations have been made as to whether this correlation is unique to archaea or is characteristic of thermophilic bacteria. I did not come. Similarly, some thermophilic bacteria for which genome sequencing has been completed have no non-thermophilic, non-thermophilic bacteria closely related to them, or there is no genome sequence information even if they exist, It has been difficult to accurately determine whether the characteristics of the amino acid composition found in thermophilic bacteria are truly characteristic of thermophilic bacteria or simply reflect species specificity.

The inventors of the present invention have a thermophilic bacterium having a maximum growth temperature of about 70 ° C. within the same genus and a highly related genus, and a non-thermophilic bacterium having various growth maximum temperatures. Focusing on genus-related species, we decided to investigate the correlation between genome sequence information and heat resistance. Among these Bacillus related species, there have been four non-thermophilic Bacillus subtilis, B. halodurans, Oceanobacillus iheyensis, and Bacillus cereus (B. cereus) has been revealed, but the genome information of thermophilic Bacillus related species has not been analyzed.
Therefore, it was decided to analyze the genome of Geobacillus kaustophilus HTA426 (GK), which is a kind of thermophilic Geobacillus kaustophilus. This microorganism is obtained from the deep-sea Mariana Trench and has a maximum growth temperature of 74 ° C.
A phylogenetic tree prepared by the neighbor joining method based on 16S rDNA of these Bacillus related species is shown in FIG. The lower left bar in FIG. 1 shows 0.01 Knuc unit. The portion indicated by the lower line (red in the original figure) indicates a thermophilic bacterium. Five microorganisms used for the following analysis, from the upper side, B. halodurans C-125 (hereinafter abbreviated as BH), Bacillus subtilis 168 (hereinafter referred to as B. subtilis 168) BS.), Bacillus cereus ATCC 14579 (hereinafter abbreviated as BC), Oceanobacillus iheyensis HTE831 (hereinafter abbreviated as OI), and Geobacillus. Kaustophilus HTA426 (hereinafter referred to as GK) is marked with an asterisk on the right shoulder.

First, the present inventors determined the entire base sequence of the thermophilic Geobacillus kaustophilus genome. Next, the amino acid composition of proteins of these five microorganisms including Geobacillus kaustophilus (GK) and 120 microorganisms whose whole genome sequences have been clarified so far are analyzed as principal components. As a result of analysis by the method (PCA), it was observed that the first main component (PC1) showed a strong correlation with the GC content and the second main component (PC2) showed a strong correlation with the growth upper limit temperature as is conventionally known. It was.
The result is shown in FIG. The original drawing of FIG. 2 is a color graph. The horizontal axis of FIG. 2 shows the analytical value of the GC content (PC1), and the vertical axis shows the analytical value of the growth upper limit temperature (PC2). The principal component analysis method (PCA) performed here is based on a general statistical method. Red squares (black in black and white figures) indicate thermophilic bacteria, blue (black in black and white figures) indicates gram-positive bacteria with low GC content, and green (slightly gray in black and white figures) contains GC High amount of gram positive bacteria. A line of 0.0152 in PC2 in FIG. 2 indicates a boundary between thermophilic bacteria (upper side) and non-thermophilic bacteria (lower side).
Moreover, even if it restricted between Bacillus (Bacillus) related species, the correlation was seen between the 2nd main component score and the growth upper limit temperature. However, this is a result of using the average amino acid composition of the whole bacterium, and the correlation is not so clear from the viewpoint of individual proteins due to the large dispersion.

Therefore, the present inventors apply the heat resistance index of each protein to the amino acid composition using the eigenvector corresponding to the second principal component as a weighting factor among the above-mentioned five types of microorganisms related to the genus Bacillus used for the analysis. First, it calculated.
As a principal component analysis method based on the amino acid composition used here, 119 types of microbial genome data were obtained from a database published by NCBI, and this was determined in the present invention. Geobacillus kaustophilus HTA426 ) Using the protein sequences identified in 120 different genomes. Among these sequences, sequences having a sequence length of less than 50 amino acids were removed, and proteins predicted to have two or more transmembrane regions using the PSORT program were also removed. Using the remaining protein sequences, the average amino acid composition is calculated for each species, and a matrix with the species as rows and amino acids as columns is input, and the principal analysis function of the statistical analysis package R is used. Component analysis was performed.
Next, based on this result, the difference between the main component score of the corresponding protein of the thermophilic Geobacil scout phyllus and the value of the four non-thermophilic bacteria was calculated. This association was performed based on the ortholog relationship estimated from the homology search result, and analysis was performed on proteins having a correspondence relationship of 1: 1. (Kreil DP and Ouzounis, CA (2001) Identification of thermophilic species by the amino acid compositions deduced from their genome. Nucleic Acids Res. 29, 1608-1615)
The selected 965 proteins are proteins that do not have two or more transmembrane regions and have approximately the same maximum temperature for growth (Geobacillus stearothermophilus) (hereinafter abbreviated as GS). )) 965 proteins common to 5 types were extracted from the genome server. In addition, it was determined by the PSORT program (Nakai, K. & Horton, P., PSORT: Trends Biochem. Sci., 24, 34-36 (1999)) whether it has two or more transmembrane regions.
As a result, the calculated “principal component score” values are shown in the following Tables 1 to 18. Each column of these tables is, from the left side, “GK ID” which is an identification symbol based on GK, “Category” indicating the classification of each protein, “Note” indicating the name of each protein, and five types on the right side. These are the identification symbols and the “principal component score” values of the microorganisms, and are arranged in the order of GK, BC, BH, BS, and OI from the left. The color assigned to the identification symbol of each microorganism is that the difference from the “principal component score” of GK to which red corresponds (difference from GK = (each value) −each GK value) is −0.005 or less. The blue color indicates that the difference from the “principal component score” of the corresponding GK is −0.010 or less, and the green color indicates that the difference from the “main component score” of the corresponding GK is −0.015. This indicates that the difference between the corresponding GK and the “principal component score” exceeds −0.015.

