Difference between revisions of "Molecular Dynamics Simulations HEXA"

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As a next step, we analyzed the solvent accesible surface area of teh wildtyp and the two mutations for each residue of the protein and for all atoms of the protein. Therefore, we received two plots for each mutation and two for the wildtyp which contains the solvent accesibility area with standard deviation for all residues (Figure 35-37) and for all atoms (Figure 38-40). Furthermore, we calculated the minimum, the maximum and the average of those distributions which allows a detailed comparison.
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As a next step, we analyzed the solvent accesible surface area of the wildtyp and the two mutations for each residue of the protein and for all atoms of the protein. Furthermore, we looked at the solvent accesibility of the whole protein during the simulations. Therefore we received three plots for each mutation and two for the wildtyp which contains the solvent accesibility area with standard deviation for all residues (Figure 35-37), for all atoms (Figure 38-40) and for the whole protein (Figure 41-43). Furthermore, we calculated the minimum, the maximum and the average of those distributions which allows a detailed comparison.
   
 
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Revision as of 09:57, 27 September 2011

Run the MD simulation

A detailed description of how to run the MD analysis software to get the same results as we did, can be found [here].

Detailed results

The detailed results and the discussion of the single results can be found for each run on their own page.

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Comparison of the results

In this section, we want to compare the different results of the MD analysis to look if there are differences between the wild type structure and the structures with the mutation. For more information about the single result analysis please look at the point Detailed results.

check the trajectory

 Wildtype  Mutation 436  Mutation 485
Item #frames Timesteps (ps) Item #frames Timesteps (ps) Item #frames Timesteps (ps)
Step 2001 5 Step 2001 5 Step 2001 5
Time 2001 5 Time 2001 5 Time 2001 5
Coords 2001 5 Coords 2001 5 Coords 2001 5

As you can see in the table above, each simulation has the same number of frames on the different items. Therefore, the different results of the different MD simulation runs are comparable. We used the results of these runs for the following comparison of the different results.

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Visualize in pymol

Next, we want to compare the pictures of the tertiary structure with pymol.

wildtype Mutation 436 Mutation 485
Figure 1: Visualisation of the MD simulation for the wildtype with pymol
Figure 2: Visualisation of the MD simulation for the wildtype with pymol
Figure 3: Visualisation of the MD simulation for the wildtype with pymol

In general, the structure of the different simulation results is equal (which can be seen in Figure 1, Figure 2 and Figure 3), which was expected, because we only mutated on amino acid in the complete system.

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create a movie

The MD simulation gave the possibility to watch movies with the protein motions. Therefore, we created for each simulation result one movie in stick view and one movie in cartoon view, which can be see on Figure ?, Figure ? and Figure ?.

wildtype Mutation 436 Mutation 485
Figure 4: Movie of the motion of the wildtype in stick view.
Figure 5: Movie of the motion of mutation 436 in stick view.
Figure 6: Movie of the motion of mutation 485 in stick view.
Figure 7: Movie of the motion of the wildtype in cartoon view
Figure 8: Movie of the motion of mutation 436 in cartoon view
Figure 9: Movie of the motion of mutation 485 in cartoon view

The motion of the complete protein seems to be very similar (compare Figure 4 - Figure 9). Therefore, it is not possible to see a difference between them.
Therefore, we also want to have a closer look to the motion of the different residues. The MD simulation simulates the motion of each residue. It is not an approximate model, because the motion of every residues was calculated. So it is possible to have a closer look to the single residues and to compare the motion of the original amino acid and the mutated amino acid. This comparions can be seen on Figure 10 - Figure 13.

  • Mutation at position 436
wildtype Mutation 436
Figure 10: Detailed view of the motion of the original amino acid at position 436
Figure 11: Detailed view of the motion of the mutated amino acid at position 436

The amino acids seem to be very similar and also the motion of the amino acid is very similar, which can be seen on Figure 10 and Figure 11. Therefore, we suggest that there is no big difference between these two amino acids and the motion of the protein. Hence, we think, that the substitution of the amino acid may not change the function and the motion of the protein.

  • Mutation at position 485
wildtype Mutation 485
Figure 12: Detailed view of the motion of the original amino acid at position 485
Figure 13: Detailed view of the motion of the mutated amino acid at position 485

First of all, we can see that the amino acids are totally different. Secondly, we can see that the original amino acid is more flexible than the mutated one, which can be seen on Figure 12 and Figure 13. The original amino acid shows more motion in the simulation than the mutated amino acid. Therefore, because of the different motion of the amino acids, we suggest that the mutated amino acid may change the function and locally the structure of the protein.

