Method, device and storage medium for storing and retrieving data of directed evolution of enzymes

Abstract

This invention relates to a method, apparatus, and storage medium for storing directed evolution data of enzymes, a method, apparatus, and storage medium for retrieving directed evolution data of enzymes, and a computer-readable storage medium for storing directed evolution data of enzymes. The storage method includes the following steps: acquiring directed evolution data of a target enzyme; performing structured processing on the directed evolution data; retrieving at least one associated enzyme whose information field matches at least one relation field of the target enzyme, to construct an association set of the target enzyme; defining data storage nodes for the target enzyme and each associated enzyme according to the relation field and information field of the target enzyme and each associated enzyme, and determining the association relationships between each data storage node, to construct a data relationship structure for the target enzyme; and storing the data relationship structure for the target enzyme in a memory.

Description

Technical Field

[0001] This invention relates to directed evolution technology of enzymes, and more particularly to a method, apparatus and storage medium for storing directed evolution data of enzymes, a method, apparatus and storage medium for retrieving directed evolution data of enzymes, and a computer-readable storage medium for storing directed evolution data of enzymes. Background Technology

[0002] Enzymes are large molecules in living organisms that perform catalytic functions. Their chemical composition is typically proteins, ribonucleic acid (RNA), or complexes of these with small organic molecules and metal ions. Enzyme-catalyzed reactions often reduce the number of steps compared to pure organic chemical synthesis, achieving higher atom economy and yield. Furthermore, enzymes themselves are degradable and obtainable from the biological world, making them renewable resources. Directed evolution of enzymes involves introducing one or more differences into the enzyme's molecular structure using molecular biology techniques, replacing one or more amino acid residues that make up the protein with different amino acids to induce mutations. Enzymes with one or more alterations in their molecular structure are called mutants. Technicians perform different mutations on a pre-existing enzyme to obtain a large number of mutant combinations. These combinations are then screened under specific reaction conditions to identify progeny enzymes with improved performance compared to the pre-existing enzyme. By repeatedly performing this mutation and screening process through a limited number of iterations, performance improvements can be accumulated, resulting in progeny enzymes with significantly improved performance than the earliest pre-existing enzyme (i.e., the ancestral enzyme) and suitable for non-natural substrates and reaction conditions.

[0003] Because the directed evolution process requires the construction and screening of a large number of mutants, the greater the number, the greater the probability of obtaining mutants with improved performance. Existing directed evolution techniques generally require repeated and extensive mutation and screening processes, resulting in long evolutionary cycles and high costs. To overcome this limitation, some directed evolution techniques based on digital methods have been proposed, enabling limited visualization based on existing data structures such as SMILES, InChI, mol2, SDF, FASTA, GenBank, PDB, and MMCIF, facilitating intuitive understanding and sharing by technical personnel. However, these existing data structures are generally constructed from single-dimensional data focused on ligand small molecules, enzyme sequences, or enzyme structures, resulting in problems such as limited data content and incompatible formats. Furthermore, they lack catalytic performance data such as catalytic activity, specificity, and tolerance, as well as data characterizing bioinformatics relationships between various enzymes, which are essential for directed evolution research. Therefore, they cannot meet the application requirements of directed evolution techniques in large-scale storage and big data retrieval, thus limiting the digital development of directed evolution techniques.

[0004] In order to overcome the above-mentioned defects in the existing technology, there is an urgent need in the field for a technology for processing enzyme directed evolution data, which can be used to integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics relationships between various enzymes, and achieve efficient storage and retrieval of this multi-dimensional data. Summary of the Invention

[0005] The following provides a brief overview of one or more aspects to offer a basic understanding of them. This overview is not an exhaustive summary of all conceived aspects, nor is it intended to identify key or decisive elements of all aspects, nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed descriptions that follow.

[0006] To overcome the aforementioned deficiencies in the prior art, the present invention provides a method, apparatus, and storage medium for storing directed evolution data of enzymes, a method, apparatus, and storage medium for retrieving directed evolution data of enzymes, and a computer-readable storage medium for storing directed evolution data of enzymes. These methods can integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics relationships between various enzymes, and achieve efficient storage and retrieval of this multi-dimensional data.

[0007] Specifically, the method for storing directed evolution data of the enzyme according to the first aspect of the present invention includes the following steps: acquiring directed evolution data of a target enzyme; performing structured processing on the directed evolution data to determine at least one relation field and at least one information field of the target enzyme; retrieving at least one associated enzyme from a database whose information field matches at least one relation field of the target enzyme, to construct an association set of the target enzyme; defining data storage nodes for the target enzyme and each associated enzyme according to at least one relation field and at least one information field of the target enzyme and each associated enzyme in the association set, and determining the association relationships between each data storage node, to construct a data relationship structure for the target enzyme; and storing the data relationship structure for the target enzyme in a memory.

[0008] Furthermore, in some embodiments of the present invention, the relation field includes at least a predecessor field. The step of retrieving at least one associated enzyme from the database whose information field matches at least one relation field of the target enzyme, to construct an association set of the target enzyme, includes: retrieving the database based on at least one information field determined by the structured processing to determine the predecessor field and information field of the target enzyme; retrieving the database based on the predecessor field to determine a predecessor enzyme whose information field matches the predecessor field of the target enzyme; retrieving the database based on the predecessor field to determine at least one associated enzyme whose predecessor field matches the predecessor field of the target enzyme; and constructing an association set of the target enzyme based on the predecessor enzyme and the at least one associated enzyme.

[0009] Furthermore, in some embodiments of the present invention, the pre-ancestor field includes a wild-type ancestor field, the pre-ancestor enzyme includes a wild-type ancestor enzyme of the target enzyme, and the at least one associated enzyme includes at least one descendant enzyme whose wild-type ancestor field corresponds to the wild-type ancestor enzyme.

[0010] Furthermore, in some embodiments of the present invention, the preceding generation field further includes a parental field indicating a unique parent. The relational field further includes a descendant field indicating at least one descendant. The step of defining data storage nodes for the target enzyme and each of the associated enzymes according to the target enzyme and at least one relational field and at least one information field of each of the associated enzymes in the association set, and determining the association relationships between each of the data storage nodes to construct a data relational structure for the target enzyme includes: defining data storage nodes for the target enzyme, the wild-type ancestral enzyme, and each of the associated enzymes according to the descendant field, the at least one information field, and the parental field; and using the data storage node of the wild-type ancestral enzyme as the ancestor node, traversing its descendant levels step by step, and using the descendant field and the parental field to characterize the evolutionary relationship between the ancestor node and each descendant node, until the traversal of the data storage nodes of each enzyme in the association set is completed, to construct the evolutionary tree structure for the target enzyme.

[0011] Furthermore, in some embodiments of the present invention, the relationship field includes at least one of a wild ancestor field, a parental field, and a progeny field. Additionally, the information field includes at least one of an alternative name field, an expression system field, a unique identifier field, a scientific name field, a remarks field, a biological origin field, a catalytic performance field, a reference field, an enzyme sequence field, and an enzyme structure field.

[0012] Furthermore, in some embodiments of the present invention, the expression system field adopts an expression system structure, which includes at least one of the following: expression host field, remarks field, enzyme-bearing gene field, and unique number field. Additionally, the catalytic performance field adopts a catalytic performance structure, which includes at least one of the following: reaction conditions field, experiment number field, reaction product field, reaction reagent field, and reaction substrate field. Furthermore, the reference field adopts a reference structure, which includes at least one of the following: citation source field, publication date field, remarks field, citation URI field, and citation title field. Furthermore, the enzyme sequence field adopts an enzyme sequence structure, which includes at least one of the following: GenBank accession number field, GI number field, mutation field, remarks field, citation URI field, sequence content field, sequence URI field, sequence category field, and UniProt ID field. In addition, the enzyme structure field adopts an enzyme structure structure, which includes at least one of the following: ligand field, mutation field, memo field, citation URI field, sequence URI field, structure URI field, structure content field, and structure category field.