As is clear from this result, even if no clear correlation was found for the whole microorganism, it was revealed that there was a clear correlation by comparing each corresponding protein. is there. In order to make this clearer, the correlation between GK and various microorganisms was graphed.
First, in graphing, the orthologs were associated with Geobacillus stearothermophilus (GS) having the same upper growth limit temperature as GK as follows. The GS draft genome sequence was obtained from the Oklahoma University FTP site. For these contig sequences, a similar sequence was searched with the TBLASTN program using each translation sequence of GK as a query, and the hit with the highest score showed 70% or more match for the region of 70% or more of the query length. It was an ortholog. Next, for GK and GS, a correlation diagram based on the value of “principal component score” in each protein is shown in FIG. The horizontal axis of FIG. 3 shows the value of “principal component score” of GK, and the vertical axis shows the value of “principal component score” of GS. A solid line in the graph indicates a portion where both values are the same, and a broken line indicates a range of ± 0.01 from the solid line. Thus, when each protein is compared between thermophilic bacteria, it turns out that the value of the "principal component score" of each protein has a very strong correlation. Similarly, FIG. 4 shows graphs showing the correlation with GK for BC, BH, BS and OI which are non-thermophilic bacteria. The upper left (a) in FIG. 4 is the correlation between GK and BC, the lower left (b) is the correlation between GK and BH, the upper right (C) is the correlation between GK and BS, and the lower right is GK and GK. Correlation with OI. The horizontal axis of each graph shows the value of “principal component score” of GK, and the vertical axis shows the value of “principal component score” of each non-thermophilic bacterium. From this graph, it can be seen that some non-thermophilic bacteria show a good correlation with GK depending on the type of protein, but some show completely different values.

In the correlation between GK and GS described above, strong correlation was observed in almost all proteins, but it can be seen that there are proteins that have almost no correlation in comparison with non-thermophilic bacteria. This may be due to the fact that the protein does not have heat resistance. On the contrary, non-thermophilic bacteria do not have heat resistance as a whole, but not all proteins produced by the microorganism have heat resistance, but have heat resistance. It is thought that some proteins are not. If a protein that has lost its heat resistance is an essential protein for life support, even if all other proteins have heat resistance, the microorganism is no longer heat resistant as a whole organism. It will not have.
This is a new finding in the present invention by the present inventors. That is, conventionally, when searching for a heat-resistant protein, it has been done by screening a heat-resistant microorganism. This is because a heat-resistant life form has a heat-resistant protein, otherwise life cannot be maintained under high temperature conditions. However, not all proteins produced by non-thermophilic bacteria must be non-thermostable. Even if non-thermophilic bacteria produce heat-resistant proteins, the problem of sustaining life is not necessarily the case. Non-thermophilic bacteria are all non-thermophilic. It is possible that it is not the result of becoming non-heat-resistant, but that it is the result of the loss of heat resistance of proteins essential for life support.
The results shown in Tables 1 to 18 and FIG. 4 clarify the possibility of producing a heat-resistant protein similar to that produced by a thermophilic bacterium even if it is a non-thermophilic bacterium. is there.

  A summary of these results in relation to the maximum growth temperature of each microorganism is shown in FIG. The horizontal axis of FIG. 5 indicates temperature, and the vertical axis indicates percentage (%). Black square marks (■) in the graph indicate GK, black circle marks (●) indicate BH, white circle marks (◯) indicate BS, white triangle marks (Δ) indicate BC, and white square marks (□ ) Indicates OI. On the horizontal axis, the upper limit temperature of growth of each microorganism is plotted, and on the vertical axis, the upper line (green in the original figure) shows that the difference in the value of “principal component score” from GK out of 965 proteins is −0. The percentage of the number of proteins exceeding .015 to the total of 965 (%) is plotted for each microorganism, with the middle line (blue in the original figure) of the protein similarly exceeding -0.010. Number percentage (%) is a line plotted for each microorganism, and the lower line (red in the original figure) similarly plots the percentage (%) of the number of proteins above -0.005 for each microorganism. Is a line. The difference in the value of the “principal component score” exceeds −0.015 (that is, −0.015 or more, the absolute value is small but the negative value is large. The same applies hereinafter). Table 19 below summarizes the numbers and ratios of proteins of these bacteria for BC, BH, BS, and OI.

Table 19 summarizes the results of predicting thermostable proteins from bacteria of each genus Bacillus based on the principal component analysis described above. In Table 19,-indicates that the difference between the PC2 value of each protein and GK was less than -0.015, and that there was no heat resistance, + indicates the difference between the PC2 value of each protein and GK- A value greater than 0.015, ++ is greater than −0.01, and ++ is greater than −0.005 and are determined to have heat resistance. In Table 19, ++ and ++ indicate the sum of ++ and ++ described above, and +, ++, and ++ indicate the sum of +, ++, and ++ described above. Table 19 summarizes the results of analysis based on 965 orthologs that have a 1: 1 correspondence between five Bacillus species.
As a result, as shown in Table 19, 83.5% of 965 proteins in BC, 79.1% in BH, 72.1% in BS, and 59.5% in OI are heat-resistant proteins. It was predicted. In this graph, BC (Δ) shows a slightly abnormal value, but it can be seen that the three types of proteins show the same tendency. That is, it is shown that the upper limit temperature for growth is higher as the microorganism produces more proteins having the same “principal component score” value as the protein produced by thermophilic bacteria. For example, OI producing the smallest amount of protein having a “principal component score” value similar to that produced by thermophilic bacteria has the lowest growth upper limit temperature among these microorganisms. In addition, BC (Δ) has the largest amount of the same protein among these four types of non-thermophilic bacteria, but the growth upper limit temperature is abnormally low. This is thought to be the result of the accidental loss of heat resistance of a protein essential for life support.

