Recombinase and recognition site screening method and system based on structure classification prediction

Abstract

The invention relates to the technical field of technical gene detection, in particular to a recombinase and recognition site screening method and system based on structure classification prediction.The method comprises the steps that to-be-matched recombinase is obtained for structure resolution prediction.The functional domain of the to-be-matched recombinase is obtained; searching in a first database according to the functional domain, searching candidate recombinase of which the similarity meets a preset condition, and screening to obtain optimal recombinase; determining an interaction region of the current large serine recombinase and the target DNA sequence from a second database, and sequentially obtaining interaction amino acid sequences corresponding to the preferable recombinase; and matching with the amino acid characteristic sequence of the current large serine recombinase in the second database to obtain the target large serine recombinase with the highest similarity in the preferred recombinase and the corresponding recognition site sequence. According to the method, the structure of the large protein is subjected to structure comparison mining and splitting, and recognition site prediction is performed on interaction region amino acid characteristics, so that the research and development period is shortened, and the research and development cost is saved.

Description

Technical Field

[0001] This application relates to the field of gene detection technology, and in particular to a screening method and system for recombinases and recognition sites based on structural classification prediction. Background Technology

[0002] Recombinases typically refer to site-specific recombinases, primarily derived from bacteriophages and fungi. They catalyze the breaking and rejoining of DNA strands between specific target sites. Based on amino acid homology and the class of active amino acids during recombination, recombinases are broadly classified into tyrosine recombinases and serine recombinases, which employ entirely different mechanisms to achieve recombination. Because recombinase-mediated recombination does not rely on the error-prone NHEJ DNA repair pathway and exhibits high specificity and conservation (catalyzing recombination only between specific sites), it has gradually attracted attention and plays a crucial role in the field of gene editing.

[0003] Compared to tyrosine recombinases with similar DNA recognition sites and reversible reactions (such as Cre and FLP), serine recombinases can recognize and catalyze recombination events between two distinct specific DNA sites (approximately 50 bp) (the two sites are called attP (attachment site in bacteriophages) and attB (attachment site in bacteria), respectively), and they possess unidirectional catalytic DNA integration capabilities. Based on size, serine recombinases can be further subdivided into large serine recombinases and small serine recombinases. Large serine recombinases (LSRs), due to their specificity, conservation, and directionality, are not only considered powerful tools in synthetic biology but have also received increasing attention in recent years for their applications in gene editing.

[0004] However, existing computer prediction methods are mainly based on biological sequence prediction and still have many shortcomings:

[0005] (1) Inaccurate database annotations: Current recombinase screening methods mainly rely on the functional annotations of sequences in the NCBI nucleic acid sequence database and sequence similarity comparison retrieval. The functional annotation information comes only from sequence similarity, and inaccurate functional annotations result in a lot of noise in the database.

[0006] (2) Inaccurate functional domain segmentation: Even if existing technologies divide sequences by functional domains (pfam) and then segment the sequences, the segmentation principle still needs to rely on sequence similarity or HMM probability for prediction.

[0007] (3) Prediction results are highly dependent on databases and software: For the prediction of recognition sites of attP and attB macroserine recombinases, existing technologies use similar sequence classification methods to make predictions. Sequences near the upstream and downstream of the macroserine recombinase are identified using existing software and databases to determine the probability of their origin from bacteriophages and bacterial genomes, thereby determining their binding boundaries and inferring their specific recognition sites. The accuracy and efficiency of this method heavily depend on metagenomic databases and software. Summary of the Invention

[0008] The main purpose of this application is to propose a predictive method for protein structure classification by applying homology features from evolutionary taxonomy to the characterization of protein three-dimensional structures for the first time through structural analysis and observation of macroserine recombinases.

[0009] To achieve the above objectives, this application provides the following technical solution:

[0010] According to a first aspect of the present invention, the present invention claims protection for a screening method for recombinases and recognition sites based on structural classification prediction, comprising:

[0011] Obtain the recombinase to be matched, perform structural decomposition and prediction on the recombinase to be matched, and obtain the functional domain of the recombinase to be matched;

[0012] Based on the functional domain, a search is performed in the first database to find first candidate recombinases whose similarity meets the first preset condition;

[0013] Based on the functional domain, a first database is screened and filtered to obtain a second candidate recombinase that meets the second preset condition;

[0014] The first and second candidate recombinases were analyzed and the preferred recombinases were selected based on preset weights.