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energy calculations for pressure, temperature, potential and total energy

In this section we compare the pressure, temperature, potential and total energy of the different runs.

Pressure
Wildtype Mutation 436 Mutation 485
Average (bar)
1.00711 1.0066 0.998385
 Minimum (bar)
-217.3543 -219.7197 -230.0158
 Maximum (bar)
231.9909 238.8288 243.7419
Figure 14: Pressure distribution of the wildtype.
Figure 15: Pressure distribution of the Mutation 436.
Figure 16: Pressure distribution of the Mutation 485.

There are differences between the pressure of the different systems, but these differences are very low and therefore, it should not change the structure a lot. Therefore, we think, that such small differences between the three different structures do not explain why two of them do not function any longer, because of the mutation. Otherwise, there are big differences in the minimum and maximum values between these three systems. There is a difference of more than 10 bar in both peaks. If we have a look at Figure 14, Figure 15, and Figure 16, where we can see the distribution of the pressure over the simulation time which are very similar. So therefore, it is not possible to see big differences between the three different simulation results

temperature
Wildtype Mutation 436 Mutation 485
 Average (in K)
297.94 297.94 297.936
 Minimum (in K)
294.82 294.63 294.99
Maximum (in K)
301.31 300.83 301.08
Figure 17: Temperature distribution of the Wildtype.
Figure 18: Temperature distribution of Mutation 436.
Figure 19: Temperature distribution of Mutation 485.

The temperature of the system is nearly the same, only the temperature of the Mutation 485 is little bit lower. But this difference is that low, so therefore, we can say, the three model have the same temperature. If we have a look at the different plots and the table of the temperatures over the simulation time, all three plots (Figure 17, Figure 18 and Figure 19) show nearly the same picture. There are in each plot some outliers to higher or lower degress, but in general almost the complete time the system has a temperature of about 298K.

Potential
Wildtype Mutation 436 Mutation 485
Average (in kJ/mol)
-1.2815e+06 -1.28165e+06 -1.28176e+06
 Minimum (in kJ/mol)
-1.2853e+06 -1.2852e+06 -1.28513e+06
 Maximum (in kJ/mol)
-1.2778e+06 -1.2771e+06 -1.27769e+06
Figure 20: Potential energy distribution of the Wildtype.
Figure 21: Potential energy distribution of Mutation 436.
Figure 22: Potential energy distribution of the Mutation 485.

The average potential of the three different structures is very similar. Althoug there are very small differences between the wildtype structure and the structures with the mutation. The Wildtype has the highest potential energy, whereas Mutation 436 has a potential energy which is a little bit lower. The structure with a mutation at position 485 has the lowest potential. The values we can see on the tabel above, are only average values, therefore, we want to have a more detailed look to the plots of the potential energy distribtuion over time (Figure 20, Figure 21 and Figure 22). Especially if we compare Figure 20 and Figure 22, we can see that almost during the complete simulation, the potential is lower than on the wildtype. If we look at Figure 21, we can see the same picture, but not that clear than on Figure 22. Therefore, both mutations change the potential energy a little bit.

Total Energy
Wildtype Mutation 436 Mutation 485
Average (in kJ/mol)
-1.0517e+06 -1.0519e+06 -1.05203e+06
 Minimum (in kJ/mol)
-1.0559e+06 -1.0557e+06 -1.0569e+06
Maximum (in kJ/mol)
-1.0472e+06 -1.0463e+06 -1.0468e+06
Figure 23: Total energy distribution of the Wildtype.
Figure 24: Total energy distribution of Mutation 436.
Figure 25: Total energy distribution of Mutation 485.

If we look at the total energy of our different systems, it is clearly to see, that the trend, we already observed by potential energy is more clear to see here. Therefore, the different mutations have an effect on the protein structure and energy. Also in this case, the change is not that much, but nevertheless, there is a change, and also only little changes in the energy of the protein can damage the function. The mutation at position 485 seems has significantly more effect on the energy of the system, than the mutation at position 436, but both mutations decrease the energy of the structure. Therefore, it is possible, that the structure become too rigid and can not bind to their targets as without the mutation.

If we look at the plots (Figure 23, Figure 24 and Figure 25) it is easy to see, that the distribution seems to be similar, but the average axis is lower on Figure 24 and Figure 25 than on the wildtype plot on Figure 23. This is the same result as we saw before on the analysis of the potential energy and it was expected, because the potential energy is a part of the total energy and therefore, if there are differences in the potential energy, there have to be changes in the total energy. In our case, the total energy shows more clearly that there is a energy difference between the wildtype structure and the mutation structures.