Next, in order to verify this, proteins were separated from these microorganisms, and each treatment was (1) unheated, (2) heated at 60 ° C for 10 minutes, and (3) heated at 70 ° C for 10 minutes. We examined the pattern of native PAGE after doing this. The results are shown in FIG. The left side of FIG. 6 (FIG. 6a) is the total protein, which is stained with Coomassie brilliant blue. As a result, almost all protein bands can be confirmed even after heat treatment (lanes 2 and 3) in the thermophilic bacterium GK, but in the other four types of non-thermophilic bacteria, more It can be seen that the protein band disappears. However, what is important here is that not all protein bands disappear. It can be seen that some protein bands remain without being lost even after heat treatment. This proves that not all the proteins produced even in the case of the non-thermophilic bacteria described above are non-thermostable.
The right side of FIG. 6 (FIG. 6b) shows the protein band having esterase (EC 3.1.1.1) activity detected by the activity staining method after separation of all proteins of each microorganism by native PAGE as in FIG. 6a. is there. BC, BH, BS, GK, and OI in each figure indicate the respective microorganisms. In each of the lanes 1 to 3 of each microorganism, lane 1 is unheated, lane 2 is 60 ° C. for 10 minutes, and lane 3 is 70 ° C. 10 Minutes. In OI in esterase (FIG. 6b), the band disappeared by heat treatment at 60 ° C. (lane 2). In addition, the main band, which was most strongly stained when BC was not treated, disappeared by heat treatment at 60 ° C. However, in BS, the band is not lost by the heat treatment, and in BH, the band is not lost even by the heat treatment at 60 ° C., but it is maintained.
In addition, GroES, which is one of the proteins essential for growth in Bacillus subtilis, and Hag (Flagellin), which is one of the typical proteins conserved among the species related to the genus Bacillus, The gene coding for was amplified by PCR, and heat resistance was verified in the same manner as described above using a gene cloned using E. coli. Each cloned and purified protein was examined for native PAGE patterns after (1) unheated, (2) heated at 60 ° C. for 10 minutes, and (3) heated at 70 ° C. for 10 minutes. . The results are shown in FIG. The left side (FIG. 7a) is Hag, and the right side (FIG. 7b) is GroES. After separation by native PAGE, the result of staining with Coomassie brilliant blue is shown. BC, BH, BS, GK, and OI in each figure indicate the respective microorganisms. In each of the lanes 1 to 3 of each microorganism, lane 1 is unheated, lane 2 is 60 ° C. for 10 minutes, and lane 3 is 70 ° C. 10 Minutes.

Then, what kind of protein is heat resistant becomes a problem. In the case of esterase, since it is possible that a plurality of proteins may be stained by a staining method, it has been found that it is difficult to uniquely identify which band actually corresponds. I decided to pay attention to Hag and GroES. Therefore, the results of verifying the Hag of each microorganism are shown in FIG. 7a and FIG. 7b for GroES. These proteins have GK identification symbols described in the above table of GK3131 (Hag) and GK0248 (GroES).
The value of the main component score of each protein of these proteins is as follows. Hag is (GK, -0.0513; BC, -0.0622; BH, -0.0567; BS, -0.0578; OI, -0.0528) (see Table 17), GroES is (GK , 0.1018; BC, 0.0826; BH, 0.1012; BS, 0.094; OI, 0.0988) (see Table 3). These are collectively shown in Table 20 below.

As for the Hag protein, bands other than BC are maintained in the same manner as when untreated even by heat treatment at 70 ° C. Regarding the GroES protein, only a slightly thin band was confirmed by heat treatment at 60 ° C. or higher for BC and BS, and it is considered that the protein was decomposed by heat treatment. For other GK, OI, and GK, bands were maintained in substantially the same manner as untreated. This indicates that some non-thermophilic bacteria have heat resistance and some do not.
Next, protein bands that did not disappear even after heat treatment at 70 ° C. for 10 minutes shown in FIG. 6a were cut out from the gel in order from the top, and the proteins contained in each band were identified using LC / MS / MS. went. The results are shown in Tables 21-25.

Table 21-25 shows the breakdown (Table 21 and Table 22) of proteins derived from Bacillus subtilis (BS) whose heat resistance has been confirmed by heat treatment experiments, and Bacillus halodurans (BH). Breakdown of proteins derived from Table (23), Breakdown of proteins derived from Oceanobacillus iheyensis (OI) (Table 24), Breakdown of proteins derived from Bacillus cereus (BC) (Table 23) 25) respectively. Each column of each table shows, from the left, the BS gene name, its product name, the corresponding GK gene name, the prediction result, the number of amino acids in the product, and the score difference of the principal component analysis of GK and BS. In the “prediction result” column, − indicates that the difference from the PC2 value of GK is less than −0.015, and it is determined that there is no heat resistance, and + indicates that the difference is greater than −0.015. ++ is greater than −0.01, and ++ is greater than −0.005 and is determined to have heat resistance.
As shown in Table 21-25, at least 38 heat-resistant proteins were identified for BC and BH, 117 for BS, and 52 for OI. Therefore, it was examined how the presence or absence of heat resistance of a protein for which heat resistance was confirmed was predicted by comparing the main component scores of GK and other species belonging to the genus Bacillus. As described above, if the difference between the main component scores of each Bacillus genus-related species and GK is −0.015 or more, 34 of 38 (89.5%) in 38 shown in Table 25 in BC However, in BH, 36 out of 38 (94.7%) shown in Table 23, BS in 103 out of 117 shown in Table 21 and Table 22 (88.0%), and OI shown in Table 24 It can be seen that 46 out of 52 (88.5%) were predicted to be heat resistant by the method of the present invention.
These results are summarized in Table 26 below. Each symbol in Table 26 is the same as in Table 19. Therefore, the method of the present invention in which the heat resistance of a protein produced by a non-thermophilic bacterium can be determined by calculating the correlation with the corresponding protein of the thermophilic bacterium, the heat resistance of the protein. It is that it shows.

