Enzyme screening method and device
Through the screening method based on the binding ability of enzyme to substrate and enzyme kinetic parameters, the problem of low enzyme screening efficiency in the prior art was solved, and high-active enzymes suitable for the microbial fermentation environment were screened, which significantly improved the fermentation efficiency.
Patent Information
- Application Number
- CN202411420231.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-12
- Publication Date
- 2025-02-14
AI Technical Summary
The existing enzyme screening methods cannot effectively screen enzymes with high activity and strong catalytic ability in the microbial fermentation environment, resulting in low microbial fermentation efficiency.
By screening in a larger range of enzyme species based on the binding ability of the enzyme to the substrate and the enzyme kinetic parameters, a variety of enzymes with low species similarity and high activity were quickly screened.
The screened enzyme has strong environmental adaptability and high catalytic capacity limits, and can efficiently convert substrates into products in a short period of time, significantly improving the efficiency of microbial fermentation.
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Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of enzyme screening, and in particular to an enzyme screening method and device. Background Art
[0002] Microbial fermentation refers to the process in which, under suitable conditions, microorganisms convert raw materials (including multiple substrates) into products needed by humans through specific metabolic pathways. During the process of microbial fermentation, microorganisms continuously produce multiple enzymes (mostly proteins), which convert multiple substrates to obtain fermentation products.
[0003] In the process of microbial fermentation, due to the presence of some enzymes with low activity (i.e., bottleneck enzymes), the substrates that need to be converted by the bottleneck enzymes are piled up, resulting in the low product yield corresponding to the substrates, which reduces the efficiency of microbial fermentation. In this case, it is necessary to screen out enzymes with higher activity that can replace the bottleneck enzymes, and promote microbial fermentation by the substituted enzymes. However, the existing enzyme screening methods often select enzymes based on experience, and the obtained enzyme types have higher similarity and cannot guarantee the activity of the enzymes, so that it is impossible to ensure that the obtained enzymes can quickly convert substrates into products under the environment of microbial fermentation, and thus the efficiency of microbial fermentation cannot be significantly improved. Summary of the invention
[0004] The present invention provides an enzyme screening method and device, which screens enzymes based on the binding ability of enzymes to substrates and enzyme kinetic parameters in a wide range of enzyme types, and quickly screens multiple enzymes with low type similarity and high activity, so that the multiple enzymes screened have strong environmental adaptability and a high upper limit of catalytic ability, thereby having a high conversion efficiency, ensuring that the multiple enzymes screened can convert more substrates into products in a short time under the environment of microbial fermentation, thereby significantly improving the efficiency of microbial fermentation.
[0005] In order to achieve the above object, the present invention adopts the following technical solution:
[0006] In the first aspect, the present invention provides an enzyme screening method, comprising: determining a candidate enzyme set according to a substrate to be converted, a product, a reaction formula for converting the substrate to be converted into a product, and / or an enzyme category for converting the substrate to be converted into a product. Clustering the candidate enzyme set. For each representative candidate enzyme of each class of candidate enzymes in multiple classes of candidate enzymes, the level of the representative candidate enzyme is evaluated according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzyme. Among them, the representative candidate enzyme includes the clustering center of each class of candidate enzymes; the molecular docking results include the number of conformations and the docking root mean square deviation, the conformation number is the number of ligand conformations whose docking energy is less than the docking energy threshold, the docking energy is the energy released by the representative candidate enzyme binding to the substrate, the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds, and the representative candidate enzyme corresponds to multiple ligand conformations; the docking root mean square deviation includes the root mean square deviation between each ligand conformation and the best ligand conformation in the multiple ligand conformations of the representative candidate enzyme; the best ligand conformation is the ligand conformation with the lowest docking energy among the multiple ligand conformations. The screening results are determined based on the representative candidate enzymes after evaluation.
[0007] The enzyme screening method provided by the present invention can quickly screen a variety of enzymes with low species similarity and high activity from a wide range of enzyme species, so that the screened enzymes have strong environmental adaptability and a high upper limit of catalytic capacity, thereby having a high conversion efficiency, ensuring that the screened enzymes can convert more substrates into products in a short time under the environment of microbial fermentation, thereby significantly improving the efficiency of microbial fermentation.
[0008] In an implementation of the first aspect, the level of the representative candidate enzyme is evaluated, including: when the number of conformations of the representative candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation of the representative candidate enzyme meets the first deviation condition, and the enzyme kinetic parameters of the representative candidate enzyme meet the parameter threshold, the level of the representative candidate enzyme is determined as a first-level candidate enzyme; the first deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the first deviation range is less than the first quantity threshold. When the number of conformations of the representative candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation of the representative candidate enzyme meets the second deviation condition, and the enzyme kinetic parameters of the representative candidate enzyme meet the parameter threshold, the level of the representative candidate enzyme is determined as a second-level candidate enzyme; the second deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the second deviation range is less than the second quantity threshold. Otherwise, the level of the representative candidate enzyme is determined as a third-level candidate enzyme.
[0009] In an implementation of the first aspect, clustering the candidate enzyme set includes: clustering the candidate enzyme set according to the similarity of the amino acid sequence of each candidate enzyme in the candidate enzyme set.
[0010] In an implementation of the first aspect, the method further includes: performing molecular docking on each representative candidate enzyme of each type of candidate enzyme in the multiple types of candidate enzymes.
