Part:BBa_K4905006
Elastin-Like Polypeptide Triblock with Leucine Zippers
Sequence and Features
Molecular weight: 105.1 kDa
Codon optimized for E.coli BL21 cells.
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Information
This part is made up of the basic parts: Leucine zipper Z1 (BBa_K4905004), Leucine zipper Z2 (BBa_K4905005), and two times Elastin-Like Polypeptide (ELP) sequence A[60]I[60] (BBa_K4905001]). This results in the sequence Z1-I[60]-A[120]-I[60]-Z2. With A[5] the sequence (VPGAG[3]VPGGG[2]).
This construct was used by the TU Eindhoven 2023 team to form a hydrogel outside as well as inside E.coli BL21 cells. The goal of this was to stop bacteria from dividing, however many more applications can be thought of for this part. Inspiration for this part was taken from Gradišar et al.[1] where they used Leucine zippers form heterodimers. We wanted to use these zippers in a similar way that Fernández‐Colino et al.[2] used leucine zippers together with Elastin-Like Polypeptides (ELPs) to form a reversible, injectable hydrogel. Furthermore, we noticed that Contreras-Llano et al.[3] were able to form a hydrogel inside of cells, however not with a protein based approach. We wanted to combine these ideas and form a protein based-hydrogel inside of E.coli and use these bacteria for therapeutic applications. However, with the hydrogel itfels, many more applications can be thought of so we wanted to characterize it as well as possible so that other teams can make use of it in the future too. Below you can read more about the experiments we did to characterize this part and about the molecular dynamics simulations that we did.
A schematic overview of what the part looks like is shown in figure 1. It is also easy to ligate other pieces of sequences together to make different constructs, with either different lengths of ELPs, different amino acids or other gBlocks at their end.
Figure 1 | Schematic overview of the sequence of this construct. (VPGAG[3]VPGGG[2]) is from now on referred to as A[5] and VPGIG will be referred to as I.
General applications
ELPs are protein polymers derived from human tropoelastin. One of their key features is that they exhibit a phase separation that is often reversible whereby samples remain soluble below their transition temperature (Tt) but form coacervates above Tt[4]. They have many possible applications in purification, sensing, activation, and nano assembly. Furthermore, they are non-immunogenic, substrates for proteolytic biodegradation, and can be decorated with pharmacologically active peptides, proteins, and small molecules. Recombinant synthesis additionally allows precise control over ELP architecture and molecular weight, resulting in protein polymers with uniform physicochemical properties suited to the design of multifunctional biologics. As such, ELPs have been employed for various uses including as anti-cancer agents, ocular drug delivery vehicles, and protein trafficking modulators[4].
Currently ELPs are also being explored in the formation of hydrogels. Their reversible behaviour is suitable for injectable hydrogels for example[2]. We think this is a part that can have many applications inside as well as outside of cells and we hope that me other iGEM teams will make use of it in the future.
Construct design
The construct consists of ELPs and two different leucine zippers that have affinity for each other. In general, ELPs have hydrophilic and hydrophobic domains that exhibit reversible phase separation behavior that is temperature-dependent. They are made from a repeating VPGXG sequence, with X replaced by specific amino acids. This results in specific properties of the ELPs, especially related to the Tt at which the ELPs will interact with each other on the hydrophobic sites[2]. When the temperature is below Tt, the water molecules surrounding the hydrophobic parts will go into the bulk water phase which gains the solvent entropy. This makes it possible to form interactions with other ELP molecules[3].
As shown in figure 2, this construct has a hydrophilic region in the middle (A[120]) and a hydrophobic region on each side of it (I[60]). On the ends the leucine zippers Z1 and Z2 are located for stronger interactions between the ELPs. Leucine zippers consist of a repeating unit that forms an alpha helix. Two leucine zippers together form ion pairs between the helices, which causes association[4]. These stronger and reversible interactions make them useful in the formation of a hydrogel at a specific Tt. In the end, the hydrogel is formed with electrostatic and hydrophobic interactions between the ELPs.
Figure 2 | Schematic representation of the composite part, an ELP with leucine zippers on the ends. It has a triblock ELP sequence that can form a thermoresponsive hydrogel.
As soon as the hydrogel is made inside E.coli BL21 cells, the cells are prevented from dividing. However, the cells remain functional. So they can still be used to express therapeutic agents, like Interleukin 10 in the TU Eindhoven 2023 teams project.