[0013] Furthermore, in some embodiments of the present invention, the reaction condition field adopts a reaction condition structure, which includes at least one of a relative humidity field, a pH field, a reaction time field, a reactor field, and a reaction temperature field. Additionally, the reaction product field adopts a reaction product structure, which includes at least one of a reaction conversion rate field, a product diastereomer excess value field, a product diastereomer ratio field, a product enantiomer excess value field, an enantiomer selectivity field, a product enantiomer ratio field, a product molecule field, a product purity field, a product positional isomer excess value field, a product positional isomer ratio field, a separation yield field, and an in-situ yield field. Furthermore, the reaction reagent field consists of at least one reaction reagent structure, each of which corresponds to a reaction reagent, and includes at least one of an addition method field, a dilution method field, an addition amount field, and a reagent molecule field. Furthermore, the reaction substrate field consists of at least one reaction substrate structure, each of which corresponds to a reaction substrate, and includes at least one of the following: addition method field, dilution method field, amount added field, and substrate molecule field.

[0014] Furthermore, in some embodiments of the present invention, the reactor field adopts a reactor structure, which includes at least one of a stirring field, a diameter field, a height field, and a shape field. Additionally, at least one of the product molecule field, the reagent molecule field, and the substrate molecule field adopts a ligand structure, which includes at least one of a CAS number field, an InChI field, a scientific name field, a SMILES field, and a chemical structure field. Furthermore, the addition method field adopts an addition method structure, which includes at least one of a method field, a rate field, and a time point field. Furthermore, the dilution method field adopts a dilution structure, which includes at least a diluent field and / or a diluent dosage field, wherein the diluent field adopts the ligand structure. Furthermore, the amount added field adopts a physical quantity structure, which includes at least one of a lower limit field, a target value field, a unit field, and an upper limit field.

[0015] Furthermore, in some embodiments of the present invention, the stirring field adopts a stirring structure, which includes at least one of a stirring amplitude field, a stirring method field, and a stirring speed field.

[0016] Furthermore, in some embodiments of the present invention, the mutation field consists of at least one mutation structure, each mutation structure corresponding to a mutation, wherein it includes at least one of a mutation sequence fragment field, a mutation location field, a template sequence fragment field, and a mutation type field.

[0017] Furthermore, in some embodiments of the present invention, each of the fields is composed of interrelated field keys and field values. The relation field key of the relation field indicates the relation type, while its relation field value indicates an association with the corresponding relation type. The information field key of the information field indicates the information type, while its information field value indicates information data belonging to the corresponding information type.

[0018] Furthermore, the method for retrieving directed evolution data of the enzyme provided by the second aspect of the present invention includes the following steps: obtaining retrieval information about the target enzyme; determining the data storage node of the target enzyme based on the retrieval information; determining the data relationship structure to which the data storage node belongs, wherein the data relationship structure is stored and obtained by the method for storing directed evolution data of the enzyme provided by the first aspect of the present invention; and outputting the directed evolution data of the enzyme recorded in at least one data storage node in the data relationship structure.

[0019] Furthermore, the storage device for the directed evolution data of the enzyme provided in the third aspect of the present invention includes a first memory and a first processor. The first processor is connected to the first memory and is configured to implement the method for storing the directed evolution data of the enzyme provided in the first aspect of the present invention.

[0020] Furthermore, the apparatus for retrieving directed evolution data of the enzymes described above, provided according to a fourth aspect of the present invention, includes a second memory and a second processor. The second processor is connected to the second memory and is configured to implement the method for retrieving directed evolution data of the enzymes described above, provided according to a second aspect of the present invention.

[0021] Furthermore, the computer-readable storage medium provided according to the fifth aspect of the present invention stores computer instructions thereon. When the computer instructions are executed by a processor, the method for storing directed evolution data of the enzyme provided in the first aspect of the present invention is implemented.

[0022] Furthermore, the computer-readable storage medium provided according to the sixth aspect of the present invention stores computer instructions thereon. When the computer instructions are executed by a processor, the method for retrieving directed evolution data of enzymes provided in the second aspect of the present invention is implemented.

[0023] Furthermore, the computer-readable storage medium provided in the seventh aspect of the present invention stores an enzyme data relation structure thereon, wherein the data relation structure is obtained by storing the directed evolution data of the enzyme provided in the first aspect of the present invention. Attached Figure Description

[0024] The above-described features and advantages of the present invention will be better understood after reading the following detailed description of embodiments of the present disclosure in conjunction with the accompanying drawings. In the drawings, components are not necessarily drawn to scale, and components having similar related characteristics or features may have the same or similar reference numerals.

[0025] Figure 1 A flowchart illustrating a method for storing enzyme-directed evolution data according to some embodiments of the present invention is shown.

[0026] Figure 2 A schematic diagram of the ECD structure of directed evolution data of an enzyme provided according to some embodiments of the present invention is shown.

[0027] Figure 3 A schematic diagram of a non-relational database of directed evolution data of enzymes provided according to some embodiments of the present invention is shown.

[0028] Figure 4 A schematic diagram of an evolutionary tree structure for directed evolutionary data of an enzyme, provided according to some embodiments of the present invention, is shown.

[0029] Figure 5 A flowchart illustrating a method for retrieving enzyme-directed evolution data according to some embodiments of the present invention is shown. Detailed Implementation

[0030] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Although the description of the present invention is presented in conjunction with preferred embodiments, this does not mean that the features of the invention are limited to these embodiments. On the contrary, the purpose of describing the invention in conjunction with embodiments is to cover other options or modifications that may be derived based on the claims of the present invention. To provide a thorough understanding of the invention, many specific details will be included in the following description. The invention may also be implemented without using these details. Furthermore, to avoid confusion or obscuring the focus of the invention, some specific details will be omitted in the description.

[0031] It is understood that although terms such as "first," "second," and "third" may be used herein to describe various components, regions, layers, and / or parts, these components, regions, layers, and / or parts should not be limited by these terms, and these terms are only used to distinguish different components, regions, layers, and / or parts. Therefore, the first components, regions, layers, and / or parts discussed below may be referred to as second components, regions, layers, and / or parts without departing from some embodiments of the present invention.

[0032] As mentioned above, existing data structures such as SMILES, InChI, mol2, SDF, FASTA, GenBank, PDB, and MMCIF are generally constructed as single-dimensional data for ligand small molecules, enzyme sequences, or enzyme structures. They suffer from problems such as limited data content and incompatible formats. Furthermore, they lack catalytic performance data such as catalytic activity, specificity, and tolerance, as well as data characterizing the bioinformatics relationships between various enzymes, which are required for directed evolution research of enzymes. Therefore, they cannot meet the application needs of directed evolution technology in large-scale storage and big data retrieval, thus limiting the digital development of directed evolution technology of enzymes.

[0033] To overcome the aforementioned deficiencies in the prior art, this invention provides a method, apparatus, and storage medium for storing directed evolution data of enzymes; a method, apparatus, and storage medium for retrieving directed evolution data of enzymes; and a computer-readable storage medium for storing directed evolution data of enzymes. These methods, apparatus, and storage media for storing directed evolution data of enzymes can integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics relationships between various enzymes, and achieve efficient storage of this multi-dimensional data. These methods, apparatus, and storage media for retrieving directed evolution data of enzymes can achieve efficient retrieval of this multi-dimensional data based on a data relationship structure that integrates multi-dimensional data involved in the directed evolution process of enzymes, characterizes the catalytic performance of enzymes, and characterizes the bioinformatics relationships between various enzymes. The computer-readable storage medium for storing directed evolution data of enzymes can integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics relationships between various enzymes, and achieve efficient storage and retrieval of this multi-dimensional data.

