In all aspects of the design of PLAnet Zero, we worked closely with subject matter experts, and multiple waste management groups and had the opportunity to discuss our project with the people we are attempting to assist with PLAnet Zero.

First Iteration (Pure Enzymes)

Over the course of the project, we went through multiple iterations of what the project could be. Firstly, we used literature inspiration to design and build a working construct. We tested this using colourmetric assys and learnt that it was active. The key insight we brought PLAnet Zero from a good piece of lab work to a field test-ready device was that in the learn phase we were diligent in getting critical feedback from our collaborators and stakeholders.

Second Iteration (Surface-Exposed Catalysts)

It was thanks to their input that the second design of the PLAnet Zero design included surface expression to make our product compatible with existing infrastructure. We built our second interaction with the use of the standard biological part BBa_K2302003 a secretion signal lpp-OmpA. This allowed us to be confident that our new design would have the intended behaviour. After successfully testing the expression of the new system we moved to assay-based testing. We learned that the system does have the desired esterase activity against model compounds.

At this point, we are happy to report that the design from the second round of iterations is ready for field trials. We acknowledge that a laboratory cuvette is a much more controlled environment than a compost heap. As projects approach deployment the tests themselves need to go through a DBLT cycle!

Third Iteration (Surface Exposed Catalysts + ncAA)

While we are currently working on field tests for the second iteration we decided that it would be a great time to begin parallelizing the project. Reasoning that improvement to the base protein should correspond to improvement to the surface exposed proteins as well. The design process we engaged in is fully detailed below.


The modelling team aimed to characterize the protein-ligand interactions between our plastic-degrading esterase enzymes of interest and a variety of ligands: polylactic acid (PLA) polymers of various sizes, as well as p-nitrophenyl butyrate (pNOB), p–nitrophenyl propanoate (pNOP), and p-nitrophenyl octanoate (NPO). We performed in silico genetic code engineering on both MGS0156 and Thermoanaerobacter thermohydrosulfuricus lipase (TTL) by substituting all methionine residues with either norleucine or methoxinine, which are non-canonical amino acids (ncAAs).

We used computational tools to determine how the ncAA variants affected the binding affinity of the MGS0156 and TTL enzymes towards a variety of ester substrates, to determine how changing the hydrophobicity or hydrophilicity of these enzymes affected their catalytic efficiency in degrading PLA and polyethylene terephthalate (PET) plastics.

Incorporation of non-canonical amino acids was explored due to experimental evidence that a substitution of all methionine residues in TTL to norleucine improved the catalytic activity by approximately 50%.[2] We determined the binding affinity of a variety of ligands with the plastic-degrading proteins of interest by performing a molecular docking simulation. The ligands all contained ester bonds; some were used as experimental substrates for determining Michaelis-Menten kinetics (NPO, pNOB), but PLA polymers of various sizes were also used as ligands to better imitate PLA composting conditions.

Figure 1. General workflow for modelling protein-ligand interactions and determining binding affinity.


First, we obtained the PDB files for our plastic-degrading enzymes (MGS0156 and TTL) from the RCSB Protein Data Bank. We used the experimentally-determined crystal structures for both MGS0156 (PDB ID: 5D8M) and Thermoanaerobacter thermohydrosulfuricus lipase (PDB ID: 7Q4J). Then, we used PyMOL to create the variants by substituting all methionine residues in both wild-type protein structures with non-canonical amino acids (norleucine and methoxinine).

  • For TTL, we performed a methionine to norleucine substitution (TTL [Nle])
  • For MGS0156, we performed both a methionine to norleucine substitution (MGS0156 [Nle]) and a methionine to methoxinine substitution (MGS0156 [Mox])

Then, we prepared the PDB files for docking by removing water and other ligand molecules using PyMOL, and converting the files from .pdb to .pdbqt format using AutoDockTools. All substrates used in the docking experiment were generated using Avogadro software and used the universal force field for energy minimization with the steepest descent algorithm.

The protein-ligand docking simulation was done using the Autodock Vina scoring function on the PyRX software. Autodock Vina performs rigid body docking, which requires less computational power but limits the flexibility of the protein and ligand.[3] AutoDock Vina provided the nine most stable conformations of the ligand in the active site, as well as their binding affinities.

A 3D model of the protein-ligand interaction was made using PyMOL, and one ligand conformation was selected for further characterization of the protein-ligand interaction (Figure 2). The ligand conformation was decided based on the distance between the hydroxyl group of the serine residue in the catalytic triad and the carbonyl carbon of the ligand, as the nucleophilic attack of the ester bond by the Ser residue is the first step in the esterase reaction mechanism. RMSD was also considered in determining the ideal ligand conformation. Lastly, the protein-ligand complex was uploaded to LigPlot+, which created a 2D image of the protein-ligand interactions and identified which residues had hydrophobic interactions or hydrogen bonds with the ligand.

