Preparation method and application of mannokinase hexaphosphate mutant
By using artificial intelligence-guided modification of mannosyl hexaphosphate mutants, the problems of low enzyme activity and poor stability have been solved, enabling efficient synthesis of mannosyl hexaphosphate, reducing production costs, and providing a new solution for drug synthesis and biotechnology applications.
Patent Information
- Application Number
- CN202511176201.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-21
- Publication Date
- 2025-12-05
AI Technical Summary
Existing enzyme catalysis systems suffer from low enzyme activity, poor stability, and insufficient substrate specificity when synthesizing mannose hexaphosphate. Traditional chemical synthesis methods are costly and require stringent conditions, making them unsuitable for large-scale production.
Using an artificial intelligence-guided approach, a protein prediction model was constructed using PyPEF software and the AAindex database to predict the mutation site combination H92L, E119R, and A138R. The mannose hexaphosphate kinase mutant was obtained through genetic modification and expressed and purified in E. coli to improve the enzyme's catalytic activity and stability.
The mutant enzyme exhibits more than 15 times increased catalytic activity and significantly improved stability, making it possible to produce mannose hexaphosphate at low cost and high efficiency, and thus has broad application prospects.
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Figure CN121065134A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the field of biotechnology, and particularly relates to a preparation method and application of a mannose-6-phosphate kinase mutant. BACKGROUND
[0002] Mannose-6-phosphate (M6P) has the molecular formula of C6H 13 O9P, which is involved in many metabolic pathways in human cells, such as gluconeogenesis, adipocyte differentiation, etc. After the folding of secreted proteins in the endoplasmic reticulum, they are transported to the Golgi apparatus, where M6P participates in the final modification of glycosylation and the marking of glycoproteins; it can also participate in the marking of intracellular lysosomal enzymes, and thus it is indirectly related to some diseases of the human body. There are reports that M6P is related to the onset of pancreatitis, and the M6P pathway can maintain the balance and function of pancreatic excretion, while the blockage of the M6P pathway can lead to the disorder of the lysosomal autophagy pathway, and thus cause the onset of pancreatitis. As a substance closely related to the environment in the living body, M6P can be used to develop its application by utilizing its diversity in participating reactions, such as phosphomannose isomerase (PMI) as an enzyme that can catalyze the isomerization of M6P to fructose-6-phosphate (F6P), which can be used as a screening system to screen whether plant transformation cells are successful. In medical applications, people have already used the feature that M6P can mark lysosomal enzymes to deliver targeted drugs for the treatment of tumors. The specific binding of M6P to the mannose-6-phosphate receptor (M6PR) can be used in the treatment of many diseases, such as tumors, varicella and herpes zoster virus, mucopolysaccharidosis, etc. M6P can also be combined with insulin growth factor II receptor (IGF2R) to treat porcine epidemic diarrhea (PED) in the livestock industry and to be applied in immunotherapy. M6PR has been proven to be related to many tumor cells, and according to this principle, mannose can be used to treat tumors. In recent years, M6P has also been valued in the field of beauty, such as improving the biomechanical properties of the skin to achieve the purpose of anti-aging and treating skin redness. Today, the application research of M6P is still a hot spot, and the numerous processes in which it is involved in the living body make its medical applications very extensive.
[0003] Traditional chemical synthesis methods usually involve complex chemical reaction steps and use expensive reagents (such as ATP) as phosphate donors. This method is costly and has harsh reaction conditions (high temperature and high pressure, etc.), which is not conducive to large-scale production. In recent years, enzyme synthesis of M6P has attracted attention due to its environmental friendliness and cost-effectiveness. Using mannose kinase to synthesize M6P can replace traditional ATP as a phosphate donor, reducing costs. However, existing enzyme catalytic systems still face challenges such as low enzyme activity, poor stability, and insufficient substrate specificity. SUMMARY
[0004] (I) Objectives of the Invention
[0005] The purpose of the present application is to provide a preparation method and application of a mannose-6-phosphate kinase mutant, to realize efficient synthesis of M6P through PPGMK modification guided by artificial intelligence, to provide the possibility for low-cost production of M6P, and to provide a new solution for drug synthesis and biotechnology application.
