Molecular Dynamics Analysis BCKDHA

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Revision as of 16:09, 13 September 2011 by Reisinger (talk | contribs) (Internal RMSD)

Contents

Wildtype

A brief check of results

To verified that the simulations finished properly we first use the command

  • gmxcheck -f wt.xtc

How many frames are in the trajectory file and what is the time resolution?

  • frames: 2001
  • time resolution: 5ps

How long did the simulation run in real time (hours), what was the simulation speed (ns/day) and how many years would the simulation take to reach a second?

  • real time: 9h27:35
  • simulation speed: 25.370 ns/day
  • simulation speed: 107991 years/second

Which contribution to the potential energy accounts for most of the calculations?

  • potential energy: -1.24431e+06

Visualization of results

To get a pdb file to be able to visualize the model with pymol we used the Swiss army knife gromacs tool trjconv:

  • trjconv -s wt.tpr -f wt.xtc -o protein.pdb -pbc nojump -dt 10
Figure1: MD simulation of the movement of BCKDHA

Quality assurance

Energy calculations

To calculate the different energies we used the command:
g_energy -f wtMD.edr -o energy.xvg
After submitting this command we had to choose the energy which should calculated.

  • Pressure: 13
  • Temperature: 12
  • Potential: 9
  • Total Energy: 11

Pressure

Figure2: Plot of the pressure during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (bar)
Pressure 1.01601 0.015 71.2152 -0.0706383

In Figure 2 the pressure of the molecular dynamic system is shown. The average value is 1.0161 bar which is shown in the table above. But as we can see the pressure ranges from about -250 bar to 250 bar. Since there is such a big range of 500 bar we are not sure if this value of 1.0161 bar is the equilibrium which should be reached or only the arithmetic average of all the values.

Temperature

Figure3: Plot of the temperature during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (K)
Temperature 297.941 0.0047 0.954498 0.00557078

In Figure 3 the temperature of the MD simulation is shown. As we can see it ranges between 294 K and 302 K so it has a very small deviation of the average value of 297.9 K. Since there is only such a small fluctuation we can see that the temperature in the system is quite stable which means that it reached an equilibrium.

Potential

Figure4: Plot of the potential during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Potential -1.24431e+06 66 1041.57 -463.992

Figure 4 shows the potential of the md system. As we can see in the picture the potential ranges from -1.24e+06 kJ/mol to -1.25e+06 kJ/mol. Although this is a very huge range of 10000 we can see that all in all the potential is very low. This low potential indicates that the protein is quite stable. Since the structure of a protein is responsible for the functino of a protein this stability is important for the function of the protein.

Total Energy

Figure5: Plot of the total energy during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Total Energy -1.02119e+06 65 1279.76 -459.819

The low potential energy already indicated that the total energy of the system has to be quite low. By looking at Figure 5 we can see that the energy is a bit higher than the potential energy but it is still very low. Additionally there is less variation in the energy since it ranges between -1.017e+06 kJ/mol and -1.025e+06 kJ/mol. Again we can say that such a low energy stands for a stable protein which indicates that the simulation was correct.

Minimum distance between periodic boundary cells

It is important to calculate the minimal distances to find out if there are direct interactions. Such interactions could appear if the distances are shorter than the cut off value of electrostatic interactions.

To calculate the minimum distance we used the command
g_mindist -f wtMD.xtc -s wtMD.tpr -od minimal-periodic-distance.xvg -pi
After submitting this command we chose group 1 to calculate the minimum distance for the whole protein.

Figure6: Minimum distance between periodic boundary cells

The shortest periodic distance is 1.40945 (nm) at time 6090 (ps) between atoms 25 and 6490. Because of this fact we can say that the minimal distance is higher than the cut off value.

Root mean square fluctuations

For calculating the RMSF of a protein each atom of this protein is compared with the calculated average stucture of the protein. By comparing them it is possible to find out how much it varies from its average position and so the flexibility of this region can be calculated. Regions with a high fluctuation are more flexible than regions with a low one.