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minimum distance between periodic boundary cells

Now we want to compare the calculations of the minimum distance between periodic boundary cells. First of all, the distance should not be 0, because than some parts of the protein will interact with itself, which should not occurr in a protein. So therefore, these minimum distance values should not be too low. Second, also small differences between the values of the different system could have big effects on the protein structure, because if some parts of the protein interact with itself, they could not interact with the original partner anylonger and therefore, the shape of the protein could be changed or destroy.

Wildtype Mutation 436 Mutation 485
 Average (in nm)
3.139 2.415 3.215
Minimum (in nm)
1.770 1.408 1.772
 Maximum (in nm)
4.081 4.096 4.217
Figure 26: Plot of the minimum distance between periodic boundary cells of the wildtype.
Figure 27: Plot of the minimum distance between periodic boundary cells of mutation 436.
Figure 28: Plot of the minimum distance between periodic boundary cells of mutation 485.

On the first view, we can see that Figure 26, Figure 27 and Figure 28 show totally different plots. First of all, it is important to keep in mind, that the MD simulation is a non-deterministic algorithm. Therefore, we can not compare the timeline itself, but we can compare the values and the distribution of the values. So therefore, we can see that on the wildtype plot the values are between 2 and 4. Most of the time the values are about 3.7, and only some values are lower than 3.
If we compare the wildtype to the plot of the structure with the mutation at position 346, we can see that almost all of the minimum distances during the simulation are lower then 3. Therefore, the distance between two interacting parts of the protein is signifiantly lower than on the wildtype (2.415 average for mutation 436, 3.139 average for wildtype). Because there is only one change in the complete sequence of the protein, we suggest, that the part with the mutation causes this changes. Therefore, the mutation lead to significantly different interaction in between the protein and therefore it probably change the shape of the protein.
If we compare the wildtype with the structure with a mutation at position 485, we can see that most of the distance is about 3. So in general, on the first view the two plots seems to be totally different. But if we have a closer look to the plots, these two plots are similar than the wildtype plot compared to the plot of mutation 436. Therefore, in this case the minimum distance increases a little bit (about 0.2 nm), but the difference is not that strong as we could observed by mutation 436. Nevertheless, also only small changes have influence of the function and the shape of the protein. Therefore, the interacting parts seems to be farther away than without the mutation.
Interesstingly, the two mutations have different effects on the interactions in the protein. Mutation 436 decrease the minimum distance between interacting atoms of the protein, whereas the Mutation at position 485 increase the minimum distance. Nevertheless, if the minimum distance decrease or increase, in both cases the mutation changes the distances and therefore, we suggest that both mutations has an effect on the protein structure and function.

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RMSF for protein and C-alpha and Pymol analysis of average and bfactor

Next we want to check if the mutations change the protein flexibility. Therefore, we calcualte the RMSF for the complete protein and the C-alpha atoms to have the possibility to differ between flexibility at the side chains and flexibility of the back bone. Furthermore, the program calcualted an average protein structure, which consists of all structures which are calculated during the simulation. The program also calculate the B-fact values on basis of the simulated structures. Furthermore, we want to visualise the most interessting results with pymol.

original & average (protein) original & B-Factors (protein) average & B-Factors (protein) original & average (c-alpha) original & B-Factors (c-alpha) average & B-Factors (c-alpha)
 Wildtype
1.556 0.349 1.684 1.373 0.279 -
 Mutation 436
1.525 0.348 1.671 1.324 0.277 1.334
 Mutation 485
1.519 0.349 1.727 1.258 0.283 1.297

First of all, we compare the RMSD between the different systems and second, we compare the RMSD between the different structures.

If we look at the RMSD values which are calculated if we align original and average structure, we can see that the RMSD value for the wildtype alignment is the highest value. The RMSDs of the mutations are similar, but the lowest RMSD value is the value for the structure with a mutation at position 485. A low RMSD value means, that there is less motion during the simluation. Therefore, our wildtype structure seems to move most during the simulation and therefore, this structures seems to be most flexible.
If we compare the RMSD values between original and B-factors, we can see, that the RMSD value is lower than by the alignment between original and average. Furthermore, there is no difference between the different systems. Therefore, the mutations do not change the flexibility of any residue. The wild type structure moves more than the structures with the mutations, but it seems ot be independent of the flexibility of the single residues. The alignments between the average structure and the B-factor structures gave higher RMSD values than the alignment between average and original. So the difference between the structure with the average B-factors and the average structure seems to be more different than the original and the average structure. Nevertheless, this fact is not that important.
It is more important to recognize, that the wildtype structure shows more motion than the mutated structures althought there is no difference in the flexibility of the different residues.

