KR102030055B1 - A method for extracting specific protein sequence of virus - Google Patents

Abstract

The present invention relates to a virus-specific protein sequence extraction system and method, and more particularly, to curate the genetic data and to link with general analysis tools to effectively use the vast amount of varying gene information and to be applied to medical research effectively It relates to a virus-specific protein sequence extraction system and method for facilitating the analysis of systematic new strains of viruses.
The present invention is to construct a database by performing a taxonomic classification of viruses, structural and functional for the new virus through the analysis of the similarity of the protein sequence to the protein coding region that affects the virus structure and function of the new virus gene sequence when the new virus emerges It can increase the speed of classification search and analysis.
In addition, the information stored in the common protein database construction unit 900 and the taxonomy database construction unit 1000 is linked to the database stored in the database construction unit 400 and / or the CDS database construction unit 500, the new virus analyzed It is possible to systematically and efficiently analyze a variety of new viruses by periodically accumulating or updating information on new viruses analyzed on their own without receiving information from GenBank.

Description

{A method for extracting specific protein sequence of virus}

The present invention relates to a virus-specific protein sequence extraction method, and more specifically, to effectively utilize a large amount of varying amounts of genetic information, and to curate the genetic data to be effectively applied to medical research and to increase the linkage with general analysis tools It relates to a virus-specific protein sequence extraction method for facilitating the systematic analysis of new viruses.

Bioinformatics is a branch of the biotechnology industry that combines biotechnololgy and information technology to collect, manage, store, and analyze a variety of information from biopheneological research. It refers to various fields.

Bioinformatics has a significant impact on a variety of industries, including pharmaceuticals, agriculture, chemistry, and the environment, and in the next 5 to 10 years, the development of related technologies will be visible and several innovative results will be visible.

Bioinformatics developed rapidly in the late 1980s with the creation of a public database that contained DNA information from various organisms discovered by individual biologists.

For example, in 1988, the US established the National Center for Biotechnology Information (NCBI) under the National Institutes of Health (NIH) to build a biological database and develop software for genome data analysis. .

Early biological data consisted mostly of information on sequence and three-dimensional structure, but new kinds of biological meaning data such as gene expression profile using DNA chip are being produced.

Biological databases that provide this information process and present the data in different ways, depending on where the focus is. Currently, a wide range of databases are available, ranging from databases that provide information across biology to databases that provide very detailed information on specific compounds or functions, and new databases are being built that efficiently retrieve and reconstruct specific biological information from existing databases. .

In addition to existing viruses, new varieties of viruses that are noisy are attracting attention because their influence is directly related to human health and life.

Treatment for viruses is a priority. To do this, the genetic registration, management, and conditional search of the virus must be systematically performed. Through this, researchers can collect and utilize the information desired by the researchers to treat and manage the virus.

Database construction for domestic and overseas virus-related database has become an important research subject, but currently provided virus DB is classified according to the characteristics of the viral genome sequence, so that the characteristics of the sequence to search for modified similar sequences Since it is necessary to search the entire DB classified according to the, there is a problem that causes a variety of errors, such as the extraction of a sequence having no similarity, such as a decrease in the search speed for long sequences.

In particular, viruses have a higher rate of genetic variation than other organisms and can cause fatal damage to humans. Therefore, in order to respond quickly to emergence of new viruses, a systematic and efficient database is needed to enable rapid classification and response to new viruses. .

Meanwhile, Korean Patent Laid-Open Publication Nos. 10-2000-0072527, 10-10790, and 10-1482010 are apparatuses for providing disease information using a genetic database through a computer communication network, and a gene sequence search method. And an ultrafast general-purpose search apparatus for whole genome sequencing.

Korean Patent Publication No. 10-2000-0072527 Korea Patent Registration No. 10-0790870 Korea Patent Registration No. 10-1482010

The present invention is to solve the problems of the prior art, the virus based on ICTV taxonomy (Order (-virales)), family (Family (-viridae)), subfamily (Subfamily (-virinae)), genus ( Genus (-virus)), by classifying by species (Species) is to provide a virus-specific protein sequence extraction system that can quickly search for allelic genetic variations and reduce the error of the search.