To calculate the minimum distance we used the command
g_rmsf -f wtMD.xtc -s wtMD.tpr -o rmsf-per-residue.xvg -ox average.pdb -oq bfactors.pdb -res
After submitting this command we had to choose the group we want the RMSF to be calculated for:

  • Protein: 1
  • C-alpha: 3
RMSF for protein RMSF for C-alpha
Figure7: RMSF for protein
Figure8: RMSF for C-alpha

Figure 7 where the RMSF for the whole protein is plotted points out that mainly the beginning of the protein features the most fluctuation. This indicates that this region of the protein is the one with the most flexibility. In the middle part of the protein there are nearly no peaks which means that this part is fixed. In the end there is a peak which is a bit higher than the rest of the protein. This could suggest that this region is also a bit flexible.
In Figure 8 we did the RMSF calculations not for the whole protein but only for the c-alpha atoms. Those atoms are the central carbon atoms of the protein which means that in this case calculation only the backbone is considered. But by comparing the two plots above with each other we can see that in both cases the beginning of the protein is the part which has definitly the huges fluctuation of the average structure. So not only the side chains differ from the average structure but also the backbone which indicates for a strong flexibility.

Pymol analysis of average and bfactors

These average.pdb file was produced automatically during the calculation of the RMSF because it is needed for comparisons. This file contains the average structure of the protein. Because of the option -oq the bfactor.pdb file was produced additionally. In this file the temperature factors (bfactors) are calculated and added to a reference structure by coloring the specific regions of the structure. Normally the parts of the protein which are most flexible have also the highest temperature. To find out if this is the fact in our case we used pymol to analyze the average structure and the bfactors structure. Additionally we compared the predicted average structure with the original structure of our protein.


Protein

1u5b/average 1u5b/bfactors bfactors/average
Figure9: Alignment of the original structure with the average structure
Figure10: Alignment of the original structure with the structure containing the bfactors
Figure11: Alignment of the average structure with the structure containing the bfactors
RMSD: 1.169 RMSD: 0.377 RMSD: 1.422


To find out how accurate the calculated average structure is we aligned it with the original structure of out protein (1u5b). As we can see in Figure 9 and additionally because of the RMSD value of 1.169 the superposition of the two structures is not covering perfectly. The middle part of the protein is aligned quite good. The most deviating parts are the two ends of the structures on the left and on the right side of the picture. By looking at the already discussed RMSF we can see that these regions are the most flexible ones so it is possible that the two structures are only in two different states of movement. Next we compared the structure of 1u5b with the structure containing the bfactors and according to Figure 10 the used reference structure on which the bfactors are added is the structure of 1u5b. This is obvious since they are superposed nearly perfectly. There is a minimal shift in the alignment but since this occurs at the whole structure we consider it to be an error of the superposition tool. Now we come to the analysis of the bfactors. In Figure 11 we can see the alignment of the structur containing the bfactors with the average structure. Of course they are a bit different again because of the different states of movement but in this figure the bfactors are the most interesting observation. As it is shown in the picture only the part in the end of the protein (left side of the picture) is colored indicating that only this part of the protein is flexible. The coloring ranges from yellow to red where yellow stands for little and red for high flexibility. This flexibility according to the bfactors is reflected by the RMSF value above. The other end of the protein is not colored but only a bit shifted. We thought that this shift could be a result of a movement but since it is not colored this theory is perhaps false. But by looking at the RMSF values above we see that there is only a very little fluctuation of the atoms. So perhaps this part is a little bit flexible but not enough to be marked as flexible by the bfactors.

C-alpha

1u5b/average 1u5b/bfactors bfactors/average
Figure12: Alignment of the original structure with the C-alpha atoms of the average structure
Figure13: Alignment of the original structure with the C-alpha atoms of the structure which contains the bfactors
Figure14: Alignment of the C-alpha atoms of the average structure with the C-alpha atoms of the structure containing the bfactors
RMSD: 0.955 RMSD: 0.300 RMSD: 0.993

To analyse the run where we only considered the C-alpha atoms of the structure again we first wanted to find out how good the average structure fits the original structure. As we can see in Figure 12 there is again a lot of variation between the average structure and the structure of u15b. But by looking at the RMSD value (0.955) we can see that it is smaller than the RMSD value considereing the whole protein for the average structure (1.169). Since we assumed that the variation is aroused by the different states of movement in the different structures we can say that the backbone has a bit less flexibility because of the lower RMSD value. The most variation is again in the both endings of the protein. Next the comparison of the original structure with the C-alpha atoms of the structure containing the bfactors gets analysed. Figure 13 and also the very low RMSD value show that the superposition of the two structures is very close. Perhaps there is a little bit of variation between the two structures or we have the same case as in Figure 10 where we assumed a mistake of the programm since there was a shift during the whole alignment. It is hard to see it here because of the spheres. The last analyses is the detailed one of the structure containing the bfactors ( Figure 14). Again the part with the highest temperature is colored where red means high flexibility and green low flexibility. As we can see only the end of the protein (right side) is colored so only this part of the protein exhibits flexibility. This observation agrees with the RMSF because in both cases the beginning of the protein is predicted to be flexible.