Next we want to look if the motions of the protein are high because of the motion of the different side chains or of the backbone. Therefore, we calculate the RMSF for the protein with only using the c-alpha atoms. Therefore, we do not regard the side chains anylonger.
If we look at the table we can see, that the RMSD values are lower. But the difference is not very high, therefore, most of the motion is because of the motion of the backbone and not of different positioning residues. The trend is the same as if we calculate the RMSD with side chains. Therefore, the backbone of the wildtype structure shows the most motion, whereas the backbone of the mutated structures show a significantly lower motion.

Furthermore, we also got a plot were we can see the RMS flucation at the different positions within the protein. Residues with high RMS fluction have a high B-factor value and therefore are very flexible. We want to compare, if there are any changes in the flexible residues in the wildtype structure and the mutated structures.
In general, there are less peaks if we look at the RMS flucation calculated with the c-alpha atoms (which can be seen in the detailed results), but for the comparison of our results, we only look at the RMS flucation of the different residues calculated with the complete protein.

Wildtype Mutation 436 Mutation 485
Figure 29: Plot of the RMSF values over the whole protein of the wildtype.
Figure 30: Plot of the RMSF values over the whole protein of mutation 436.
Figure 31: Plot of the RMSF values over the whole protein of mutation 485.
 Number of peaks (nm > 0.2)
7 2 8

On the first look the plots (Figure 29, Figure 30 and Figure 31) are relatively similar. All three plots show the same distribution of peaks, although the height of the peak is very different. We decided to make a cutoff by 0.2nm to decide that this residue is flexible. Therefore, the wildtype has 7 very flexible residues, whereas mutation 436 has only 2 very flexible regions. Mutation 485 has 8 very flexible residues and is therefore very similar to the result of the wildtype.
In general, we distribution of the flexibility is similar for all three structures. But there are big differences in the height of the peaks and in the intensitiy of the flexibility. Therefore, we can see that especially mutation 436 change the flexibility of the different residues within the protein and therefore, the flexibility of the complete protein.

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Radius of gyration

The Radius of gyration is the RMS distance of the protein parts from their centre. So therefore, it is possible to get a good insight into the shape of the protein during simulation, because if the radius is higher, this means the distance between the different protein parts and the protein centre is higher and therefore the protein has a bigger shape than before.
As result of the calculation we got a plot for each structure in which we can see the radius of gyration and also the components of the complete radius. The first component of the lot correspond to the longest axis of the molecule. Therefore, we not only know the radius of gyration, but also which axis are the main component of this radius.

wildtype Mutation 436 Mutation 485
 Average (Rg in nm)
2.407 2.408 2.416
 Minimum (Rg in nm)
2.346 2.344 2.347
 Maximum (Rg in nm)
2.440 2.436 2.339
Figure 32: Distribution of the radius of gyration over time of the wildtype
Figure 33: Distribution of the radius of gyration over time for of Mutation 436
Figure 34: Distribution of the radius of gyration over time of Mutation 485

First of all, the radius of gyration (on Figure 32, Figure 33 and Figure 34) seems to be very similar between the different structures. Therefore, all structures nee almost the same space, which was expected, because the structures has the same length and therefore they should approximilaty need the same space.

Wildtype Mutation 436 Mutation 485 Wildtype Mutation 436 Mutation 485 Wildtype Mutation 436 Mutation 485
 RgX (in nm) RgY (in nm) RgZ (in nm)
Average 2.153 2.094 2.145 1.609 1.853 1.630 2.084 1.929 2.094
Minimum 2.012 1.986 1.992 1.423 1.581 1.444 1.945 1.618 1.809
Maximum 2.214 2.179 2.212 1.807 2.102 1.927 2.238 2.212 2.219

If we have a closer look at the different axis of the protein we can see that there are big differences. The x axis seems to be similar between the different structures. But the y and z axis differ extremly between the structures. On the wildtype, the value of the z axis is almost similar to the x axis value, whereas the value for the y axis is very low. The axis on the plot for mutation 436 are more flexible. There are some situation in which the value for the y and the z axis is almost the same, some situations in which the value of y is near by the value of x and some situations in which the value of z is near by the value of x. Therefore, this structures seems to pulsate in a way, because there are always changes in the radius of gyration for the y and the z axes. For the mutation 485, most of the time the z axis value is similar to the x axis value and the y axis value is very low. This is very similar to the wildtype. There are some situations in which the y and the z axis values are very similar. So therefore, again this structure seems to move more along the axes than the wildtype.
So in general, we already know that our wildtye structure is very flexible and has a lot of motion. Nevertheless, this system seems not to slide along any axes, as the structures with the mutation do.