[0006] (II) Technical Solutions
[0007] To solve the above problems, the first aspect of the present application provides a preparation method of a mannose-6-phosphate kinase mutant, comprising:
[0008] Constructing a protein prediction model based on PyPEF software using AAindex;
[0009] Predicting a mutation site combination using the protein prediction model, and generating a mutant gene according to the predicted mutation site combination, wherein the mutation site combination comprises H92L, E119R and A138R;
[0010] Cloning the mutant gene into a pET-28a(+) expression vector and then introducing it into E. coli for expression and purification to obtain a mannose-6-phosphate kinase mutant.
[0011] Preferably, the constructing of the protein prediction model based on PyPEF software using AAindex comprises:
[0012] Obtaining PPGMK amino acid sequences from different species and performing homology analysis thereon to construct a homologous dataset;
[0013] Based on the homologous dataset, the catalytic activity of the corresponding amino acid is determined in combination with Swiss-Prot, and the physicochemical properties of the corresponding amino acid are obtained using the AAindex database;
[0014] Based on the amino acid sequence, the physicochemical properties and catalytic activity of the amino acid, a three-dimensional dataset is constructed;
[0015] Based on the three-dimensional dataset, a preset model is trained and optimized to obtain a protein prediction model, and the preset model is constructed based on PyPEF software.
[0016] Preferably, the predicting of the mutation site combination using the protein prediction model and the generating of the mutant gene according to the predicted mutation site combination comprises:
[0017] The mutation region corresponding to the protein composed of the PPGMK amino acid sequence is determined by molecular dynamics. The protein is a protein in a public database, and is a sequence of a known species directly obtained from the public database UniProt.
[0018] The PPGMK amino acid sequence is converted into a multidimensional feature vector based on AAindex parameters obtained from the AAindex database.
[0019] The multidimensional feature vector is input into the protein prediction model, and the combination of mutation sites with a predicted relative activity > 15 is screened out by the protein prediction model.
[0020] The combination of mutation sites is introduced into the PPGMK gene of wild-type E. coli by PCR method to generate a mutant gene.
[0021] Preferably, in the homology analysis, PPGMK amino acid sequences with a homology greater than 30% are integrated to construct a homology dataset.
[0022] Preferably, in constructing the three-dimensional dataset, principal component analysis is used for feature dimension reduction, and the first n principal components are selected according to the results of dimension reduction, where n > 20.
[0023] Preferably, the preset model is an amino acid sequence-enzyme activity quantitative structure-activity relationship model, and the least squares method is used to complete modeling. The "amino acid sequence-enzyme activity quantitative structure-activity relationship model" is a reasonable description of the QSAR (Quantitative Structure-Activity Relationship) model, and its core is to correlate the relationship between amino acid sequence (structure) and enzyme activity (function) through mathematical modeling.
[0024] Preferably, the training of the preset model based on the three-dimensional dataset and the optimization include:
[0025] The model parameters are optimized by 5-fold cross-validation, and the optimal number of principal components is determined.
[0026] Based on the number of principal components, the physicochemical property parameters with a contribution value > 5% to enzyme catalytic activity are screened out by a genetic algorithm to construct a protein prediction model.
[0027] Preferably, the mutation region corresponding to the protein includes 65-70 amino acid residues, preferably 68 amino acids, around the active pocket of the protein.
[0028] Another aspect of the present application provides a use of the mannose-6-phosphate kinase mutant in synthesizing mannose-6-phosphate, wherein the mannose-6-phosphate kinase mutant is prepared by any one of the methods described above.
[0029] Preferably, the reaction system used in the synthesis process comprises 5mM-500mM of mannose and 5mM-500mM of phosphate donor as substrates, and 0.1M Tris-HCl as buffer.