[0011] In an implementation of the first aspect, molecular docking is performed on each representative candidate enzyme of each type of candidate enzyme in the plurality of types of candidate enzymes, comprising:
[0012] The boundary of the representative candidate enzyme is used as the binding range of the representative candidate enzyme and the substrate, and the representative candidate enzyme and the substrate are molecularly docked to obtain multiple ligand conformations; the boundary of the representative candidate enzyme is the distance between the two farthest residues on the representative candidate enzyme. The number of ligand conformations with docking energy less than the docking energy threshold in the multiple ligand conformations is taken as the number of conformations of the representative candidate enzyme; the root mean square deviation between the docking energy of each ligand conformation in the multiple ligand conformations and the docking energy of the best ligand conformation is taken as the docking root mean square deviation of the representative candidate enzyme.
[0013] In an implementation of the first aspect, the method further comprises: predicting the enzyme kinetic parameters of each representative candidate enzyme of each class of candidate enzymes in the plurality of classes of candidate enzymes
[0014] In a second aspect, the present invention provides an enzyme screening device, comprising a set determination module, a clustering module, a rating module and a screening module. The set determination module is used to determine a candidate enzyme set according to substrate to be converted, product, reaction formula of substrate to be converted into product, bottleneck enzyme and / or enzyme category of substrate to be converted into product. The clustering module is used to cluster the candidate enzyme set. The rating module is used to evaluate the level of the representative candidate enzyme for each type of candidate enzyme in the multi-class candidate enzyme according to the molecular docking result and enzyme kinetic parameter of the representative candidate enzyme. Among them, the representative candidate enzymes include the cluster center of each type of candidate enzymes; the molecular docking results include the number of conformations and the root mean square deviation of docking, the number of conformations is the number of ligand conformations whose docking energy is less than the docking energy threshold, the docking energy is the energy released by the representative candidate enzyme binding to the substrate, the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds, and the representative candidate enzyme corresponds to multiple ligand conformations; the root mean square deviation of docking includes the root mean square deviation between each ligand conformation and the best ligand conformation in the multiple ligand conformations of the representative candidate enzyme; the best ligand conformation is the ligand conformation with the lowest docking energy among the multiple ligand conformations. The screening module is used to determine the screening results according to the representative candidate enzymes after the evaluation level.
[0015] In an implementation of the second aspect, the rating module is specifically used to determine the level of the representative candidate enzyme as a first-level candidate enzyme when the number of conformations representing the candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation representing the candidate enzyme satisfies the first deviation condition, and the enzyme kinetic parameters representing the candidate enzyme meet the parameter threshold; the first deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the first deviation range is less than the first quantity threshold. When the number of conformations representing the candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation representing the candidate enzyme satisfies the second deviation condition, and the enzyme kinetic parameters representing the candidate enzyme meet the parameter threshold, the level of the representative candidate enzyme is determined as a second-level candidate enzyme.
[0016] In an implementation of the second aspect, the device further comprises a molecular docking module. The molecular docking module is used to perform molecular docking on each representative candidate enzyme of each type of candidate enzyme in the multiple types of candidate enzymes.
[0017] In an implementation of the second aspect, the molecular docking module is specifically used to use the boundary of the representative candidate enzyme as the range of binding between the representative candidate enzyme and the substrate, perform molecular docking on the representative candidate enzyme and the substrate, and obtain multiple ligand conformations. The number of ligand conformations whose docking energy is less than the docking energy threshold in the multiple ligand conformations is taken as the number of conformations of the representative candidate enzyme; the root mean square deviation between the docking energy of each ligand conformation in the multiple ligand conformations and the docking energy of the best ligand conformation is taken as the docking root mean square deviation of the representative candidate enzyme.
[0018] In an implementation of the second aspect, the device further comprises a prediction module, which is used to predict enzyme kinetic parameters of each representative candidate enzyme of each class of candidate enzymes in the multiple classes of candidate enzymes.
[0019] In a third aspect, the present invention provides an electronic device, comprising a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device performs the method described in the first aspect or any one of its implementations.
[0020] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising computer program instructions, which, when executed by a computer, enable the computer to execute the method as described in the first aspect or any one of its implementations.
[0021] In a fifth aspect, the present invention provides a computer program product, comprising computer program instructions, which, when executed on a computer, enable the computer to execute the method as described in the first aspect or any one of its implementations.
[0022] The technical effects corresponding to the above-mentioned second to fifth aspects and their possible implementations can refer to the above-mentioned description of the technical effects of the first aspect and its possible implementations, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 This is one of the schematic diagrams of an enzyme screening method provided in the examples of the present application;
[0024] Figure 2 This is the second schematic diagram of an enzyme screening method provided in an embodiment of the present application;
[0025] Figure 3 This is the third schematic diagram of an enzyme screening method provided in the embodiments of the present application;
[0026] Figure 4 This is the fourth schematic diagram of an enzyme screening method provided in the embodiments of the present application;
[0027] Figure 5 This is the fifth schematic diagram of an enzyme screening method provided in the embodiments of the present application;
[0028] Figure 6 This is one of the structural schematic diagrams of an enzyme screening device provided in the embodiments of the present application;
[0029] Figure 7 This is the second structural schematic diagram of an enzyme screening device provided in an embodiment of the present application;
[0030] Figure 8 This is the third structural schematic diagram of an enzyme screening device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0031] The terms "first" and "second" etc. in the description and claims of the present invention are used to distinguish different objects rather than to describe a specific order of the objects.
[0032] The “and / or” in the embodiments of the present application indicates the relationship between objects. For example, A and / or B may indicate the following three situations: A exists alone, B exists alone, and A and B exist at the same time.
[0033] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.
[0034] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two. For example, a plurality of ligand conformations refers to two or more than two ligand conformations.
[0035] The method and device provided in the embodiments of the present application relate to enzyme screening and can be used for enzyme screening. Specifically, enzymes are screened from a set of candidate enzymes based on molecular docking results and enzyme kinetic parameters.