[0015] The interaction region between the current large serine recombinase and the target DNA sequence is determined from the second database, and the interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the interaction region.

[0016] The interacting amino acid sequence is matched with the amino acid feature sequence of the current macroserine recombinase in the second database to obtain the target macroserine recombinase with the highest similarity among the preferred recombinases and the corresponding attP and attB recognition site sequences.

[0017] Furthermore, the step of obtaining the recombinase to be matched, performing structural decomposition and prediction on the recombinase to be matched, and obtaining the functional domain of the recombinase to be matched further includes:

[0018] The recombinase to be matched is the recombinase of interest;

[0019] The recombinase to be matched is sequenced to obtain the baseline target sequence;

[0020] Alphafold software was used to predict the structure of the recombinase to be matched, and the theoretical structure of the recombinase to be matched was obtained.

[0021] The theoretical structure is split into three-dimensional structural functional domains to obtain multiple functional domains of the recombinase to be matched after structural splitting.

[0022] Furthermore, the method also includes:

[0023] The plurality of functional domains include at least:

[0024] The ser functional domain, rec functional domain, zn functional domain, coil functional domain, and tail functional domain;

[0025] The zn functional domain comprises two discontinuous parts;

[0026] The coil and tail functional domains are local structures composed of long helices, located at the C-terminus of the recombinase to be matched.

[0027] Furthermore, the theoretical structure is subjected to three-dimensional structural functional domain decomposition to obtain the basis for multiple functional domains of the recombinase to be matched after structural decomposition, including:

[0028] By calculating the residue contact distance between each structural unit of the protein of the recombinase to be matched, while ensuring that the internal residues of the theoretical structure are in the closest contact and the structural units are in the most distant contact, the optimal structural decomposition result is obtained.

[0029] Furthermore, the step of searching the first database based on the functional domain to find a first candidate recombinase whose similarity meets a first preset condition further includes:

[0030] The first database stores protein structures;

[0031] Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the first similarity score of each protein structure in the first database.

[0032] Protein structures with a similarity score greater than a first similarity threshold are selected as first candidate recombinases.

[0033] Furthermore, the process of sequentially matching multiple functional domains with similar protein structures in the first database to obtain similarity scores for each protein structure in the first database also includes:

[0034] Construct a similarity score calculation model:

[0035]

[0036] Among them, L target It is the length of the target protein's amino acid sequence, L common It is the number of residues appearing in the template and the target structure, d i It is the distance between the template and the i-th pair of residues in the target structure;

[0037] The TM-score is a score that evaluates the structural similarity between two proteins, ranging from 0 to 1. When the TM-score is 0.5, it indicates that the two proteins have random similarity. When the TM-score is greater than 0.5, the probability of structural similarity between the two proteins increases. The larger the TM-score value, the higher the structural similarity between the two proteins.

[0038] Furthermore, the step of filtering the first database based on the functional domain to obtain a second candidate recombinase that meets the second preset condition further includes:

[0039] Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the second similarity score of each protein structure in the first database.

[0040] Protein structures with a second similarity score greater than the second similarity threshold are selected as second candidate recombinases.

[0041] Furthermore, the step of determining the interaction region between the current large serine recombinase and the target DNA sequence from the second database, and sequentially obtaining the interaction amino acid sequence corresponding to the preferred recombinase based on the interaction region, further includes:

[0042] Obtain the crystal structure (4KIS) of the current large serine recombinase and target DNA sequence from the RCSB PDB database;

[0043] The regions where the amino acids of the current macroserine recombinase interact with DNA are meticulously divided to determine the locations where the current macroserine recombinase and the target DNA sequence directly interact, which are then defined as the interaction regions.

[0044] The interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the functional domain position corresponding to the interaction region.

[0045] Furthermore, the step of sequentially obtaining the interacting amino acid sequence corresponding to the preferred recombinase based on the functional domain positions corresponding to the interacting regions further includes:

[0046] The preferred recombinase was dissected to obtain functional domain structures with independent three-dimensional structures. The functional domain structures and the crystal structure 4KIS were then compared using Tmalign based on the structure.