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solvent accesible surface area

As a next step, we analyzed the solvent accesible surface area of the wildtyp and the two mutations for each residue of the protein and for all atoms of the protein. Furthermore, we looked at the solvent accesibility of the whole protein during the simulations. Therefore we received three plots for each mutation and two for the wildtyp which contains the solvent accesibility area with standard deviation for all residues (Figure 35-37), for all atoms (Figure 38-40) and for the whole protein (Figure 41-43). Furthermore, we calculated the minimum, the maximum and the average of those distributions which allows a detailed comparison.

wildtype Mutation 436 Mutation 485
Average (in nm²)
0.537 0.553 0.542
Minimum (in nm²)
0.004 0.003 0.007
Maximum (in nm²)
2.058 2.005 2.014
Figure 35: Solvent accesibility of each residue in the protein with standard deviation for the wildtyp
Figure 36: Solvent accesibility of each residue in the protein with standard deviation for Mutation 436
Figure 37: Solvent accesibility of each residue in the protein with standard deviation for Mutation 485

First of all, we analyze the solvent accesibility of each residue. Looking at the table above, we can see that the values for the minimum, the maximum and the average agree mostly for wildtyp, muation 436 and mutation 484. The same can be seen by regarding the plots of the solvent accesibility of each residue. This indicates that both mutations do not change the solvent accesibility of the residues dramatically. Furthermore, the plots display that in all three cases the amplitude of the fluctation is not that high with some exceptions. Besides, the standard deviation is very low in all three plots which indicates that there are no extrem outliers in there. Both curves point out that there are mainly sparse moving residues during the complete simulation with some exceptions where the residues are very flexible. All in all, this suggest that the real movement which is sparse will not be strong influenced by the two mutations.


wildtype Mutation 436 Mutation 485
Average (in nm²)
0.031 0.032 0.032
Minimum (in nm²)
0 0 0
Maximum (in nm²)
0.560 0.558 0.561
Figure 38: Solvent accesibility of each atom of the complete protein with standard deviation for the wildtyp
Figure 39: Solvent accesibility of each atom of the complete protein with standard deviation for Mutation 436
Figure 40: Solvent accesibility of each atom of the complete protein with standard deviation for Mutation 485


wildtype Mutation 436 Mutation 485
Average (in nm²)
135.036 138.727 135.452
Minimum (in nm²)
129.084 127.066 129.167
Maximum (in nm²)
142.218 146.571 142.977
Figure 41: Area of the protein which is accesible to the surface during the simulation with standard deviation for the wildtyp
Figure 42: Area of the protein which is accesible to the surface during the simulation with standard deviation for Mutation 436
Figure 43: Area of the protein which is accesible to the surface during the simulation with standard deviation for Mutation 485

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hydrogen-bonds between protein and protein / protein and water

wildtype Mutation 436 Mutation 485
Figure 44: Number of hydrogen-bonds between the protein and the surrounding water for the wildtyp
Figure 45: Number of hydrogen-bonds between the protein and the surrounding water for Mutation 436
Figure 46: Number of hydrogen-bonds between the protein and the surrounding water for Mutation 485
Figure 47: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for the wildtyp
Figure 48: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for Mutation 436
Figure 49: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for Mutation 485


Wildtype Mutation 436 Mutation 485
bonds in the protein possible bonds in the protein bonds in the protein possible bonds in the protein bonds in the protein possible bonds in the protein
Average 328.758 1537.77 319.787 1534.866 323.337 1543.024
Minimum 294 1486 292 1483 300 1491
Maximum 361 1587 356 1584 354 1602


wildtype Mutation 436 Mutation 485
Figure 44: Number of hydrogen-bonds between the protein and the surrounding water for the wildtyp
Figure 45: Number of hydrogen-bonds between the protein and the surrounding water for Mutation 436
Figure 46: Number of hydrogen-bonds between the protein and the surrounding water for Mutation 485
Figure 47: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for the wildtyp
Figure 48: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for Mutation 436
Figure 49: Number of hydrogen-bonds and possible hydrogen-bonds between the protein and the surrounding water for Mutation 485


Wildtype Mutation 436 Mutation 485
bonds in the protein possible bonds in the protein bonds in the protein possible bonds in the protein bonds in the protein possible bonds in the protein
Average 836.94 981.18 853.403 999.847 847.965 999.310
Minimum 768 853 778 905 783 882
Maximum 916 1091 907 1106 912 1126