[0034] In some non-limiting embodiments, the storage method provided in the first aspect of the present invention can be implemented by the storage device provided in the third aspect of the present invention. Specifically, the storage device is configured with a first memory and a first processor. The first memory includes, but is not limited to, the computer-readable storage medium provided in the fifth aspect of the present invention, on which computer instructions are stored. The first processor is connected to the first memory and is configured to execute the computer instructions stored in the first memory to implement the storage method for directed evolution data of enzymes provided in the first aspect of the present invention.

[0035] In some non-limiting embodiments, the retrieval method provided in the second aspect of the present invention can be implemented by the retrieval device provided in the fourth aspect of the present invention. Specifically, the retrieval device is configured with a second memory and a second processor. The second memory includes, but is not limited to, the computer-readable storage medium provided in the sixth aspect of the present invention, on which computer instructions are stored. The second processor is connected to the second memory and is configured to execute the computer instructions stored in the second memory to implement the retrieval method for directed evolution data of enzymes provided in the second aspect of the present invention.

[0036] The working principle of the above-described storage device and storage medium will first be described with reference to some embodiments of storage methods. Those skilled in the art will understand that these storage methods are merely non-limiting embodiments provided by the present invention, intended to clearly demonstrate the main concept of the invention and provide specific solutions convenient for public implementation, rather than limiting all functions or all operating methods of the above-described storage device and storage medium. Similarly, the storage device and storage medium are also merely a non-limiting embodiment provided by the present invention, and do not constitute a limitation on the entities performing the steps in these storage methods.

[0037] Please refer to the following first. Figure 1 , Figure 1 A flowchart illustrating a method for storing enzyme-directed evolution data according to some embodiments of the present invention is shown.

[0038] like Figure 1 As shown, in the process of storing directed evolution data of enzymes, the storage device can first acquire the directed evolution data of the target enzyme. Here, the directed evolution data includes, but is not limited to, multi-dimensional related data such as the enzyme's alternative names, wild ancestor information, natural host information, DNA information of the gene carrying the enzyme, scientific name, biological origin information, evolutionary parent information, catalytic performance data, references or cited materials describing the enzyme, sequence data, and structural data.

[0039] The storage device can then perform structured processing on the acquired directed evolution data to determine at least one relational field and at least one information field for the target enzyme.

[0040] In some embodiments, the above-described structured processing can be performed based on a pre-built ECD (EvoCloud Droplet) structure. Please refer to [reference needed]. Figure 2 , Figure 2 A schematic diagram of the ECD structure of directed evolution data of an enzyme provided according to some embodiments of the present invention is shown.

[0041] like Figure 2 As shown, in the process of structuring enzyme directed evolution data, the storage device can first fill the enzyme directed evolution data into the [A1~A12] fields according to the specified data type based on the pre-constructed data structure, thereby constructing an ECD structure for the directed evolution data of each enzyme, so as to integrate the multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, and realize the efficient storage and retrieval of these multi-dimensional data.

[0042] The data types and data structures involved in this ECD structure are described in the [A0] field below.

[0043] [A0-1] String: A general concept in electronic computer systems.

[0044] [A0-2] Integer: A general concept in electronic computer systems.

[0045] [A0-3] Floating-point number: A general concept in electronic computer systems.

[0046] [A0-4] Date and time: A general concept in electronic computer systems.

[0047] [A0-5] Charging Structure: Describes the method of adding a certain material in the reaction that measures the catalytic performance of an enzyme, and includes the following member fields:

[0048] [A0-5-1] Method field: Describes the feeding method. Its data type is string, and the allowed value is one of the string enumeration values ​​["continuous feeding", "one time charging", "other", "portionwise charging"], which respectively represent continuous feeding, one-time feeding, other, and batch feeding.

[0049] [A0-5-2] Speed ​​field: Describes the feeding speed; its data type is a physical quantity structure. If the method field is "continuous feeding", the unit field can be one of the string enumeration values ​​["L / h", "mL / h", "mL / min", "mL / s", "VVH", "VVM", "VVS"]. If the method field is "portionwise charging", the unit field can be one of the string enumeration values ​​["L / time", "mL / time", "V / time"].

[0050] [A0-5-3] The `timePoints` field describes the time points when feeding is performed. Its data type is an array of several physical quantity structures. If the `method` field is set to "continuous feeding" or "one time charging", the `timePoints` field contains only one member: the feeding start time. If the `method` field is set to "portionwise charging", the `timePoints` field can contain multiple members, each representing the time point of each feeding operation. The unit field for each member in the `timePoints` field can have a value from the string enumeration ["day", "h", "min", "s"].

[0051] [A0-6] Dilution structure: Describes the solution composition of a material used in a reaction that measures the catalytic performance of an enzyme, when the material is used in solution form. It includes the following member fields:

[0052] [A0-6-1] Solvent field: Describes the solvent or diluent of the solution. Its data type is ligand structure.

[0053] [A0-6-2] Loading field: Describes the amount of solvent or diluent used. Its data type is a physical quantity structure, and its unit field allows values ​​to be one of the string enumeration values ​​["L", "mL", "V", "μL"].

[0054] [A0-7] Ligand Structure: Describes information about a small molecule, such as its structure, composition, and index conforming to general rules. It contains the following member fields:

[0055] [A0-7-1] CAS field: Describes the CAS number of a substance. This number is assigned to each registered substance in the Chemical Abstracts Service (CISA), a subsidiary of the American Chemical Society. It is widely used to describe chemicals, especially those intended for sale and production. The data type is string.

[0056] [A0-7-2] inChI field: Describes a substance's InChI (International Chemical Identifier), a string jointly developed by the International Union of Pure and Applied Chemistry (IUPAC) and the National Institute of Standards and Technology (NIST) to uniquely identify a compound's IUPAC name. The data type is string.

[0057] [A0-7-3]iupacName field: Describes the scientific name of a substance according to the systematic nomenclature rules. This nomenclature is defined by the International Union of Pure and Applied Chemistry (IUPAC) and is a method for systematically naming chemical substances, specifying chemical terms from organic to inorganic, from molecules to polymers, and in various other aspects. The data type is string.

[0058] [A0-7-4]smiles field: A SMILES (Simplified Molecular InputLine Entry System) string describing a substance, a specification for explicitly describing molecular structure using ASCII strings. SMILES strings can be imported by most molecular editing software and converted into two-dimensional graphics or three-dimensional molecular models, and are one of the common solutions for processing the chemical composition of small molecules in current computer systems. The data type is string.

[0059] [A0-7-5] Structure field: A mol2 format text describing the chemical structure of a substance, including the elemental composition, interconnections, valence states, charges, and three-dimensional coordinates of the atoms contained in its molecule. Biochemical calculation software such as SYBYL and Discovery Studio typically use the mol2 format to store the chemical information of small molecules. The data type is string.

[0060] [A0-8] Mutation structure: Describes a difference in an amino acid or base sequence relative to its natural ancestor at some point, i.e., a mutation, and contains the following member fields:

[0061] [A0-8-1] MutationMotif field: Describes a fragment of the sequence at the location of the mutation. Its data type is string. If the type field is "nucleotide", the mutationMotif field allows one or more string enumeration values ​​["A", "C", "G", "T"] in one or three combinations, representing adenine deoxyribonucleotide, cytosine deoxyribonucleotide, guanine deoxyribonucleotide, and thymine deoxyribonucleotide, respectively. If the type field is "peptide", the mutationMotif field can be a string enumeration value ["A", "C", "D", "E", "F", "G", "H", "I", "K", "L", "M", "N", "P", "Q", "R", "S", "T", "V", "W", "Y"], representing alanine residue, cysteine ​​residue, aspartic acid residue, glutamic acid residue, phenylalanine residue, glycine residue, histidine residue, isoleucine residue, lysine residue, leucine residue, methionine residue, asparagine residue, proline residue, glutamine residue, arginine residue, serine residue, threonine residue, valine residue, tryptophan residue, and tyrosine residue.