[0047] Based on the consistency information sites from the structural alignment, the DNA interaction amino acid sequence in each of the preferred recombinases is extracted, and three discontinuous interaction amino acid sequences in the ser, rec, and zn functional domains of the preferred recombinases are ligated and merged to obtain a novel DNA interaction feature sequence, which is used as the interaction amino acid sequence corresponding to the preferred recombinase.

[0048] According to a second aspect of the present invention, the present invention claims protection for a screening system for recombinases and recognition sites based on structural classification prediction, comprising:

[0049] One or more processors;

[0050] A memory having stored one or more programs that, when executed by one or more processors, enable the one or more processors to implement the described method for screening recombinases and recognition sites based on structure classification prediction.

[0051] This application relates to the field of gene detection technology, and in particular to a method and system for screening recombinases and recognition sites based on structural classification prediction. The method involves obtaining a recombinase to be matched, performing structural segmentation prediction to obtain the functional domains of the recombinase; searching a first database based on these functional domains to find candidate recombinases with similarity meeting preset conditions and selecting preferred recombinases; identifying the interaction region between the current macroserine recombinase and the target DNA sequence from a second database, and sequentially obtaining the corresponding interaction amino acid sequences of the preferred recombinase; matching these sequences with the amino acid feature sequences of the current macroserine recombinase in the second database to obtain the target macroserine recombinase with the highest similarity among the preferred recombinases and its corresponding recognition site sequence. This invention performs structural comparison and mining of large proteins, and segments them by predicting recognition sites based on the amino acid features of the interaction regions, thus shortening the development cycle and saving development costs. Attached Figure Description

[0052] Figure 1 A flowchart illustrating the workflow of a screening method for recombinases and recognition sites based on structural classification prediction, as claimed in the embodiments of this application.

[0053] Figure 2 A classic structural breakdown diagram of a recombinase for a screening method based on structural classification prediction of recombinases and recognition sites, which is claimed in an embodiment of this application.

[0054] Figure 3A comparison diagram of the three-dimensional structure functional domains of a large serine recombinase, based on a screening method for recombinases and recognition sites according to a structural classification prediction method claimed in this application.

[0055] Figure 4 A schematic diagram of the interaction crystal structure of a large serine recombinase and its target DNA in a screening method for recombinases and recognition sites based on structural classification prediction, as claimed in the embodiments of this application.

[0056] Figure 5 A schematic diagram of the recombinase A0A7V3J217 splitting, representing a screening method for recombinases and recognition sites based on structural classification prediction claimed in this application. Detailed Implementation

[0057] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0058] The terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0059] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0060] According to a first embodiment of the present invention, the present invention claims protection for a screening method for recombinases and recognition sites based on structural classification prediction, as detailed in the appendix. Figure 1 ,include:

[0061] Obtain the recombinase to be matched, perform structural decomposition and prediction on the recombinase to be matched, and obtain the functional domain of the recombinase to be matched;

[0062] Based on the functional domain, a search is performed in the first database to find first candidate recombinases whose similarity meets the first preset condition;

[0063] Based on the functional domain, a first database is screened and filtered to obtain a second candidate recombinase that meets the second preset condition;

[0064] The first and second candidate recombinases were analyzed and the preferred recombinases were selected based on preset weights.

[0065] The interaction region between the current large serine recombinase and the target DNA sequence is determined from the second database, and the interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the interaction region.

[0066] The interacting amino acid sequence is matched with the amino acid feature sequence of the current macroserine recombinase in the second database to obtain the target macroserine recombinase with the highest similarity among the preferred recombinases and the corresponding attP and attB recognition site sequences.

[0067] In this embodiment, the recombinase to be matched is Bxb1 recombinase;

[0068] The recombinase to be matched is structurally decomposed into a three-dimensional spatial coordinate point sequence for prediction;

[0069] Protein structure is characterized as points in three-dimensional space;

[0070] Amino acids form a primary sequence. They are arranged to form helices, folds, turns, and random coils, which constitute secondary structures. Secondary structures are often represented by letters (A, B, T, L).

[0071] Secondary structures are stacked to form the three-dimensional structure of a protein, which is represented by three-dimensional coordinate points in space.

[0072] Amino acid sequences are matched using sequence similarity (for example, how many of 100 amino acids are the same).