Results
Protein expression and purification
This part was expressed in BL2 E.coli. The full plasmid that the DNa was cloned into can be seen below in figure 3. To check its expression we ran an SDS-PAGE gel of which the results can be seen in figure 4. The bands on the gel showed up where we expected, so this means that protein expression was succesfull.
Figure 3 | Full plasmid containing the sequence for this part in a pET24(+) vector that was transformed into E.coli BL21 cells for protein expression. Figure 4 | SDS page gel run with this part. The band can be seen at the expected weight of 105.1 kDa.
All gels were formed by resuspending the ELPs in MilliQ (MQ) water at different w/v%. The leucine zipper-containing ELPs were expected to instantaneously form a gel upon increasing the temperature above Tt, as has also been reported in the literature[5].
We saw that for the constructs containing the leucine zippers, there formed a viscous fluid upon dissolving the ELPs. Subsequently, after warming the solution to room temperature, it became very turbid and a gel started to form. This is supported by the images below in figure 5.
The construct containing Z1-A120-Z2 formed a gel at 5% and 10% (w/v%) as described above. Upon cooling the gel down to 4°C again, the gel remained intact. As a control, Z2-A120-Z2 that had non-complementary leucine zippers was also dissolved to form solutions of 5% and 10% (w/v%). This construct too, was able to form a gel instantly upon heating to RT. However, in contrast to the leucine zipper-ELPs, the gel disassembled again when the solution was cooled to 4°C. This indicates that the latter of the two constructs shows reversibility, which is expected when the ELPs are brought below their Tt, while the former construct does not show this reversibility.
Characterization
Hydrogel formation
Transition temperature determination with UV-Vis
As mentioned before, the transition temperature of the hydrogel is influenced by the amino acids that are used in the ELP, furthermore we expected that the leucine zippers would strengthen the interaction between the peptides and cause a lower transition temperature. The transition temperatures of our constructs Z1-A120-Z2 and, as a control to see the transition temperature without the effect of leucine zippers, Z2-A120-Z2 were determined with the use of UV-visible spectroscopy. Solutions of 5 and 20 μM were made in MQ water. Absorbances were measured at 350 nm. Tts were determined to be around 23.5°C and 21°C for both constructs, respectively. This is remarkable, since the expectation was that the construct containing Z1 and Z2, two leucine zippers that are be able to dimerize, would have a lower Tt, with the reasoning that the interaction of these domains would cause the ELPs to become insoluble sooner. However, it is possible that the Leucine zippers already bring the hydrophobic domains in a different conformation which causes the transition temperature to actually become higher.
Absorbances were also measured upon cooling the solution back down to find out whether the interaction was reversible. Once the solution goes below Tt, the absorbances of returned back to base levels, indicating that the ELPs can be reversibly precipitated and resuspended again. Furthermore, the spectra below look identical, which further confirms that the interactions are all reversible.
Dye release from hydrogel
To determine the relative ability for diffusion of small molecules through our hydrogels, we made gels at different percentages containing the fluorescent dye rhodamine B. In the future, apart from dyes, it could also be interesting to look at drug diffusion out of the hydrogel. First, a calibration curve was made to determine at which concentration rhodamine B should be added to the gel. Figure 8 shows a linear relationship up to 26 μM of Rhodamine B, with equation: y = 2*106x + 963.16 (R² = 0.993). We decided to make the gels with a Rhodamine B concentration of 104 μM, since the amount of dye diffusing out of the gels would be significantly lower than this amount. The gels were made at a volume of 100 μL. They were then brought to room temperature (RT) and washed with 1.5 mL of warm MQ. Then, 1 mL of warm MQ was pipetted on top of the gels, and they were incubated up to 8 hours at RT, with samples of 100 μL being taken every 2 hours. After measuring the fluorescence intensity, the values were corrected for the reduction in volume upon taking the samples.
The hydrogel consisting with a w/v% of 10% shows a linear relationship between fluorescence intensity over time between t=0 and t=8, with a linear equation of: y = 3310.8x + 5222.4. Therefore the diffusion rate, as calculated from the calibration curve, is 3.7*10-3 mg/mL/h. The 5% gel shows a faster diffusion rate , which appears to be non-linear between t=0 and t=8. This can be attributed to the fact that the supernatant on top of the gel came close to being saturated, which is likely also the case for the 10% gel, but at a later timepoint. These results can be seen in figure 9 below.