[0062] [A0-8-2] Position field: Describes the position of the mutation location relative to the entire sequence. Its data type is integer, and positive integers are allowed.

[0063] [A0-8-3] TemplateMotif field: Describes a fragment of the sequence corresponding to the mutation site in the ancestor of nature. Its data type is string. If the type field is "nucleotide", the templateMotif field allows one or more string enumeration values ​​["A", "C", "G", "T"] in one or three combinations, representing adenine deoxyribonucleotide, cytosine deoxyribonucleotide, guanine deoxyribonucleotide, and thymine deoxyribonucleotide, respectively. If the type field is "peptide", the templateMotif field can have one of the string enumeration values ​​["A", "C", "D", "E", "F", "G", "H", "I", "K", "L", "M", "N", "P", "Q", "R", "S", "T", "V", "W", "Y"], representing alanine residue, cysteine ​​residue, aspartic acid residue, glutamic acid residue, phenylalanine residue, glycine residue, histidine residue, isoleucine residue, lysine residue, leucine residue, methionine residue, asparagine residue, proline residue, glutamine residue, arginine residue, serine residue, threonine residue, valine residue, tryptophan residue, and tyrosine residue.

[0064] [A0-8-4] Type field: Describes the type of mutation. Its data type is string, and the allowed value is one of the string enumeration values ​​["nucleotide", "peptide"], which represent mutations in the base sequence and mutations in the amino acid sequence, respectively.

[0065] [A0-9] Physical Quantity Structure: Describes a physical quantity. Scientifically, a physical quantity consists of a numerical value and a unit. Furthermore, in engineering, since absolute precision is impossible in any measurement or instrument setting, it is necessary to specify the minimum and maximum permissible deviations of the physical quantity from the target value as a process parameter.

[0066] [A0-9-1] Lower Limit (loweLimit) field: The lower limit of allowed values, and its data type is floating point.

[0067] [A0-9-2] Target Value field: The set target value, whose data type is floating point.

[0068] [A0-9-3] Unit field: The unit of the physical quantity, which is generally the basic unit specified by IUPAP or the product of their finite powers. Its data type is string.

[0069] [A0-9-4] UpperLimit field: The upper limit of allowed values, and its data type is floating point.

[0070] Furthermore, based on the definition of the [A0] field above, the [A1~A12] fields of the ECD structure can be defined as follows.

[0071] [A1] Alias ​​field: Describes an alternative name for the enzyme. Its data type is an array of strings. Enzymes can usually have multiple aliases, used for abbreviation in literature or as trade names, etc.

[0072] [A2] Wild Ancestor (acestorId) field: A unique identifier describing the wild ancestor of the enzyme in the storage system. Its data type is string.

[0073] [A3] Expression System field: Describes the enzyme's expression system. Its data type is an expression system structure, containing the following member fields:

[0074] [A3-1] Host field: Describes the expression host of the enzyme, and its data type is string. The source of the enzyme can be its natural source organism, i.e., the natural host, or an engineered host such as recombinant cells used for molecular cloning or overexpression.

[0075] [A3-2] Note field: Note information, its data type is string.

[0076] [A3-3] Vector field: Describes the DNA used to carry the enzyme gene; its data type is string. In different hosts, the enzyme gene can be integrated into the cell's chromosome or chromatin DNA, i.e., the genome, or it can be embedded in small DNA independent of the genome, such as plasmids or organelle DNA.

[0077] [A4]id field: Describes the enzyme's unique identifier in the storage system; its data type is string.

[0078] [A5] Name field: Describes the scientific name of the enzyme; its data type is string.

[0079] [A6] Note field: Note information, its data type is string.

[0080] [A7] Organism field: Describes the biological origin of the enzyme. Its data type is string. It is usually the organism from which the enzyme was first discovered or isolated, and follows the scientific name of the binomial nomenclature commonly used in modern biological taxonomy.

[0081] [A8] ParentId field: A unique identifier describing the evolutionary parent of the enzyme in the storage system. Its data type is string.

[0082] [A9] Catalytic Performance (performances) field: Describes the enzyme's catalytic performance data. Its data type is an array of several catalytic performance (performance) structures. Each catalytic performance (performance) structure represents one piece of enzyme reaction performance data and contains the following member fields:

[0083] [A9-1] The `conditions` field describes the conditions and parameters of the reaction that measure the catalytic performance of an enzyme. Its data type is a `conditions` structure, containing the following member fields:

[0084] [A9-1-1] Humidity field: Relative humidity, its data type is floating point, and the allowed value is 0 to 100%.

[0085] [A9-1-2]pH field: pH value, its data type is floating point, and the allowed value is 0 to 14.

[0086] [A9-1-3] Reaction Time field: Describes the reaction time that measures the catalytic performance of an enzyme. Its data type is a physical quantity structure, and its unit field allows one of the string enumeration values ​​["ms", "s", "min", "h", "day"].

[0087] [A9-1-4] Reactor field: Describes the container in which the reaction takes place to measure the catalytic performance of an enzyme. Its data type is a reactor structure, which contains the following member fields:

[0088] [A9-1-4-1] Agitation field: Describes the agitation method and speed. Its data type is an agitation structure, which contains the following member fields:

[0089] [A9-1-4-1-1]Magnitude field: Describes the magnitude of stirring, such as the size of the stirring magnet, the diameter of the mechanical stirring paddle, the flow rate of the air rise or the velocity of the crossflow, etc. Its data type is a physical quantity structure.

[0090] [A9-1-4-1-2] Method field: Describes the mixing method. Its data type is string, and the allowed value is one of the string enumeration values ​​["Air lift", "Cross current", "Linear shaking", "Magneticagitation", "Mechanic agitation", "Orbit shaking", "Other", "Vertex mixing"], which respectively represent air lift mixing, cross-flow mixing, reciprocating oscillation, magnetic stirring, mechanical stirring, circular oscillation, other, and vortex mixing.

[0091] [A9-1-4-1-3] Speed ​​field: describes the stirring speed. Its data type is a physical quantity structure, and its unit field allows values ​​to be one of the string enumeration values ​​["Hz", "m / s", "rad / s", "rpm"].

[0092] [A9-1-4-2] Diameter field: Describes the diameter of the reactor. Its data type is a physical quantity structure, and its unit field allows one of the string enumeration values ​​["cm", "dm", "m", "mm"].

[0093] [A9-1-4-3] Height field: Describes the height of the reactor. Its data type is a physical quantity structure, and its unit field allows values ​​to be one of the string enumeration values ​​["cm", "dm", "m", "mm"].

[0094] [A9-1-4-4] Shape field: Describes the shape of the reactor. Its data type is string, and the allowed value is one of the string enumeration values ​​["Eppendorf tube", "Glass vial", "Hydrogenation Reactor", "Jacket", "Microplate vial", "Round bottom flask", "T-flask", "Test tube", "Other"], representing centrifuge tube, glass bottle, hydrogenation reaction flask, jacketed reaction flask, microplate well, round bottom flask, conical flask, test tube, and others, respectively.

[0095] [A9-1-5] Temperature field: Describes the temperature at which the reaction takes place to measure the catalytic performance of the enzyme. Its data type is a physical quantity structure, and its unit field allows values ​​to be one of the string enumeration values ​​["℃", "K"].