[0036] It is understandable that during the microbial fermentation process, enzymes, as catalysts in microorganisms, can accelerate the rate of chemical reactions without being consumed in the reaction. However, due to the microbial fermentation environment inhibiting the activity of certain enzymes, or the insufficient activity of certain enzymes themselves, some substrates cannot be converted into products during the microbial fermentation process, resulting in insufficient fermentation. In this case, it is necessary to screen out enzymes that can replace the above-mentioned insufficiently active enzymes and fully convert the excess products into substrates.
[0037] Up to now, enzymes are divided into six categories, namely oxidoreductases, transferases, hydrolases, lyases, isomerases and ligases. Due to the wide variety of enzymes, each category is further divided into subclasses, sub-subclasses and enzyme series. For example, hydrolases (EC 3) are a large family that includes enzymes that catalyze hydrolysis reactions of various substrates, such as amylases, proteases, lipases, etc.
[0038] It should be understood that with the development of biochemistry and molecular biology, new enzymes are constantly being discovered, which means that the number of members in each class of enzymes is increasing. Therefore, how to screen out enzymes that are suitable for specific products and transformation environments from a large number of enzymes remains to be explored.
[0039] It should be noted that enzymes, as biological macromolecules, include protein enzymes and RNA molecule enzymes. In the embodiments of the present application, the object of enzyme screening is protein enzymes.
[0040] In order to solve the problem that the existing enzyme screening methods in the background technology often select enzymes based on experience, the obtained enzyme types have high similarity and the activity of the enzymes cannot be guaranteed, so that it cannot be guaranteed that the obtained enzymes can quickly convert substrates into products in the environment of microbial fermentation, and thus cannot significantly improve the efficiency of microbial fermentation, the embodiment of the present application provides an enzyme screening method and device, which screens enzymes based on the binding ability of the enzyme to the substrate and the enzyme kinetic parameters in a large range of enzyme types, and quickly screens out a variety of enzymes with low type similarity and high activity, so that the environmental adaptability of the screened multiple enzymes is strong and the upper limit of the catalytic ability is high, so as to have a higher conversion efficiency, and ensure that the screened multiple enzymes can convert more substrates into products in a short time in the environment of microbial fermentation, thereby significantly improving the efficiency of microbial fermentation.
[0041] Exemplarily, the enzyme screening method provided in the embodiment of the present invention can be performed by an electronic device with a processing function, for example, the electronic device can be a computer, a server, etc. Taking the electronic device as a computer as an example, the hardware part of the computer can include: a processor, a memory, a network interface, a user interface, a communication bus, etc.
[0042] The processor is used to control the electronic device to perform related processing and computing tasks, such as determining a set of candidate enzymes, clustering the set of candidate enzymes, and rating representative candidate enzymes. The processor may include a central processing unit (CPU) or other processors, and the processor may be single-core or multi-core, for example, the processor may include multiple CPUs.
[0043] The memory is used to store computer instructions and related data, for example, substrates, products, reaction formulas, enzyme types that convert substrates, molecular docking results, and docking root mean square deviations. The memory can be a random access memory (RAM), a read only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, or an optical memory, a disk storage medium or other magnetic storage device, or any other medium that can be used to store program codes or data that can be accessed by a computer. Optionally, the memory can be integrated in the processor, and the memory can also be independent of the processor.
[0044] The network interface is used for the computer to communicate with other devices or communication networks. The network interface can be a transceiver with transceiver functions. Optionally, the network interface can include a standard wired interface, a wireless interface (such as a WI-FI interface, a Bluetooth interface, a 5G interface).
[0045] The communication bus is used to realize the connection and communication between various components. For example, the processor, memory, network interface and user interface mentioned above can be interconnected through the communication bus.
[0046] The user interface may include a display screen and an input unit (such as a keyboard). Optionally, the user interface may also include a standard wired interface and a wireless interface.
[0047] Those skilled in the art will appreciate that the above-mentioned computer may also include more or fewer components, or a combination of certain components, or different arrangements of components, which is not limited in the embodiments of the present application.
[0048] like Figure 1 As shown, an enzyme screening method provided in the embodiments of the present application includes S101-S104.
[0049] S101. Determine a set of candidate enzymes according to substrates to be converted, products, reaction formulas for converting substrates to be converted into products, and / or enzyme categories for converting substrates to be converted into products.
[0050] In one implementation, first, based on the substrate to be converted and the product, a reaction formula for converting the substrate to be converted into the product and an enzyme category for converting the substrate to be converted into the product are obtained. Then, multiple commonly used enzymes in the above enzyme category are selected, and experiments are conducted in the conversion environment of the above substrate to be converted. The name and amino acid sequence length of the most active enzyme among the above multiple enzymes are used as search conditions, and multiple related enzymes obtained by searching through enzyme databases (such as NCBI, Uniprot, Interpro, etc.) form a candidate enzyme set.
[0051] In the above process, since there may be enzymes with repeated amino acid sequences in the enzyme database, deduplication software (such as CD-Hit) can be used to deduplicate the multiple related enzymes obtained by the search.
[0052] The data sets corresponding to the various related enzymes obtained by searching the enzyme database include information such as the ID of each enzyme in the various related enzymes, the enzyme amino acid sequence, and the source of the enzyme. Specifically, the ID of the enzyme may be accession or uniprot_id, etc., wherein accession is the ID of the enzyme in the NCBI database, and uniprot_id is the ID of the enzyme in the Uniprot database.