[0030] (III) Beneficial effects
[0031] The above technical solution of the present application has the following beneficial technical effects: In view of the problems of low enzyme activity and poor stability of mannose-6-phosphate kinase, the present application provides a preparation method and application of a mannose-6-phosphate kinase mutant, which is based on the PyPEF software to construct a protein prediction model using AAindex; the protein prediction model is used to predict the mutation site combination, and the mutant gene is generated according to the predicted mutation site combination, which includes H92L, E119R and A138R. The present application successfully constructs an enzyme mutant with improved enzyme catalytic activity and stability through the mannose-6-phosphate kinase modification guided by artificial intelligence technology. Finally, the mutant gene is cloned into the pET-28a(+) expression vector and then introduced into E. coli for expression and purification, obtaining the mannose-6-phosphate kinase mutant, and the enzyme activity of the mutant in synthesizing M6P is increased by more than 15 times compared with the wild type. The modification based on the present application not only improves the industrial properties of the enzyme, but also provides the possibility for efficient production of M6P (mannose-6-phosphate), lays the foundation for future large-scale production, and has a wide application prospect. BRIEF DESCRIPTION OF DRAWINGS
[0032] Figure 1 is a preparation method flowchart of the mannose-6-phosphate kinase mutant of the present application;
[0033] Figure 2 is a modification flowchart of the mannose-6-phosphate kinase mutant of the present application;
[0034] Figure 3 is a performance evaluation diagram of the protein prediction model of the present application;
[0035] Figure 4 is a technical route diagram of the construction and expression of the mannose-6-phosphate kinase mutant of the present application;
[0036] Figure 5 is a comparison result of SDS-PAGE of wild-type mannose-6-phosphate kinase and the mannose-6-phosphate kinase mutant of the present application;
[0037] Figure 6is the ion chromatography detection result of the wild type catalytic product;
[0038] Figure 7 is the ion chromatography detection result of the mutant catalytic product of the application;
[0039] Figure 8 is the comparative column chart of the M6P production of the wild type and the mutant catalytic product of the application. DETAILED DESCRIPTION
[0040] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be given below in combination with specific embodiments and with reference to the drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present application. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present application.
[0041] The application of artificial intelligence technology in the field of biological catalysis provides new possibilities for enzyme modification. Through machine learning and bioinformatics methods, mutations of enzymes can be predicted and designed to improve their catalytic performance and adaptability. Therefore, in view of the problems of low enzyme activity and poor stability of mannose-6-phosphate kinase, the present application provides a preparation method and application of a mannose-6-phosphate kinase mutant, as shown in Figure 1 The preparation method comprises the following steps:
[0042] S1, constructing a protein prediction model based on PyPEF software and AAindex;
[0043] S2, predicting a mutation site combination using the protein prediction model, and generating a mutant gene according to the predicted mutation site combination, wherein the mutation site combination comprises H92L, E119R and A138R;
[0044] S3, cloning the mutant gene into a pET-28a(+) expression vector and then introducing it into E. coli for expression and purification to obtain a mannose-6-phosphate kinase mutant.
[0045] The following will be described in combination with specific embodiments.
[0046] Example 1: Modification of mannose-6-phosphate kinase mutant
[0047] As shown in Figure 2 , first, a protein prediction model is constructed using PyPEF software combined with AAindex, a mutation site combination is predicted using the protein prediction model, and a mutant gene is generated according to the predicted mutation site combination, wherein the mutation site combination comprises H92L, E119R and A138R, and the specific steps include:
[0048] (1) Data collection (corresponding to Figure 2Feature engineering was employed: PPGMK amino acid sequences from different species were collected from public databases, and sequences with >30% homology were constructed using BLAST alignment. Combined with experimentally determined catalytic activity data from Swiss-Prot, physicochemical property parameters of amino acids were extracted from the AAindex database. Principal component analysis (PCA) was used to reduce the dimensionality of redundant parameters, retaining the first 20 principal components to construct a three-dimensional dataset containing sequence features, physicochemical properties, and catalytic activity, thus transforming the original data into features recognizable by the model.