Radius of gyration

The radius of gyration reflects how the structure changes during the simulation and how the shape changes during the time.

To calculate the radius of gyration we used the command
g_gyrate -f wtMD.xtc -s wtMD.tpr -o radius-of-gyration.xvg
After submitting this command we chose group 1 to calculate the radius of gyration for the whole protein

Figure15: Radius of gyration during the MD simulation

According to the black line in Figure 15 the radius of gyration ranges between 2.22 and 2.4. nm during the whole simulation. The black line describes the general change in the shape of the protein. But by looking at the plot more closely we can see that there is trend. In the beginning the radius has its maximal value of about 2.4 nm but during the simulation it falls have of the time. But after about 6300 ps the decline of the radius stopps. After this moment the value is between 2.23 and 2.27 nm which shows that the fluctuation is very small. But the fact there is still variation until the end of the simulation shows that there the protein moves all the time indicating the flexibility of the protein. The changes in the profile of the protein are specified by the red (x axis), green (y axis) and blue (z axis) lines.

Structural analysis

First we had to use the command
trjconv -f wtMD.xtc -o wtMD_nojump.xtc -pbc nojump
This is important because the protein possibly jumps out of the box so the trajectory has to be rebuild. This has the effect that the particles are back in the center.

Solvent accessible surface area

The solvent accessible surface area (SASA) of a protein is the part of the surface which is reachable a solvent. This definition of SASA can be devided into two subgroups - hydrophilic SASA and hydrophobic SASA. Which means that the possibility that a solvent can reach the surface depends on its properties.

To calculate the solvent accessible surface area we used the command
g_sas -f wtMD_nojump.xtc -s wtMD.tpr -o solvent-accessible-surface.xvg -oa atomic-sas.xvg -or residue-sas.xvg
After submitting this command we had to choose two groups. Both times we chose protein.

SAS over time per residue SAS over time per atom Solvent accessible surface
Figure16: Plot of the average solvent accessibe surface over time per residue
Figure17: Plot of the average solvent accessibe surface over time per atom
Figure18: Plot of the solvent accessible surface of the protein during the md simulation


In Figure 16 the average sas for each residue during the simulation is shown. We can see that there is much variation and the solvent asseccible areas for the residues range between 0 nm2 and 2.3 nm2. As there are also regions which have a sas of 0 nm2 we can see that there are parts which are not accessible for solvents but the most regions are accessible. The most most accessible one is in the total beginning since the peak is definitly the highest one. Additionally there are two high peaks in the middle of the protein which differ completely from the peaks next to them since they are all quite. This shows that there are only a few parts in the the center of the protein which are accessible for solvents but here the accessibility is very good. Figure 17 the average solvent accessibe surface over time per atom is shown. Again there is a lot variation in the sas. It ranges between 0 nm2 and 0.55 nm2. The last plot ( Figure 18) shows the general sas for the whole protein during the simulation. The red line describes the accessibility for hydrophilic solvents and the black line for hydrophobic solvents. As we can see the accessibility for hydrophobic solvents is a little bit higher but not a lot. The green line which hardly fluctuate shows the general sas for the protein during the whole simulation indicating that the sas is always quite the same.

Hydrogen bonds

There are two different possibilities of hydrogen bonds. They can be inside of the protein (protein-protein) or between the protein and the surrounding solvents. For the building of a hydrogen bond it is important that the hydrogen-donor and the hydrogen-acceptor are not to far away from each other. This means that high flexibility of a protein would lead to high variation in the hydrogen bonds.

To calculate the hydrogen bonds between protein and protein and between protein and water we used the commands

echo 1 1 | g_hbond -f wtMD_nojump.xtc -s wtMD.tpr -num hydrogen-bonds-intra-protein.xvg
echo 1 12 | g_hbond -f wtMD_nojump.xtc -s wtMD.tpr -num hydrogen-bonds-protein-water.xvg

protein and protein protein and water
Figure19a: Internal hydrogen bonds and pairs within 0.35 nm during the simulation
Figure20a: Hydrogen bonds with the surrounding solvents and pairs within 0.35 nm during the simulation
Figure19b: Internal hydrogen bonds during the simulation
Figure20b: Hydrogen bonds with the surrounding solvents during the simulation


Donors Acceptors avg.# of h-bonds possible # of h-bonds
protein-protein 594 1158 308.847 343926
protein-water 29470 30034 806.073 4.42551e+08