[0053] Optionally, the substrate to be converted, the product and the reaction formula for converting the substrate to be converted into the product can also be used as search conditions. The reaction formula for converting the substrate to be converted into the product and the enzyme type for converting the substrate to be converted into the product can also be used as search conditions, and the embodiments of the present application are not limited thereto.
[0054] In one application scenario, the substrate to be converted is lycopene, and the product is β-carotene. According to the reaction formula for converting lycopene to β-carotene, the enzyme that can convert lycopene to β-carotene is lycopene β-cyclase. Using lycopene β-cyclase as a search condition, more than 10,000 related enzymes can be retrieved from the database UniProt, and the more than 10,000 related enzymes are used as a candidate enzyme set.
[0055] It should be noted that among the enzyme information stored in the above enzyme database, only a small part of the enzymes have their data recorded in detail based on literature reports, and the information of the vast majority of the remaining enzymes is predicted by existing methods, which is not very reliable. Therefore, the enzymes retrieved based on the above enzyme database cannot be directly applied to actual scenarios, and the retrieved enzymes need to be screened, and then the enzymes with higher activity and higher conversion efficiency after screening are put into actual scenarios.
[0056] In the embodiment of the present application, after obtaining the candidate enzyme set, enzyme screening is implemented by multiple screening methods. The following describes in detail one screening process in the multiple screening through S102-S103.
[0057] S102. Clustering the candidate enzyme set.
[0058] In the embodiment of the present application, the candidate enzyme set is clustered according to the similarity of the amino acid sequence of each candidate enzyme in the candidate enzyme set.
[0059] In one implementation, the candidate enzyme set is clustered by multi-to-multi sequence search MMseqs2 to obtain multiple categories of candidate enzymes. Each category of candidate enzymes in the multiple categories of candidate enzymes includes multiple candidate enzymes and representative candidate enzymes. For example, with the similarity of the amino acid sequence being 0.3, the candidate enzyme set is clustered to obtain multiple categories of candidate enzymes.
[0060] Since MMseqs2 is a commonly used clustering analysis software for protein and nucleic acid sequence sets in the art, the clustering process thereof is not described in detail in the present embodiment.
[0061] Optionally, clustering of the candidate enzyme set may be achieved by linear clustering, cascade clustering algorithm or random selection, etc., which is not limited in the embodiments of the present application.
[0062] S103. For each representative candidate enzyme of each category of candidate enzymes in the multiple categories of candidate enzymes, the level of the representative candidate enzyme is evaluated according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzyme.
[0063] Among them, the representative candidate enzymes include the clustering centers of each type of candidate enzymes; the molecular docking results include the conformation number and the docking root mean square deviation, the conformation number is the number of ligand conformations whose docking energy is less than the docking energy threshold, and the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme is bound; the docking root mean square deviation includes the root mean square deviation between each ligand conformation and the optimal ligand conformation in the multiple ligand conformations of the representative candidate enzymes; the levels include primary candidate enzymes, secondary candidate enzymes and tertiary candidate enzymes.
[0064] Optionally, representative candidate enzymes may also be obtained by random selection or other judgment criteria, which is not limited in the embodiments of the present application.
[0065] Exemplary, combined Figure 4 ,like Figure 5 As shown, S103 includes S1031-S1033.
[0066] S1031. When the number of conformations representing the candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation representing the candidate enzyme meets the first deviation condition, and the enzyme kinetic parameters representing the candidate enzyme meet the parameter threshold, the level of the representative candidate enzyme is determined as a first-level candidate enzyme; the first deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the first deviation range is less than the first quantity threshold.
[0067] S1032. When the conformation number of the representative candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation of the representative candidate enzyme meets the second deviation condition, and the enzyme kinetic parameters of the representative candidate enzyme meet the parameter threshold, the level of the representative candidate enzyme is determined as a secondary candidate enzyme.
[0068] S1033. Otherwise, the level of the representative candidate enzyme is determined as a third-level candidate enzyme.
[0069] Optionally, in the evaluation method of the primary candidate enzyme corresponding to the above S1031, the conformation threshold is 20. The first deviation condition is: the number of ligand conformations with a maximum root mean square deviation rmsd_ub value greater than 10 among the multiple ligand conformations representing the candidate enzyme is less than or equal to 3, and the maximum root mean square deviation rmsd_ub values of the multiple ligand conformations representing the candidate enzyme are all less than or equal to 13. The enzyme kinetic parameters representing the candidate enzyme meet the parameter threshold: the enzyme kinetic parameter value is in the top 50% of the enzyme kinetic parameter values of all candidate enzymes in descending order.
[0070] In the evaluation method of the secondary candidate enzyme corresponding to the above-mentioned S1032, the second deviation condition is: the number of ligand conformations whose maximum root mean square deviation rmsd_ub value is greater than 20 among the multiple ligand conformations representing the candidate enzyme is less than or equal to 1, the number of ligand conformations whose maximum root mean square deviation rmsd_ub value is in the range of [13,20) among the multiple ligand conformations is less than or equal to 2, and the number of ligand conformations whose maximum root mean square deviation rmsd_ub value is in the range of [10,13) among the multiple ligand conformations is less than or equal to 10.
[0071] Based on the one screening process introduced in S102 - S103 , the following describes multiple screening processes in an application scenario.
[0072] In the metabolic pathway with glucose as the initial substrate and β-carotene as the final product, the substrate lycopene of CrtY (lycopene β-cyclase) accumulates in large quantities, while the yield of its product β-carotene is not high. CrtY is the bottleneck enzyme in this metabolic pathway. According to the name of the enzyme Lycopene beta-cyclase, it was searched in the database, and after deduplication and a series of operations, 1,184 amino acid sequences of CrtY remained as a candidate enzyme set.