[0073] Structural similarity is matched by the distance difference between points in a three-dimensional coordinate system, and is represented by the TM-score.

[0074] First, we used structure prediction tools such as Alphafold to predict the structure of the recombinases of interest. Then, we split the three-dimensional structure of the protein into three-dimensional functional domains according to spatial distance. Based on the individual three-dimensional functional domains, we performed structural similarity search to obtain protein structures with local structural similarities. After summarizing and filtering, we obtained novel large serine recombinases.

[0075] On the other hand, in the prediction of attP and attB recognition sites, based on the protein electron microscopy structure of the macroserine recombinase interacting with DNA, the regions of DNA interaction within the macroserine domain are divided. By comparing and searching the existing macroserine database with the characteristics of the amino acid arrangement in the interaction regions, the attP and attB recognition sites of this novel macroserine recombinase are obtained. This enables the discovery of novel recombinases and recognition sites based on structure, further enriching the recombinases with different editing preferences and expanding the original tool library for precisely manipulating large fragments of the genome in gene editing.

[0076] Furthermore, the step of obtaining the recombinase to be matched, performing structural decomposition and prediction on the recombinase to be matched, and obtaining the functional domain of the recombinase to be matched further includes:

[0077] The recombinase to be matched is the recombinase of interest;

[0078] The recombinase to be matched is sequenced to obtain the baseline target sequence;

[0079] Alphafold software was used to predict the structure of the recombinase to be matched, and the theoretical structure of the recombinase to be matched was obtained.

[0080] The theoretical structure is split into three-dimensional structural functional domains to obtain multiple functional domains of the recombinase to be matched after structural splitting.

[0081] Furthermore, the method also includes:

[0082] The plurality of functional domains include at least:

[0083] The ser functional domain, rec functional domain, zn functional domain, coil functional domain, and tail functional domain;

[0084] The zn functional domain comprises two discontinuous parts;

[0085] The coil and tail functional domains are local structures composed of long helices, located at the C-terminus of the recombinase to be matched.

[0086] In this embodiment, Alphafold software is used to predict the structure of the recombinase of interest, obtaining its theoretical structure. A SWORD2-based method is then used to perform three-dimensional structural domain decomposition of the obtained structure. This is primarily achieved by calculating the residue contact distances between different structural units of the protein to simultaneously ensure the closest contact between residues within each structural unit and the furthest contact between structural units, thus obtaining the optimal structural decomposition result based on these conditions.

[0087] For example, spatial proximity is used as the basis for splitting, and the spatial distance between each higher-level structure is greater than... Those that are different structural domains, and those that are spatially separated by a distance of not less than 3i, are considered as the same structural domain;

[0088] (pronounced i);

[0089] At the same time, when dividing structural domains, higher-level structures, such as spiral structures and layered structures, are not interrupted;

[0090] Since the classic structure of recombinase mainly consists of three parts: the serine recombinase domain, the recombinase domain, and the zn-recom-ribbon domain, and the zn-recom-ribbon domain is usually composed of two discontinuous parts, plus a local structure consisting of two longer helices located at the C-terminus of the recombinase, the recombinase can be divided into five basic three-dimensional functional domains, named ser, rec, zn, coil, and tail. A schematic diagram of the decomposed three-dimensional functional domains is shown below. Figure 2 As shown;

[0091] Furthermore, the theoretical structure is subjected to three-dimensional structural functional domain decomposition to obtain the basis for multiple functional domains of the recombinase to be matched after structural decomposition, including:

[0092] By calculating the residue contact distance between each structural unit of the protein of the recombinase to be matched, while ensuring that the internal residues of the theoretical structure are in the closest contact and the structural units are in the most distant contact, the optimal structural decomposition result is obtained.

[0093] Furthermore, the step of searching the first database based on the functional domain to find a first candidate recombinase whose similarity meets a first preset condition further includes:

[0094] The first database stores protein structures;

[0095] Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the first similarity score of each protein structure in the first database.

[0096] Protein structures with a similarity score greater than a first similarity threshold are selected as first candidate recombinases.

[0097] In this embodiment, the first similarity score refers to the zn functional domain, coil functional domain, and tail functional domain in the functional domain.