Although the method of the present invention has been described based on Bacillus related species, the method of the present invention is not limited to the exemplified Bacillus related species and corresponds to the protein to be tested. Those skilled in the art will readily understand that thermostable proteins can be applied to any species as long as they exist.
The “heat-resistant organism” in the present invention may be any organism that can maintain life at or above the temperature at which a human can maintain life, and specifically, it is about 50 ° C. or more, preferably 60 ° C. or more, more preferably An organism that can sustain life in an environment of 65 ° C or higher. Examples include thermophilic bacteria and hot spring organisms. As the “thermostable organism” in the method of the present invention, a thermostable organism having a relationship with an organism producing the test protein is preferable. Examples of the “relevance” herein include closeness by biology classification, genetic closeness in embryology, and functional closeness of the protein to be tested.
In the present invention, the “protein possessed by a thermostable organism” is a protein produced by the thermostable organism, and whether the protein is produced by the thermostable organism regardless of whether or not it is a protein necessary for life support. If it is.
In the present invention, the “protein corresponding to the test protein possessed by the thermostable organism” may be a protein having the same kind as that of the test protein, preferably the same function as that of the test protein. It is not necessary to have a biological relationship, but those having a biological or developmental relationship are preferable. For example, as described above, examples include correspondence relationships based on biological orthologous genes, and relationships between proteins having the same kind of functions among organisms of the same or the same kind.
The “protein corresponding to the test protein possessed by the thermostable organism” in the method of the present invention is not necessarily one protein, and may be two or more proteins. And when two or more proteins can be selected as such a protein, it is also possible to judge comprehensively by comparing with each other.

  In the method of the present invention, as a technique for calculating the “heat resistance index of the test protein based on amino acid composition”, based on the gene encoding the protein identified in the genome of the organism exemplified above, Proteins are extracted, and among these proteins, proteins whose amino acid sequence is less than 50 amino acids are removed, and proteins in which two or more transmembrane regions are predicted using the PSORT program are also removed. Using the amino acid sequences of the remaining proteins, the average amino acid composition is calculated for each biological species, the biological average is calculated for the calculated average amino acid composition, a matrix having amino acids as columns is input, and the statistical analysis package R Method Based on Principal Component Analysis Using the Princomp Function (Kreil DP and Ouzounis, CA (2001) Identification of the Nucleic Acids Res. 29, 1608-1615) is effective, but the number of proteins whose heat resistance has been verified experimentally is not limited to this. If there are more than a certain number, it is possible to improve by incorporating the knowledge by methods such as discriminant analysis and regression analysis. Further, in the present invention, it is preferable to use the whole protein (full length), but it is also possible to carry out using only each domain and partial length of the protein.

As the “comparison of analysis values” in the method of the present invention, the method of taking the difference between them as shown in the above example is simple and preferable, but is not limited thereto. When a large amount of data is accumulated, it is possible to make a comparison based on a difference from the overall average value or a value subjected to statistical processing such as a deviation.
In addition, the criterion for comparison can be set within a range in which it can be confirmed that the test protein actually has heat resistance. In the above-described example, heat resistance is within a range where the difference between the principal component score calculated from the eigenvector value (weighting coefficient of each amino acid) and the number of amino acids of each protein is about −0.005 to −0.015 or less. Can be determined. Such a determination is not necessarily limited to whether or not it exists, but can also be displayed as a percentage (%) as the possibility of having heat resistance.

  In the method of the present invention, the data for calculating a specific analysis value by principal component analysis based on the amino acid composition of the protein to be tested includes amino acid sequence and / or base sequence data of the protein. It is not limited, and it may be only the amino acid composition. As such data, data having a large amount of information is preferable in order to increase the determination accuracy. However, as shown in the above example, the base sequence encoding the protein can be mentioned as a simple and preferable example. In addition to this, it is possible to add more 3D protein data, but what kind of data is necessary is not only an improvement in the accuracy of judgment, but also a processing method for processing this data Depends heavily on.

Specifically, the method of the present invention comprises the following steps (1) to (6).
(1) Obtaining an amino acid sequence of a protein and / or a base sequence encoding it.
(2) Calculate the “unique analysis value” of the protein based on the amino acid sequence and / or base sequence data.
(3) Select “protein corresponding to the test protein possessed by the thermostable organism” with the protein as the test protein.
(4) Obtain analytical value data of the selected “corresponding protein”.
(5) Compare the two.
(6) To make a determination based on the result of the comparison.
In these steps, the processing method can be set in advance for matters other than the determination of the arrangement in (1) and the selection in (3), and can be processed by an electronic computer. Further, if the step (3) is also classified in advance based on enzyme classification or the like, it is possible to select a “corresponding protein” to be selected from the accumulated data. If it does so, it can be set as the process by an electronic computer except the step of said (1).
That is, the present invention is programmed so that the above-described method of the present invention can be processed by an electronic computer, and the processing inputs (a) the amino acid sequence or base sequence data of the protein to the program. (B) Extracting the “corresponding protein” from the accumulated data based on the protein classification symbol, function data, origin data, etc. (C) a method of referring to a specific analysis value of the “corresponding protein” extracted in the step (b) described above as a value of calculated or accumulated data, and (d) a specific analysis value of the protein. , Processed by an electronic computer as a method of comparing specific analysis values of “corresponding proteins”, (e) a method of displaying (outputting) the comparison results It is intended to provide the law.