The faster diffusion rate of the 5% gel is in line with our hypothesis that a lower weight percentage gel is able to release small molecules faster than a 10% gel. Since Rhodamine B is a much smaller molecule than a cytokine like IL-10, it would be interesting to see how the diffusion of such a larger molecule would be affected by our gels. The weight percentage of the gel might therefore not only affect the division rate of the bacteria, but it can also play a role in the release rate of the therapeutic.
CCK8
Cell counting kit 8 (CCK8) is an assay which is commonly used to determine the number of alive cells in a sample. The kit uses a highly water-soluble tetrazolium salt, WST-8, which produces a formazan dye upon reduction in the presence of an electron mediator. The amount of the formazan generated by dehydrogenases is directly in proportion to the number of living cells. Yang et al. (2021) have demonstrated that this assay is also suitable for the detection of living E.coli [6].
We used this assay to test whether our hydrogelated cells would be more resistant to several conditions, including incubation with ampicillin, H2O2, and freeze-drying. Ampicillin prevents the synthesis of the bacterium’s cell wall. It does this by binding to enzymes necessary for the formation of the cell wall [7]. Our hypothesis is that if our hydrogel prevents the bacteria from dividing, they should be affected less by the presence of this antibiotic, and therefore show a higher survival rate than for bacteria which do not contain the hydrogel.
We also wanted to test whether our bacteria would have a higher survival rate when exposed to oxidizing conditions, since inflammatory bowel disease (IBD) is known to cause oxidative stress in the gut [8,9].
Lastly, since the concept of our treatment is to put them in a capsule which can be orally administered, the bacteria need to be able to survive freeze-drying, so that they can produce the therapeutic locally when they are reconstituted in the GI tract.
Ampicillin resistance
Three different conditions were tested over a period of time. In one sample, the ELPs without any crosslinker (A120) were expressed and samples were taken at 12h, 20h and 36h of protein expression. This same procedure was followed for the other sample, in which the ELPs including the leucine zippers were expressed (Z1-A120-Z2). As a control, a culture of bacteria was also made in which no proteins were expressed (Figure 10). Before incubation, all samples started at a baseline of OD600 = 0.5. They were then either incubated with ampicillin (1 mg/mL) or without for 1h at 37°C.
E.coli where no protein expression was induced, and which were treated with ampicillin, showed at most a conversion of 0.71% ± 0.05% compared to cells which were not treated. E.coli where expression of A120 was induced, resulted in a maximum conversion of 6.80% ± 0.17% after 36h of protein expression. This is likely due to the fact that this construct is also able to form a gel, although less strong compared to the Z1-A120-Z2 construct, leading to an attenuation in cell division. Finally, Z1-A120-Z2 was expressed for the three timepoints. A significant increase was observed in the conversion of substrate, most notably after 20h of expression (20.86% ± 4.14%). We had expected to see a higher percentage after 36h of expression, since at this timepoint, more bacteria should be gelated and thus unable to divide. That being said, The standard deviation of the samples is quite high, with this small number of measurements, it is hard to say whether the values would be similar given a larger sample size. Other explanations could be that some of the cells were over-gelated, which might have led to a premature death unrelated to the incubation with ampicillin. Additionally, cell death could also have occurred due to nutrients in the culturing medium running out.
For comparison, OD600 of all samples was also measured after incubation with or without ampicillin. When the samples were incubated with ampicillin, they all decreased in OD600. The samples incubated without ampicillin in which ELPs were expressed show a relatively stable OD600 compared to the sample in which no expression was induced. This was the only sample in which a significant increase in OD600 could be observed.
The OD600 was also measured over time for each of the three samples. After 20h of expression, these were diluted to OD = 0.1 and then measured every 30 minutes. From the graph, it becomes clear that when no expression of ELPs was induced, the bacteria divided more rapidly then when expression was induced. This can be seen in figure 11. These findings are in line with the results from the ampicillin treatment. It seems that the presence of the ELPs does not altogether inhibit division, but it does slow it down, which seems to be the reason why they are killed slower upon addition of ampicillin. That being said, it is hard to draw a conclusion as to whether the attenuation of bacterial division is driven by the formation of a gel inside the cytosol, or simply because of the crowded environment inside the cell, caused by the presence of a high amount of protein. Therefore, additional controls could be added, like samples in which a mono or diblock ELP is expressed, in order to account for molecular crowding.