In another aspect, the present invention provides a method for extracting a specific protein sequence for each virus to facilitate analysis of a new virus by generating a Blast Family CDS database building unit and a Blast Genus CDS database building unit from the database building unit 400 and comparing and analyzing the new virus. It aims to provide.

In order to achieve the above object, the present invention provides a virus information collection unit 100 for collecting information related to the virus of the gene information provided by the gene bank (GenBank);

Parsing the GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition, and sequence portion of the information collected from the virus information collection unit 100, and sequence or protein sequence A format conversion unit 200 for converting to a FASTA format expressed as a character string;

Based on the taxonomy information, based on the Accession number and Version number, the order (Order (-virales)), family (-viridae), subfamily (-virinae), genus (Genus (-virus)), A virus classification unit 300 for classifying FASTA files according to a virus classification system defined by International Committee on Taxonomy of Viruses (ICTV) for each species;

A database constructing unit 400 for generating a Blast (Basic Local Alignment Search Tool) database based on a file converted from the virus classification unit 300 into a FASTA format classified according to the ICTV virus standard classification system;

The Blast Family CDS database construction unit for generating a database by extracting meta information and sequence information about CDS from data classified as a family in the ICTV classification system of the database construction unit 400, and the ICTV of the database construction unit 400. A CDS database construction unit 500 including a Blast Genus CDS database construction unit for generating a database by extracting meta information and sequence information about CDS from data classified as Geuns in the classification system;

ORF protein sequence that extracts the genome sequence of the new virus, converts the extracted genome sequence into FASTA format, extracts the candidate gene sequence that can be encoded with protein, creates a Multi ORF FASTA file, and divides it into a single ORF FASTA file. Extracting unit 600;

A protein sequence comparison unit 700 comparing the protein sequence of the database of the CDS database construction unit 500 and the single ORF FASTA file of the ORF protein sequence extraction unit 600;

After checking the virus of the single ORF FASTA file of the new virus with high homology and the CDS database constructing unit 500 based on the protein sequences compared in the protein sequence comparison unit 700, the protein sequences commonly held between them Protein sequence analysis unit 800 for analyzing the affinity between gene sequences through Multiple Sequence Alignment (MSA) to extract the;

A protein common sequence database constructing unit 900 for storing an ID and a common protein sequence for the single ORF FASTA file of the new virus identified by the protein sequence analyzing unit 800; And

It provides a database system for building a viral genome comprising a taxonomy database construction unit 1000 for storing information about which strain the new virus identified in the protein sequence analysis unit 800 belongs.

In one embodiment of the present invention, the format conversion unit 200 is characterized in that for converting the format using a BioPython (BioPython) module.

In one embodiment of the present invention, the database building unit 400 is characterized in that to create a Blast database using the makeblastdb.

In addition, the present invention is made in the form of a program to be executed by the processing unit including a computer, in the virus-specific protein sequence extraction method using a virus-specific protein sequence extraction system,

A virus information collecting step of collecting information related to a virus from a gene bank (GenBank) by the virus information collecting unit 100 (S10);

The format conversion unit 200 parses (syntactic) parsing the GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition, and sequence portion of the information collected from the virus information collection unit 100. A format conversion step (S20) of converting the nucleotide sequence or the protein sequence into the FASTA format expressed as a string;

Virus classification unit 300 based on taxonomy information based on Accession number and Version number (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus ( Genus (-virus)), virus classification step of classifying the FASTA file by the species (Species) (S30);

A database building step of generating, by the database building unit 400, a Blast (Basic Local Alignment Search Tool) database based on a file converted into a FASTA format that is classified taxonomically from the virus classification unit 300 (S40);

The Blast Family CDS database construction unit 500 generates a database by extracting the meta information and the sequence information of the CDS among the data classified as Family in the ICTV classification system in the database construction unit 400, and A CDS database construction step (S50) of generating a Blast Genus CDS database construction unit for generating a database by extracting meta information and sequence information of CDS among data classified as Genus in the ICTV classification system of the database construction unit 400;