  In the processing by the electronic computer described above, the analysis value in the protein corresponding to the test protein of the thermostable organism can be calculated each time, but the value calculated by the principal component analysis based on the amino acid composition of the protein Can be classified and listed according to the type of each protein to be stored data. Such accumulated data can be accumulated in a recording medium that can be processed by an electronic computer so that it can be used as information for processing by the electronic computer. Examples of such a recording medium include a hard disk, a DVD disk, a CD-ROM, an MO, and a flexible disk.

Therefore, as a program of the present invention for causing a computer to execute the following steps to determine whether or not a test protein has heat resistance, for example,
(1) inputting an amino acid sequence of a protein to be tested;
(2) A protein search step for searching for a known protein in a relationship with a corresponding protein (corresponding protein) produced by a species different from the test protein in another organism,
(3) calculating a specific analysis value by principal component analysis based on the amino acid composition of the protein to be tested;
(4) a specific analysis value of the corresponding protein searched in the step (2);
Calculate the specific analysis value of the test protein calculated in the step (3),
Calculating the difference between the two,
(5) Based on the difference calculated in (4) above, determining whether the test protein is similar to the corresponding protein searched in the step (2); and
(6) a step of displaying the corresponding protein searched in the step (2) and the result determined in the step (5);
By comparing the specific analysis value based on the amino acid composition of the test protein with the specific analysis value of the known corresponding protein, it is determined whether or not the test protein has heat resistance. A program for this.

In the following, the program of the present invention will be described. In the following description, the corresponding protein is an ortholog-related protein, and the inherent analysis value based on the amino acid composition is the value of the second principal component of the principal component analysis. This will be described as an example. The program of the present invention can be executed stand-alone, but in the following description, a server type program will be described as an example. The following description is an illustration of the present invention, and the present invention is not limited to these examples.
An execution flowchart of the client is shown in FIG. When activated, a startup screen is displayed, and at that time, data necessary for an ortholog search or the like is read. When the startup setting is completed, an input screen from a terminal or the like is displayed. The input of the test protein may be any of type-in, FD, CD, online, etc., and the amino acid sequence and / or base sequence of the test protein and its origin are input. In FIG. 8, it is shown as a “variable plot”.
When the input is completed, the ortholog is searched next, but as an option, it is designed so that the organism to be searched can be selected. The selection of species is not essential, and all accumulated species can be targeted. Search the ortholog for the specified species.
Various parameters such as the amino acid sequence, amino acid composition, function, origin, and expression organ of the test protein can be used as the method for searching the ortholog. In this example, the ortholog is searched by searching for homology based on the amino acid sequence. is doing. In this example, an ortholog is a protein that is highly homologous to the test protein, for example, a protein having a homology of 70% or more, 80% or more, or 85% or more and that is derived from a species different from the test protein. The candidate is selected.

As a result of this ortholog search, if no corresponding orthologous protein is found (“no” of “no ortholog list” in FIG. 8), the comparison is not possible, so the processing ends.
When one or more orthologs are found (in FIG. 8, in “yes” of “no ortholog list”), an ortholog list is created, and the value of the second principal component based on the amino acid composition for each ortholog (Score) is calculated, and the value (score) of the second principal component of the protein to be tested is compared with the value (score) of the second principal component of the corresponding protein, and the difference is calculated for discrimination.
In this example, the difference between the two is ± 0.005, ± 0.010, and ± 0.015 as defaults in this example, but the user can also set the options as an option. It has become. The result is displayed in an Excel format or a screen display format.
The display of the result is based on a tabular format, but can be displayed as a graph specified by the user based on the tabular format. Moreover, you may color according to the magnitude | size of a difference. As a color tone at this time, red, blue, green, or the like may be set as a default.

FIG. 9 shows a flowchart up to data entry on the server side. When an activation request is received from the client, the program starts and data is read. When the data format check is completed, character strings other than amino acid character strings are deleted to recognize amino acids. The number of amino acids is counted from the input amino acid sequence, and if the number of amino acids is less than 50, the process is terminated (“Minimum Length check” in FIG. 9). Next, the “SOSUI” program is used to test whether the input protein has a transmembrane domain. This program is a program for estimating a transmembrane domain from a sequence of hydrophobic amino acids. If it is determined by the “SOSUI” program that there are two or more transmembrane domains, the input protein is handled as a membrane protein, and the processing is terminated as a non-processing target of this program.
When the number of amino acids of the input protein is 50 or more and there are less than one site estimated to be a transmembrane domain, the amino acid composition is analyzed. In the analysis of amino acid composition, the content of each amino acid is calculated in% for each of the 20 types of amino acids in the translation region (ORF). Next, principal component analysis is performed. For this principal component analysis, a commercially available program for statistical processing can be used. The value of the second type component is calculated by principal component analysis, and the data input process is terminated.

In the search for the corresponding protein, homology is searched from the N-terminal side and the C-terminal side of the protein, for example, the homology is searched using BLASTP, and the protein having the highest homology is used as the corresponding protein. If no homology is found by default with 70% or less, the corresponding protein is not found, but the user can also set the minimum homology.
The program of the present invention refers to a database of known proteins for searching for the corresponding protein. For this purpose, it is necessary to accumulate data of known proteins, and the program of the present invention may have a step for inputting data of known proteins for searching for corresponding proteins. Data sources of such data include those published in various academic journals and databases that can be used on the Internet. In the case of a database that can be used on the Internet, it is also possible to set to automatically download new information automatically by periodic or non-periodic automatic access. The data obtained in this way can be stored in the reference file of the program of the present invention as stored data in the same flow as shown in FIG.
The program of the present invention refers to a database of values of the second principal component of principal component analysis based on the amino acid composition of known proteins. This value can be calculated from the amino acid sequence of the known protein database for searching for the corresponding protein, so when the known protein for searching the corresponding protein is input, the calculated data is accumulated data. Can be entered as
The program of the present invention may further include such an input step.