These results were compared to the classic colony counting method. From each sample, a diltion of 105 was made and then plated out on an LB-agar plate. The plates were incubated at 37°C overnight. Images of the plates were taken (Figure 12) and the number of colonies was counted using the colony counter tool from ImageJ. The results of which are summarized in Table 1 As expected, the wild-type E.coli treated with ampicillin did not form any colonies, whereas untreated bacteria formed several hundreds of colonies. Samples containing A120 and Z1-A120-Z2 both showed a significantly smaller amount of colonies.
| No expression | A120 | Z1-A120-Z2 | ||||
|---|---|---|---|---|---|---|
| Amp | No Amp | Amp | No Amp | Amp | No Amp | |
| 12h | 0 | 614 | 0 | 4 | 2 | 16 |
| 20h | 0 | 597 | 0 | 166 | 21 | 242 |
| 36h | 0 | 1610 | 35 | 169 | 142 | 297 |
Microscopy (FRAP)
Characterization of our gelated cells with the use of microscopy required us to design a model protein which could interact with the hydrogel, and which we could visualize under the microscope. We decided to use VPGIG[60]-mNeonGreen, since the hydrophobic ELP part of the protein is able to make hydrophobic interactions with the gel. We cloned the gene fragment into a pBad vector under the control of an arabinose promotor, to allow for orthogonality between this vector and the pET24a(+) vector encoding the zipper-ELP construct. Success of cloning was verified by a double digestion of the plasmids as well as sequencing.
However, to our surprise, the sequencing results indicated that instead of a VGPIG[60] fragment, the mNeonGreen was attached to a VPGAG[3]VPGGG[2][12] fragment, which is hydrophilic, relative to the VPGIG[60] fragment. This is likely due to a labeling mistake by a previous user of the plasmid. Due to a lack of time, we decided to continue using this construct in our microscopy experiments as a model protein to monitor the diffusion of proteins within the gelated bacteria.
Z1-A120-Z2 and [A3G2][12]-mNeonGreen were co-expressed in E.coli BL21(DE3). SDS-PAGE was then used to confirm the presence of both proteins. After some trial and error using different conditions for the co-expression, we managed to express both the ELPs, as well as the fluorescent protein.
The bacteria containing Z1-A120-Z2 and [A3G2][12]-mNeonGreen were then used to determine if diffusion throughout the cell was affected by the formation of the gel. This was done by using Fluorescence recovery after photobleaching (FRAP). We hypothesized that once the gel is formed intracellularly, the diffusion rate is negatively affected due to an increase of viscosity of the cytosol. Figure 15 shows two samples before and after photobleaching. Following bleach of E.coli which co-expressed Z1-A120-Z2 and and [A3G2][12]-mNeonGreen, a gradual recovery of fluorescence could be observed up to 30 seconds post-bleach (Fig. 15A, Fig. 16A). The control, containing only [A3G2][12]-mNeonGreen, showed a virtually instantaneous recovery, as evidenced by Fig 15B, Fig 16B.
The data was fitted with the following equation: y = a∗(1-exp(-t/τ))+c (4) Where A is the mobile fraction, t is time and τ is the time constant. This was done for each of the measurements, resulting in four graphs for the co-expressed sample and two graphs for the control. Using the equations, the recovery half-life (τ1/2) was calculated for each data set which is summarized in Table 2 below.
| Measurement | τ1/2 (s) |
|---|---|
| 1 | 11.89 |
| 3 | 7.08 |
| 4 | 10.87 |
| 5 | 8.43 |
| Average | 9.57+/-1.91 |
Freeze-drying
Since our ML-I Biolab did not contain a freeze-drying setup, we had to make one ourselves. We did this in one of the fumehoods in the biolab and we attempted to freeze-dry six different types of sample (Table 3). Three for each of the different conditions also tested previously (no expression, A120 and Z1-A120-Z2) and these .same three, but with 100 mM threhalose added. This is a sugar which protects the bacterial membrane during freeze-drying [10], and was therefore meant to be used in the samples for a positive control. However, even after running the setup for over 8h, some samples did not sublimate unfortunately. And since this setup required us to refill the cold trap with liquid nitrogen every couple of hours, we could not leave it overnight. Therefore, only two of the samples, Wt and Z1-A120-Z2, were dried relatively well. These were then reconstituted and subseqeuntly assayed using CCK8. Using the calibration curve made for this assay, the OD600 values were calculated from the measured OD450 values. These were then divided by 0.5, the original OD600 at which the samples were made, to obtain the final survival rate of the bacteria.
