BHET hydrolase designed based on inverse folding algorithm and preparation method thereof

Abstract

The invention discloses a BHET hydrolase designed based on an inverse folding algorithm and a preparation method of the BHET hydrolase, and relates to the technical field of biology. The preparation method comprises the following steps: selecting polyester hydrolase PHL7, learning a protein crystal structure by using a deep learning algorithm Protein MPNN, carrying out three-dimensional structure modeling by using Esmfold, carrying out molecular docking on candidate protein and BHET, carrying out molecular dynamics simulation, and screening out protein which is well combined with a substrate; performing expression and purification; the invention further discloses the application of the BHET hydrolase in hydrolysis of BHET. Through the screening process, the BHET hydrolase can be simply, rapidly and efficiently screened from the candidate sequences generated in a large scale, and the source of the BHET hydrolase is expanded.

Description

Technical Field

[0001] The invention relates to the field of biotechnology, and in particular to a BHET hydrolase designed based on an inverse folding algorithm and a preparation method thereof. Background Art

[0002] Waste polyethylene terephthalate (PET) has caused pollution to the global environment. How to properly dispose of waste PET has become an important issue in the management of environmental pollution. At present, the main methods for treating PET are landfill, heat treatment and chemical recovery. The main disadvantage of heat treatment is the production of carcinogens dioxins and furans, and the main disadvantage of chemical recovery is the high working cost. These methods are not conducive to the sustainable development of the environment and economy. In addition, compared with the solution produced by chemical treatment of PET, the monomer solution obtained after enzyme-mediated depolymerization of PET is easier to filter and recycle. Therefore, biodegradable PET technology is increasingly recognized by all sectors of society. It not only has mild action conditions and relatively low energy consumption, but also the degradation products are harmless and can be recycled. Bis(2-hydroxyethyl)terephthalate (BHET) is an intermediate compound in the degradation process of PET. It competes with PET for the substrate binding site of the enzyme, thereby inhibiting the further degradation of PET. However, there are few types of BHET hydrolases that specifically hydrolyze BHET. The search for new BHET hydrolases will help further improve the degradation efficiency of PET.

[0003] Therefore, technicians in this field are committed to developing a fast, efficient and convenient BHET hydrolase with high catalytic activity and good heat resistance and a preparation method thereof, which may not only improve the efficiency of PET recycling, but also help promote the development of protein design. Summary of the invention

[0004] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is to develop a fast, efficient and convenient BHET hydrolase with high catalytic activity and good heat resistance and a preparation method thereof.

[0005] To achieve the above object, the present invention provides a novel BHET hydrolase designed based on an inverse folding algorithm, the amino acid sequence of which is shown in SEQ ID NO:1.

[0006] Furthermore, the distance between the H atom of the catalytic residue Ser and the N atom of His and the distance between the carbonyl carbon of the substrate and the O atom of the catalytic residue Ser of the novel BHET hydrolase are both less than

[0007] The present invention also provides a method for preparing a novel BHET hydrolase, comprising the following steps:

[0008] Step 1: Analyze the characteristics of enzymes with BHET hydrolysis activity through literature research, select polyester hydrolase PHL7, and obtain the protein crystal structure and corresponding amino acid sequence of the hydrolase through the PDB database;

[0009] Step 2: Use the deep learning algorithm ProteinMPNN to learn the protein crystal structure of the hydrolase obtained in step 1 and generate sequences in batches;

[0010] Step 3: Use Esmfold to perform three-dimensional structural modeling on the sequence obtained in step 2, and retain the structure with higher confidence as the candidate protein;

[0011] Step 4: Molecular docking of the candidate protein obtained in step 3 with BHET to obtain the enzyme-ligand complex structure;

[0012] Step 5: Perform molecular dynamics simulation on the composite structure obtained in step 4 to screen out proteins that bind well to the substrate;

[0013] Step 6: Express and purify the protein screened in step 5.

[0014] Furthermore, step 3 also includes retaining candidate sequences and corresponding structures whose predicted local distance difference test is greater than or equal to 85.