The ORF protein sequence extracting unit 600 extracts the gene sequence of the new virus, converts the extracted gene sequence into the FASTA format, and extracts the candidate gene sequence that can be encoded by the protein to generate a multi ORF FASTA file. ORF protein sequence extraction step (S60) of dividing into a plurality of single ORF FASTA files according to the protein coding start sequence and end sequence by the codon table in the process;

A protein sequence comparison step 700 compares the protein sequence of the database of the CDS database construction unit 500 and the single ORF FASTA file of the ORF protein sequence extraction unit 600 (S70);

After the protein sequence analysis unit 800 identifies the virus of the single ORF FASTA file and the CDS database constructing unit 500 of the highly homologous new virus based on the protein sequences compared in the protein sequence comparison unit 700, A protein sequence analysis step (S80) of extracting protein sequences commonly held in the liver and analyzing affinity and phylogenetic tree among these sequences;

A common protein sequence database constructing step for storing a common protein sequence and a common protein sequence for a single ORF FASTA file of the new virus identified by the protein sequence analyzing unit 800 by the protein common sequence database constructing unit 900 (S90); And

Taxonomy database construction unit 1000 extracts a specific protein sequence for each virus comprising a Taxonomy database construction step (S100) for storing information on which virus Taxonomy the new virus identified in the gene sequence analysis unit 800 belongs to Provide a method.

In one embodiment of the present invention, the format conversion step (S20) is characterized in that the format conversion using a BioPython (BioPython) module.

In one embodiment of the present invention, the database construction step (S40) is characterized in that to create a Blast database using the makeblastdb.

In one embodiment of the present invention, the ORF protein sequence extraction step (S60) is characterized by generating a multi ORF FASTA file by searching for a protein coding region using the ORF Finder.

The present invention converts a nucleotide sequence or a protein sequence of a virus into a FASTA format expressed as a string, but the virus is based on ICTV taxonomy (Order (-virales)), Family (-viridae), and Subfamily (- virinae)), genus (Genus (-virus)), species (Species) can be classified by the search for genetic variations between homogeneous and faster search errors can be reduced.

In addition, according to the present invention, the Blast Family CDS database building unit and the Blast Genus CDS database building unit are generated from the database building unit 400 and compared with the new virus to simplify the analysis of the new virus.

In addition, the information stored in the common protein database construction unit 900 and the taxonomy database construction unit 1000 is linked to the database stored in the database construction unit 400 and / or the CDS database construction unit 500, the new virus analyzed It is possible to systematically and efficiently analyze a variety of new viruses by periodically accumulating or updating information on new viruses analyzed on their own without receiving information from GenBank.

1 is a block diagram of a virus-specific protein sequence extraction system according to an embodiment of the present invention.
2 is a view showing an example of dividing a file name according to a characteristic of a sequence used in a virus-specific protein sequence extraction method according to an embodiment of the present invention;
Figure 3 is a block diagram showing an example of a Blast database generation file used in the virus-specific protein sequence extraction method according to an embodiment of the present invention.
Figure 4 is a block diagram showing the collection of virus raw data used in virus-specific protein sequence extraction method according to an embodiment of the present invention and Blast database by virus Taxonomy.
5 is a flow chart of a virus-specific protein sequence extraction method according to an embodiment of the present invention.

Hereinafter, the present invention will be described in detail with reference to Examples. The terms, examples, etc. used in the present invention are merely illustrated to explain the present invention in more detail and to help those skilled in the art, and the scope of the present invention is not limited thereto.

Technical terms and scientific terms used in the present invention represent the meanings that are commonly understood by those of ordinary skill in the art unless otherwise defined.

1 is a block diagram of a virus-specific protein sequence extraction system according to an embodiment of the present invention, Figure 2 is a characteristic of the sequence used in the virus-specific protein sequence extraction method according to an embodiment of the present invention FIG. 3 is a block diagram illustrating a Blast database used in a virus-specific protein sequence extraction method according to an embodiment of the present invention, and FIG. 4 is one of the present inventions. In the virus-specific protein sequence extraction method according to an embodiment is a block diagram for separating the virus raw data according to the ICTV classification system and building a Blast database, Figure 5 is a virus-specific protein sequence according to an embodiment of the present invention Flow chart of the extraction method.