[0049] (2) Model building (corresponding) Figure 2 Model Training: A machine learning framework was built using PyPEF software, and a quantitative structure-activity relationship model of amino acid sequence-enzyme activity was established using partial least squares (PLS). Model parameters were optimized through 5-fold cross-validation, and the optimal number of principal components was determined to be 12. The model achieved R on the training set. 2 The R score reached 0.932, with an RMSE of 0.47; on the independent test set, R... 2 =0.914, RMSE=0.885. A genetic algorithm was introduced for feature selection to screen out 12 key physicochemical properties that contribute more than 5% to enzyme activity, and a protein prediction model was constructed (the final prediction model, named SUEM840101).
[0050] (3) Site prediction: The crystal structure of PPGMK protein was analyzed, and molecular dynamics simulations were used to determine the location of the active pocket. The 68 amino acid residues within the range are mutation hotspots. Using a combinatorial design strategy, 2176 three-point mutation combinations were generated, and the amino acid sequences were converted into 12-dimensional feature vectors based on AAindex parameters and input into the SUEM840101 model. The top 10 combinations with predicted relative activity >15 were selected, among which the H92L / E119R / A138R combination predicted an activity of 17.507343. This combination can improve substrate binding affinity by destroying the salt bridge near the active site and forming new hydrophobic interactions. The following Examples 1-14 all use the H92L / E119R / A138R combination. In addition, except for the H92L / E119R / A138R combination, other combinations must meet the following conditions and may be considered as candidates: (1) The mutation site is located around the "active pocket". (1) Mutation hotspot region; (2) Relative activity predicted by model >15; (3) After mutation, substrate binding or catalytic efficiency is improved by changing the interaction between residues (such as salt bridge, hydrophobic interaction, hydrogen bond, etc.).
[0051] also, Figure 2 The model calibration in the model is used to back-optimize the prediction model based on experimental yield data, thereby improving the accuracy of subsequent virtual mutations.
[0052] As Figure 3 shown, the predicted values of SUEM840101 model for the activity of the test mutants are highly consistent with the experimental values (R 2 = 0.914), and all data points are distributed near the reference line y = x, indicating that the model has excellent generalization ability.
[0053] Example 2: Construction and expression of mannose-6-phosphate kinase mutants
[0054] After cloning the mutant gene into the pET-28a(+) expression vector, it was introduced into E. coli for expression and purification to obtain the mannose-6-phosphate kinase mutant. Specifically, using the wild-type PPGMK gene from E. coli as a template, Over-lap PCR technology was used to introduce H92L / E119R / A138R mutations. The mutant gene was cloned into the pET-28a(+) vector, transformed into the BL21(DE3) strain, and induced for expression by IPTG. The purity of the purified mutant was verified by SDS-PAGE to be >95%. According to the prediction results of Example 1, primers containing H92L, E119R, and A138R site mutations were designed. As Figure 4 shown, site-directed mutagenesis includes using the wild-type mannose-6-phosphate kinase encoding gene (cloned from a sequenced strain and constructed into the pET-28a vector) as a template for site-directed mutagenesis. Two pairs of primers were used in the first round of PCR to amplify two DNA fragments containing the mutation sites, with some overlapping sequences between the two fragments. In the second round of PCR, the product of the first round of PCR was used as a template, and the outer primers were used for amplification to obtain the complete mutant gene. Verification standards include sequencing the mutant gene to ensure that the mutation sites are accurate and correct.
[0055] Expression host selection includes: after the correctly sequenced mutant gene is digested by restriction enzymes NdeI and XhoI, it is ligated to the same digested pET-28a expression vector to construct the recombinant expression plasmid pET-28a-PPGMKmut. The recombinant plasmid is transformed into E. coli BL21(DE3) competent cells, and positive clones are selected by kanamycin resistance.
