Esterification reaction lipase screening method based on covalent bond docking

Abstract

The invention discloses an esterification reaction lipase screening method based on covalent bond docking, and belongs to the technical field of protein docking simulation. According to the method, parameters of an acylase intermediate are constructed, and then covalent docking and energy screening are performed on the acylase intermediate, so that prediction of lipase reaction activity and substrate selectivity is realized, and the defects that carbonyl carbon cannot be automatically identified, Ser-C covalent bonds cannot be established, double bonds / bond angles cannot be managed, and the reaction efficiency is low in traditional docking are overcome. The problems that in a covalent system, simulation of a nucleophilic attack path lacks a unified distance, angle and dihedral angle constraint system, and automatic and high-throughput screening of multiple lipases and multiple substrates is difficult to achieve are solved.

Claims

1. A method for high-throughput screening of lipases involved in esterification reactions based on covalent bond docking, characterized in that, Including the following steps: (1) Enzyme structure pretreatment and setting of Ser residue parameters for activity Download the PDB file of the lipase to be screened from the database, extract chain A from the PDB file and remove the heteroatoms, save the clean PDB file and obtain the number of active serine residues; Download the standard serine parameter file from the Rosetta database, modify its geometric parameters and change the residue name to SRX to obtain the SRX parameter file; (2) Generation of acyl donor conformation and acylation enzyme intermediate parameter files Create substrate SIMILES files and generate SDF files. Use the Rosetta script molfile_to_params.py to process the SDF files and generate substrate params parameter files and PDB files. Open the PDB file of a single conformation using PyMOL, find the ordinal number of the carbonyl carbon atom and the atomic number of the atom bonded to the carbonyl carbon, add the virtual atom V1, the link bond between the carbonyl carbon and the virtual atom, and add the geometric parameters to the substrate parameter file to obtain the substrate parameter file. (3) Formation of non-covalent complexes between enzyme and substrate Using pymol, the clean PDB file of the lipase to be screened obtained in (1) and the single conformation PDB file obtained in (2) were extracted and saved as a complex PDB file. The active residue SER in the complex PDB file was renamed to SRX to obtain the target PDB file for covalent docking. (4) Simulated covalent docking Using the number of active serine residues obtained in step (1), the spatial coordinates of the OG atom covalently docked to the residue are found; Replace the residue name in the corresponding RESIDUE_SELECTORS section of the docking template .xml file with the substrate name; replace the corresponding spatial coordinate value in the Coordinates section of the docking template .xml file with the spatial coordinate of the OG atom, and the resulting file is the docking control file; Based on the docking control file, Rosetta is used to perform covalent docking simulation prediction between the enzyme and the substrate, outputting low-energy conformations and obtaining the total score of the covalent docking conformation. The smaller the total score, the easier the covalent binding is to occur, that is, the stronger the lipase catalytic activity.

2. The method according to claim 1, characterized in that, In step (1), the database is rcsb pdb.

3. The method according to claim 1, characterized in that, In step (1), you can use pymol or pdb-tools to extract chain A from the PDB file of the lipase to be screened, delete heteroatoms (ligands, water), and save it as a clean PDB file.

4. The method according to claim 1, characterized in that, The geometric parameters in step (1) include bond length d and angle. θ 1. Dihedral angle φ 1.

5. The method according to claim 1, characterized in that, The geometric parameters in step (2) include bond length d and angle. θ 1. Angle θ 2. Angle θ 3 and dihedral φ 1.

6. The method according to claim 1, characterized in that, In step (4), the number of low-energy conformations is ≥50.

7. The application of the method according to any one of claims 1 to 6 in screening enzymes and substrates.

8. A lipase esterification reaction prediction system, characterized in that, It includes modules for enzyme structure and active site residue geometry constraints, ligand conformation and tetrahedral geometry constraints, enzyme and substrate complexes, covalent docking, and covalent docking score ranking visualization. The enzyme structure and active site residue geometry constraint module functions as follows: Download the PDB file of the lipase to be screened from the database, extract chain A from the PDB file and remove the heteroatoms, save the clean PDB file and obtain the number of active serine residues; Download the standard serine parameter file from the Rosetta database, modify its geometric parameters and change the residue name to SRX to obtain the SRX parameter file; The ligand conformation and tetrahedral geometry constraint module functions as follows: Create substrate SIMILES files and generate SDF files. Use the Rosetta script molfile_to_params.py to process the SDF files and generate substrate params parameter files and PDB files. Open the PDB file of a single conformation using PyMOL, find the ordinal number of the carbonyl carbon atom and the atomic number of the atom bonded to the carbonyl carbon, add the virtual atom V1, the link bond between the carbonyl carbon and the virtual atom, and add the geometric parameters to the substrate parameter file to obtain the substrate parameter file. Enzyme and substrate non-covalent complex module The clean PDB file of the lipase and the PDB file of the single conformation substrate were extracted using pymol and saved as a complex PDB file. The active residue SER in the complex PDB file was renamed to SRX to obtain the target PDB file for covalent docking. The covalent docking module has the following functions: The number of active serine residues was obtained by processing the enzyme structure and active site residue geometry constraint module, and the spatial coordinates of the OG atom covalently docked to this residue were found. Replace the residue name in the corresponding RESIDUE_SELECTORS section of the docking template .xml file with the substrate name; replace the corresponding spatial coordinate value in the Coordinates section of the docking template .xml file with the spatial coordinate of the OG atom, and the resulting file is the docking control file; Rosetta was used to perform covalent docking simulations and predictions between enzymes and substrates based on docking control files. The covalent docking score ranking visualization module has the following functions: A chart is generated based on the total score of the covalent docking conformation. The smaller the total score, the easier the covalent bonding is to occur, which means the stronger the lipase catalytic activity.

9. A method for enzyme-catalyzing the conversion of vinyl acetylacetonate, vinyl butyrylate, or vinyl octanoate to the corresponding butyl ester, characterized in that, Use lipases with amino acid sequences as shown in SEQ ID NO.1~4.

10. The application of lipases with amino acid sequences as shown in SEQ ID NO. 1~4 in the preparation of ethyl acetylacetonate, vinyl butyrylate or vinyl octanoate into the corresponding butyl ester products.

Images