[0073] The process of performing multiple screenings (including the first round of screening, the second round of screening and the third round of screening) on the above candidate enzyme set is as follows.
[0074] Step 1: Cluster the above candidate enzyme set with similarity A through MMseqs2 to obtain multiple categories of candidate enzymes, where each category of candidate enzymes includes multiple candidate enzymes and a representative candidate enzyme.
[0075] Optionally, the above A can be 0.3 or other values, which is not limited in the embodiments of the present application.
[0076] Step 2: Perform molecular docking on the representative candidate enzymes in each category of representative candidate enzymes, and rank all representative candidate enzymes according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzymes.
[0077] The above steps 1 to 2 correspond to the first round of screening.
[0078] Step 3: For each class of candidate enzymes with a number greater than 100, cluster them using MMseqs2 with a similarity of A=A+0.1 to obtain new multiple classes of candidate enzymes, each of which also includes multiple candidate enzymes and a new representative candidate enzyme; for each class of candidate enzymes with a number less than 100, randomly select multiple candidate enzymes as new representative candidate enzymes.
[0079] Step 4: Perform molecular docking on the new representative candidate enzymes obtained in step 3, and rate all new representative candidate enzymes according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzymes.
[0080] The above steps 3 to 4 correspond to the second round of screening.
[0081] Step 5: For each type of candidate enzyme among the multiple types of candidate enzymes, when the proportion of candidate enzymes rated as third-level candidate enzymes is greater than 0.5, the candidate enzyme of this type is eliminated.
[0082] Otherwise, for each class of candidate enzymes with a number greater than 60, clustering is performed using MMseqs2 with a similarity of A=A+0.1 to obtain new multiple classes of candidate enzymes, which also include multiple candidate enzymes and a new representative candidate enzyme. For each class of candidate enzymes with a number less than or equal to 60, multiple candidate enzymes are randomly selected as new representative candidate enzymes.
[0083] Step 7: Perform molecular docking on the representative candidate enzymes of the new multiple categories of candidate enzymes, and rate all new representative candidate enzymes according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzymes.
[0084] Step 8: Repeat steps 5 to 6 until the number of candidate enzymes in the multiple categories of candidate enzymes obtained by clustering is less than or equal to 60.
[0085] Step 9: For each type of candidate enzyme among the multiple types of candidate enzymes, when the proportion of candidate enzymes rated as third-level candidate enzymes is greater than 0.5, the candidate enzymes of this type are eliminated.
[0086] Step 10, judging the number of candidate enzymes in the multiple categories of candidate enzymes, when the number of candidate enzymes in the multiple categories of candidate enzymes is less than or equal to twice the number of clustering times, all candidate enzymes that have not been rated are used as new representative candidate enzymes; otherwise, randomly selecting multiple candidate enzymes as new representative candidate enzymes.
[0087] Step 11: molecular docking is performed on the representative candidate enzymes of the new multiple categories of candidate enzymes, and all new representative candidate enzymes are rated according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzymes.
[0088] Step 12: Repeat steps 9 to 11 until each candidate enzyme in the remaining multiple types of candidate enzymes is rated.
[0089] The above steps 5 to 12 correspond to the third round of screening.
[0090] Through the above three rounds of screening, a total of 173 candidate enzymes were molecularly docked with substrates, from which 38 CrtYs rated as first-level candidate enzymes, 55 CrtYs rated as second-level candidate enzymes, and 80 CrtYs rated as third-level candidate enzymes were screened out.
[0091] S104. Determine the screening result according to the representative candidate enzymes after evaluation.
[0092] Exemplarily, corresponding to the multiple screening processes of CrtY mentioned above, the physicochemical properties, resulting conformations and hydrogen bonds of the 38 CrtYs rated as primary candidate enzymes are predicted, and the best 8 CrtYs are screened and obtained as enzyme screening results based on the prediction results.
[0093] In one implementation, combining Figure 1 ,like Figure 2 As shown, before S103, the method further includes: S105, performing molecular docking on each representative candidate enzyme of each type of candidate enzyme in the multiple types of candidate enzymes.
[0094] Exemplary, combined Figure 2 ,like Figure 3 As shown, S105 includes S1051-S1052.
[0095] S1051. Using the boundary of the representative candidate enzyme as the binding range of the representative candidate enzyme and the substrate, molecular docking is performed on the representative candidate enzyme and the substrate to obtain multiple ligand conformations.
[0096] The ligand conformation is a geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds. The boundary of the representative candidate enzyme refers to the distance between the two farthest residues on the representative candidate enzyme. Specifically, a cube constructed with the center position of the representative candidate enzyme as the center point and the boundary of the representative candidate enzyme as the side length is the range (i.e., box) where the representative candidate enzyme binds to the substrate.
[0097] It should be understood that in the actual molecular docking process, the above-mentioned box is used to locate the active pocket (active domain on the representative candidate enzyme that can bind to the substrate) at which the substrate can bind to the representative candidate enzyme surface during the molecular docking process. Since any position on the representative candidate enzyme can bind to the substrate, the above-mentioned box should cover the entire outer surface of the representative candidate enzyme. The box set by the method of S1051 above can cover the entire outer surface of the representative candidate enzyme, thereby simulating all binding situations of the representative candidate enzyme with the substrate.