Figure 19a (left) shows the number of internal hydrogen bonds during the simulation. According to the black line in this plot which describes the hydrogen bonds the number of bonds is about 300. This number is supported by the table above. Since the black line shows nearly no variation during the whole simulation it seems that there is no change in the number of hydrogen bonds. But by looking at Figure 19b we can see that the number of hydrogen bonds change since there is much fluctuation in the curve. Although they vary between 280 and 335 a trend can be seen. In the beginning the average number is about 310 then they go down to about 300 and rise again to 320. So we see that the number of hydrogen bonds first decline a bit but after one third of the simulation they rise again. By comparing this trend with the one in Figure 20b we can say that they are completely oppositional. First the number is low then rises a bit and after about one third of the time they fall again. It has to be recognized that the number of extrenal hydrogen bonds is always much higher than the internal one since the range lies between 740 and 860 but it is interesting that they are completely opposed. It is obvious that they have to be like this because of the movement of the shape of the protein. Since there is movement which is indicated by the alternating hydrogen bonds we can say that the protein is very flexible during the simulation. The red lines in Figure 19a and Figure 20a display the pairs within 0.35 nm. There are much more pairs within this distance inside of the protein (1400-1500 pairs) than with the surrounding solvents (1000 -1200 pairs). Additionally there is much more variation in the number of pairing with the solvents during the simulation than inside of the protein.

salt bridges

Ramachandran plot

In a Ramachandran plot the backbone dihedral angles ψ and φ of the amino acid residues are visualized. On the left upper corner the beta sheets are shown. Under the beta sheets the alpha helices are described. On the right side the lefthanded helices of the protein are shown.


To calculate the ramachandran plot we used the command
g_rama -f wtMD_nojump.xtc -s wtMD.tpr -o ramachandran.xvg

Ramachandran plot of our simulation general Ramachandran plot
Figure21: Ramachandran plot of our protein
Figure22: General Ramachandran plot (<ref>http://en.wikipedia.org/wiki/File:Ramachandran_plot_general_100K.jpg</ref>)


Figure 21 shows the Ramachandran plot of the protein predicted by MD. As we can see the regions for beta sheets and alpha helices are very black and also the part for lefthanded helices. Additionally to these fields the other three corners are black. By comparing it to the general Ramachandran plot (Figure 22) we can say that there are much more black fields in the plot of the simulation. This shows that the angles are not that concentrated on one position but vary a lot. Since there are regions which are completely white it is obvious that some positions and angle combinations not occur in the simulated protein. The fact that there are so many different angle positions and not only the ones like in the general Ramachandran plot could indicate that this protein is flexible.

Analysis of dynamics and time-averaged properties

RMSD matrix

A RMSD matrix is helpful to find groups of structures which are similar between the different points of time. When there are groups of structures which are similar the RMSD value is lower between them and high to other groups. The range of the RMSD value is from 0 (blue) to 0.579 (red).

To calculate the RMSD matrix we used the command
g_rms -s wtMD.tpr -f wtMD_nojump.xtc -f2 wtMD_nojump.xtc -m rmsd-matrix.xpm -dt 10
After submitting this command we had to choose two groups. Both times we chose protein.

Figure23: RMSD matrix of the structures of our protein during the simulation

Figure23 shows the correlation between the several structures of our protein during the simulation. It is obvious that there have to be a diagonal which is turquoise and blue. As we can see there is only one part in the matrix which is turquoise and it is in the end of the simulation between 6000 ps and 10000 ps. This shows that these groups of structures are all quite similar. Additionally there are red parts between 6500 ps till 9000 ps and 1000 ps till 2500 ps. This shows that the group of structures which are similar in the end are quite different from the groups in the first part of the simulation. It is also very interesting that the groups of structuers which are completely in the beginning of the simulation seem to be very different to the whole rest of structures during the simulation since thw border of the matrix is red and only in the bottom left corner it is colored green.

Cluster analysis

The similarity of structures which is analysed above can also be calculated and shown by clustering the structures which are similar to each other. This is done in the next step.

To calculate the cluster we used the command
echo 6 6 | g_cluster -s wtMD.tpr -f wtMD_nojump.xtc -dm rmsd-matrix.xpm -dist rmsd-distribution.xvg -o clusters.xpm -sz cluster-sizes.xvg -tr cluster-transitions.xpm -ntr cluster-transitions.xvg -clid cluster-id-over-time.xvg -cl clusters.pdb -cutoff 0.1 -method gromos -dt 10

For the analysis of the first two cluster we used pymol.