[0096] [A9-2]id field: describes the experiment number, and its data type is string.

[0097] [A9-3] Product field: Describes the products and results of the reaction used to measure the catalytic performance of an enzyme. Its data type is a product structure, which contains the following member fields:

[0098] [A9-3-1] Conversion Ratio field: Describes the conversion rate of the reaction that measures the catalytic performance of the enzyme. Its data type is a floating point number, and the allowed value is a number from 0 to 1.

[0099] [A9-3-2]de field: Describes the diastereomer excess value of the reaction product used to measure the catalytic performance of an enzyme. Its data type is floating point, and it allows values ​​from 0 to 1.

[0100] [A9-3-3]dr field: describes the ratio of diastereomers of the products of the reaction that measures the catalytic performance of an enzyme. Its data type is floating point and allows values ​​greater than 0.

[0101] [A9-3-4]ee field: describes the enantiomer excess value of the reaction product used to measure the catalytic performance of an enzyme. Its data type is floating point, and the allowed value is a number from 0 to 1.

[0102] [A9-3-5] EnantioselectivityRatio field: Describes the enantioselectivity of the reaction for which the enzyme performs a catalytic performance. Its data type is a floating-point number, and values ​​greater than zero are allowed.

[0103] [A9-3-6]er field: Describes the enantiomeric ratio of the products of the reaction that measures the catalytic performance of the enzyme. Its data type is floating point and allows values ​​greater than 0.

[0104] [A9-3-7] The molecule field describes the product molecule of the reaction that measures the catalytic performance of an enzyme. Its data type is ligand structure.

[0105] [A9-3-8] Purity field: Describes the purity of the product of the reaction that measures the catalytic performance of the enzyme. Its data type is floating point, and the allowed value is a number from 0 to 1.

[0106] [A9-3-9]re field: Describes the regioisomeric excess value of the product positional isomers of the reaction that measures the catalytic performance of an enzyme. Its data type is floating point, and it allows values ​​from 0 to 1.

[0107] [A9-3-10]rr field: Describes the ratio of product positional isomers in a reaction that measures the catalytic performance of an enzyme. Its data type is floating point, and it allows values ​​greater than 0.

[0108] [A9-3-11] Isolated Yield field: Describes the isolated yield of the reaction used to measure the catalytic performance of the enzyme. Its data type is a floating point number, and the allowed value is a number from 0 to 1.

[0109] [A9-3-12] Solution Yield field: Describes the in-situ yield of the reaction used to measure the catalytic performance of the enzyme. Its data type is a floating-point number, and the allowed value is a number from 0 to 1.

[0110] [A9-4] The `reagents` field describes the reagents involved in the reaction that measures the catalytic performance of the enzyme. Its data type is an array of `reagents` structures. Each `product` structure represents a reagent and contains the following member fields:

[0111] [A9-4-1] Charging field: describes the way the reagent is added to the reaction, and its data type is the charging structure.

[0112] [A9-4-2] Dilution field: Describes how a reagent is diluted when added in solution form. Its data type is a dilution structure.

[0113] [A9-4-3] Loading field: Describes the amount of reagent added. Its data type is physical quantity. Its unit field allows one of the string enumeration values ​​["eq.", "g", "L", "kg", "mg", "mL", "mmol", "mol", "V", "X", "μL"].

[0114] [A9-4-4] Molecule field: Describes the reagent molecule, and its data type is ligand structure.

[0115] [A9-5] The `substrates` field describes the substrate or main reactant used to measure the catalytic performance of an enzyme. Its data type is an array of `substrate` structures. Each `substrate` structure represents a substrate or main reactant and contains the following member fields:

[0116] [A9-5-1]Charging Field: Describes the way the substrate is added to the reaction in which the enzyme’s catalytic performance is measured. Its data type is the Charging structure.

[0117] [A9-5-2] Dilution field: Describes the dilution method when the substrate is added in solution during the reaction that measures the catalytic performance of an enzyme. Its data type is the dilution structure.

[0118] [A9-5-3] Loading field: Describes the amount of substrate added to the reaction that measures the catalytic performance of the enzyme. Its data type is a physical quantity structure, and its unit field allows one of the following string enumeration values: ["eq.", "g", "L", "kg", "mg", "mL", "mmol", "mol", "V", "X", "μL"].

[0119] [A9-5-4] The molecule field describes the substrate molecule of the reaction that measures the catalytic performance of an enzyme. Its data type is ligand structure.

[0120] [A10] References field: Describes information about references or cited materials. Its data type is an array of reference structures. Each reference structure represents one reference or cited material and contains the following member fields:

[0121] [A10-1] Citation field: Describes the source of the citation, such as journals, books, dissertations, and their volume, issue, and page numbers. Its data type is string.

[0122] [A10-2] Date field: Describes the earliest date and time of publication of the citation, and its data type is date and time.

[0123] [A10-3] Note field: Describes the notes in the citation, and its data type is string.

[0124] [A10-4] Reference URI field: A Uniform Resource Identifier that describes the access to the citation from the Internet or a storage system. Its data type is string.

[0125] [A10-5] Title field: Describes the title of the citation; its data type is string.

[0126] [A11] Sequences field: Describes the enzyme sequence. Its data type is an array of sequence structures. Each sequence structure represents one enzyme sequence and contains the following member fields:

[0127] [A11-1] GenBank Accession Field: Describes the GenBank Accession of the enzyme sequence, i.e., the accession number in the GenBank database. Its data type is string. GenBank is a DNA sequence database established by the National Center for Biotechnology Information (NCBI) in the United States. It obtains sequence data from public resources, primarily provided directly by researchers or from large-scale genome sequencing projects. To ensure the data is as complete as possible, GenBank has established cooperative relationships with EMBL (European EMBL-DNA Database) and DDBJ (Dual Degrees Data Bank of Japan) for data exchange.

[0128] [A11-2]gi field: describes the GI number of the enzyme sequence, i.e., the GenInfoIdentifier, and its data type is string.

[0129] [A11-3] Mutations field: Describes all the differences in the enzyme sequence relative to its natural ancestor, i.e., mutations. Its data type is an array of mutation structures. Each mutation structure represents a mutation.

[0130] [A11-4] Note field: Describes notes about the enzyme sequence. Its data type is string.

[0131] [A11-5] ReferenceURI field: Describes the source from which this enzyme sequence was first reported, such as a reference or the Uniform Resource Identifier (URI) of the corresponding entry in a public database. Its data type is string.

[0132] [A11-6] Sequence field: Describes the specific content of the enzyme sequence. Its data type is string, and the allowed values ​​must conform to the FASTA format.

[0133] [A11-7] SequenceURI field: Describes a Uniform Resource Identifier (URI) for accessing this enzyme sequence from the Internet or a storage system. Its data type is string.

[0134] [A11-8] Type field: Describes the type of the enzyme sequence. Its data type is string, and the allowed value is one of the string enumeration values ​​["Nucleotide", "Peptide"], which represent the base sequence and amino acid sequence, respectively.

[0135] [A11-9] The uniProt field: Describes the UniProt ID of the enzyme sequence; its data type is string. UniProt is an abbreviation for Universal Protein, the most comprehensive and resource-rich protein database. It integrates data from the Swiss-Prot, TrEMBL, and PIR-PSD databases. Its data mainly comes from protein sequences obtained after the completion of genome sequencing projects. It contains a wealth of information on the biological functions of proteins from the literature.

[0136] [A12] Structures field: Describes the enzyme structure. Its data type is an array of several structure objects. Each structure object represents a three-dimensional structure of an enzyme and contains the following member fields:

[0137] [A12-1] Ligands field: Describes the ligands in the enzyme structure, that is, the small molecular components of the enzyme structure other than the main chain that makes up the protein. These can typically be water molecules, water-soluble ions, water-soluble small organic solutes, or small organic molecules bound to the protein surface or interior, such as substrates, products, inhibitors, etc. Its data type is an array of several ligand structures. Each ligand structure represents one ligand in the enzyme structure.