[0098] Specifically, the representative candidate enzyme is docked with the substrate by molecular docking software (such as AutoDock Vina). The pdbqt file representing the candidate enzyme and the pdbqt file of the substrate are first imported into the molecular docking software, and then the range of binding between the representative candidate enzyme and the substrate and the docking energy threshold representing the binding between the candidate enzyme and the substrate are set. The molecular docking software performs molecular docking on the representative candidate enzyme and the substrate, and outputs multiple ligand conformations whose docking energy between the representative candidate enzyme and the substrate is less than the docking energy threshold, the docking energy of each ligand conformation in the multiple ligand conformations, and the maximum root mean square deviation rmsd_ub and the minimum root mean square deviation rmsd_lb of each ligand conformation in the multiple ligand conformations.
[0099] As you can understand, pdbqt file is a commonly used file format in the field of molecular docking. It is an extended format of pdb file. pdbqt file is mainly used to store information such as atomic coordinates, partial charges, and AutoDock 4 atomic species of receptors (enzymes) and ligands (substrates) for calculation and analysis in the process of molecular docking.
[0100] The above-mentioned docking energy (Binding Energy or Docking Energy) refers to the energy released by the binding of the candidate enzyme to the substrate, and the docking energy is a negative value. The docking energy reflects the stability of the interaction between the receptor and the ligand. The lower the docking energy, the more stable the binding. For the same substrate, the posture of the substrate is different, and the energy released by the binding of the candidate enzyme to the substrate is also different. The above-mentioned molecular docking software usually calculates the docking energy representing the candidate enzyme and the substrate through a molecular mechanics model or an empirical scoring function.
[0101] The maximum root mean square deviation rmsd_ub refers to the root mean square deviation between the ligand conformation and the best ligand conformation when matching each atom in the ligand conformation with the corresponding same atom in the best ligand conformation, ignoring any symmetry. The best ligand conformation is the ligand conformation with the lowest docking energy when the candidate enzyme binds to the substrate.
[0102] The minimum root mean square deviation rmsd_lb refers to the root mean square deviation between the ligand conformation and the best ligand conformation in the process of matching each atom in the ligand conformation with the atom of the same element type and the closest position in the best ligand conformation.
[0103] S1052. The number of ligand conformations whose docking energies are less than a docking energy threshold among the multiple ligand conformations is taken as the number of conformations representing the candidate enzyme; the root mean square deviation between the docking energies of each ligand conformation among the multiple ligand conformations and the docking energy of the best ligand conformation is taken as the docking root mean square deviation representing the candidate enzyme.
[0104] In an embodiment of the present application, the number of multiple ligand conformations obtained by S1051 representing the candidate enzyme and the substrate whose docking energy is less than the docking energy threshold is taken as the number of conformations representing the candidate enzyme, and the maximum root mean square deviation rmsd_ub and the minimum root mean square deviation rmsd_lb of each ligand conformation in the multiple ligand conformations obtained by S1051 are taken as the docking root mean square deviation representing the candidate enzyme.
[0105] In another implementation, combining Figure 3 ,like Figure 4 As shown, before S103, the method further includes: S106, predicting enzyme kinetic parameters of each representative candidate enzyme of each class of candidate enzymes in the multiple classes of candidate enzymes.
[0106] The above enzyme kinetic parameters include the catalytic constant Kcat, the Michaelis constant Km and the catalytic efficiency Kcat / Km.
[0107] The above-mentioned catalytic constant Kcat refers to the number of moles of substrate converted into product per mole of enzyme active site per second. The catalytic constant Kcat can directly reflect the catalytic production capacity of the enzyme under optimal conditions (such as when the enzyme concentration is saturated). The larger the Kcat value, the faster the catalytic rate of the enzyme.
[0108] The above-mentioned catalytic constant Km refers to the concentration of the substrate when the enzymatic reaction reaches half of the maximum speed. The Michaelis constant Km reflects the affinity between the enzyme and the substrate. The smaller the Km value, the higher the affinity between the enzyme and the substrate, that is, the enzyme can achieve a higher reaction rate at a lower substrate concentration.
[0109] The above catalytic efficiency Kcat / Km combines the catalytic constant Kcat and the catalytic constant Km, and is used to compare the catalytic efficiency of different enzymes or the same enzyme catalyzing different substrates. For the same enzyme, when the Kcat / Km value is large, it means that the enzyme can catalyze the conversion of substrates into products at a faster rate at a lower substrate concentration, that is, the catalytic efficiency of the enzyme is high; on the contrary, when the Kcat / Km value is small, it means that the enzyme needs a higher substrate concentration to achieve a certain reaction rate, or the catalytic rate of the enzyme is slow, that is, the catalytic efficiency of the enzyme is low.
[0110] Therefore, the catalytic constant Kcat, the Michaelis constant Km and the catalytic efficiency Kcat / Km can reflect the catalytic ability of the representative candidate enzyme for the substrate and the activity of the candidate enzyme. The representative candidate enzyme obtained by enzyme kinetic parameter screening has higher catalytic ability and higher activity.
[0111] Specifically, the enzyme kinetic parameters of each representative candidate enzyme of each class of candidate enzymes in multiple classes of candidate enzymes can be measured by a machine learning model. Exemplarily, the UniKP model predicts the Kcat / Km value of the representative candidate enzyme through the amino acid sequence of the representative candidate enzyme, and the TurNuP model predicts the Kcat value of the representative candidate enzyme through the amino acid sequence of the representative candidate enzyme, the Smiles sequence of the substrate to be converted, and the Smiles sequence of the product, and then obtains the Km value of the representative candidate enzyme through the Kcat / Km value and the Kcat value.
[0112] The UniKP model and TurNuP model are common models in this field and will not be described here. The Smiles sequence is called Simplified Molecular Input Line Entry Specification, which is an ASCII string used to represent the structure of a chemical molecule. It can clearly express the composition and structural information of the molecule in text form.