The main functions of the program of the present invention are summarized as follows.
Using the amino acid sequences of heat-resistant microorganisms and several closely related non-heat-resistant amino acids as inputs, the results of principal component analysis based on the amino acid composition are displayed as a scatter diagram. In the main component scoring chart in units of microorganisms, it is possible to estimate microorganisms having heat resistance, and it is possible to obtain exceptional microorganism candidates whose actual growth temperature does not match the estimation result from the principal component analysis.
Due to the function of comparing the second principal component of the protein having an ortholog relationship between the thermophilic bacterium and the non-thermophilic bacterium, the heat-resistant protein present in the non-thermophilic bacterium can be estimated. In addition, in the case of an exceptional microorganism whose actual growth temperature and the estimation result from the principal component analysis do not match, it is possible to estimate a gene that is deeply involved in heat resistance.
The program of the present invention is composed of a calculation step for creating a data set necessary for heat resistance prediction and two steps for predicting heat resistance based on the amino acid composition of a protein for which the presence or absence of heat resistance is desired. The processing contents and order are as follows.
(1) Processing contents and order of data set creation step (a) Minimum sequence exclusion An amino acid sequence shorter than a certain length is deleted.
(B) Exclusion of hydrophobic region A sequence containing two or more transmembrane regions is deleted from data hit by SOSUI (program for estimating transmembrane domain).
(C) Determination of orthologs between each organism species BLASTP is performed on all rounds, and one with the best result is obtained one by one.
A FASTA file that leaves only the resulting ortholog is created (W1).
(D) Calculation of amino acid composition The amino acid composition is calculated in units of orthologs and averaged in units of species.
Calculate based on the file W1. The amino acid composition of the ortholog unit is saved as a W2 file.
(E) Principal component analysis The principal component score is calculated based on the amino acid composition.
Based on the principal component score for each species, the principal component score scatter diagram display data is output to a W3 file.
A score is calculated for each ortholog using the eigenvector of the second principal component and the file W2, and stored in the W4 file.

(2) Processing contents and processing order of heat resistance prediction step (a) Whole distribution map display Files I2, I3, W3 are read, and a scatter diagram for each species
(Each element can be selected, etc.) Create and display.
From this overall distribution map, the organism (the organism with the corresponding protein) to be compared and the species to be compared (s) can be selected.
(B) Compare the scores of the proteins having an ortholog of all the proteins of the organism having the corresponding protein and the organism having the test protein.
(C) Read the files W1 and W4 for the selected species and acquire information.
(D) List differences in the scores of proteins that have an ortholog of all the proteins contained in the corresponding control species and the organisms with the corresponding proteins. (Displays three different colors depending on the size of the difference)
(E) In addition, the difference between the one-to-one ortholog scores of the organism having the corresponding protein and the control organism is displayed as a scatter diagram.
Table 27 below summarizes the main functions of the program of the present invention.

The program of the present invention can be recorded on a computer-readable recording medium so that the computer can execute the program. Examples of such a recording medium include a hard disk, a DVD disk, a CD-ROM, an MO, and a flexible disk.
Therefore, the present invention also provides a computer-readable recording medium on which the program of the present invention is recorded.
In the recording medium of the present invention, a database of known proteins for searching for the corresponding protein referred to by the program of the present invention and a database of specific analysis values based on the amino acid composition of the known proteins are recorded together. It can also be left.

The method of the present invention is very quick and inexpensive because it can predict the heat resistance of a protein on a computer by calculating a specific analysis value of the protein without an experiment. In addition, since the present invention can be determined not by an individual organism but by a protein unit produced by the organism, a search for thermostable enzymes that conventionally had to rely on thermophilic bacteria for its resources. The range can be expanded to the range of proteins produced by mesophilic bacteria, and the screening range for thermostable proteins can be expanded. In addition, it has become possible to narrow down candidates for thermostable enzymes in advance for screening thermostable enzymes from mesophilic bacteria, which has been extremely time-consuming and laborious, so that the search for thermostable enzymes that can be used in various processes is now possible. Can be easily performed.
Furthermore, by using a computer program developed in accordance with the present invention, a thermostable enzyme from a non-thermophilic bacterium having a thermophilic bacterium as a related bacterium can be easily predicted, thereby providing a thermostable enzyme rich in diversity that has never existed before. The time required for searching can be significantly reduced. In addition, the program of the present invention can predict the heat resistance of a protein whose heat resistance is to be known on a personal computer running on Windows (registered trademark). it can.

  Hereinafter, the experimental results that are the basis of the program of the present invention will be described more specifically by way of examples. However, the present invention is not limited to these examples.

Calculation method of data of 120 species of bacteria.
119 types of microbial genome data were obtained from the database published by NCBI, and the genome of Geobacillus kaustophilus HTA426 determined in the present invention was identified in 120 types of genomes. The protein sequence was used for analysis. Among these protein sequences, a protein having a sequence length of less than 50 amino acids is removed, and further 2 using the PSORT (K. Nakai, P. Horton, Trends Biochem. Sci., 24, 34-6, 1999) program. Proteins predicted to have more than one transmembrane region were also removed. Using the remaining protein sequence, calculate the average amino acid composition for each species, enter a matrix with the species as rows and amino acids as columns, and the method of Craile et al. (D. Kreil, C. Ouzounis, Nucleic According to Acids Res, 29, 1608-15, 2001), principal component analysis was performed. For the analysis, the princomp function of the statistical analysis package R was used.

Calculation method of intrinsic analysis value data of 965 proteins The correspondence of five kinds of orthologs of GK, BC, BH, BS, OI is MBGD (I. Uchiyama, Nucleic Acids Res 31, 58-62, 2003) ) Performed using a clustering program on the server. Only ortholog groups present in all five and having a one-to-one correspondence were used for the analysis. Furthermore, a group including 4 or more proteins predicted to have 2 or more transmembrane regions by PSORT was excluded. Using the eigenvector of the second principal component obtained by the principal component analysis described in Example 1, the heat resistance index of each protein was calculated as the inner product of the amino acid composition vector and the eigenvector.