[0056] Purification includes: picking positive clones to inoculate into LB liquid medium containing kanamycin (50 μg / mL), 37°C shaking culture to OD600 0.6-0.8. Add IPTG to a final concentration of 0.5 mM to induce expression, 25°C induction for 12 h. After induction, centrifuge at 4°C, 8000 rpm for 10 min to collect the bacteria. Resuspend the bacteria in a buffer containing 0.1 M Tris-HCl, and perform cell disruption. Centrifuge at 4°C, 12000 rpm for 30 min, and collect the supernatant. Purify the supernatant by Ni-NTA affinity chromatography column, and perform gradient elution with elution buffer containing different concentrations of imidazole, and collect the elution peak of the target protein. Detect the purification effect by SDS-PAGE electrophoresis, as shown in Figure 5 As shown in Figs. a (mutant), b (wild type), and c (mutant after purification), the mutant can express the target protein, and high-purity product can be obtained after purification. In this application, the purity of the mutant protein after purification reaches more than 95%.
[0057] Example 3: Mutant enzyme catalyzing the synthesis of mannose hexaphosphate
[0058] In a reaction system of 0.1 M Tris-HCl buffer, 400 mM mannose, and 400 mM phosphate, mannose hexaphosphate is catalytically synthesized by 37°C shaking reaction for 8 hours. After removing impurities by centrifugation at 12000 rpm for 10 minutes, the product is quantitatively analyzed by ion chromatography, and the detection results are as shown in Figure 6 and Figure 7 As shown in Figs. a (mutant), b (wild type), and c (mutant after purification), the mutant can express the target protein, and high-purity product can be obtained after purification. In this application, the purity of the mutant protein after purification reaches more than 95%. Figure 8 As shown in Figs. a (mutant), b (wild type), and c (mutant after purification), the mutant can express the target protein, and high-purity product can be obtained after purification. In this application, the purity of the mutant protein after purification reaches more than 95%. Figure 8 is a comparison column chart of the product yield of M6P catalyzed by wild type and mutant of each embodiment. The enzyme activity U is calculated according to the following formula:
[0059]
[0060] wherein, C m6p is the concentration of M6P, ρ is the liquid density of M6P, M1 is the total mass of the system used, M2 is the mass of the enzyme, and T is the enzyme catalysis time. Figure 6 is the ion chromatography detection result of the product yield catalyzed by wild type; Figure 7 is the ion chromatography detection result of the product yield catalyzed by mutant.
[0061] Example 4: Mutant enzyme catalyzing the synthesis of mannose hexaphosphate
[0062] The mutant enzyme catalyzes the synthesis of mannose hexaphosphate in a reaction system of 0.1M Tris-HCl buffer, 50mM mannose and 200mM phosphate, and the product is quantitatively analyzed by ion chromatography after removing impurities by centrifugation at 12000rpm for 10 minutes. The experimental results show that the activity of the mutant enzyme is 2.50U, which is 1.77 times higher than that of the wild-type enzyme (1.41U); and the corresponding product yield is 13.84g / L (mutant) and 8.57g / L (wild-type), respectively, and the synthesis ability is increased by 1.61 times.
[0063] Example 5: Mutant enzyme catalyzes the synthesis of mannose hexaphosphate
[0064] The mutant enzyme catalyzes the synthesis of mannose hexaphosphate in a reaction system of 0.1M Tris-HCl buffer, 15mM mannose and 25mM phosphate, and the product is quantitatively analyzed by ion chromatography after removing impurities by centrifugation at 12000rpm for 10 minutes. The experimental results show that the activity of the mutant enzyme is 1.27U, which is 2.76 times higher than that of the wild-type enzyme (0.46U); and the corresponding product yield is 4.01g / L (mutant) and 1.57g / L (wild-type), respectively, and the synthesis ability is increased by 2.55 times.