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Ramachandran plot

wildtype Mutation 436 Mutation 485 Typical Ramachandran Plot
Figure 44: Ramachandran Plot of the wildtyp
Figure 45: Ramachandran Plot of Mutation 436
Figure 46: Ramachandran Plot of Mutation 485
Figure 47:Typical Ramachandran Plot


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RMSD matrix

wildtype Mutation 436 Mutation 485
Figure 48: RMSD matrix of our structures during the simulation for the wildtyp
Figure 49: RMSD matrix of our structures during the simulation for Mutation 436
Figure 50: RMSD matrix of our structures during the simulation for Mutation 485

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cluster analysis

wildtype Mutation 436 Mutation 485
Figure 51: Visualization of the 231 different clusters for the wildtyp
Figure 52: Visualization of the 231 different clusters for Mutation 436
Figure 53: Visualization of the 231 different clusters for Mutation 485
Figure 54: Distribution of the RMSD value over the different clusters for the wildtyp
Figure 55: Distribution of the RMSD value over the different clusters for Mutation 436
Figure 56: Distribution of the RMSD value over the different clusters for Mutation 485


Cluster 1 Cluster 2 RMSD for the Wildtyp RMSD for Mutation 436 RMSD for Mutation 485
cluster 1 cluster 2 0.654 0.880 0.790
cluster 1 cluster 5 0.899 0.068 0.755

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internal RMSD

Wildtype Mutation 436 Mutation 485
Average (RMSD in nm)
0.238 0.242 0.243
Minimum (RMSD in nm)
4.89e-7 0.141 4.906e-07
Maximum (RMSD in nm)
0.312 0.409 0.289
Figure 32: Plot of the distance RMS values in the protein for the wildtype
Figure 33: Plot of the distance RMS values in the protein for Mutation 436
Figure 34: Plot of the distance RMS values in the protein for Mutation 485

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Discussion

In this section we want to discuss if the MD simulation could give us hints, that the mutations are bad for the protein. Sadly, we analysed in this case two mutations which are effective, but if the mutation has no effect on the protein function we suggest, that the values in the analysis are very similar. If this is not the case we suggest, that the mutation is effectiv.

In the following table we want to list if there are any differences between the wildtype and the mutation.

By the visualisation in pymol we can see, that there is a difference in the motion of the residues of the wildtype and the mutated structure at position 485, but there is no difference between wildtype and mutation 436.

protein motion
Difference wt - mut 436 Difference wt - mut 485
Difference no yes

Now we want to compare the energy calculations for the different structures. By analysing Pressure there is a difference, if the deflection is more than 0.001 in average. By the minimum and maximum comparison there we count a difference by a deflection of more than -3.
By the temperature there has to be a difference of more than 1 K.
By comparison the potential and the total energy, we count a difference, if there is a deflection of more than 20 kJ/mol.

energy calculations
Wildtype Mutation 436 Mutation 485
Pressure
Average (bar) 1.00711 1.0066 0.998385
Minimum (bar) -217.3543 -219.7197 -230.0158
Maximum (bar) 231.9909 238.8288 243.7419
Temperatur
Average (K) 297.94 297.94 297.936
Minimum (K) 294.82 294.63 294.99
Maximum (K) 301.31 300.83 301.08
 Potential
Average (kJ/mol) -1.2815e+06 -1.28165e+06 -1.28176e+06
Minimum (kJ/mol) -1.2853e+06 -1.2852e+06 -1.28513e+06
Maximum (kJ/mol) -1.2778e+06 -1.2771e+06 -1.27769e+06
 Total energy
Average (kJ/mol) -1.05177e+06 -1.0519e+06 -1.05203e+06
Minimum (kJ/mol) -1.05599e+06 -1.0557e+06 -1.05687e+06
Maximum (kJ/mol) -1.04718e+06 -1.0463e+06 -1.04680e+06
energy calculations
Difference wt - mut 436 Difference wt - mut 485
Pressure
Average no no
Minimum no yes
Maximum yes yes
Temperatur
Average no no
Minimum no no
Maximum no no
 Potential energy
Average no yes
Minimum no no
Maximum no no
 Total energy
Average no no
Minimum yes yes
Maximum yes yes

There is no difference in the pressure of the different systems. There are some differences in the minimum and maximum value, but the average value is nearly the same, so therefore, we count differences in pressures as no. There is also no difference in the temperatur if we compare the different systems. If we have a look to the potential energy of the different structures, we can see, that there are differences in average. The minimum and maximum values are nearly the same, but the average value differs. The difference is more significant at the second mutation, so therefore, we counted this as a difference. Differences in the potential engery are very important for function, because if the protein has a difference in energy, the function could change. If we look at the total energy of the protein, we can see that the differences are very small and therefore, we decided that there is no difference in average, although there are differences in the minimum and maximum values.