Analysis of total proteins GK, BS and BC use LB medium (pH 7), and BH and OI use Horikoshi II medium (pH 9.5) (Takami, H, Kobayashi, T., Aono, R , and Horikoshi, K. Appl. Microbiol. Biotechnol. 38, 101-108, 1992). The culture temperature was 37 ° C except for 55 ° C of GK. The cultured cells were obtained by centrifugation, washed with 50 mM phosphate buffer, and then resuspended in the same buffer to obtain a bacterial solution. Next, the bacterial cell disruption solution prepared by using this bacterial solution in a French press was centrifuged, and the bacterial cell residue removed was used as a protein solution for the analysis of total proteins. The protein solution was heat-treated at 60 ° C. and 70 ° C. for 10 minutes and then rapidly cooled to obtain a heat-treated protein solution. The total protein was analyzed by native gel electrophoresis, and the gel concentration was 12.5%. The gel after electrophoresis was stained with Coomassie brilliant blue.

Identification of thermostable protein The protein solution of each organism prepared by the method described in Example 3 above was separated by native gel electrophoresis in the same manner as in Example 3, and stained with Coomassie Brilliant Blue. Protein bands that did not disappear after heat treatment were excised from lane 3 in Fig. 6 after electrophoresis of four protein solutions excluding GK that had been heat-treated at 70 ° C for 10 minutes. The peptides were fractionated using an LC / MS / MS system after trypsin treatment, and the mass was calculated. Mass spectrometry is performed using the Bioworks 3.1, Xcalibour system manufactured by Thermo Electron and collated with the protein database of each Bacillus-related species, and the protein contained in each band is identified. Went.
The results are shown in Tables 21-25.

Analysis of esterase The protein solution of each organism prepared by the method described in Example 3 above was similarly separated by native gel electrophoresis, and only the band having esterase activity was detected by the method described below.
2 ml of 1% α-naphthyl acetate dissolved in 50% acetone and 100 mg of fast blue BB salt are added to 100 ml of 0.05 M Tris hydrochloride buffer (pH 7.4) and stirred. After being transferred to a plastic container, the gel after electrophoresis is immersed and shielded from light and kept at 37 ° C. for 10 minutes. When a band having esterase activity appeared, the previous solution was discarded and the gel was washed with distilled water.
The obtained esterase from each organism was subjected to native gel electrophoresis as an untreated solution, heat-treated at 60 ° C. and 70 ° C. for 10 minutes, and then rapidly cooled as a heat-treated protein solution. A gel concentration of 12.5% was used.

Analysis of flagellin The hag gene was amplified by PCR using a primer set designed from the base sequences of the hag gene of five strains. Next, these PCR products were ligated to a plasmid vector (pCRT7TOPOTA) for TA cloning having His-tag at the N-terminus and transformed into E. coli BL21 DE3. The transformed Escherichia coli was cultured until OD600 reached 0.6, 0.5 mM IPTG was added, and expression was performed at 30 ° C. for 3 to 5 hours. The bacterial cell disruption solution prepared by crushing the bacterial cells with a French press in the same manner as described above was applied to a TALON Metal Affinity column for easy purification of only proteins with His-tags. Then, the target protein was purified with 150 mM imidazole, 50 mM sodium phosphate and 300 mM NaCl. The degree of purification of the purified protein was confirmed by SDS-PAGE.
Using the purified protein, heat treatment was performed according to the method of Example 4, and the protein was separated by native gel electrophoresis and then stained with Coomassie brilliant blue.

Analysis of GroES GroES gene was amplified by PCR using a primer set designed from the base sequences of groES genes of 5 strains, and the protein was purified in the same manner as in Example 5. In addition, GroES was similarly analyzed using the purified protein through heat treatment and electrophoresis.

Thermostable proteins such as thermostable enzymes are used in various industrial fields such as sugar industry, protein industry and fertilizer industry, and their importance is extremely high. In addition, the use of thermostable enzymes, such as DNA polymerase, is indispensable in gene manipulation techniques.
The program of the present invention provides a new technique for searching for thermostable proteins such as thermostable enzymes by a simple technique, and is extremely useful industrially. In addition, the method of the present invention teaches that the search range of thermostable proteins can be further expanded from only those derived from conventional thermophilic bacteria, and makes a great contribution to the industry.