[0065] Example 6: Mutant enzyme catalyzes the synthesis of mannose hexaphosphate
[0066] The mutant enzyme catalyzes the synthesis of mannose hexaphosphate in a reaction system of 0.1M Tris-HCl buffer, 88mM mannose and 92mM phosphate, and the product is quantitatively analyzed by ion chromatography after removing impurities by centrifugation at 12000rpm for 10 minutes. The experimental results show that the activity of the mutant enzyme is 4.74U, which is 5.71 times higher than that of the wild-type enzyme (0.83U); and the corresponding product yield is 22.33g / L (mutant) and 12.17g / L (wild-type), respectively, and the synthesis ability is increased by 1.83 times.
[0067] Example 7: Mutant enzyme catalyzes the synthesis of mannose hexaphosphate
[0068] The mutant enzyme catalyzes the synthesis of mannose hexaphosphate in a reaction system of 0.1M Tris-HCl buffer, 110mM mannose and 105mM phosphate, and the product is quantitatively analyzed by ion chromatography after removing impurities by centrifugation at 12000rpm for 10 minutes. The experimental results show that the activity of the mutant enzyme is 5.10U, which is 4.72 times higher than that of the wild-type enzyme (1.08U); and the corresponding product yield is 29.87g / L (mutant) and 11.64g / L (wild-type), respectively, and the synthesis ability is increased by 2.57 times.
[0069] Example 8: Mutant enzyme catalyzed synthesis of mannose hexakisphosphate
[0070] In the reaction system of 0.1M Tris-HCl buffer, 45mM mannose and 55mM phosphate, mannose hexakisphosphate was catalytically synthesized by oscillation reaction at 37℃ for 2 hours. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 2.4U, which was 2.79 times higher than that of the wild-type enzyme (0.86U); the corresponding product yields were 11.31g / L (mutant) and 7.79g / L (wild-type), respectively, and the synthesis ability was increased by 1.45 times.
[0071] Example 9: Mutant enzyme catalyzed synthesis of mannose hexakisphosphate
[0072] In the reaction system of 0.1M Tris-HCl buffer, 18mM mannose and 165mM phosphate, mannose hexakisphosphate was catalytically synthesized by oscillation reaction at 37℃ for 1 hour. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 0.68U, which was 4.25 times higher than that of the wild-type enzyme (0.16U); the corresponding product yields were 4.39g / L (mutant) and 1.21g / L (wild-type), respectively, and the synthesis ability was increased by 3.57 times.
[0073] Example 10: Mutant enzyme catalyzed synthesis of mannose hexakisphosphate
[0074] In the reaction system of 0.1M Tris-HCl buffer, 170mM mannose and 22mM phosphate, mannose hexakisphosphate was catalytically synthesized by oscillation reaction at 37℃ for 1 hour. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 0.83U, which was 3.60 times higher than that of the wild-type enzyme (0.23U); the corresponding product yields were 5.54g / L (mutant) and 2.01g / L (wild-type), respectively, and the synthesis ability was increased by 2.75 times.
[0075] Example 11: Mutant enzyme catalyzed synthesis of mannose hexakisphosphate
[0076] In the reaction system of 0.1M Tris-HCl buffer, 260mM mannose and 378mM phosphate, the mutant enzyme catalyzed the synthesis of mannose hexaphosphate by oscillating reaction at 37°C for 6 hours. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 6.42U, which was 4.62 times higher than that of the wild-type enzyme (1.39U); the corresponding product yield was 43.31g / L (mutant) and 18.26g / L (wild-type), respectively, and the synthesis ability was improved by 2.37 times.
[0077] Example 12: Mutant enzyme catalyzed synthesis of mannose hexaphosphate
[0078] In the reaction system of 0.1M Tris-HCl buffer, 450mM mannose and 300mM phosphate, the mutant enzyme catalyzed the synthesis of mannose hexaphosphate by oscillating reaction at 37°C for 8 hours. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 11.31U, which was 7.85 times higher than that of the wild-type enzyme (1.44U); the corresponding product yield was 80.12g / L (mutant) and 25.47g / L (wild-type), respectively, and the synthesis ability was improved by 3.15 times.