[0138] [A12-2] Mutations field: Describes all the differences between the sequence corresponding to the enzyme structure and its natural ancestor, i.e., mutations. Its data type is an array of mutation structures. Each mutation structure represents a mutation.

[0139] [A12-3] Note field: Notes describing the enzyme structure; its data type is string.

[0140] [A12-4] Reference URI field: Describes the source from which this enzyme structure was first reported, such as a reference or the Uniform Resource Identifier of the corresponding entry in a public database. Its data type is string.

[0141] [A12-5] SequenceURI field: Describes the source of the first report of the enzyme sequence corresponding to this enzyme structure, such as the Uniform Resource Identifier (URI) of the corresponding entry in a reference or public database. Its data type is string.

[0142] [A12-6] StructureURI field: A Uniform Resource Identifier (URI) describing access to this enzyme structure from the Internet or storage system. Its data type is string.

[0143] [A12-7] Structure field: Describes the specific content of the enzyme sequence. Its data type is string, and the allowed values ​​must conform to the PDB format.

[0144] [A12-8] Type field: Describes the type of enzyme structure. Its data type is string, and the allowed value is one of the string enumeration values ​​["CryoSEM", "NMR", "Other", "Predicted Model", "XRD"], which represent cryo-electron microscopy, nuclear magnetic resonance, other, predicted structure model, and X-ray crystal diffraction structure, respectively.

[0145] In some embodiments, in response to completing the structuring process and obtaining the ECD structure of the target enzyme, the storage device can store the directed evolution data of the target enzyme into the computer-readable storage medium provided in the seventh aspect of the present invention according to the architecture of the ECD structure, and collect ECD structures of various enzymes to construct the EvoCloud database of directed evolution data of enzymes.

[0146] Furthermore, the aforementioned ECD structure can use JSON (JavaScript Object Notation) as its container format, which is the format defined by the ECMA-404 standard (European Computer Manufacturers Association Standard 404). JSON is a widely used computer program data exchange format. Its serialization, deserialization, node insertion, node deletion, and node editing are directly supported by the latest mainstream high-level computer programming languages ​​such as ECMAScript (ECMA-262), C (ISO / IEC 9899:2011), C++ (ISO / IEC 14882), Java (ISO / IEC TR 13066), and C# (ECMA-334). It can be directly understood and processed by computer programs without additional data processing.

[0147] Furthermore, the ECD structure provided by this invention can be implemented using a dictionary-based non-relational database organization structure. Please refer to... Figure 3 , Figure 3 A schematic diagram of a non-relational database of directed evolution data of enzymes provided according to some embodiments of the present invention is shown.

[0148] like Figure 3As shown, in different computer programming languages ​​or database systems, a dictionary structure, also known as an associative array or map, is an abstract data structure containing multiple ordered pairs similar to (key, value). This data structure supports various common operations such as pair retrieval, adding pairs, deleting pairs, and modifying pairs. For example, in a pair retrieval operation, the operation parameter is the key to be searched, and the returned value is the corresponding value. If the corresponding key-value pair does not exist, some implementations will raise an exception, while others will create and add a new key-value pair using the given key, where the "value" is the default value of its type (zero, empty container, etc.). As another example, in the add pair operation, the storage device can add a new key-value pair and establish a mapping from the new key to the new value; the operation parameters are the key and value to be added. As yet another example, in the delete pair operation, the storage device can remove a key-value pair and cancel the mapping from that key to that value; the operation parameter is the key to be deleted. For example, in the operation of modifying a pair, the storage device can change the value of an existing key-value pair and map the original key to the new value, with the operation parameters being the key and the value.

[0149] In some embodiments, the storage device may use the [A2] wild ancestor (acestorId) field and [A8] parentId field, etc., of the ECD structure as relation fields indicating bioinformatics associations, and the remaining fields (i.e., [A1], [A3] to [A7], [A9] to [A12] fields) or all fields (i.e., [A1] to [A12] fields) of the ECD structure as information fields recording the directed evolution data of the target enzyme. Here, each field consists of interrelated field keys and field values. Specifically, the relation field key of the relation field indicates the relation type, and its relation field value indicates the associated enzyme with the corresponding relation type. The information field key of the information field indicates the information type, and its information field value indicates the information data belonging to the corresponding information type.

[0150] Because computer programming languages ​​such as JavaScript (i.e., ECMAScript, a computer programming language defined by the international standard ECMA-262) have built-in basic data types that provide support for dictionary structures, modern NoSQL (No-only Structural Query Language) database systems such as IndexedDB, Redis, and MongoDB directly support dictionary structures as a way to store data. Furthermore, CAM (Content-Addressable Memory) also implements hardware-level support for dictionary structures. Therefore, ECD structures stored in a dictionary format can be directly understood and processed by computer programs without additional data processing. In addition, because dictionary structures store data in a one-to-one key-value relationship, their retrieval efficiency is far higher than other relational storage methods, making them more suitable for the large-scale storage, indexing, and computational optimization design of enzyme-directed evolution data.

[0151] Furthermore, after completing the structured processing of the directed evolution data of enzymes and determining the ECD structure of the target enzyme, this invention can also use the ECD structure to construct a data relationship structure for the directed evolution data of enzymes, in order to characterize the bioinformatics associations between various enzymes. This data relationship structure includes, but is not limited to, an evolutionary tree structure constructed based on parent-child relationships.

[0152] Please refer to the reference. Figure 1 and Figure 4 , Figure 4 A schematic diagram of an evolutionary tree structure for directed evolutionary data of an enzyme, provided according to some embodiments of the present invention, is shown.

[0153] like Figure 1 and Figure 4 As shown, in the embodiment of the above-described phylogenetic tree structure, the storage device can use the predecessor field and / or descendant field in the ECD structure as relation fields indicating evolutionary relationships, and use the remaining fields or all fields of the ECD structure as information fields recording the directed evolutionary data of the enzyme, to define the evoNode structure of the data storage node of the phylogenetic tree structure. Here, the predecessor field includes, but is not limited to, the [A2] wild ancestor (acestorId) field and / or the [A8] parent Id field of the ECD structure. The descendant field includes, but is not limited to, the descendant field indicating at least one descendant.

[0154] Specifically, in defining the `evoNode` structure, the storage device can first configure `children`, `ecd`, and `parent` fields for the `evoNode` structure. The `children` field is an array of at least one `evoNode` structure, used to record all the child enzymes (or mutants) of the enzyme (or mutation) represented by this storage node. All members of the `children` field of the same storage node are sibling nodes. The `ecd` field is an `ECD` structure, used to record detailed information about the enzyme (or mutation) represented by this storage node. The `parent` field is a pointer, pointing to the storage node of the unique parent enzyme that evolved to represent the enzyme (or mutation) of this storage node, or null, used to describe the unique parent of the enzyme (or mutation) represented by this storage node. Here, if the value of the `parent` field is a null pointer, it means that this storage node is the root of the entire evolutionary tree structure, i.e., an ancestor node.

[0155] After the definition of the evoNode structure is completed, the storage device can retrieve at least one associated enzyme from the EvoCloud database whose information field matches at least one relation field of the target enzyme, based on at least one relation field of the target enzyme, to construct an association set of the target enzyme, and construct the data relationship structure of the target enzyme based on each associated enzyme in the association set.