[0098] Furthermore, the process of sequentially matching multiple functional domains with similar protein structures in the first database to obtain similarity scores for each protein structure in the first database also includes:

[0099] Construct a similarity score calculation model:

[0100]

[0101] Among them, L target It is the length of the target protein's amino acid sequence, L common It is the number of residues appearing in the template and the target structure, d i It is the distance between the template and the i-th pair of residues in the target structure;

[0102] The TM-score is a score that evaluates the structural similarity between two proteins, ranging from 0 to 1. When the TM-score is 0.5, it indicates that the two proteins have random similarity. When the TM-score is greater than 0.5, the probability of structural similarity between the two proteins increases. The larger the TM-score value, the higher the structural similarity between the two proteins.

[0103] In this embodiment, the structure search function of the Foldseek database is used to search for similar protein structures in the database for the five obtained three-dimensional structural functional domains (Tmscore>0.75).

[0104] like Figure 3 As shown, the horizontal and vertical axes represent the results of splitting similar target proteins into their corresponding five three-dimensional structural functional domains using the five three-dimensional structural functional domains of Bxb1.

[0105] The values ​​in the figure are structural similarity scores (1-TMscore); the closer to red, the less similar they are, and blue indicates greater similarity; the figure can be divided into 5 blue regions along the diagonal, which correspond to the 5 three-dimensional structural functional domains mentioned above; the results show that the similarity within functional domains is high, while the similarity between functional domains is low.

[0106] The Foldseek database stores the overall structures of known serine recombinases;

[0107] Furthermore, the step of filtering the first database based on the functional domain to obtain a second candidate recombinase that meets the second preset condition further includes:

[0108] Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the second similarity score of each protein structure in the first database.

[0109] Protein structures with a second similarity score greater than the second similarity threshold are selected as second candidate recombinases.

[0110] In this embodiment, the second similarity score refers to the ser functional domain and the rec functional domain in the functional domain.

[0111] The second similarity threshold is greater than the first similarity threshold;

[0112] For example, the first similarity threshold is set to 0.2; the second similarity threshold is set to 0.75;

[0113] Specifically, during similarity matching, serine recombinases in the Foldseek database do not necessarily include the zn functional domain, coil functional domain, and tail functional domain.

[0114] When the zn, coil, or tail functional domains are missing, similar sequences are considered similar when matching similarity in other functional domains.

[0115] Furthermore, the step of determining the interaction region between the current large serine recombinase and the target DNA sequence from the second database, and sequentially obtaining the interaction amino acid sequence corresponding to the preferred recombinase based on the interaction region, further includes:

[0116] Obtain the crystal structure (4KIS) of the current large serine recombinase and target DNA sequence from the RCSB PDB database;

[0117] The regions where the amino acids of the current macroserine recombinase interact with DNA are meticulously divided to determine the locations where the current macroserine recombinase and the target DNA sequence directly interact, which are then defined as the interaction regions.

[0118] The interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the functional domain position corresponding to the interaction region.

[0119] Furthermore, the step of sequentially obtaining the interacting amino acid sequence corresponding to the preferred recombinase based on the functional domain positions corresponding to the interacting regions further includes:

[0120] The preferred recombinase was dissected to obtain functional domain structures with independent three-dimensional structures. The functional domain structures and the crystal structure 4KIS were then compared using Tmalign based on the structure.

[0121] Based on the consistency information sites from the structural alignment, the DNA interaction amino acid sequence in each of the preferred recombinases is extracted, and three discontinuous interaction amino acid sequences in the ser, rec, and zn functional domains of the preferred recombinases are ligated and merged to obtain a novel DNA interaction feature sequence, which is used as the interaction amino acid sequence corresponding to the preferred recombinase.

[0122] In this embodiment, reference is made to the appendix. Figure 4 The interaction crystal structure of macroserine recombinase A118 with its target DNA was obtained. Based on the different domains interacting with DNA, the interaction sites were marked in red, green, and cyan, respectively. Using the known 4KIS crystal structures of A118 macroserine recombinase and target DNA sequences from the RCSB PDB database, the regions where the macroserine recombinase-encoding amino acids interact with DNA were meticulously divided. The locations where the LSR directly interacts with the target DNA were determined to be primarily amino acids 134-146 in the tail of the helical structure within the ser domain, amino acids 207-217 in the helical structure within the recombinase's three-dimensional functional domain, and amino acids 280-303 in the zn functional domain. Alignment and matching of the known interaction amino acid positions of the A118 macroserine recombinase and target DNA sequence crystal structures from the 4KIS were then performed to the subsequent recombinase data.