[0079] Example 13: Mutant enzyme catalyzed synthesis of mannose hexaphosphate
[0080] In the reaction system of 0.1M Tris-HCl buffer, 400mM mannose and 500mM phosphate, the mutant enzyme catalyzed the synthesis of mannose hexaphosphate by oscillating reaction at 37°C for 8 hours. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 20.50U, which was 13.31 times higher than that of the wild-type enzyme (1.54U); the corresponding product yield was 109.33g / L (mutant) and 31.45g / L (wild-type), respectively, and the synthesis ability was improved by 3.48 times.
[0081] Example 14: Mutant enzyme catalyzed synthesis of mannose hexaphosphate
[0082] In the reaction system of 0.1M Tris-HCl buffer, 120mM mannose and 180mM phosphate, the mutant enzyme catalyzed the synthesis of mannose hexaphosphate by oscillating reaction at 37°C for 4 hours. After removing impurities by centrifugation at 12000rpm for 10 minutes, the product was quantitatively analyzed by ion chromatography. The experimental results showed that the activity of the mutant enzyme was 5.36U, which was 5.15 times higher than that of the wild-type enzyme (1.04U); the corresponding product yield was 29.68g / L (mutant) and 13.44g / L (wild-type), respectively, and the synthesis ability was improved by 2.21 times.
[0083] The H92L / E119R / A138R combination in the present application can significantly improve enzyme activity (>15 times, corresponding to Example 3), which is mainly due to the optimization of the "structure-function" relationship of the enzyme molecule, and the principle is as follows:
[0084] (1) Destroying the unfavorable salt bridge to release the flexibility of the active center
[0085] The original residues H92 (histidine, positively charged) and E119 (glutamic acid, negatively charged) may form an "unnecessary salt bridge" near the active center. This strong electrostatic interaction may limit the conformational change of the active center, hindering the entry of the substrate or the release of the product. After mutation, H92→L (leucine, hydrophobic and not charged), E119→R (arginine, positively charged): the original salt bridge is destroyed, the spatial restriction of the active center is removed, and the conformational flexibility is increased, which is more easily adapted to the substrate.
[0086] (2) Forming new hydrophobic interactions to enhance the binding affinity of the substrate
[0087] A138→R (arginine, positively charged and longer side chain) may form a new electrostatic attraction with the substrate (such as mannose hexaphosphate, containing polar groups such as phosphate groups), or form a hydrophobic interaction network with surrounding residues. The enhancement of hydrophobic interaction can stabilize the binding conformation of the substrate-enzyme complex, reduce the binding free energy, and improve the enzyme's ability to capture the substrate (i.e., reduce the Km value), thereby accelerating the reaction under the same substrate concentration.
[0088] (3) Synergistic optimization of the catalytic microenvironment
[0089] The synergistic effect of three-site mutation may: adjust the spatial arrangement of key residues in the active center, so that the catalytic groups (such as nucleophilic groups, proton donors / acceptors) are closer to the substrate reaction site; change the charge distribution or hydrophobicity of the active pocket, and match the physicochemical properties (such as polarity, charge) of the substrate, further improving the catalytic efficiency.
[0090] The present application relates to a method for improving the activity of mannose-6-phosphate kinase under the guidance of artificial intelligence, and a method for synthesizing mannose-6-phosphate using the improved enzyme. A model is constructed using AAindex by PyPEF. A more accurate model is obtained by PLS regression. The model is SUEM840101. The possible three-site combination is predicted using the obtained model, and the relative activity of H92L / E119R / A138R is predicted to be 17.507343. It has potential research value. According to the prediction results, a PPGMK mutant with improved catalytic activity is designed and constructed, which overcomes the problems of low enzyme activity and poor stability, and the enzyme activity for synthesizing M6P is increased by more than 15 times compared with the wild type.
[0091] It should be understood that the foregoing detailed description of the application, rather than limiting the application, is intended to explain and describe the current implementation of the application. Therefore, any modification, equivalent replacement or improvement made without departing from the spirit and scope of the application should be included in the protection scope of the application. In addition, the appended claims of the application are intended to cover all changes and modifications falling within the scope and boundary of the appended claims, or the equivalent form of such scope and boundary.