[0156] Specifically, given an input value s (e.g., enzyme sequence data, enzyme structural data, enzyme ligand molecule information, etc.), the storage device can first search the EvoCloud database for entries with s as the primary key, i.e., find a data entry eIn that uniquely satisfies eIn.id = s. In this way, the storage device can determine the ECD structure of the target enzyme based on the data entry eIn, and use this ECD structure to construct the ECD information field of this evoNode storage node.

[0157] Subsequently, the storage device can use the [A2] wild-type ancestor (acestorId) field of the target enzyme's ECD structure as the ancestor field, and search the EvoCloud database based on the value of the [A2] field. This retrieves entries in the EvoCloud database where the primary key of the wild-type ancestor of eIn is the primary key; that is, it finds a data entry e0 that uniquely satisfies e0.id = e.ecd.ancestorId. Thus, the storage device can determine the ancestor enzyme whose information field matches the [A2] field of the target enzyme based on this data entry e0, thereby determining the ECD structure of the wild-type ancestor enzyme of the target enzyme.

[0158] Furthermore, the storage device can construct an array ePrime in computer memory, whose members are all ECD data structures. Then, the storage device can retrieve the EvoCloud database based on the value of the [A2] field of the target enzyme, traverse all entries e[i] in the EvoCloud database, and add all e[i].ecds that satisfy e[i].ecd.ancestorId = eIn.ecd.ancestorId to the end of the ePrime array and push them onto the stack, thereby identifying at least one associated enzyme's ECD structure whose [A2] field matches the target enzyme's [A2] field. Here, at least one associated enzyme whose [A2] field matches the target enzyme's [A2] field has the same wild-type ancestor enzyme as the target enzyme and belongs to the descendant enzymes of that wild-type ancestor enzyme.

[0159] Then, the storage device can construct an association set of the target enzyme based on the wild ancestral enzyme and the ECD structure of the at least one associated enzyme, and construct an evolutionary tree structure of the target enzyme based on the wild ancestral enzyme and the ECD structure of each associated enzyme in the association set.

[0160] Specifically, in constructing the evolutionary tree structure of the target enzyme, the storage device can first create a variable E in computer memory with the data type of the aforementioned evoNode structure, initialize its parent field E.parent = null (null pointer), and initialize its ecd field to E.ecd = e0.ecd, thereby determining the data storage node of the aforementioned wild ancestral enzyme as the ancestral node of the entire evolutionary tree structure. Then, the storage device can traverse the aforementioned array ePrime, construct a new evoNode structure for each member ePrime[j] that satisfies ePrime[j].ecd.parentId = E.ecd.id, initialize its parent field to point to E, and add it to the end of the array E.children and push it onto the stack, thereby determining the association between the ancestral node variable E and its respective child generation data storage nodes.

[0161] Next, the storage device can delete the member ePrime[j] corresponding to each child-1 generation data storage node from the array ePrime, and determine whether there are other members in the array ePrime. In response to the result of the determination that there are other members in the array ePrime, the storage device can traverse the array ePrime again, construct a new evoNode structure for each member ePrime[l] that satisfies ePrime[l].ecd.parentId = E.children[k].ecd.id, initialize its parent field to point to the corresponding E.children[k] node, and add it to the end of the array E.children[k].children and push it onto the stack, so as to determine the association relationship between each child-1 generation data storage node and its corresponding child-2 generation data storage nodes.

[0162] Similarly, the storage device can further delete the member ePrime[1] corresponding to each second-generation data storage node from the array ePrime, and further determine whether there are other members in the array ePrime. In response to the result of the determination that there are other members in the array ePrime, the storage device can traverse the array ePrime again and repeat the above operation of constructing and initializing the new evoNode structure until all members in the array ePrime are deleted. Thus, the variable E finally obtained by the storage device can form Figure 4 The diagram shows an evolutionary tree structure containing the target enzyme.

[0163] Subsequently, in response to constructing an evolutionary tree structure for the target enzyme, the storage device can store the directed evolutionary data of the target enzyme and its associated enzymes into the computer-readable storage medium provided in the seventh aspect of the present invention according to the architecture of the aforementioned evolutionary tree structure, and collect evolutionary tree structures for various target enzymes to construct an evolutionary tree database of directed evolutionary data of enzymes.

[0164] Thus, the method for storing directed evolution data of enzymes provided in the first aspect of the present invention, the device for storing directed evolution data of enzymes provided in the third aspect of the present invention, the computer-readable storage medium provided in the fifth aspect of the present invention, and the computer-readable storage medium provided in the seventh aspect of the present invention can integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics relationships between various enzymes, and achieve efficient storage of this multi-dimensional data.

[0165] Furthermore, according to the second, fourth, and sixth aspects of the present invention, this disclosure also provides a method, apparatus, and computer-readable storage medium for retrieving directed evolution data of enzymes. The working principles of the above-described retrieval apparatus and storage medium will be described below with reference to embodiments of some retrieval methods. Those skilled in the art will understand that these retrieval methods are merely non-limiting embodiments provided by the present invention, intended to clearly demonstrate the main concepts of the invention and provide specific solutions convenient for public implementation, and are not intended to limit all functions or all working methods of the above-described retrieval apparatus and storage medium. Similarly, the retrieval apparatus and storage medium are also merely non-limiting embodiments provided by the present invention and do not constitute a limitation on the entities performing the steps in these retrieval methods.

[0166] Please refer to Figure 5 , Figure 5 A flowchart illustrating a method for retrieving enzyme-directed evolution data according to some embodiments of the present invention is shown.

[0167] like Figure 5 As shown, in the process of retrieving directed evolution data of a target enzyme, a technician can first connect the retrieval device to the computer-readable storage medium provided in the seventh aspect of the present invention, and input retrieval information s such as the sequence data, structural data, and ligand molecule information of the target enzyme through the human-computer interaction interface of the retrieval device. In response to obtaining the retrieval information s about the target enzyme, the retrieval device can first search for entries with s as the primary key in the EvoCloud database, that is, find a data entry eIn that uniquely satisfies eIn.id = s. In this way, the retrieval device can determine the ECD structure of the target enzyme based on the data entry eIn, and output one or more of the [A1] to [A12] fields of the target enzyme according to the preset retrieval instructions and / or the retrieval instructions given by the technician.

[0168] Furthermore, after determining the ECD structure of the target enzyme, the retrieval device can also search the aforementioned phylogenetic tree database for evoNode data storage nodes containing the ECD structure of the target enzyme, and determine the phylogenetic tree structure to which the evoNode data storage node belongs. Then, according to preset retrieval instructions and / or retrieval instructions given by a technician, the retrieval device can output the values ​​of one or more subfields (i.e., [A1] to [A12]) in the ecd field of one or more evoNode data storage nodes corresponding to the phylogenetic tree structure. This enables efficient retrieval of multi-dimensional data involving the directed evolution of each associated enzyme, including enzyme sequence, enzyme structure, catalytic performance, and bioinformatics associations. This allows technicians to easily and quickly understand the directed evolution data of various associated enzymes, such as the wild-type ancestral enzyme, parent n-generation enzyme, daughter n-generation enzyme, and sibling enzyme of the target enzyme.

[0169] Therefore, the method for retrieving directed evolution data of enzymes provided in the second aspect of the present invention, the apparatus for retrieving directed evolution data of enzymes provided in the fourth aspect of the present invention, the computer-readable storage medium provided in the sixth aspect of the present invention, and the computer-readable storage medium provided in the seventh aspect of the present invention can integrate multi-dimensional data involved in the directed evolution process of enzymes, characterize the catalytic performance of enzymes, characterize the bioinformatics associations between various enzymes, and achieve efficient retrieval of this multi-dimensional data.

[0170] Although the methods described above are illustrated and depicted as a series of actions for the sake of simplicity, it should be understood and appreciated that these methods are not limited by the order of the actions, as some actions may occur in a different order and / or concurrently with other actions from the illustrations and descriptions herein or not illustrated and described herein but which may be understood by those skilled in the art, according to one or more embodiments.