[0015] Furthermore, step 4 also includes globally docking the candidate protein and the BHET molecule using AMDock software, screening the candidate protein that can be docked into the correct pocket, and obtaining the enzyme-ligand complex structure of the candidate protein.

[0016] Furthermore, step 5 also includes:

[0017] Step 5.1, using Amber software, the enzyme-ligand complex structure is placed in a cubic water box constructed by the TIP3P model, and counterions are added to obtain an enzyme-protein system in the solution;

[0018] Step 5.2, performing energy minimization optimization on the enzyme-protein system in the solution obtained in step 5.1, removing obvious unreasonable factors in the system, and obtaining an energy-minimized enzyme-protein system;

[0019] Step 5.3, constraining the protein backbone atoms of the enzyme protein system with minimized energy in step 5.2, specifically: gradually raising the temperature from 0°C to 338°C to obtain the constrained enzyme protein system;

[0020] Step 5.4, performing a 1 ns pre-equilibrium kinetic simulation on the constrained enzyme-protein system obtained in step 5.3 to obtain an enzyme-protein system after pre-equilibrium kinetic simulation;

[0021] Step 5.5: The enzyme-protein system after the pre-equilibrium kinetic simulation obtained in step 5.4 is subjected to three independent isothermal kinetic simulations of 50 ns under the NPT ensemble.

[0022] Furthermore, in step 5.1, the counter ions are: Na+ and Cl-.

[0023] Furthermore, step 5.5 also includes: visualizing the enzyme protein structure change information of the enzyme protein system during the kinetic simulation process, and selecting a stable structure; a stable structure is: the distance between the catalytic residues Ser and His and the distance between the substrate and the catalytic residue Ser are both less than

[0024] Furthermore, step 6 further comprises: codon optimization of the protein screened out in step 5 through an Escherichia coli overexpression system, and then inserting the gene and the histidine tag into the NdeI / XhoI site of pET-26b(+), and introducing the plasmid into E. coli Bl21(DE3) for cell culture at 37°C; after the OD reaches 0.4-0.6, adding isopropyl thiogalactoside at a final concentration of 0.3 mM and culturing at 30°C for 5 hours, and then centrifuging to obtain a cell solution; and then lysing, eluting and concentrating the cell solution at 4°C, and finally purifying it by two steps of nickel column affinity chromatography and desalting column chromatography.

[0025] The present invention also provides application of a novel BHET hydrolase in hydrolyzing BHET.

[0026] In preferred embodiment 1 of the present invention, the design and screening process of BHET hydrolase is described in detail;

[0027] In another preferred embodiment 2 of the present invention, the expression and purification process of the designed BHET hydrolase is described in detail;

[0028] In another preferred embodiment 3 of the present invention, the expression and purification of the designed BHET hydrolase and the activity identification process of the designed BHET hydrolase are described in detail.

[0029] The beneficial technical effects of the present invention are as follows:

[0030] A new type of BHET hydrolase was designed using a deep learning algorithm, which expanded the sequence space and the source of BHET hydrolases. Molecular docking was used to quickly screen the sequences, and the screening process can quickly and efficiently screen the generated large batches of sequences and quickly and efficiently screen out BHET hydrolases.

[0031] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a comparison diagram of the tertiary structures of PHL7 of a preferred embodiment 1 of the present invention and the designed BHET hydrolase;

[0033] Figure 2 1 is a comparison of the tertiary structures of PHL7 and the designed BHET hydrolase according to a preferred embodiment 1 of the present invention; 2 is a diagram showing the amino acid comparison result of PHL7 and the designed BHET hydrolase;

[0034] Figure 3 This is a product diagram of BHET hydrolysis by BHET hydrolase A3 designed in a preferred embodiment 3 of the present invention. DETAILED DESCRIPTION

[0035] The following describes several preferred embodiments of the present invention with reference to the drawings in the specification, so that the technical content is clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned in the text.

[0036] Example 1: Design and screening of BHET hydrolases

[0037] The present invention uses the crystal structure of polyester hydrolase PHL7 as the initial structure, and uses the published ProteinMPNN inverse folding algorithm to learn protein structure and generate a large number of candidate sequences. The tertiary structure of PHL7 and the designed BHET hydrolase (A3) are compared as shown in Figure 2. Figure 1 As shown, part A represents the three-dimensional structure of the hydrolase PHL7, and part B represents the predicted structural model of A3.