The present invention is to create a database to facilitate the systematic analysis of new strains of viruses by curating genetic data and improving linkage with general analysis tools to effectively use vast amounts of genetic information that are constantly changing and applied to medical research. will be. Here, curating refers to an activity that collects, selects, and adds new values to and propagates a variety of information, including activities of curators to collect, synthesize, and guide information to those who need the information.

In particular, the difference from the existing viral gene database is that the virus is based on ICTV taxonomy (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus (-virus). By subdividing the data by species and Species, the database is subdivided for quick and efficient retrieval of homogeneous genetic variation, and the system can be expanded to concentrate on virus genetic analysis, and to manage virus classification and tracking. The system can be expanded to enable the system to secure a foundation as an integrated system for viruses.

In addition, the Blast Family CDS database building unit and the Blast Genus CDS database building unit are generated from the database building unit 400 and compared with the new virus, and the information about the analyzed new virus is stored in the gene sequence database building unit and the Taxonomy database building unit. As a result, the analysis of new viruses can be performed simply and efficiently.

As shown in Figure 1, the virus-specific protein sequence extraction system according to an embodiment of the present invention is a virus information collection unit 100, format conversion unit 200, virus classification unit 300, database construction unit (400), CDS database construction unit 500, ORF protein sequence extraction unit 600, protein sequence comparison unit 700, protein sequence analysis unit 800, protein common sequence database construction unit 900 and Taxonomy database construction The unit 1000 is included.

The virus information collecting unit 100 collects virus-related information (gbvrl file) among information of genes provided by a gene bank (GenBank).

GenBank refers to a database of nucleic acid and protein sequences operated by NCBI under the National Li-brary of Medicine (NLM).

The National Center for Biotechnology Information (NCBI) is also known as the National Center for Biotechnology Information (NCBI) and is located at the National Library of Medicine (NLM) under the National Institutes of Health (NIH). It was established on November 4, 1988 as an operating organization. NCBI provides and shares biotechnology information through GenBank, a worldwide database of databases, and PubMed, a bibliographic database. All of this information can be viewed online using the Entrez search engine, and the primary task of bioinformatics is to build a database and develop an analytical tool for analyzing vast amounts of data in biology and medicine using computers. We developed a program for sequence searching, which is the most widely used analysis tool. Research in computer information processing technology to analyze the structure and function of biologically important molecules, study at the molecular level of biological and medical problems using mathematical and computational methods, and store and analyze knowledge of molecular biology, biochemistry and genetics Development of automation system, development of DB and S / W, collection of biotechnology information, cooperation with research institutes, academic societies, industry, government agencies, strengthened scientific information exchange, support of basic and applied research training in computer biology, various DB and S / His activities include supporting the use of W, DB, data accumulation and exchange, and developing standards for biological nomenclature. GenBank has established a sequencing database cooperation system with the DNA Data Bank of Japan (DDBJ) and the European Molecular Biology Laboratory (EMBL).

The format converting unit 200 parses the information collected from the virus information collecting unit 100 by parsing the GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition, and sequence part. Converts nucleotide sequences or protein sequences into FASTA format expressed as a string.

Here, syntactic parsing refers to the process of decomposing a series of strings into meaningful tokens and creating a parse tree of them, and the FASTA format is represented using a single character code. Refers to a text based format for expressing either a nucleotide sequence or a peptide sequence.

In other words, the format conversion unit 200 first processes the data into a file in FASTA format to facilitate the construction of a database.

At this time, the format conversion unit 200 may be characterized in that for converting the format using a BioPython (BioPython) module.

The BioPython module is a Python module (project) created by biologists that contains basic biological tools such as access to NCBI and Blast. The Biopython project is also a project to build Python libraries for free use in molecular biology calculations.

Virus classification unit 300 is based on taxonomy information based on the Accession number and Version number (Order (-virales)), family (Family (-viridae)), subfamily (Subfamily (-virinae)), genus ( Genus (-virus)) and FASTA files are classified by Species.

That is, the virus classification unit 300 classifies the virus based on the ICTV taxonomy (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus (-virus). Secondary processing of data into Species.