| Sample | Success? |
|---|---|
| No expression | Yes |
| No expression + 100 mM trehalose | No |
| A120 | No |
| A120 + 100 mM trehalose | No |
| Z1-A120-Z2 | Yes |
| Z1-A120-Z2 + 100 mM trehalose | No |
Molecular Dynamics simulation
Introduction
Molecular dynamics (MD) simulations are commonly used to see how proteins or other molecules move over time. This can contribute to the understanding of molecular systems, which cannot be seen with the eye or even with the best microscopes. There are many different software packages available that can be used for MD simulations, each one with its own advantages and limitations. However, they are all based on the same principle: calculating the force between all atoms in the system with their known positions. At every time step, the positions and velocities are updated to form a trajectory of the atoms. This timestep is in the range of a few femtoseconds (10-15 s), which is needed to keep the system numerically stable. On molecule scale, this can show how proteins fold to reduce the energy in the system, or how proteins interact with each other [4] .
In our application of forming a hydrogel with Elastin-Like Polypeptides (ELPs), it can be useful to see how the ELPs will behave at different temperatures. Above a certain transition temperature (Tt), there is a disruption in the thermal energy of the water molecules around the ELPs, which causes the water molecules to move away from the ELPs. This makes room for interactions between the ELPs. It has been found that there will be conformational changes in another ELP sequence when the temperature rises above Tt, which makes them more ordered and increases the hydrophobicity [5] .
It is interesting to see how this applies to our own ELP. This will help us to understand the mechanism behind the hydrogel formation and to see what it actually looks like. We will analyze different properties of the proteins, like the secondary structure formation, compactness, and the surface area that is accessible for the solvent, to see how the conformation differs at specific temperatures below and above the Tt.
Methods
MD simulations are typically computationally expensive. This made it necessary to shorten our ELP sequence to make the computational time manageable. We chose to shorten the hydrophobic parts to I[10] instead of I[60] and to shorten the hydrophilic part to A[50] instead of A[120] or A[100], as shown in Figure 1. The leucine zippers stay the same. In this length reduction, the proportions are not the same as in the original ELP. However, we wanted to make sure that the hydrophobic parts were not shorter than the leucine zippers. This keeps more distance between the leucine zippers and the hydrophilic part and it prevents too unrealistic folding. The hydrophilic part is kept long, since this part gives the ELP its length and it might be interesting how this part behaves during the folding. The choices made for this might affect the outcome, but the combination of regions is still the same and the difference between the temperatures can still be compared.
SoftwareIn the MD simulation, we used VMD 1.9.4 software for the visualization and NAMD 2.14 software for the simulation itself. This choice is based on the paper from López Barriero et al. who also used this software in a related topic. We had a meeting with one of the authors of this paper, Diego López Barreiro, who explained that they chose this combination of software because they were made by the same people and thus have a more integrated workflow. Since there are also clear tutorials available, we chose to use this software [6] .
For the MD simulation, different input files are needed. A more detailed description of these input files can be found below. PyMol is used to make the PDB files of the ELP, with a FASTA file of the amino acid sequence as input. The PDB file is then imported in VMD, where the PSF file is made with integrated option of the automatic PSF builder. The CHARMM force field topology file for proteins is used in this step, with the corresponding parameter file for the next steps. For the different parts of the MD simulation, configuration files are made. This is the direct input in the MD simulation [7] .
Implicit solvent simulationAs first step, a generalized born implicit solvent is used to fold the protein. In an implicit solvent, the solvent (in this case water) molecules are not individually modeled, but with an approximation of the mean force from the solvent on the protein. Different theories can be used for this, where we will use the generalized born model. Implicit solvents are faster than an explicit solvent with simulated water molecules and more detailed than a simulation in vacuum [8] . The MD simulation is performed at the temperatures 276 K, 288 K, 298 K, and 310 K, since the transition temperature was found to be 293 K in the conducted UV-VIS experiments. Simulations at 288 K and 298 K are runned in triplet to reduce the chance of coincidence in the results . This is necessary, since the initial velocities are chosen by the NAMD software and thus differ every time. Different velocities can cause differences in the final stable conformations, which can affect the results of the analytical methods.