[0038] Esmfold was used to model the three-dimensional structure of the candidate sequences, and the candidate sequences and corresponding structures with predicted local distance difference test (pLDDT) greater than or equal to 85 were retained. The candidate proteins and BHET molecules were docked globally using AMDock software, and the candidate proteins whose substrates could dock to the correct pockets were screened and their complex structures were obtained. The complex structure of the enzyme and substrate was placed in a cubic water box constructed by the TIP3P model using Amber software, and counterions (Na+, Cl-) were added at the same time, which was conducive to maintaining the overall electrical neutrality of the system and simulating the real enzyme protein solution environment. Then, the enzyme protein system in the solution was energy minimized and optimized to remove obvious unreasonable factors in the system. Then, the protein skeleton atoms in the system were constrained and gradually heated from 0℃ to a high temperature environment (338℃), which was conducive to maintaining the rationality of the overall structure. After that, the system was subjected to a 1ns pre-equilibrium dynamic simulation, which was conducive to the early relaxation of the structure. Finally, each system was subjected to three independent isothermal dynamic simulations of 50ns under the NPT ensemble, which was conducive to the full relaxation and optimization of the three-dimensional structure of the protein. Finally, the enzyme protein structural change information (RMSD) during the kinetic simulation was visualized, and the more stable structure was selected. The distance between the catalytic residues Ser and His and the distance between the substrate and the catalytic residue Ser were calculated, and the distances between these two distances in the simulation were selected. The results of the amino acid sequence comparison between the screened proteins and PHL7 are shown in Figure 2 shown.

[0039] Example 2: Expression and purification of the designed BHET hydrolase

[0040] The candidate protein obtained in Example 1 was codon optimized by the E. coli overexpression system, and then the gene and 6 histidine tags were inserted into the NdeI / XhoI site of pET26b, and the plasmid was introduced into E. coli Bl21 (DE3) for cell culture at 37°C. After the OD reached 0.4-0.6, isopropylthiogalactoside (IPTG) was added at a final concentration of 0.3mM and cultured at 30°C for 5 hours, and then centrifuged. The cell solution was then lysed, eluted and concentrated at 4°C, and finally the protein was obtained after two-step purification by nickel column affinity chromatography and desalting column chromatography.

[0041] Example 3: Activity identification of the designed BHET hydrolase

[0042] The protein obtained in Example 2 was reacted with BHET dissolved in dimethyl sulfoxide (DMSO) at a final concentration of 10 mM at 55°C and 1M phosphate buffer at pH 8. Samples were taken after 4 hours of incubation, and an equal volume of acetonitrile was added to stop the reaction. The substrate solution without enzyme treatment was used as a control. The reaction products were analyzed by high performance liquid chromatography (HPLC) using an Agilent 1260 Infinity II system equipped with an Agilent Poroshell 120EC-C18 column (150×4.6 mm, 4 μm) and a detection wavelength of 280 nm. The column oven was set at 30°C, with eluent A (H2O containing 0.1% [v / v] trifluoroacetic acid) and eluent B (acetonitrile) as mobile phases, and maintained at the following gradient for 20 min: 0-4 min, 5% B; 4-16 min, 5%-30% B; 16-18 min, 30% B; 18-20 min, 5% B, the flow rate was fixed at 0.7 ml / min, and the column temperature was 30°C. The product of BHET hydrolysis by the designed BHET hydrolase A3 is shown in the figure Figure 3 As shown, part A is the content of the hydrolysis product formed after incubation with BHET at 37°C for 17h; part B is the content of the hydrolysis product formed after incubation with BHET at 55°C for 3h. The ordinate is the concentration of BHET, MHET and TPA in the reaction solution after the reaction. The error bars represent the standard error of three independent experiments.