[0171] Those skilled in the art will understand that information, signals, and data can be represented using any of a variety of different techniques and arts. For example, the data, instructions, commands, information, signals, bits, symbols, and chips described throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, light fields or optical particles, or any combination thereof.

[0172] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in a generalized manner in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in different ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the invention.

[0173] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or performed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but in alternatives, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors cooperating with a DSP core, or any other such configuration.

[0174] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor such that the processor can read and write information to / from the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside as discrete components in the user terminal.

[0175] In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functionality may be stored or transmitted as one or more instructions or code on or through a computer-readable medium. A computer-readable medium includes both computer storage media and communication media, encompassing any medium that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium accessible to a computer. By way of example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage, disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and is accessible to a computer. Any connection is also legitimately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of a medium. As used in this article, disk and disc include compact discs (CDs), laser discs, optical discs, digital multi-purpose discs (DVDs), floppy disks, and Blu-ray discs. Disks typically reproduce data magnetically, while discs reproduce data optically using lasers. Combinations of these should also be included within the scope of computer-readable media.

[0176] The prior description of this disclosure is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for storing directed evolutionary data of enzymes, characterized in that, Includes the following steps: Obtain directed evolution data for the target enzyme; The directed evolution data is structured to determine at least one relational field and at least one informational field for the target enzyme. The relational field includes a predecessor field and a descendant field. The predecessor field includes a wild ancestor field and a parent field indicating a unique parent. The descendant field includes a descendant field indicating at least one offspring. The informational field includes at least one of the following: an alternative name field, an expression system field, a unique identifier field, a scientific name field, a remarks field, a biological origin field, a catalytic performance field, a reference field, an enzyme sequence field, and an enzyme structure field. The database is retrieved based on at least one information field determined by the structured processing to determine the previous generation field and information field of the target enzyme; The database is retrieved based on the prior field to identify a prior enzyme whose information field matches the prior field of the target enzyme, wherein the prior enzyme includes the wild-type ancestral enzyme of the target enzyme; The database is retrieved based on the previous ancestor field to identify at least one associated enzyme whose previous ancestor field matches the previous ancestor field of the target enzyme, wherein the at least one associated enzyme includes at least one descendant enzyme whose wild ancestor field matches the wild ancestor enzyme. Based on the previous enzyme and the at least one associated enzyme, construct the association set of the target enzyme; Based on the offspring field, the at least one information field, and the parent field, data storage nodes for the target enzyme, the wild-type ancestral enzyme, and each of the associated enzymes are defined respectively. Using the data storage node of the wild ancestral enzyme as the ancestor node, its offspring at each level are traversed sequentially, and the evolutionary relationship between the ancestor node and each level of offspring nodes is characterized by the offspring field and the parent field, until the data storage nodes of all enzymes in the association set are traversed, thereby constructing an evolutionary tree structure for the target enzyme; and The data relationship structure regarding the target enzyme is stored in the memory.

2. The storage method of claim 1, wherein, The expression system field adopts an expression system structure, which includes at least one of the following: expression host field, remarks field, enzyme-carrying gene field, and unique number field, and / or The catalytic performance field adopts a catalytic performance structure, which includes at least one of the following: reaction conditions field, experiment number field, reaction product field, reaction reagent field, and reaction substrate field, and / or The reference field adopts a reference structure, which includes at least one of the following: citation source field, publication date field, remarks field, citation URI field, and citation title field, and / or The enzyme sequence field adopts an enzyme sequence structure, which includes at least one of the following: GenBank accession number, GI number, mutation field, remarks field, citation URI field, sequence content field, sequence URI field, sequence category field, and UniProt ID field, and / or The enzyme structure field adopts an enzyme structure structure, which includes at least one of the following: ligand field, mutation field, memo field, citation URI field, sequence URI field, structure URI field, structure content field, and structure category field.

3. The storage method of claim 2, wherein, The reaction condition field adopts a reaction condition structure, which includes at least one of the following: relative humidity field, pH field, reaction time field, reactor field, and reaction temperature field, and / or The reaction product field adopts a reaction product structure, which includes at least one of the following: reaction conversion rate field, product diastereomer excess value field, product diastereomer ratio field, product enantiomer excess value field, enantiomer selectivity field, product enantiomer ratio field, product molecule field, product purity field, product positional isomer excess value field, product positional isomer ratio field, separation yield field, and in-situ yield field, and / or The reaction reagent field comprises at least one reaction reagent structure, each reaction reagent structure corresponding to a reaction reagent, wherein at least one of the following is included: addition method field, dilution method field, amount added field, reagent molecule field, and / or The reaction substrate field consists of at least one reaction substrate structure, each of which corresponds to a reaction substrate, and includes at least one of the following: addition method field, dilution method field, amount added field, and substrate molecule field.

4. The storage method of claim 3, wherein, The reactor field adopts a reactor structure, which includes at least one of the following: a stirring field, a diameter field, a height field, and a shape field, and / or At least one of the product molecule field, the reagent molecule field, and the substrate molecule field adopts a ligand structure, wherein the ligand structure includes at least one of the following: CAS number field, InChI field, scientific name field, SMILES field, and chemical structure field, and / or The addition method field adopts an addition method structure, which includes at least one of the following: method field, speed field, and time point field, and / or The dilution method field uses a dilution structure, which includes at least a diluent field and / or a diluent dosage field, wherein the diluent field uses the ligand structure, and / or The input quantity field adopts a physical quantity structure, which includes at least one of the following: a lower limit field, a target value field, a unit field, and an upper limit field.

5. The storage method of claim 4, wherein, The stirring field adopts a stirring structure, which includes at least one of the stirring amplitude field, stirring method field, and stirring speed field.

6. The storage method of claim 2, wherein, The mutation field consists of at least one mutation structure, each mutation structure corresponding to a mutation, and includes at least one of the following: mutation sequence fragment field, mutation location field, template sequence fragment field, and mutation type field.

7. The storage method according to any one of claims 1 to 6, characterized in that, Each of the aforementioned fields consists of interrelated field keys and field values, wherein, The relation field key of the relation field indicates the relation type, while its relation field value indicates the associated enzyme with the corresponding relation type. The information field key of the information field indicates the information type, while its information field value indicates the information data belonging to the corresponding information type.

8. A method for retrieving directed evolutionary data of enzymes, characterized in that, Includes the following steps: Obtain search information about the target enzyme; The data storage node of the target enzyme is determined based on the search information; Determine the data relationship structure to which the data storage node belongs, wherein the data relationship structure is obtained by the method for storing directed evolution data of enzymes according to any one of claims 1 to 7; and Output the directed evolution data of the enzyme recorded in at least one data storage node in the data relationship structure.

9. A storage device for directed evolution data of enzymes, characterized in that, include: First memory, and A first processor, connected to the first memory, is configured to implement a method for storing directed evolution data of enzymes as described in any one of claims 1 to 7.

10. A device for retrieving directed evolution data of enzymes, characterized in that, include: Second memory, and A second processor, connected to the second memory, is configured to implement the method for retrieving enzyme-directed evolution data as described in claim 8.

11. A computer-readable storage medium storing computer instructions thereon, characterized in that, When the computer instructions are executed by the processor, the method for storing enzyme-directed evolution data as described in any one of claims 1 to 7 is implemented.

12. A computer readable storage medium having stored thereon computer instructions, wherein, When the computer instructions are executed by the processor, the method for retrieving enzyme-directed evolution data as described in claim 8 is implemented.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an enzyme data relation structure, wherein the data relation structure is obtained by implementing the method for storing directed evolution data of enzymes as described in any one of claims 1 to 7.

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