Claims
1. A method for producing a mutant of mannose-6-phosphate kinase, characterized by, The application relates to a method for preparing a mutant of a hexokinase, and belongs to the technical field of bioengineering. The method comprises the following steps: a protein prediction model is constructed based on a PyPEF software and AAindex; a mutant site combination is predicted by using the protein prediction model, and a mutant gene is generated according to the predicted mutant site combination, wherein the mutant site combination comprises H92L, E119R and A138R; 2. The method of preparing a mutant of mannose-6-phosphate kinase according to claim 1, wherein the mutant gene is cloned into a pET-28a(+) expression vector and then introduced into E. coli to be expressed and purified, so that a hexokinase mutant is obtained. The method for constructing the protein prediction model based on the PyPEF software and the AAindex comprises the following steps: PPGMK amino acid sequences of different species are obtained and homology analysis is performed to construct a homologous data set; based on the homologous data set, catalytic activity of corresponding amino acids is determined in combination with Swiss-Prot, and physicochemical properties of the corresponding amino acids are obtained from an AAindex database; a three-dimensional data set is constructed based on the amino acid sequences, the physicochemical properties of the amino acids and the catalytic activity; 3. The method of producing a mutant of mannose-6-phosphate kinase according to claim 1, wherein a preset model is trained and optimized based on the three-dimensional data set to obtain the protein prediction model, wherein the preset model is constructed based on the PyPEF software. The method for predicting the mutant site combination by using the protein prediction model and generating the mutant gene according to the predicted mutant site combination comprises the following steps: a mutation region corresponding to a protein is determined by combining molecular dynamics, wherein the protein is composed of a PPGMK amino acid sequence; the PPGMK amino acid sequence is converted into a multi-dimensional feature vector based on AAindex parameters, wherein the AAindex parameters are obtained from the AAindex database; the multi-dimensional feature vector is input into the protein prediction model, and a mutant site combination with a predicted relative activity > 15 is screened out by the protein prediction model; 4. The method of preparing a mutant of mannose-6-phosphate kinase according to claim 2, wherein a mutant gene is generated by introducing the mutant site combination into a PPGMK gene of a wild-type E. coli by a PCR method.
5. The method of preparing a mutant of mannose-6-phosphate kinase according to claim 2, wherein In the homology analysis, PPGMK amino acid sequences with homology greater than 30% are integrated to construct the homologous data set.
6. The method of preparing a mutant of mannose-6-phosphate kinase according to claim 2, wherein In the construction of the three-dimensional data set, principal component analysis is performed for feature dimension reduction, and the first n principal components are selected according to the result of the dimension reduction, wherein n > 20.
7. The method for preparing the mannosyl hexaphosphate kinase mutant according to claim 2, characterized in that, The preset model is an amino acid sequence-enzyme activity quantitative structure-activity relationship model, and the least square method is used to complete modeling. The method for training the preset model based on the three-dimensional data set and optimizing the preset model to obtain the protein prediction model comprises the following steps: model parameters are optimized by 5-fold cross validation, and an optimal principal component number is determined; 8. The method for preparing the mannosyl hexaphosphate kinase mutant according to claim 1, characterized in that, The mutated region of the protein corresponds to 65 to 70 amino acid residues around the active pocket of the protein. the range of 65 to 70 amino acid residues.
9. Use of a mutant of mannose-6-phosphate kinase in the synthesis of mannose-6-phosphate, characterized in that, based on the principal component number, physicochemical property parameters with a contribution degree value to enzyme catalytic activity > 5% are screened out by a genetic algorithm to construct the protein prediction model.
10. Use of a mutant mannose-6-phosphate kinase according to claim 9 for the synthesis of mannose-6-phosphate, characterized in that, The hexokinase mutant is prepared by the method in any one of claims 1-8. In the synthesis process, a reaction system adopted comprises 5mM-500mM mannose and 5mM-500mM phosphate donor as substrates, and 0.1M Tris-HCl as a buffer.