Figure 2. Sample figure of interaction between catalytic triad of MGS0156 [Nle] and PLA dimer. The MGS0156 residues are depicted in green, and the ligand (PLA dimer) is depicted in cyan. The measured distances (yellow dashed lines) depict key steps in ester bond hydrolysis mechanism in the degradation of PLA.


Our first experiment was mutating all methionines in the TTL enzyme to norleucine. This experiment was inspired by a 2022 study by Haernvall et al.[2], in which they mutated Met→Nle mutation in TTL and found the incorporation of norleucine increased the catalytic activity of TTL by 50%.[2] PLA has a hydrophobic surface, so we substituted the 10 methionine residues in TTL with norleucine, which removes the thiol group of the methionine residues and makes the residues more hydrophobic and less vulnerable to oxidation (Figure 3). In doing so, we aimed to make the active site more hydrophobic to accommodate PLA.

Figure 3. The substitution of methionine residues of TTL with norleucine using PyMOL.


Binding affinity results indicate that the incorporation of norleucine into TTL improved the binding affinity of the ligands (NPO and pNOB) to the TTL active site. A lower (more negative) value for binding affinity indicates stronger binding, so the ligands were more tightly bound in the TTL [Nle] variant than TTL [wt].

The residues involved in the substrate binding were identified using LigPlot+. Green dashed lines indicate atoms that are involved in the hydrogen bond interaction, where hydrophobic interaction between residues was indicated as red dashed lines. The Met142 residue in TTL [wt] is not involved in the substrate binding to both NPO and pNOB (Figure 5), where the Nle142 residue in TTL [Nle] was identified to involve in hydrophobic interaction with both substrates (Figure 6). This in silico analysis of the protein-ligand interaction matched with the finding in the literature. [1] This result gives us a preliminary insight on Met142Nle can potentially increase the binding affinity, or decrease the Km value of the Michaelis Menten parameter, and hence improve the overall enzyme specificity toward the substrates.

Figure 4. Binding affinity of wild-type TTL and the TTL norleucine variant docked with the ligands NPO and pNOB using AutoDock Vina. The desired outcome is a more negative binding affinity, since it indicates stronger interactions between protein and ligand.


Figure 5. 2D representation of the protein-ligand binding of TTL [wt] with NPO and pNOB.


Figure 6. 2D representation of the protein-ligand binding of TTL [Nle] with NPO and pNOB.


MGS0156 is an α/β hydrolase enzyme that hydrolyzes the ester bond of PLA and other various plastics and breaks down the PLA polymer to monomers or shorter oligomers. It has a highly hydrophobic active site to accommodate the hydrophobic PLA dimer and it has maximum activity at 35-40°C.[1] According to experiments of MGS0156 activity using polycaprolactone as a substrate, MGS0156 has stronger binding affinity to longer oligomers, and it is believed that an oligomer only binds to MGS0156 once, where it is then cleaved into shorter oligomers one-by-one.[1] By modifying methionine residues to either more or less hydrophobic ncAAs, we wanted to see how changing the hydrophobicity of the enzyme would affect the binding affinity of various ligands.

As we had promising results in the substitution of methionine with norleucine in TTL, we performed the same substitution on MGS0156 (Figure 7). By removing the thiol functional group, the incorporation of norleucine makes the enzyme more hydrophobic and less vulnerable to oxidation. We also created a variant with all methionine residues substituted with methoxinine. By eliminating the thiol group and introducing a more electronegative hydroxyl group, we wanted to observe the effect of increasing the hydrophilicity of the enzyme on its catalytic efficiency and binding affinity.

Figure 7. 2D The substitution of methionine residues with either norleucine or methoxinine residues in MGS0156.


Figure 8. 2D Binding affinity (from AutoDock Vina) of wild-type MGS0156 and the norleucine variant docked with NPO, pNOB, and pNOP as ligands.


The binding affinity data obtained from AutoDock Vina indicated that the Met → Nle substitution did not significantly change the binding affinity of the NPO, pNOB, and pNOP ligands (Figure 8). The improvement in binding affinity observed in the TTL simulation does not hold for the MGS0156 enzyme when docked with NPO, pNOB, and pNOP.

Figure 9. Binding affinity (from AutoDock Vina) of wild-type MGS0156 and the norleucine variant docked with PLA dimer, pentamer, and dodecamer.