Just like in López Barreiro et al., first energy minimalization is done for 20 000 time steps. Then, Langevin dynamics is used with Generalized Born implicit solvent. The simulation step was 2 fs with a simulation time of 50 ns. The cutoff distance is 18 Å, the switch distance 16 Å[6].
Analyzation methodsThe results are analyzed with Root Mean Square Distance (RMSD), ratio of secondary structures, Radius of Gyration and Relative shape anisotropy, and Solvent Accessible Surface Area (SASA) to show the different behaviors of the ELP at different temperatures. They are calculated with the MDTraj python library. For the analysis, the analyzation methods are calculated for the 1000 frames of the last 5 ns, which has a stable conformation at all temperatures. Even when the conformation is stable, there are still some small differences. These differences are taken into account with this distribution of the results of the last 5 ns.
RMSDRMSD can be used to measure the difference in position between the backbone of a protein and its initial structural conformation. During the folding process, the RMSD curve rises until the point where the folding stops and the conformation is stable [9] . So with the RMSD curve we can see if the folding is finished and from what time the further analysis can start.
Radius of Gyration and shapeThe radius of gyration is a measure of how compact the protein is. It indicates the total size of the chain molecule. This can be used as a measure for the variation of the structure of the protein during the MD simulation [10] . The Rg will start very high at the start of the MD simulation and will drop until the protein comes into a stable conformation. Literature found that there is a drop in the average radius of gyration around the critical temperature when comparing the stable regions of the protein at different temperatures[5].
To get more insights in the compactness of the ELP, we will also compute the relative shape anisotropy. In this method, the result will be between 0 (symmetric sphere) and 1 (linear chain)[11].
Secondary structuresWith an analysis of the secondary structure, we can assess how structured the protein is at the different temperatures. The DSSP method is used, which recognizes structures based on H-bonding patterns. In this method, residues are classified into coils, alpha-helices, or beta-sheets. For every frame, the ratio of them is calculated by dividing them with the total amount of residues. This results in three plots with the ratios of coils, alpha-helices and beta-sheets at different temperatures. It is observed in literature that ELPs form more secondary structures at higher temperatures[5].
SASASASA is a way to define the peptide surface and interior. It measures the surface area of the protein that is accessible by solvent molecules[12]. It is suggested in the literature that the behavior of ELPs related to the transition temperature abruptly decreases SASA[5]. It is also suggested that there is less heterogeneity in the structure when the temperature is increased.
Results
In figure …, some frames are shown from one of the simulations at … °C. The left figure is from frame 3000, the middle figure from frame …, and the right figure is from frame … . These frames are a bit different for the other simulations, but the process is comparable when comparing them by eye. The frames are not included here, but can be found at the wiki of the TU Eindhoven 2023 team. When comparing the simulations at the four temperatures, they all start with folding at the ends of the ELP. This was as expected since those parts are the most hydrophobic. Some of the simulations also show the folding of the ELP in the middle at the more hydrophilic part. However, there is no clear relationship between temperature and this folding behavior. So it is probably caused by luck in the simulation.
RMSDRMSD plots are made for each of the three simulations at the four temperatures. They are made for the complete 50 ns, but also for the last 5 ns to show how stable the conformation is related to frame 9000. This is important since there can still be a lot of changes in the structure while the moved distance of the atoms stays the same. Since there are a lot of plots made, they are not visualized here. However, they can be found on the wiki of the TU Eindhoven 2023 team.
For all of the measurements, the equilibrium seems to be reached. When looking at the plots of the last 5 ns, most RMSD plots have a variability of a maximum of 1 nm. Only the third simulation at 37 °C has a slightly larger difference. An RMSD of 0 describes a stable conformation, but there are always some small deviations. So it can be said that an RMSD of 0.25 nm has a high stability, but also 0.2-0.5 nm will give a high stability[10]. With this information and when looking at the course of the curves, it can still be concluded that the conformations are relatively stable since the RMSD is still very small.
Secondary structureIn Figure … a, b, and c, the boxplots for the secondary structure analysis of the individual simulations are shown. This shows some variability between the simulations of a single temperature, but also overlapping deviations. This happens especially for the α-helix and β-sheet plots. The simulation results are taken together for each temperature to make them easier to analyze, which is shown in Figure … d, e, and f.