[0043] The preferred specific embodiments of the present invention are described in detail above. It should be understood that ordinary technicians in the field can make many modifications and changes based on the concept of the present invention without creative work. Therefore, all technical solutions that can be obtained by technicians in the technical field based on the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A novel BHET hydrolase designed based on an inverse folding algorithm, characterized in that: The amino acid sequence of the novel BHET hydrolase is shown in SEQ ID NO:

1.

2. The novel BHET hydrolase according to claim 1, characterized in that The distance between the H atom of the catalytic residue Ser and the N atom of His and the distance between the carbonyl carbon of the substrate and the O atom of the catalytic residue Ser of the novel BHET hydrolase are both less than 3. The method for preparing the novel BHET hydrolase according to claim 1, characterized in that: The method comprises the following steps: Step 1: Analyze the characteristics of enzymes with BHET hydrolysis activity through literature research, select polyester hydrolase PHL7, and obtain the protein crystal structure and corresponding amino acid sequence of the hydrolase through the PDB database; Step 2: Use the deep learning algorithm ProteinMPNN to learn the protein crystal structure of the hydrolase obtained in step 1 and generate sequences in batches; Step 3: Use Esmfold to perform three-dimensional structural modeling on the sequence obtained in step 2, and retain the structure with higher confidence as the candidate protein; Step 4: Molecular docking of the candidate protein obtained in step 3 with BHET to obtain the enzyme-ligand complex structure; Step 5: Perform molecular dynamics simulation on the composite structure obtained in step 4 to screen out proteins that bind well to the substrate; Step 6: Express and purify the protein screened in step 5.

4. The preparation method according to claim 3, characterized in that: The step 3 also includes retaining candidate sequences and corresponding structures whose predicted local distance difference test is greater than or equal to 85.

5. The preparation method according to claim 3, characterized in that: The step 4 also includes globally docking the candidate protein and the BHET molecule using AMDock software, screening the candidate protein that can be docked to the correct pocket, and obtaining the enzyme-ligand complex structure of the candidate protein.

6. The preparation method according to claim 3, characterized in that: The step 5 also includes: Step 5.1, placing the enzyme-ligand complex structure in a cubic water box constructed by the TIP3P model using the Amber software, and adding counter ions to obtain an enzyme-protein system in the solution; Step 5.2, performing energy minimization optimization on the enzyme-protein system in the solution obtained in step 5.1, removing obvious unreasonable factors in the system, and obtaining an energy-minimized enzyme-protein system; Step 5.3, constraining the protein backbone atoms of the enzyme protein system with minimized energy in the system 5.2 described in step 5. Specifically, gradually raising the temperature from 0° C. to 338° C. to obtain a constrained enzyme protein system; Step 5.4, performing a 1 ns pre-equilibrium kinetic simulation on the constrained enzyme-protein system obtained in step 5.3 to obtain an enzyme-protein system after pre-equilibrium kinetic simulation; Step 5.5: The enzyme-protein system after the pre-equilibrium kinetic simulation obtained in step 5.4 is subjected to three independent isothermal kinetic simulations of 50 ns under the NPT ensemble.

7. The preparation method according to claim 6, characterized in that: The counter ion in step 5.1 is: Na + and Cl - .

8. The preparation method according to claim 6, characterized in that: The step 5.5 also includes: visualizing the enzyme protein structure change information of the enzyme protein system during the kinetic simulation process, and selecting a stable structure; the stable structure is: the distance between the catalytic residues Ser and His and the distance between the substrate and the catalytic residue Ser are both less than 9. The preparation method according to claim 3, characterized in that: The step 6 also includes: codon optimization of the protein screened out in the step 5 through an Escherichia coli overexpression system, then inserting the gene and the histidine tag into the NdeI / XhoI site of the plasmid pET-26b(+), introducing the plasmid into E.coli Bl21(DE3) and culturing the cells at 37°C; after the OD reaches 0.4-0.6, adding isopropyl thiogalactoside with a final concentration of 0.3 mM and culturing at 30°C for 5 hours, and then centrifuging to obtain a cell solution; then lysing, eluting and concentrating the cell solution at 4°C, and finally purifying it by two steps of nickel column affinity chromatography and desalting column chromatography.

10. Use of the novel BHET hydrolase according to claim 1 in hydrolyzing BHET.

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