At this time, the virus classification unit 300 may be characterized in that to generate (classify) the file name according to the taxonomy name.

GenBank data of NCBI which is widely used at present is divided into ANNOTAION part and SEQUENCE information part which contain meta information of genome. It contains meta information (SOURCE, CDS, GENE, etc.) that contain the characteristics of each part of the genome, and the SEQUENCE part contains only the sequence information of the genome, so it can be used for ICTV classification system using ACCESSION information, VERSION information, and Taxonomy information. The virus must be classified accordingly to facilitate the construction of an efficient virus database.

Viruses are classified by order (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus (-virus), and Species. You can design a taxonomy.

For systematic classification, based on the taxonomy information and based on the ACCESSION and VERSION numbers, the order (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus (- virus)), by classifying FASTA files based on ICTV taxonomy by species, it is possible to construct a systematic database that can easily and efficiently search (FIG. 2).

The database constructing unit 400 generates a BLAST (Basic Local Alignment Search Tool) database for sequence comparison based on a file converted into a FASTA format that is classified taxonomically from the virus classification unit 300.

That is, the BLAST database is generated after finishing the sequence characteristics and taxonomic classification as shown in FIG.

An example of the database thus generated is shown in FIG. 4.

The database constructing unit 400 may construct each database classified by sequence characteristics and taxonomically from the virus classification unit 300.

When classified taxonomically, the database is divided into Genbank taxon DB and Refseq taxon DB, each DB including Blast Order DB, Blast Family DB, Blast Subfamily DB, Blast Genus DB and Blast Species DB.

The generated database may be logically divided into one storage device or may be physically divided into a plurality of storage devices.

Homology search is required to analyze the newly sequenced genome. Homology search is the search for evolutionary and functionally similar sequences in the established gene sequence database. This is a search that finds the function and evolution of new genomes through sequence pattern matching of newly discovered genomes. to be. The most popular analysis tool for a long time is BLAST (Basic Local Alignment Search Tool).

In addition, the results obtained by the analysis tool can be imaged by various visualization tools. The most basic visualization to analyze the homology of sequencing is the Align type visualization, and the Genom Browser visualization tool can be used to best express the homology sequencing results.

At this time, the database building unit 400 may be characterized by generating a Blast database using the makeblastdb.

The CDS database construction unit 500 constructs a Blast Family CDS database that generates a database by extracting meta information and sequence information about CDS, which is a protein coding region that can be converted into a protein, from the Refseq taxon DB of the database construction unit 400. And a Blast Genus CDS database construction unit for generating a database by extracting meta information and sequence information about CDS from the Refseq taxon DB of the database construction unit 400.

The generated Blast Family CDS database construction unit and the Blast Genus CDS database construction unit may provide information on which taxynomy the new virus belongs to by comparing the gene sequence of the new virus.

The ORF protein sequence extracting unit 600 extracts the gene sequence of the new virus, converts the extracted gene sequence into a FASTA format, extracts a candidate gene sequence that can be encoded with a protein, and generates a multi ORF FASTA file. Split into a single ORF FASTA file.

In order to extract the gene sequence of the new virus, sequence equipment is used. Since the virus has a faster mutation rate and a shorter sequence length than other microorganisms, it is necessary to directly insert the virus into a virus generation area and to analyze the sequence within minutes. Conventional genomic sequencing equipment is heavy and expensive, while MinION sequence equipment is compact and allows fast sequence extraction. In this case, the sequence sequence alone does not know which virus the new virus belongs to, so a detailed analysis should be performed.

First, the sequenced gene sequence is converted to FASTA format, which is a standard genomic data format, and a candidate protein sequence that can be encoded into a protein is extracted using an ORF (Open Reading Frame) Finder. The genome can be divided into the Intron region and the Exon region. Among them, the protein-encoded region is the Exon region, from which the protein sequence can be extracted. In this step, the ORF Finder repeats the genome sequence in the forward direction and the reverse direction, and generates an ORF based on the ATG protein coding start gene codon and TAA, TGA, and TAG protein coding end genes.