Figure24: Visualisation of the cluster of structure groups
Figure25: Plot of the RMSD values of the clusters


The programm was able to find 542 cluster. In figure 24 the clustered structures of the protein are visualised. The plot of the clustures show the RMSD values of the different plots. The RMSD values range from 0.07 nm to 0.57 nm. The fact that these values are quite low indicates that the all of the groups of structures are not completely different. As we can see most of the clusters have an RMSD value of about 0.35 which shows that that the main part of the structures have a bit similarity to other groups of structures. There is also a little number of groups with a value of 0.57 which shows that these groups of structures only have a bit similartiy during the simulation. Since the peaks between 0.1 and 0.2 are very small there only a few groups of structures which show a very high similarity during the simulation.
Furthermore we compared two of the clusters to each other by comparing the structures. We chose cluster 1 and cluster 2 for this comparison. Since the RMSD value is 0.709 we can see that the clusters are not completely different and there are groups of structures in the clusters which still have similarities.

Internal RMSD

The internal RMSD are the atomic distances inside the protein. With this measure it is possible to get information about the changes of the structure during the simulation.


To calculate the internal RMSD we used the command
g_rmsdist -s wtMD.tpr -f wtMD_nojump.xtc -o distance-rmsd.xvg
After submitting this command we chose group 1 to calculate the internal RMSD for the protein

Figure26: Internal RMSD of our protein during the simulation

The internal RMSD values ranges from 0.1 nm to 0.45 nm so we can see that there is a lot fluctuation during the simulation. In the beginning the values are very low but then tey rose very fast until 1500 ps. After this point they only range between 0.3 nm and 0.4 nm which is not a huge variation. After about 5000 ps they rise again a bit so that the average value for the following time is 0.4 nm. After 10000 ps it seems that the RMSD converges against 04.nm.

Mutation M82L

A brief check of results

How many frames are in the trajectory file and what is the time resolution?

  • frames: 2001
  • time resolution: 5

How long did the simulation run in real time (hours), what was the simulation speed (ns/day) and how many years would the simulation take to reach a second?

  • real time: 1d03h11:10
  • simulation speed: 8.828 ns/day
  • simulation speed: 310388 years/second

Which contribution to the potential energy accounts for most of the calculations?

  • potential energy: -1.24452e+06

Quality assurance

Energy calculations

Pressure

Figure27: Plot of the pressure during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (bar)
Pressure 0.998885 0.018 71.3509 0.00251495

Temperature

Figure28: Plot of the temperature during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (K)
Temperature 297.939 0.0044 0.959135 0.00200358

Potential

Figure29: Plot of the potential during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Potential -1.24452e+06 98 1059.66 -676.063

Total Energy

Figure30: Plot of the total energy during the MD simulation
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Total Energy -1.02137e+06 98 1298.13 -674.564

Minimum distance between periodic boundary cells

Figure31: Minimum distance between periodic boundary cells


The shortest periodic distance is 1.91319 (nm) at time 630 (ps), between atoms 25 and 5578

Root mean square fluctuations

RMSF for protein RMSF for C-alpha
Figure32: RMSF for protein
Figure33: RMSF for C-alpha

Pymol analysis of average and bfactors

Protein

1u5b mutated/average 1u5b mutated/bfactors bfactors/average
Figure34: Alignment of the mutated structure with the average structure
Figure35: Alignment of the mutated structure with the structure containing the bfactors
Figure36: Alignment of the average structure with the structure containing the bfactors
RMSD: 1.170 RMSD: 0.388 RMSD: 1.294

C-alpha

1u5b mutated/average 1u5b mutated/bfactors bfactors/average
Figure37: Alignment of the mutated original structure with the C-alpha atoms of the average structure
Figure38: Alignment of the mutated original structure with the C-alpha atoms of the structure which contains the bfactors
Figure39: Alignment of the C-alpha atoms of the average structure with the C-alpha atoms of the structure containing the bfactors
RMSD: 0.886 RMSD: 0.289 RMSD: 0.930

Radius of gyration

Figure40: Radius of gyration during the MD simulation

Structural analysis

Solvent accessible surface area

SAS over time per residue SAS over time per atom Solvent accessible surface
Figure41: Plot of the average solvent accessibe surface over time per residue
Figure42: Plot of the average solvent accessibe surface over time per atom
Figure43: Plot of the solvent accessible surface of the protein during the md simulation


