Team:TJUSLS China/Design
Overview
Based on literature materials, we learned five methods to improve the thermostability of enzymes, salt bridges, hydrogen bonds, hydrophilic interaction, prolines, and disulfide bonds.
However, in most cases the positive mutant library may not cooperate to reach the target results owing to the universality of epistatic effects, the robustness of protein structure remains high uncertainty in practical engineering.
To solve this problem, we tried to find out unstable regions in PETase by reading literature as well as doing structural analysis and visual screening via the software pymol and some web tools.
After operating thousands of rational designs by combinations of residue mutations in these unstable regions, we have obtained many successful mutant models whose thermostabilities are predicted and proved by the software foldX.
Then, we test and verify their real stability and enzymatic activity through practical experiments.
Issues
Polyethylene terephthalate (PET) has become one of the most widely used artificial synthetic plastics in the industry for its excellent durability and convenient processing performance. However, with its extensive utilization and low recovery rate, it has brought serious ecological damage. In industrial applications, a higher degradation temperature can improve the chain mobility and accessibility of the ester bond of highly crystalline PET. But the high temperature degradation of the physical side will cause significant energy loss, and will bring pollution to the environment. Using enzymatic hydrolysis can avoid energy loss and environmental pollution. Because of the mildness of the enzyme action, it is denatured and inactivated at high temperatures. Therefore, improving the thermal stability of the PET degrading enzyme (IsPETase ) is the key to improving the biodegradation efficiency.
Solutions
Rational design
Develop 5 methods to improve the thermostability of PETaseSalt bridges and hydrogen bonding enhance the stability of enzymes by forming new ion bonds or hydrogen bonds, increasing the intercellular force.
By replacing hydrophilic residues with hydrophobic residue, the enzyme structure becomes tighter, thus improving the stability of enzymes.
By mutating some of the residues in the loop into prolines, the rigidity of the loop is reinforced, and then the thermostability of the enzyme is strengthened.
Thermostability of the enzyme is improved by means of mutating certain residues into cysteines to form disulfide bonds - covalent bonds with extremely strong force.
We tried to find out unstable regions in PETase by reading literature as well as doing structural analysis and visual screening via the software pymol including 3103 helix, paralleled β-sheet, big loop near the face, loose N-terminal and untightening hydrophobic core.
We performed thousands of rational combinations of mutations on residues in these unstable regions.
Through thousands of attempts, we obtained more than 600 protein mutants. Such as, by forming hydrogen bonds Q119D makes α2 more stable, by forming salt bridges T77E makes β2-β3 loop more stable and N114R makes β4- α2 loop more stable, by forming T-type pi-interaction S54W reduces the flexibility of β1.
Thermostability prediction via foldX
Since we have designed too many mutants, it is very difficult to verify all of them in a short period of time, so we must find a way to help us initially screen. Based on literature FoldX shows a good performence in most of studies compared to other algorithms, so we selected FoldX to initially screen. The software package FoldX includes different subroutines e.g. RepairPDB, BuildModel, PrintNetworks, AnalyseComplex, stability and so on. For example the repair function of FoldX reduces the energy content of a protein structure model to a minimum by rearranging side chains and the function BuildModel introduces mutations and optimizes,the structure of the new protein variant. The energy function of FoldX is able to calculate the energy difference in accurate manner between the wildtype and a variant of the protein.
The core function of FoldX, the empirical forcefield algorithm, is based on free energy (ΔG) terms aiming to calculate the change of ΔG in kcal/mol. This equation includes terms for polar and hydrophobic desolvation or hydrogen bond energy ΔGwb of a protein interacting with solvent and within the protein chain. Increased protein rigidity works against entropy and consequently,results in entropy costs.Furthermore the energy algorithm also addresses the free energy change at protein interfaces of oligomeric proteins. This term is mainly ΔGkon which calculates the electrostatic contribution of interactions at interfaces. The parameters which are important for the energy calculation were determined in laboratory experiments, e.g. for amino acid residues and explored on protein chains. Beside this distinct parameters the letters of the total energy equation, a to l, represent the weights of separate terms. The algorithm works with optimal accuracy when the hypothetical unfolding energy difference of the hypothetical energy from a wild-type variant is determined in comparison to a mutated protein.
Furthermore, FoldX shows very good performance with respect to calculation time even on single core computers. it can be used with a graphical user interface as plugin tool in YASARA.
Results
We finally ontained 587 mutants and selected 26 best mutants for next experimental verification.
Experimental verification
Issues
The reliability of the prediction results of bioinformatics tools cannot reach 100%, so we need other methods to further verify.
Solutions
We can purify these protein mutants and carry out experiments to determine of enzymatic activity and melting temperature (TM) of these protein enzymes.
To generate mutants
1.Circuit construction
We use Overlap PCR to construct these mutants’genes, and then comstruct them into the peT-21a(+) vector.
2.Protein expression
We use Ecoli.BL21 to express our protein mutants, because it contains less proteinase. Finally 7 mutants expressed successfully and 19 mutants formed inclusion bodies.
Issues
Inclusion bodies cannot founction as enzymes,we should find methods to make them express successfully.
Solutions
Add tags to help disslove
We have added different tags in the genetic circuits,constructed 57 circuits including GST, MBP, and SUMO, because they are soluble and they can help inclusion bodies disslove successfully.
Optimize the expression conditions
By optimizing the expression conditions of the protein, the protein can be folded more easily. For example, by lowering the expression temperature of the protein, its expression speed can be slowed down, giving it more time to fold successfully.
Results
All protein mutants express successfully
Protein purification
We used affinity chromatography of glutathione transferase, immobilized metal ion affinity chromatography and Gel filtration to purify our protein mutants.
Enzyme thermostability determination
To test the thermostability of our Improved Parts, first, we need to set up a reaction system as shown in the Fig.14. All enzyme reactions were performed in duplicate in 1.5 mL microcentrifuge tubes with a piece of PET Flack, 4.2mg enzyme and reaction buffer at the Optimum pH of PETase, and then were heated from 40°C to 80°C to test it’s thermostability. We used HPLC to analyze the reaction mixture and got the HPLC chromatogram of products as shown in Fig.14.
In the reaction system, the first cut of the polyester chain could produce two chains, one with TPA-terminal and another with HE- terminal. The second cut of the two different chains could produce TPA and MHET respectively, and both produced one chain with HE-terminal. The 3rd cut of the two HE-terminal chains produced MHET and chains with HE-terminal, and so on. MHET is the main reaction product, so, its concentration could show enzyme performance at certain temperature, namely thermostability. Accordingly, we used HPLC to measure the main reaction product---MHET, to assay its thermostability. We got its HPLC Peak Area by Integration, and then figured out its concentration. Using this method, we tested our mutants.
We heated up from 40 degree centigrade to 80 degree to verify the thermal stability of mutants. In conclusion, the thermostability of Super1 to Super 7 has greatly improved compared with WT(wild type PETase). Among them, Super 5 shows the best performance, the released product of which was increased by 163 times. The tolerance temperature of Super5 is increased from 40℃（wild type）to 65 ℃ .