[0123] For novel recombinases discovered through structural similarity mining, we used the structure of each independent three-dimensional functional domain after splitting to perform a structure-based alignment with the 4KIS crystal structure using Tmalign. Based on the consistency information sites in the structural alignment, we extracted the DNA interaction amino acid sequences in each recombinase. Then, we ligated and merged these three discontinuous interaction amino acid sequences from the ser, recombinase, and zn three-dimensional functional domains to obtain a novel DNA interaction feature sequence. All collected and summarized known macroserine recombinase sequences were subjected to the same method for information extraction based on structure alignment, resulting in a macroserine recombinase database composed of interaction amino acid feature sequences. In this database, we matched the interaction amino acid feature sequences of novel recombinases obtained through structure mining to obtain the LSR with the closest interaction amino acids in the database, thus also obtaining the attP and attB recognition sequences of the novel macroserine recombinase.

[0124] For example, a novel recombinase, designated A0A7V3J217 (SEQ ID No. 1), containing 447 amino acids, was discovered based on structural similarity. Using spatial proximity as the separation criterion, the spatial distance between each higher-order structure is greater than... As different structural domains, the spatial distance between them is not less than Using the same structural domain, the recombinase A0A7V3J217 was dissected. The dissection results are shown in the diagram. Figure 5 As shown in Table 1, the structures of the separated domains were aligned using Tmalign. The alignment results are shown in Table 1. The ser, recombinase, and zn three-dimensional domains with high structural similarity were obtained through alignment. Three consecutive interacting amino acid sequences—amino acid positions 134-146 (helical tail) in the ser domain, 207-217 (helical structure) in the recombinase domain, and 280-303 (interacting amino acid positions) in the zn domain—were ligated to obtain the DNA interaction feature sequence SEQ ID No. 2 (as shown in Table 1, where "|" indicates the ligation site). This interaction amino acid feature sequence was then matched against a large serine recombinase database to obtain the corresponding attP and attB recognition sequences.

[0125] Table 1. Examples of structural alignment and sequence acquisition processes for novel recombinases to be tested.

[0126]

[0127] According to a second embodiment of the present invention, the present invention claims protection for a screening system for recombinases and recognition sites based on structural classification prediction, comprising:

[0128] One or more processors;

[0129] A memory having stored one or more programs that, when executed by one or more processors, enable the one or more processors to implement the described method for screening recombinases and recognition sites based on structure classification prediction.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0131] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0132] The specific embodiments of the invention have been described in detail above, but they are only examples, and this application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this application. Therefore, all equivalent changes, modifications, and improvements made without departing from the spirit and principles of this application should be covered within the scope of this application.

Claims

1. A method for screening recombinases and recognition sites based on structural classification prediction, characterized in that, include: Obtain the recombinase to be matched, perform structural decomposition and prediction on the recombinase to be matched, and obtain the functional domain of the recombinase to be matched. Based on the functional domain, a search is performed in the first database to find the first candidate recombinase whose similarity meets the first preset condition; Based on the functional domain, a first database is screened and filtered to obtain a second candidate recombinase that meets the second preset condition; The first and second candidate recombinases were analyzed and the preferred recombinases were selected based on preset weights. The interaction region between the current large serine recombinase and the target DNA sequence is determined from the second database, and the interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the interaction region. The interacting amino acid sequence is matched with the amino acid feature sequence of the current macroserine recombinase in the second database to obtain the target macroserine recombinase with the highest similarity among the preferred recombinases and the corresponding attP and attB recognition site sequences.

2. The method for screening recombinases and recognition sites based on structural classification prediction as described in claim 1, characterized in that, The step of obtaining the recombinase to be matched, performing structural decomposition prediction on the recombinase to be matched, and obtaining the functional domain of the recombinase to be matched further includes: The recombinase to be matched is the recombinase of interest; The recombinase to be matched is sequenced to obtain the baseline target sequence; Alphafold software was used to predict the structure of the recombinase to be matched, and the theoretical structure of the recombinase to be matched was obtained. The theoretical structure is split into three-dimensional structural functional domains to obtain multiple functional domains of the recombinase to be matched after structural splitting.