Since there are several ORF candidates in the gene sequence of the virus, a Multi ORF FASTA file is generated heading the ORF number and position, and each ORF contains the specific protein candidate sequence of the specific virus. Divide the Multi ORF FASTA into a Single ORF FASTA file using the Biopython tool for a 1: 1 comparison for each ORF.

The protein sequence comparison unit 700 compares the database of the CDS database construction unit 500 and the gene sequence of the single ORF FASTA file of the gene sequence extraction unit 600. In this case, PASC (Pairwise Sequence Comparison) analysis is performed, and through this, highly homologous sequences can be extracted.

The protein sequence analysis unit 800 checks the viruses of the Single ORF FASTA file and the CDS database construction unit 500 of the highly homologous new virus based on the protein sequences compared in the protein sequence comparison unit 700, and then, Protein sequences commonly possessed by the liver are extracted and the evolutionary affinity between these protein sequences is analyzed.

First, an identity matrix having the X and Y axes of the protein sequence stored in the CDS database construction unit 500 and the protein sequence of the single ORF is formed, and then the protein sequence having high homology with the single ORF is identified.

After extracting an ORF having high homology, MSA (Multiple Sequence Alignment) is performed to extract a protein sequence that is commonly held.

The evolutionary affinity between sequences can be analyzed by calculating the phylogenetic tree by calculating the distance to the ORF on which the MSA was performed.

The protein common sequence database constructing unit 900 stores an ID and a common protein sequence for the single ORF FASTA file of the new virus identified by the protein sequence analyzing unit 800.

Taxonomy database construction unit 1000 stores information about which taxonomy the new virus identified in the protein sequence analysis unit 800 belongs.

Information stored in the protein common sequence database constructing unit 900 and the Taxonomy database constructing unit 1000 may be linked to a database stored in the database constructing unit 400 and / or the CDS database constructing unit 500. Through this, it is possible to systematically and efficiently analyze various new viruses by periodically accumulating or updating information about new viruses analyzed on their own without receiving information about new viruses analyzed from GenBank.

As shown in FIG. 5, a virus-specific protein sequence extraction system using a virus-specific protein sequence extraction system is formed in a program form executed by an arithmetic processing means including a computer according to an embodiment of the present invention. The method includes collecting virus information (S10); Format conversion step (S20); Virus classification step (S30); Database construction step (S40); CDS database construction step (S50); ORF protein sequence extraction step (S60); Protein sequence comparison step (S70); Protein sequencing step (S80); Protein common sequence database construction step (S90); And Taxonomy database construction step (S100).

In the virus information collecting step S10, the virus information collecting unit 100 collects virus-related information (gbvrl file) from a gene bank (GenBank).

For example, the virus information collecting step S10 may collect a gbvrl file related to a virus among GenBank file data provided by NCBI.

Format conversion step (S20) is a format conversion unit 200 parses the information collected from the virus information collection unit 100 GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition and sequence parts ((syntactic) parsing) converts a nucleotide sequence or protein sequence into a FASTA format expressed as a string.

The format conversion unit 200 first processes the data into a file in a FASTA format to facilitate database construction, and reproduces the file for database construction.

At this time, the format conversion unit 200 is characterized in that for converting the format using a BioPython (BioPython) module.

The BioPython module is a Python module (project) created by biologists that contains basic biological tools such as access to NCBI and Blast.

Virus classification step (S30) is the virus classification unit 300 based on the taxonomy information based on the ACCESSION number and VERSION number (Order (-virales)), family (Family (-viridae)), subfamily (Subfamily ( -virinae)), FAus files are classified by genus (-virus) and species (Species).

That is, the virus classification step S30 classifies the information related to the virus based on the ICTV taxonomy.

Database building step (S40) generates a BLAST (Basic Local Alignment Search Tool) database on the basis of the file is converted into a FASTA format that the database building unit 400 is classified taxonomically from the virus classification unit 300.

CDS database construction step (S50) is the CDS database construction unit 500, Blast Family CDS database construction unit for generating a database by extracting meta information and sequence information about the CDS from the Family DB of the database construction unit 400, The Blast Genus CDS database construction unit generates a database by extracting the meta information and the sequence information of the CDS from the Genus DB of the database construction unit 400.