4124 out of 6658 atoms were classified as hydrophobic

Hydrogen bonds

protein and protein protein and water
Figure44a: Internal hydrogen bonds and pairs within 0.35 nm during the simulation
Figure45a: Hydrogen bonds and pairs within 0.35 nm with the surrounding solvents during the simulation
Figure44b: Internal hydrogen bonds during the simulation
Figure45b: Hydrogen bonds with the surrounding solvents during the simulation


Donors Acceptors avg.# of h-bonds possible # of h-bonds
protein-protein 594 1158 304.417 343926
protein-water 29474 30038 817.490 4.4267e+08

salt bridges

Ramachandran plot

Ramachandran plot of our simulation general Ramachandran plot
Figure46: Ramachandran plot of our protein
Fgure47: General Ramachandran plot (<ref>http://en.wikipedia.org/wiki/File:Ramachandran_plot_general_100K.jpg</ref>)

Analysis of dynamics and time-averaged properties

RMSD matrix

Figure48: RMSD matrix of the structures of our protein during the simulation

Cluster analysis

Figure49: Visualisation of the cluster of structure groups
Figure50: Plot of the RMSD values of the clusters

Found 525 clusters

RMSD: 0.822

Internal RMSD

Figure51: Internal RMSD of our protein during the simulation

Mutation C264W

A brief check of results

How many frames are in the trajectory file and what is the time resolution?

  • frames:
  • time resolution:

How long did the simulation run in real time (hours), what was the simulation speed (ns/day) and how many years would the simulation take to reach a second?

  • real time: 1d03h22:33
  • simulation speed: 8.767 ns/day
  • simulation speed: 312557 years/second

Which contribution to the potential energy accounts for most of the calculations?

  • potential energy: -1.24420e+06


Quality assurance

Energy calculations

Pressure

Pressure BCKDHA MD mut1.png
Energy Average Err.Est. RMSD Tot-Drift (bar)
Pressure 1.00041 0.0069 71.2651 -0.0331535

Temperature

Temperature BCKDHA MD mut5.png
Energy Average Err.Est. RMSD Tot-Drift (K)
Temperature 297.94 0.0064 0.956382 -8.60686e-05

Potential

Potential BCKDHA MD mut5.png
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Potential -1.2442e+06 75 1052.26 -477.246

Total Energy

Total energies BCKDHA MD mut5.png
Energy Average Err.Est. RMSD Tot-Drift (kJ/mol)
Total Energy -1.0211e+06 75 1292.04 -477.313

Minimum distance between periodic boundary cells

The shortest periodic distance is 2.01518 (nm) at time 1590 (ps), between atoms 166 and 6569

Root mean square fluctuations

RMSF for protein RMSF for C-alpha
Rmsf-per-residue-protein BCKDHA MD mut5.png
Rmsf-per-residue-ca BCKDHA MD mut5.png

Pymol analysis of average and bfactors

Protein

1u5b mutated/average 1u5b mutated/bfactors bfactors/average
Alignment of the mutated structure with the average structure
Alignment of the mutated structure with the structure containing the bfactors
Alignment of the average structure with the structure containing the bfactors
RMSD: 1.393 RMSD: 0.389 RMSD: 1.463

C-alpha

1u5b mutated/average 1u5b mutated/bfactors bfactors/average
Alignment of the original structure with the C-alpha atoms of the average structure
Alignment of the original structure with the C-alpha atoms of the structure which contains the bfactors
Alignment of the C-alpha atoms of the average structure with the C-alpha atoms of the structure containing the bfactors
RMSD: 1.106 RMSD: 0.301 RMSD: 1.112

Radius of gyration

Radius-of-gyration BCKDHA MD mut5.png

Structural analysis

Solvent accessible surface area

SAS over time per residue SAS over time per atom Solvent accessible surface
Plot of the average solvent accessibe surface over time per residue
Plot of the average solvent accessibe surface over time per atom
Plot of the solvent accessible surface of the protein during the md simulation

Hydrogen bonds

protein and protein protein and water
Internal hydrogen bonds and pairs within 0.35 nm during the simulation
File:Hydrogen-bonds-protein-water
Figure20: Hydrogen bonds with the surrounding solvents during the simulation
Internal hydrogen bonds during the simulation


Donors Acceptors avg.# of h-bonds possible # of h-bonds
protein-protein 595 1159 302.744 344802
protein-water align="center" align="center"|

salt bridges

Ramachandran plot

Analysis of dynamics and time-averaged properties

RMSD matrix

Cluster analysis

Internal RMSD