The MGS0156 [Nle] variant had worse binding affinity than wild-type MGS0156 when docked with a PLA dimer. However, the binding affinities of the PLA pentamer and dodecamer are improved in the MGS0156 [Nle] variant when compared to the wild-type (Figure 9). Since the MGS0156 norleucine variant only improved binding affinity in the larger PLA polymers, it’s possible that the incorporation of norleucine improved the hydrophobicity of the enzyme and allowed the active site to better accommodate a larger, more hydrophobic PLA polymer. Since the use of larger PLA polymers are similar to PLA composting conditions, the MGS0156 [Nle] variant may improve enzymatic degradation of PLA in compost.

Figure 10. 2D representation of protein-ligand interaction of MGS0156 [wt] and MGS0156 [Nle] with NPO and pNOB, generated by LigPlot+. Solid purple lines indicate ligand structure. Solid orange lines indicate hydrogen bonding residues, and green dashed lines indicate hydrogen bonds. Red dashed lines indicate hydrophobic interactions.


The conformation of the substrate differs significantly between MGS0156 [wt] and MGS0156 [Nle], and different residues participate in substrate binding between the MGS0156 variants. All MGS0156 protein-ligand interactions between all variants and ligands tested are all generally different in ligand conformation and the residues involved. So, the changes in binding affinity observed between the MGS0156 [wt] and MGS0156 [Nle] variant are likely due to general structural changes in the protein that may change the characteristics of the active site.

In Figure 10, there are no methionine or norleucine residues in the active site that interact directly with the ligand. This is true for all MGS0156-substrate interactions, with one exception (Figure 11).

Figure 11. A 2D representation of the interaction between a PLA pentamer and wild-type MGS0156, and the MGS0156 norleucine variant. Solid purple lines indicate ligand structure. Solid orange lines indicate hydrogen bonding residues, and green dashed lines indicate hydrogen bonds. Red dashed lines indicate hydrophobic interactions.


In addition to significantly different ligand binding conformation and residues involved, the MGS0156 [Nle] variant contains a methionine residue that has been substituted with norleucine (Met378 → Nle378), but this methionine residue is absent from the protein-ligand interaction between MGS0156 [wt] and the PLA pentamer. This is the only MGS0156 interaction tested that involved a methionine/norleucine residue in the active site, and it is also the transformation that caused the largest observed improvement in binding affinity. The MGS0156 [wt] docked with PLA pentamer has a computationally-determined binding affinity of -5.6kcal/mol, whereas the MGS0156 [Nle] variant docked with PLA pentamer has a binding affinity of -6.5kcal/mol, suggesting the presence of norleucine in the active site significantly increased the binding strength of MGS0156. This improvement in MGS0156 is similar to the significant improvement in binding affinity observed by the incorporation of norleucine into TTL, and suggests that engineering PLA-degrading enzymes to contain norleucine in their active site may greatly improve binding affinity and catalytic efficiency, and therefore increase the rate of PLA decomposition.

We converted all methionine to methoxinine to make the enzyme more hydrophilic. To prove the principle that increasing hydrophobicity of methionine residues can increase the binding affinity toward hydrophobic substrate, methoxinine with the similar electronic properties to methionine but more hydrophilic is expected to have the opposite effect as norleucine. Methoxinine has a similar structure to methionine, however the oxygen atom of methoxinine is more electronegative than the sulfur of methionine. Similar to norleucine, methoxinine is also oxidation resistant.

A ligand docking simulation with the MGS0156 methoxinine mutant was performed, using NPO, pNOB, and a PLA dimer as the ligand. The findings were contradictory; while the methoxinine mutant had significantly improved the binding affinity of both pNOB and NPO when compared to both the norleucine mutant and wild-type MGS0156, the incorporation of methoxinine worsened the binding affinity of the PLA dimer.

Figure 11. Binding affinity (from AutoDock Vina) of wild-type MGS0156 and the methoxinine variant docked with NPO, pNOB, pNOP, and the native substrates PLA dimer, pentamer, and dodecamer.


The incorporation of methoxinine into the MGS0156 enzyme improves the binding affinity of the NPO, pNOB, and pNOP ligands (Figure 12). And, similar to the MGS0156 [Nle] variant, the MGS0156 [Mox] variant had improved the binding affinity of the PLA pentamer and dodecamer, but the PLA dimer had weaker binding when compared to the binding affinities of wild-type MGS0156.