FIG. 1 shows a phylogenetic tree created by the neighbor joining method based on the 16S rDNA of a Bacillus-related species used in the method of the present invention. FIG. 2 shows the amino acid composition of the proteins of 120 microorganisms whose whole genome sequences have been clarified so far by the principal component analysis method (PCA), with the first principal component as the GC content (PC1), It is the graph created with the color which shows the result of having analyzed the component as growth upper limit temperature (PC2). FIG. 3 shows the “principal component score” for each protein for Geobacillus stearothermophilus (GS), which has almost the same maximum temperature as that of thermophilic Geobacillus kaustopilus (GK). The correlation diagram based on the value of is shown. The horizontal axis of FIG. 3 shows the value of “principal component score” of GK, and the vertical axis shows the value of “principal component score” of GS. FIG. 4 is a graph showing the correlation between GK for thermophilic Geobacillus kaustopilus (GK) and non-thermophilic bacteria BC, BH, BS, and OI. The upper left of FIG. 4 is the correlation between GK and BC, the lower left is the correlation between GK and BH, the upper right is the correlation between GK and BS, and the lower right is the correlation between GK and OI. The horizontal axis of each graph shows the value of “principal component score” of GK, and the vertical axis shows the value of “principal component score” of each non-thermophilic bacterium. FIG. 5 shows GK (black square mark (■)), BC (white triangle mark (△)), BH (black circle mark (●)), BS (white circle mark (◯)), and OI (white square mark (□). )) And the growth upper limit temperature of each microorganism, and a graph summarizing the relationship between the contents of proteins with different differences in GK “principal component score” among 965 proteins. The horizontal axis of FIG. 5 indicates temperature, and the vertical axis indicates percentage (%). On the horizontal axis, the maximum growth temperature of each microorganism is plotted. On the vertical axis, the upper line (green in the original figure) shows that the difference in the value of “principal component score” from GK out of 965 proteins is −0. The percentage of the number of proteins exceeding .015 to the total of 965 (%) is plotted for each microorganism, with the middle line (blue in the original figure) of the proteins similarly exceeding -0.01. Number percentage (%) is a line plotted for each microorganism, and the lower line (red in the original figure) similarly plots the percentage (%) of the number of proteins above -0.005 for each microorganism. Is a line. FIG. 6 is a color photograph, instead of a drawing, showing the result of examining the native PAGE pattern after separating proteins of GK, BC, BH, BS, and OI microorganisms. The left side of FIG. 6 (FIG. 6a) is the total protein, and the left side (FIG. 6b) shows a band having esterase activity of each microorganism. BC, BH, BS, GK, and OI in each figure indicate the respective microorganisms. In the lanes 1 to 3 of each microorganism, 1 is unheated, 2 is 60 ° C. for 10 minutes, and 3 is 70 ° C. for 10 minutes. FIG. 7 is a color photograph, instead of a drawing, showing the results of examining the pattern of native PAGE after separating Hag and GroES proteins from GK, BC, BH, BS, and OI microorganisms. The left side (FIG. 7a) of FIG. 7 is Hag, and the left side (FIG. 7b) is the result of isolating and developing GroES of each microorganism. BC, BH, BS, GK, and OI in each figure indicate the respective microorganisms. In the lanes 1 to 3 of each microorganism, 1 is unheated, 2 is 60 ° C. for 10 minutes, and 3 is 70 ° C. for 10 minutes. FIG. 8 is a flowchart showing processing from the user side of the program of the present invention. FIG. 9 is a flowchart of input processing from the server side of the program of the present invention.

Claims (19)

A program for causing a computer to execute the following steps to determine whether or not a test protein has heat resistance,
Inputting the amino acid sequence of the protein to be tested;
Among the known proteins in the species that are different from the species that produce the test protein, a protein that is produced by a species that is different from the species that produces the test protein and that has a relationship between the test protein and the ortholog , Corresponding protein search step)
Calculating specific analysis values by principal component analysis based on amino acid composition for each of the test protein and the corresponding protein,
Calculating a difference between the specific analysis value of the corresponding protein and the specific analysis value of the test protein,
Determining whether the test protein is similar to the corresponding protein based on the difference; and
Displaying the corresponding protein and the result determined in the determining step;
And execute
For each of the test protein and the corresponding protein, a step of calculating a specific analysis value by principal component analysis based on an amino acid composition,
Calculating an average amino acid composition for each species from genome data obtained from a database;
Calculating an eigenvector of the second principal component by principal component analysis from the matrix of the calculated average amino acid composition for each species,
Calculating a specific analysis value (heat resistance index) of the test protein as an inner product from the vector of the amino acid composition of the test protein and the eigenvector of the second principal component; and
Calculating an intrinsic analysis value (heat resistance index) of the protein to be tested as an inner product from the amino acid composition vector of the corresponding protein and the eigenvector of the second principal component;
including,
A program for discriminating whether or not a test protein has heat resistance by comparing a specific analysis value based on the amino acid composition of the test protein and a specific analysis value of the corresponding protein.   The program according to claim 1, wherein the biological species different from the biological species producing the test protein is a thermostable organism.   The program according to claim 1, wherein the amino acid composition of the test protein is calculated from the amino acid sequence of the test protein.   The program according to any one of claims 1 to 3, wherein the amino acid composition of the corresponding protein is calculated from the amino acid sequence of the corresponding protein.   The program according to any one of claims 1 to 4, wherein a known protein in a biological species different from the biological species producing the test protein is searched from a database of known proteins.   The program according to any one of claims 1 to 5, wherein the amino acid sequence of the corresponding protein is obtained from a database of known proteins.   The program according to claim 6, wherein the database of known proteins is a database of genomic data.   The program according to claim 6, wherein the database of known proteins is a database of microbial genome data. From the genome data acquired from the database, calculating the average amino acid composition for each species,
The protein sequence is performed using the remaining protein sequence by removing a sequence having a sequence length of less than 50 amino acids, removing a protein having two or more transmembrane regions predicted. The program in any one of.   The program according to any one of claims 1 to 9, wherein the genome data acquired from the database is microbial genome data.   The program according to any one of claims 1 to 10, wherein the matrix of the calculated average amino acid composition for each biological species is a matrix having the biological species as rows and the average amino acid composition as columns. Based on the difference, determining whether the test protein is similar to the corresponding protein,
The program according to any one of claims 1 to 11, which is a step of determining that the protein to be tested is heat-resistant when the difference is within a predetermined range.   The program according to any one of claims 1 to 12, comprising a step of checking whether or not the protein is a processing target.   The program according to any one of claims 1 to 13, wherein the protein to be processed has 50 or more amino acids and 1 or less transmembrane domain.   The program according to claim 1, comprising a step for inputting data of a known protein for searching for a corresponding protein.   The program according to any one of claims 1 to 15, further comprising a step for inputting a unique analysis value based on an amino acid composition of a known protein.   A computer-readable recording medium having recorded thereon a program to be executed by the computer according to claim 1.   The recording medium according to claim 17, wherein the recording medium also records data of known proteins necessary for searching for the corresponding protein.   The recording medium according to claim 17 or 18, wherein the recording medium also records data of a specific analysis value based on an amino acid composition of a known protein.