Overall, almost no secondary structures seem to be formed. The rate of the coils is much higher than the rates for alpha-helices and beta-sheets. It is possible that more secondary structures make the ELP more stable, but that it is stuck in a local minimum. This can be proven with more simulations and some other simulation techniques.
When comparing the boxplots of the different temperatures, there does not seem to be a convincing difference in the secondary structure formation. There are some small differences in the medians and distributions, but there is no clear relation between those differences. We can thus conclude that there is no difference in the secondary structure between the temperatures.
Radius of gyrationThe radius of gyration results of the individual simulations are shown in Figure … a. The individual simulation results of 3 and 37°C show large differences in the results. This can be caused by the different velocities that are chosen for the single simulations. Since the individual simulations of 3 and 37°C differ a lot, the total boxplot in Figure … b shows a large distribution of the results.
There is a clear difference between the radius of gyration at 15 °C and 25 °C, which are just below and just above the transition temperature. When looking at the median at 37 °C, also these results show a lower radius of gyration than 15 °C. At 3 °C, the radius of gyration is for two of the simulations very low compared to the other temperatures. When looking at the final conformations of the simulations, this can be caused by the shape of the stable configurations. When the shape is more cylindrical instead of spherical, which seems especially the case for the simulations at 15°C, the radius of gyration will increase. As mentioned in the methods section, we also computed the relative shape anisotropy.
In Figure … a, the relative shape anisotropy is shown for the individual simulations. There is clearly a difference in the shape between the different simulations, also in those with the same temperature. For example 25°C, which has a clear variability between the simulations. Some of the differences were already expected after the analysis of the radius of gyration. The second simulation at 3°C is clearly less spherical than the other two simulations at that temperature. Overall, when looking at figure … b, the shape of the ELP at 15°C is less spherical than at 25°C. Because of the large variabilities between the measurements at 3 and 37°C, it cannot be concluded how this is affected at lower and higher temperatures.
This analysis suggests that there is a difference in the compactness of the ELP below and above the transition temperature. Below the transition temperature, the ELP is less compact. At a temperature above the transition temperature, the ELP will become more hydrophobic with fewer solvent molecules around it. This makes the folded ELP more compact, but also more likely to induce interactions with other ELPs. However, for harder conclusions with the role of solvent molecules included, explicit simulations are needed.
SASAIn Figure … a, the individual results show some deviations between the simulations at specific temperatures, especially at 3 and 37 °C. When taking the individual simulations together for each temperature in Figure … b, there are some small deviations shown. SASA at 25 °C seems to be lower than SASA at 15 °C, while the median SASA at 3 °C is also in this case lower than the rest of the temperatures, but with a large deviation. The results for 37 °C also have a large deviation, with a median higher than the median of 15 °C. When comparing the results with the relative shape anisotropy, there is a relationship between more spherical simulation results and a lower SASA. There seems to be a smaller difference than the difference found in the radius of gyration and the anisotropy, which might be because ends that stick out probably have more effect on SASA than the relative shape anisotropy.
The conclusion will be that there is a small but significant difference in SASA at 15 and 25 °C, but that SASA at 37°C becomes higher again. So there is a small effect of the transition temperature on SASA, but not as clear as the radius of gyration. It was expected that SASA would become much lower when passing the transition temperature[2], but in our ELPs it seems more subtle. This might thus be caused by the ends of the ELP that stick out of the spherical shape of the folded ELP.
Conclusion
In the analysis of the MD simulation of a shortened version of our ELP, different analyzation methods were applied. These bring us to the conclusion that especially the shape of the folded ELP will be altered when increasing the temperature. At a higher temperature, the results suggest a more compact ELP with a more spherical shape. When the temperature increases even more to 37°C, the difference with 15°C will slightly decrease. A temperature of 3°C generally results in more compact conformations but with a large variability between the simulations. The explanation for the more compact ELP at higher temperatures is that the residues become more hydrophobic and thus have more interactions with each other. When multiple ELPs are brought together, it is expected that this property results in increased interactions between the ELPs, especially between the hydrophobic ends and between the leucine zippers.
The radius of gyration and relative shape anisotropy give the most convincing difference between temperatures below and above the transition temperature, where the secondary structure analysis did not find a clear difference. For SASA, there seems to be a difference, but it is not as clear as the radius of gyration and relative shape anisotropy. For more convincing results, it would probably be better to use explicit solvent simulations and more simulations at more temperatures. However, due to time limitations, it was for us not possible to carry this out.
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