We postulated that the incorporation of norleucine would increase the hydrophobicity of the enzyme, and therefore allow better binding of hydrophobic PLA to the active site. This was true for larger PLA polymers (pentamer, dodecamer), but not for the other, smaller ligands tested (NPO, pNOB, pNOP, and PLA dimer). So, we tested the more hydrophilic methoxinine variant to determine whether improved binding affinity of PLA polymers to MGS0156 [Nle] was due to increased enzyme hydrophobicity or some other cause. MGS0156 [Mox] had improved binding affinity for all ligands (except the PLA dimer) compared to the wild-type and the MGS0156 [Nle] variant. Therefore, increasing the hydrophobicity of MGS0156 may not be an effective strategy for significantly improving the catalytic efficiency of MGS0156. Or, perhaps a greater increase in hydrophobicity is required to improve MGS0156. We do not know the mechanism by which incorporation of methoxinine into MGS0156 improves the binding affinity, but it warrants further exploration.

The residues of MGS0156 (wild-type and the ncAA variants) that participated in either hydrogen bonding or hydrophobic interactions with the various ligands were determined by LigPlot+ and recorded. This was done for MGS0156 [wt], as well as the ncAA variants MGS0156 [Nle] and MGS0156 [Mox] with all 6 ligands (NPO, pNOB, pNOP, PLA dimer, PLA pentamer, and PLA dodecamer), so the highest possible occurrence of any MGS0156 residue is 18.

Table 1. This table shows the MGS0156 residues that participate in the most protein-ligand interactions, according to LigPlot+. Residues are listed in descending order according to their frequency of participation in protein-ligand interactions, both hydrogen bonds and hydrophobic interactions. Data was taken from LigPlot+ 2D representation of protein-ligand interactions for MGS0156 [wt], MGS0156 [Nle], and MGS0156 [Mox] for all 6 ligands (NPO, pNOB, pNOP, PLA dimer, PLA pentamer, and PLA dodecamer), so the frequency is the total incidences of residue participating in protein-ligand interaction out of all 18 MGS0156 docking simulations. (* indicates residues of MGS0156 catalytic triad)


There were 33 MGS0156 residues total that participated in substrate binding in the various simulations, but the 20 most frequent were recorded in Table 1. The residues that frequently interacted with the ligands could be potential mutagenesis targets for further experiments, both in silico and in the wet lab (Table 1). What is evident from the LigPlot+ data is the high incidence of leucine residues interacting with the ligands. 7 out of the top 11 residues that most frequently interact with the ligands are leucine residues. The high frequency of leucine residues likely contributes to the hydrophobicity of the enzyme, and therefore they should not be altered in mutagenesis experiments. Instead, the other residues listed could be altered to find a sequence that increases the binding affinity and catalytic activity of MGS0156

Build & Test

For our build process we adaopted the selective pressure incorporation (SPI) technique to incorporate the ncAAs. The procedure is listed in detail in at the end of the results page. We chose this method as it allows you to globally replace a selected amino acid without further DNA constructs or gene manipulation (provided you have the correct auxotrophy). As we had methionine auxotrophic E.coli this build method allows for a convinient build process.

For testing we decided to use enzymatic assays as it is a controlled system as should be sufficient for testing out if we did in fact improve the enzymes.


From the testing we learned that ncAA are in fact a valid stratagy for improving the substrate affinity of our catalysts. Unfortunately, it appears they bind too tightly and the catalytic turnover is dramatically decreased. We will attempt to test to ncAA modified enzymes using bulk plastic assays to see if the increased affinity is more favourable when dealing with bulk materials.

If this is not the case we will use ncAAs that show a more moderate increase in hydrophobicity or investigate different amino acids located further from the active site. Hopefully, this will surve to guide the substrate to the active site, rather than locking it it.

As of writing we are currently considering three test system in increasing order of complexity. Colourmetric assys < bulk plastic test < compost field tests. Unfortunately, we cannot share what we have learned from the other tests yet, but we are already looking towards the next design cycle.


  1. Feng, S.; Yue, Y.; Chen, J.; Zhou, J.; Li, Y.; Zhang, Q. (2020). Biodegradation mechanism of polycaprolactone by a novel esterase MGS0156: a QM/MM approach. Environ Sci Process Impacts, 22(12), 2332-2344.

  2. Haernvall, K.; Fladischer, P.; Schoeffmann, H.; Zitzenbacher, S.; Pavkov-Keller, T.; Gruber, K.; Schick, M.; Yamamoto, M.; Kuenkel, A.; Ribitsch, D.; Guebitz, G. M.; Wiltschi, B. (2022). Residue-Specific Incorporation of the Non-Canonical Amino Acid Norleucine Improves Lipase Activity on Synthetic Polyesters. Front Bioeng Biotechnol, 10.

  3. Hernández-Santoyo, A.; Tenorio-Barajas, A.Y.; Altuzar, V.; Vivanco-Cid, H.; Mendoza-Barrera, C. (2013). Protein-protein and protein-ligand docking. Protein Eng Technol Appl, 63-81.