[0113] Furthermore, the physicochemical properties of the candidate enzymes can be predicted by ExPASy, and the resulting conformation and hydrogen bond representing the binding of the candidate enzymes to the substrate can be obtained by the molecular docking software, so as to screen the enzymes in the candidate enzyme set by comprehensively considering the enzyme kinetic parameters, physicochemical properties, resulting conformation and hydrogen bond of the candidate enzymes, and obtain the enzymes with the best catalytic performance, activity and physicochemical properties. ExPASy is an online service platform that provides protein and proteomics related databases and analysis tools.
[0114] It should be noted that the embodiment of the present application does not limit the execution order of S105 and S106. S105 may be executed first and then S106, S106 may be executed first and then S105, or S105 and S106 may be executed simultaneously.
[0115] In an enzyme screening provided in an embodiment of the present application, enzymes are screened from a wide range of enzyme types based on the binding ability of the enzyme to the substrate and the enzyme kinetic parameters. While ensuring that the activity of the enzyme is high, the similarity of the types of the multiple enzymes screened is reduced, thereby improving the environmental adaptability of the multiple enzymes screened and the stability of converting substrates into products, thereby ensuring that the obtained enzymes can quickly convert substrates into products in the environment of microbial fermentation, thereby significantly improving the efficiency of microbial fermentation.
[0116] Accordingly, the present application embodiment provides an enzyme screening device, such as Figure 6 As shown, it includes a set determination module 501 , a clustering module 502 , a clustering module 503 and a screening module 504 .
[0117] The set determination module 501 is used to determine the candidate enzyme set according to the substrate to be converted, the product, the reaction formula for converting the substrate to be converted into the product, the bottleneck enzyme and / or the enzyme category for converting the substrate to be converted into the product. For example, the set determination module 501 is used to implement S101 of the above enzyme screening method.
[0118] The clustering module 502 is used to cluster the candidate enzyme set. For example, the clustering module 502 is used to implement S102 of the above enzyme screening method.
[0119] The rating module 503 is used to evaluate the level of the representative candidate enzyme for each type of candidate enzyme in the multiple types of candidate enzymes according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzyme. Among them, the representative candidate enzyme includes the cluster center of each type of candidate enzyme; the molecular docking results include the number of conformations and the docking root mean square deviation, the conformation number is the number of ligand conformations whose docking energy is less than the docking energy threshold, the docking energy is the energy released by the binding of the representative candidate enzyme to the substrate, the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds, and the representative candidate enzyme corresponds to multiple ligand conformations; the docking root mean square deviation includes the root mean square deviation between each ligand conformation and the best ligand conformation in the multiple ligand conformations of the representative candidate enzyme; the best ligand conformation is the ligand conformation with the lowest docking energy among the multiple ligand conformations. For example, the rating module 503 is used to implement S103 of the above-mentioned enzyme screening method.
[0120] The screening module 504 is used to determine the screening result according to the representative candidate enzymes after the evaluation level. For example, the screening module 504 is used to implement S104 of the above enzyme screening method.
[0121] Optionally, rating module 503 is specifically used for: when the number of conformations representing candidate enzymes is greater than or equal to the conformation threshold, the docking root mean square deviation representing candidate enzymes satisfies the first deviation condition, and the enzyme kinetic parameters representing candidate enzymes meet the parameter threshold, the level of the representative candidate enzyme is determined as a first-level candidate enzyme; the first deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the first deviation range is less than the first quantity threshold. When the number of conformations representing candidate enzymes is greater than or equal to the conformation threshold, the docking root mean square deviation representing candidate enzymes satisfies the second deviation condition, and the enzyme kinetic parameters representing candidate enzymes meet the parameter threshold, the level of the representative candidate enzyme is determined as a second-level candidate enzyme. Otherwise, the level of the representative candidate enzyme is determined as a third-level candidate enzyme. For example, rating module 503 is specifically used to implement S1031-S1033 of the above-mentioned enzyme screening method.
[0122] In one implementation, combining Figure 6 ,like Figure 7As shown, the enzyme screening device further includes a molecular docking module 505. The molecular docking module 505 is used to perform molecular docking on each representative candidate enzyme of each class of candidate enzymes in the multiple classes of candidate enzymes. For example, the molecular docking module 505 is specifically used to implement S105 of the above enzyme screening method.
[0123] Optionally, the molecular docking module 505 is specifically used to use the boundary of the representative candidate enzyme as the range of binding between the representative candidate enzyme and the substrate, and to perform molecular docking on the representative candidate enzyme and the substrate to obtain multiple ligand conformations. The number of ligand conformations whose docking energy is less than the docking energy threshold in the multiple ligand conformations is used as the number of conformations representing the candidate enzyme; the root mean square deviation between the docking energy of each ligand conformation in the multiple ligand conformations and the docking energy of the best ligand conformation is used as the docking root mean square deviation of the representative candidate enzyme. For example, the molecular docking module 505 is specifically used to implement S1051-S1052 of the above-mentioned enzyme screening method.
[0124] In another implementation, combining Figure 7 ,like Figure 8 As shown, the enzyme screening device further includes a prediction module 506. The prediction module 506 is used to predict the enzyme kinetic parameters of each representative candidate enzyme of each candidate enzyme in the multiple candidate enzymes. For example, the prediction module 506 is specifically used to implement S106 of the above enzyme screening method.
[0125] Each module of the enzyme screening device can also be used to execute other steps in the above method embodiment. All relevant contents involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.