Now we compare the minimum distance between periodic boundary cells of the different structures. We decided to see a difference between the two structures if the defluction between the two values is more than 0.1nm.

 minimum distance between periodic boundary cells
Wildtype Mutation 436 Mutation 485
Average (nm) 3.139 2.415 3.215
Minimum (nm) 1.770 1.408 1.772
Maximum (nm) 4.081 4.096 4.217
minimum distance between periodic boundary cells
Difference wt - mut 436 Difference wt - mut 485
Average yes no
Minimum yes no
Maximum no yes


In this case there is a difference between wildtype and mutation 436 in average and minimum and the maximum value of the wildtype and mutation 485. So in this case, the mutation at position 436 seems to change the structure more than the mutation at position 485.

By the comparions of the RMSF calclation of the different structure, we count only the significant peaks with more than 0.2. If the number is not the same we count this as difference.

 RMSF calculation
Wildtype Mutation 436 Mutation 485
RMSF for protein
#high B-factor regions 7 2 8
 RMSF for c-alpha
#high B-factor regions 3 1 3
RMSF calculation
Difference wt - mut 436 Difference wt - mut 485
RMSF for protein
#high B-factor regions yes yes
 RMSF for c-alpha
#high B-factor regions yes no

As we can see in the table above, there is always a difference in the number of peaks if we calculate the RMSF for the wohle protein. Nevertheless, the difference between wildtype and mutation 436 is a way more significant than the difference between wildtype and mutation 485. Furthermore, if we only compare the c-alpha atoms, the number of peaks of the wildtype and mutation 485 is equal. Therefore, the mutation at position 436 seems to change the protein more than the mutation at position 485.

Now, we want to compare the Radius of gyration between the different structures. In this case, we mark a difference is there is a defluction of 0.01 nm.

 Radius of gyration
Wildtype Mutation 436 Mutation 485
 Rg
Average (nm) 2.407 2.408 2.416
Minimum (nm) 2.346 2.344 2.347
Maximum (nm) 2.440 2.436 2.449
 RgX
Average (nm) 2.153 2.094 2.145
Minimum (nm) 2.012 1.986 1.992
Maximum (nm) 2.214 2.179 2.212
 RgY
Average (nm) 1.609 1.853 1.630
Minimum (nm) 1.423 1.581 1.444
Maximum (nm) 1.807 2.102 1.927
 RgZ
Average (nm) 2.084 1.929 2.094
Minimum (nm) 1.945 1.618 1.809
Maximum (nm) 2.238 2.212 2.219
Radius of gyration
Difference wt - mut 436 Difference wt - mut 485
 Rg
Average no yes
Minimum no no
Maximum yes no
 RgX
Average yes yes
Minimum yes yes
Maximum yes no
 RgY
Average yes yes
Minimum yes yes
Maximum yes yes
 RgZ
Average yes yes
Minimum yes yes
Maximum yes yes

In this case, most of the time, there is a difference between wildtype and mutation. In average, there is only a difference between Mutation 485 and wildtype, if we look at the complete radius of gyration. But if we have a closer look and compare how the average value of the complete radius is composed, we can see that there are significant differences. There is always a difference between the wildtype and the mutated structures.

Another very important properity of each protein is the area which is accessible to the surface. By comparions of the solvent accessible surface area of each residue and each atom, there is a difference if there is a deflection of 0.01 nm². The last comparison is an average value for the complete protein over time and therefore, we only counted a difference, the defluction is more than 1 nm².

solvent accessible surface area
Wildtype Mutation 436 Mutation 485
Solvent accessible area of each residue
Average (in nm²) 0.537 0.553 0.542
Minimum (in nm²) 0.004 0.003 0.007
Maximum (in nm²) 2.058 2.005 2.014
 Solvent accessible area of each atom
Average (in nm²) 0.031 0.032 0.032
Minimum (in nm²) 0 0 0
Maximum (in nm²) 0.560 0.558 0.561
 Solvent accessible area of the protein over time
Average (in nm²) 135.036 138.727 135.452
Minimum (in nm²) 129.084 127.066 129.167
Maximum (in nm²) 142.218 146.571 142.977
Solvent accessible surface area
Difference wt - mut 436 Difference wt - mut 485
Solvent accessible area of each residue
Average yes no
Minimum no no
Maximum yes yes
 Solvent accessible area of each atom
Average no no
Minimum no no
Maximum no no
 Solvent accessible area of the protein over time
Average yes no
Minimum yes no
Maximum yes no

There is a difference of the solvent accessible area of each residue between wildtype and the mutations, but the solvent accessible area of each atom is equal in average. More important is the solvent accessible surface area of the whole protein over time and there we can see, is only a difference between wildtype and mutation 436. The area of the wildtype and the mutation at position 485 is nearly the same.