3. The screening method for recombinases and recognition sites based on structural classification prediction as described in claim 2, characterized in that, Also includes: The plurality of functional domains include at least: The ser functional domain, rec functional domain, zn functional domain, coil functional domain, and tail functional domain; The zn functional domain comprises two discontinuous parts; The coil and tail functional domains are local structures composed of long helices, located at the C-terminus of the recombinase to be matched.

4. The method for screening recombinases and recognition sites based on structural classification prediction as described in claim 2, characterized in that, The basis for performing three-dimensional structural functional domain decomposition on the theoretical structure to obtain multiple functional domains of the recombinase to be matched after structural decomposition includes: By calculating the residue contact distance between each structural unit of the protein of the recombinase to be matched, while ensuring that the internal residues of the theoretical structure are in the closest contact and the structural units are in the most distant contact, the optimal structural decomposition result is obtained.

5. The screening method for recombinases and recognition sites based on structural classification prediction as described in claim 1, characterized in that, The step of searching the first database based on the functional domain to find a first candidate recombinase whose similarity meets a first preset condition further includes: The first database stores protein structures; Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the first similarity score of each protein structure in the first database. Protein structures with a similarity score greater than a first similarity threshold are selected as first candidate recombinases.

6. The screening method for recombinases and recognition sites based on structural classification prediction as described in claim 5, characterized in that, The process involves sequentially matching multiple functional domains against similar protein structures in the first database to obtain similarity scores for each protein structure in the first database, and also includes: Construct a similarity score calculation model: Among them, L target It is the length of the target protein's amino acid sequence, L common It is the number of residues appearing in the template and the target structure, d i It is the distance between the template and the i-th pair of residues in the target structure; It is a distance scale for standardized distances; The TM-score is a score that evaluates the structural similarity between two proteins, ranging from 0 to 1. When the TM-score is 0.5, it indicates that the two proteins have random similarity. When the TM-score is greater than 0.5, the probability of structural similarity between the two proteins increases. The larger the TM-score value, the higher the structural similarity between the two proteins.

7. The screening method for recombinases and recognition sites based on structural classification prediction as described in claim 6, characterized in that, The step of filtering and selecting from the first database based on the functional domain to obtain a second candidate recombinase that meets the second preset condition further includes: Multiple functional domains are sequentially matched with similar protein structures in the first database to obtain the second similarity score of each protein structure in the first database. Protein structures with a second similarity score greater than the second similarity threshold are selected as second candidate recombinases.

8. The method for screening recombinases and recognition sites based on structural classification prediction as described in claim 1, characterized in that, The step of determining the interaction region between the current large serine recombinase and the target DNA sequence from the second database, and sequentially obtaining the interaction amino acid sequence corresponding to the preferred recombinase based on the interaction region, further includes: Obtain the crystal structure (4KIS) of the current large serine recombinase and target DNA sequence from the RCSB PDB database; The regions where the amino acids of the current macroserine recombinase interact with DNA are meticulously divided to determine the locations where the current macroserine recombinase and the target DNA sequence directly interact, which are then defined as the interaction regions. The interaction amino acid sequence corresponding to the preferred recombinase is obtained sequentially based on the functional domain position corresponding to the interaction region.

9. The screening method for recombinases and recognition sites based on structural classification prediction as described in claim 8, characterized in that, The step of obtaining the interaction amino acid sequence corresponding to the preferred recombinase sequentially based on the functional domain positions corresponding to the interaction regions further includes: The preferred recombinase was dissected to obtain functional domain structures with independent three-dimensional structures. The functional domain structures and the crystal structure 4KIS were then compared using Tmalign based on the structure. Based on the consistency information sites from the structural alignment, the DNA interaction amino acid sequence in each of the preferred recombinases is extracted, and three discontinuous interaction amino acid sequences in the ser, rec, and zn functional domains of the preferred recombinases are ligated and merged to obtain a novel DNA interaction feature sequence, which is used as the interaction amino acid sequence corresponding to the preferred recombinase.

10. A screening system for recombinases and recognition sites based on structural classification prediction, characterized in that, include: One or more processors; A memory having stored one or more programs that, when executed by one or more processors, cause the one or more processors to implement a method for screening recombinases and recognition sites based on structural classification prediction according to any one of claims 1 to 9.

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