[0126] The embodiment of the present application also provides an electronic device, including: a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device executes the method described in the above embodiment. Among them, the processor can implement the above set determination module 501, clustering module 502, rating module 503 and screening module 504; the above memory can also be used to store substrates, products, reaction formulas, enzyme categories that will transform substrates, molecular docking results, docking root mean square deviations, etc.
[0127] An embodiment of the present application further provides a computer-readable storage medium, which includes a computer program. When the computer program runs on a computer, the method described in the above embodiment is executed.
[0128] An embodiment of the present application further provides a computer program product, which includes computer program instructions. When the computer program instructions are run on a computer, the method described in the above embodiment is executed.
[0129] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.
[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. An enzyme screening method, characterized in that: include: Determine a candidate enzyme set according to a substrate to be converted, a product, a reaction formula for converting the substrate to be converted into the product, and / or an enzyme type that converts the substrate to be converted into the product; clustering the candidate enzyme set; For each representative candidate enzyme of each class of candidate enzymes in the plurality of classes of candidate enzymes, evaluating the level of the representative candidate enzyme according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzyme; Wherein, the representative candidate enzymes include the clustering center of each type of candidate enzymes; the molecular docking results include the number of conformations and the docking root mean square deviation, the number of conformations is the number of ligand conformations whose docking energy is less than the docking energy threshold, the docking energy is the energy released when the representative candidate enzyme binds to the substrate, the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds, and the representative candidate enzyme corresponds to multiple ligand conformations; the docking root mean square deviation includes the root mean square deviation between each ligand conformation and the best ligand conformation in the multiple ligand conformations of the representative candidate enzyme; the best ligand conformation is the ligand conformation with the lowest docking energy among the multiple ligand conformations; The screening results are determined based on the representative candidate enzymes after evaluation.
2. The method according to claim 1, characterized in that The step of evaluating the level of the representative candidate enzyme comprises: When the conformation number of the representative candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation of the representative candidate enzyme meets the first deviation condition, and the enzyme kinetic parameter of the representative candidate enzyme meets the parameter threshold, the level of the representative candidate enzyme is determined as a first-level candidate enzyme; the first deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the first deviation range is less than the first quantity threshold; When the number of conformations of the representative candidate enzyme is greater than or equal to the conformation threshold, the docking root mean square deviation of the representative candidate enzyme meets the second deviation condition, and the enzyme kinetic parameter of the representative candidate enzyme meets the parameter threshold, the level of the representative candidate enzyme is determined as a secondary candidate enzyme; the second deviation condition is that in the docking root mean square deviation, the number of root mean square deviations that meet the second deviation range is less than the second quantity threshold; Otherwise, the level of the representative candidate enzyme is determined as a third-level candidate enzyme.
3. The method according to claim 1 or 2, characterized in that The clustering of the candidate enzyme set comprises: The candidate enzyme set is clustered according to the similarity of the amino acid sequence of each candidate enzyme in the candidate enzyme set.
4. The method according to claim 1 or 2, characterized in that: The method further comprises: Molecular docking is performed on each representative candidate enzyme of each type of candidate enzyme in the plurality of types of candidate enzymes.
5. The method according to claim 4, characterized in that The molecular docking of each representative candidate enzyme of each type of candidate enzyme in the multiple types of candidate enzymes comprises: Taking the boundary of the representative candidate enzyme as the binding range of the representative candidate enzyme and the substrate, molecular docking is performed on the representative candidate enzyme and the substrate to obtain multiple ligand conformations; the boundary of the representative candidate enzyme is the distance between the two farthest residues on the representative candidate enzyme; The number of ligand conformations whose docking energy is less than the docking energy threshold in the multiple ligand conformations is taken as the conformation number of the representative candidate enzyme; the root mean square deviation between the docking energy of each ligand conformation in the multiple ligand conformations and the docking energy of the best ligand conformation is taken as the docking root mean square deviation of the representative candidate enzyme.
6. The method according to claim 1 or 2, characterized in that: The method further comprises: Enzyme kinetic parameters are predicted for each representative candidate enzyme of each class of candidate enzymes in the plurality of classes of candidate enzymes.
7. An enzyme screening device, characterized in that: It includes a set determination module, a clustering module, a rating module, and a screening module; The set determination module is used to determine a set of candidate enzymes according to a substrate to be converted, a product, a reaction formula for converting the substrate to be converted into the product, a bottleneck enzyme and / or an enzyme category for converting the substrate to be converted into the product; The clustering module is used to cluster the candidate enzyme set; The rating module is used to assess the level of each representative candidate enzyme of each class of candidate enzymes in the multiple classes of candidate enzymes according to the molecular docking results and enzyme kinetic parameters of the representative candidate enzyme; Wherein, the representative candidate enzymes include the clustering center of each type of candidate enzymes; the molecular docking results include the number of conformations and the docking root mean square deviation, the number of conformations is the number of ligand conformations whose docking energy is less than the docking energy threshold, the docking energy is the energy released when the representative candidate enzyme binds to the substrate, the ligand conformation is the geometric shape corresponding to the posture of the substrate when the representative candidate enzyme binds, and the representative candidate enzyme corresponds to multiple ligand conformations; the docking root mean square deviation includes the root mean square deviation between each ligand conformation and the best ligand conformation in the multiple ligand conformations of the representative candidate enzyme; the best ligand conformation is the ligand conformation with the lowest docking energy among the multiple ligand conformations; The screening module is used to determine the screening results according to the representative candidate enzymes after the evaluation level.
8. An electronic device, characterized in that: It comprises a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device executes the method as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that: The method comprises computer program instructions, which, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.
10. A computer program product, characterized in that The method comprises computer program instructions, and when the computer program instructions are executed on a computer, the computer is caused to execute the method according to any one of claims 1 to 6.