Another very important characteristic for the stability of a protein is the number of hydrogen bonds in the protein and between the protein and the water. If there is a difference of more than 5 hydrogen bonds we decided to count them as not similar.

hydrogen-bonds
Wildtype Mutation 436 Mutation 485
 bonds within the protein
 real occurring bonds
Average 328.758 319.787 323.337
Minimum 294 292 300
Maximum 361 356 354
 possible bonds
Average 1537.77 1534.866 1543.024
Minimum 1468 1483 1491
Maximum 1587 1584 1602
bonds between protein and water
real occurring bonds
Average 836.94 853.403 847.965
Minimum 768 778 783
Maximum 916 907 982
 possible bonds
Average 981.18 999.847 999.310
Minimum 853 905 882
Maximum 1091 1106 1126
Hydrogen-bonds
Difference wt - mut 436 Difference wt - mut 485
bonds within the protein
 real occurring bonds
Average yes yes
Minimum no yes
Maximum yes yes
 possible bonds
Average yes yes
Minimum yes yes
Maximum no yes
 bonds between protein and water
 real occurring bonds
Average yes yes
Minimum yes yes
Maximum yes yes
 possible bonds
Average yes yes
Minimum yes yes
Maximum yes yes


There is almost at every comparions a difference between wildtype and mutation. The number of real occurring hydrogen-bonds as well as the number of possible hydrogen bonds differ between them. Therefore, the structure of the mutated proteins seems to change dramatically.

Now we want to compare the Ramachandran plots of the different structures. Here we only do a visuale comparison.

Ramachandran Plot
Difference wt - mut 436 Difference wt - mut 485
Difference no yes

The Ramachandran plots for the wildtype and mutation 436 are quite equal, whereas there a big differences between the wildtype and the mutation 485 ramachandran plot.

Furthermore, we want to compare the RMSD matrices of the different structures, which is also done visualy.

RMSD matrix
Difference wt - mut 436 Difference wt - mut 485
Difference no yes

The RMSD matrices of the wildtype and mutation 436 are quite similar. There are differences, but in general the color of the plots are relatively equal, whereas, the plot of mutation 485 is much darker and therefore different.

Now we want to have a look to the number of the different clusters. If there is a difference of more than 5 clusters, we count it as not equal.

Cluster analysis
Wildtype Mutation 436 Mutation 485
#Clusters 225 231 225
Cluster analysis
Difference wt - mut 436 Difference wt - mut 485
Difference yes no

The algorithm found 225 different clusters for the wildtype and mutation 485, but it found 231 clusters for mutation 436.

As last point we compared the internal RMSD of the proteins. If there is a difference of more than 0.01 the structures are counted as different.

Internal RMSD
Wildtype Mutation 436 Mutation 485
Average 0.238 0.242 0.243
Minimum 4.89e-7 0.141 4.906e-07
Maximum 0.312 0.409 0.289
Internal RMSD
Difference wt - mut 436 Difference wt - mut 485
Average no no
Minimum yes no
Maximum yes no


In this analysis we can see, that the internal RMSD between the wildtype structure and the mutated structures is almost the same and therefore, there is no difference in the internal RMSD values.



No we want to decide if the mutations are silent or non-silent. Therefore, we count how often is there a difference between the average values of the wildtype and the mutated structures.

Wildtype vs. Mutation 436 Wildtype vs. Mutation 485
#Differences 13 13
Ratio 56% 56%
Conclusion non-silent non-silent
correctness wrong right

Both mutations have the same number of differences between it and the wildtype. Therefore 56% of the criteria are different from the wildtype. We predicted both mutations as non-silent.
This is wrong. Only one mutation is non-silent. Mutation 436 indeed is silent. There are hints, that this mutation is silent, because there is no difference in the motion of the mutated amino acid and in the energy values. But there are a lot of difference in other analysis.
Therefore, we have a prediction correctness of 50% which is really bad. So we can see, Molecular Dynamics could be very helpful by analysing a mutation, but it can also fail. MD is a very time-consuminig analyse procedure and therefore, in our case, it was not very helpful, with a prediction correctness of 50%. Therefore, we think, it is useful to analyse the mutations first with other methods and only in special cases or cases of doubt it is useful to use the MD simulation.

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