ORF protein sequence extraction step (S60) is the ORF protein sequence extraction unit 600 extracts the protein sequence of the new virus, converts the extracted protein sequence to FASTA format, and then extracts the candidate protein sequence that can be encoded with a protein Create a Multi ORF FASTA file and split it into a Single ORF FASTA file.

In the protein sequence comparison step S70, the protein sequence comparison unit 700 compares the database of the CDS database constructing unit 500 and the gene sequence of the single ORF FASTA file of the ORF protein sequence extracting unit 600.

Protein sequencing step (S80) is the protein sequence analysis unit 800 is a single ORF FASTA file and CDS database construction unit 500 of the new high homology based on the gene sequence compared in the protein sequence comparison unit 700 After identifying the virus of), the protein sequences commonly possessed between them are extracted and the affinity between these protein sequences is analyzed.

In the protein common sequence database constructing step (S90), the protein common sequence database constructing unit 900 stores the ID and the common protein sequence for the single ORF FASTA file of the new virus identified in the protein sequence analyzing unit 800.

Taxonomy database construction step (S100) is the Taxonomy database construction unit 1000 stores information about which taxonomy the new virus identified in the protein sequence analysis unit 800 belongs.

In addition, the extraction method of the present invention may further comprise the step of linking, the information stored in the gene sequence database construction unit 900 and the Taxonomy database construction unit 1000 in the linking step is the database construction unit 400 And / or a database stored in the CDS database construction unit 500. Through this, it is possible to systematically and efficiently analyze various new viruses by periodically accumulating or updating information about new viruses analyzed on their own without receiving information about new viruses analyzed from GenBank.

Genetically homologous sequences have very high similarities. Therefore, the existing BLAST DB is composed of the sequence DB for all organisms. This compares all sequences in the emergence of a new virus, which takes a long search time and speed and has the disadvantage of searching for unnecessary sequences.

However, the database constructed in accordance with the present invention performs the ICTV virus taxonomic classification to build a BLAST DB, and at the same time based on this to facilitate the comparative search for protein sequences that influence the structure and function of the organism based on the taxonomic classification. By further subdividing the BLAST DB into CDS-based BLAST DB, it is possible to quickly identify whether a new virus is similar to the existing virus and what function it is likely to have when a new virus emerges. By narrowing the scope of the experiment, economic savings can be achieved.

100: virus information collector
200: format conversion unit
300: virus classification unit
400: database construction unit
500: CDS database construction unit
600: ORF protein sequence extraction unit
700: protein sequence comparison
800: protein sequence analysis unit
900: common protein sequence database construction unit
1000: Taxonomy database construction unit
S10: Virus Information Collection Step
S20: Format Conversion Step
S30: virus classification step
S40: Database construction step
S50: CDS database construction step
S60: ORF protein sequence extraction step
S70: protein sequence comparison step
S80: Protein sequencing step
S90: Build Protein Common Sequence Database
S100: Taxonomy Database Construction Steps

Claims (6)

A virus information collecting unit 100 collecting information related to viruses among gene information provided by a gene bank (GenBank);
Parsing the GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition, and sequence portion of the information collected from the virus information collection unit 100, and sequence or protein sequence A format conversion unit 200 for converting to a FASTA format expressed as a character string;
Based on the taxonomy information, based on the Accession number and Version number, the order (Order (-virales)), family (-viridae), subfamily (-virinae), genus (Genus (-virus)), Virus classification unit 300 for classifying FASTA files by Species;
A database constructing unit 400 for generating a Blast (Basic Local Alignment Search Tool) database based on a file converted from the virus classification unit 300 into a FASTA format classified according to the ICTV virus standard classification system;
Blast Family CDS database construction unit for generating a database by extracting meta information and sequence information of the CDS from the Family DB of the database construction unit 400, and meta information about the CDS from the Genus DB of the database construction unit 400 And a CDS database construction unit 500 consisting of a Blast Genus CDS database construction unit for generating a database by extracting sequence information;
ORF protein sequence that extracts the gene sequence of the new virus, converts the extracted gene sequence into FASTA format, extracts the candidate gene sequence that can be encoded with protein, generates a Multi ORF FASTA file, and divides it into a single ORF FASTA file. Extracting unit 600;
A protein sequence comparison unit 700 for comparing the DNA sequence of the database of the CDS database construction unit 500 and the single ORF FASTA file of the ORF protein sequence extraction unit 600;
After checking the virus of the single ORF FASTA file of the new virus with high homology and the CDS database constructing unit 500 based on the protein sequences compared in the protein sequence comparison unit 700, the protein sequences commonly held between them Extracting the protein sequence analysis unit 800 for analyzing the affinity between these protein sequences;
A protein common sequence database constructing unit 900 for storing an ID and a common protein sequence for the single ORF FASTA file of the new virus identified by the protein sequence analyzing unit 800; And
In the virus-specific protein sequence extraction system comprising a Taxonomy database construction unit 1000 for storing information about which Taxonomy new virus identified in the protein sequence analysis unit 800,
The format conversion unit 200 converts the format using a BioPython module,
The database building unit 400 generates a Blast database using makeblastdb,
The ORF protein sequence extracting unit 600 extracts a candidate gene sequence that can be encoded into a protein using an ORF finder,
The information stored in the protein common database constructing unit 900 and the Taxonomy database constructing unit 1000 are linked to the databases stored in the database constructing unit 400 and the CDS database constructing unit 500, thereby analyzing the new virus. Virus-specific protein sequence extraction system, characterized in that the systematic analysis of a variety of new viruses by accumulating or updating the information about the new virus analyzed by itself without being provided from GenBank (GenBank).
delete delete delete In the form of a program executed by a computer processing unit including a computer, in the virus-specific protein sequence extraction method using the virus-specific protein sequence extraction system of claim 1,
A virus information collecting step of collecting information related to a virus from a gene bank (GenBank) by the virus information collecting unit 100 (S10);
The format conversion unit 200 parses (syntactic) parsing the GenBank GI number, GenBank Accession number, GenBank Version number, Taxonomy information, genome definition, and sequence portion of the information collected from the virus information collection unit 100. A format conversion step (S20) of converting the nucleotide sequence or the protein sequence into the FASTA format expressed as a string;
Virus classification unit 300 based on taxonomy information based on Accession number and Version number (Order (-virales)), Family (-viridae), Subfamily (-virinae), Genus ( Genus (-virus)), virus classification step of classifying the FASTA file by the species (Species) (S30);
A database building step of generating, by the database building unit 400, a Blast (Basic Local Alignment Search Tool) database based on a file converted into a FASTA format that is classified taxonomically from the virus classification unit 300 (S40);
The CDS database construction unit 500 extracts the meta information and the sequence information of the CDS from the Family DB of the database construction unit 400 and generates a database of the Blast Family CDS database construction unit, and the database construction unit 400 A CDS database construction step (S50) of generating a Blast Genus CDS database construction unit for generating a database by extracting meta information and sequence information about CDS from a Genus DB;
The ORF protein sequence extracting unit 600 extracts the gene sequence of the new virus, converts the extracted gene sequence into a FASTA format, extracts a candidate gene sequence that can be encoded with a protein, and generates a multi ORF FASTA file. ORF protein sequence extraction step of dividing into a single ORF FASTA file (S60);
A protein sequence comparison step 700 compares the protein sequence of the database of the CDS database construction unit 500 and the single ORF FASTA file of the ORF protein sequence extraction unit 600 (S70);
After the protein sequence analysis unit 800 confirms the viruses of the single ORF FASTA file and the CDS database construction unit 500 of the highly homologous new virus based on the gene sequence compared in the protein sequence comparison unit 700, A protein sequence analysis step (S80) of extracting protein sequences commonly held in the liver and analyzing affinity between these protein sequences;
A common protein sequence database constructing step of storing a common protein sequence and a common protein sequence for the single ORF FASTA file of the new virus identified by the protein sequence analyzing unit 800 at step S90; And
Taxonomy database construction unit 1000 virus-specific protein sequence extraction method comprising a Taxonomy database construction step (S100) for storing information on which Taxonomy new virus identified in the protein sequence analysis unit 800 belongs to .
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