Difference between revisions of "Molecular Dynamics Simulations HEXA"
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(→Run the MD simulation) |
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− | * RMSF for protein and C-alpha |
+ | * RMSF for protein and C-alpha and Pymol analysis of average and bfactor |
In the next step, we analysed the root mean square fluctuations for the complete protein and also for the C-alpha atoms. With the RMSF you can calculate the differences between two nearly identical structures. In our case, we have a lot of very similar structures. In general we use the same structure but over the simulation time, the structure moves and therefore we got a lot of very similar, but not equal structures during the simulation. We calculate the RMSF between the start structure and the average structure, which is the average of all structures calculated during the simulation. Furthermore, we also calculated the B-factors of the different residues of the structures. Therefore, we can get a good insight in the flexibility of the protein structure. |
In the next step, we analysed the root mean square fluctuations for the complete protein and also for the C-alpha atoms. With the RMSF you can calculate the differences between two nearly identical structures. In our case, we have a lot of very similar structures. In general we use the same structure but over the simulation time, the structure moves and therefore we got a lot of very similar, but not equal structures during the simulation. We calculate the RMSF between the start structure and the average structure, which is the average of all structures calculated during the simulation. Furthermore, we also calculated the B-factors of the different residues of the structures. Therefore, we can get a good insight in the flexibility of the protein structure. |
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We visualised the rmsf-per-residue file with xmgrace. The pdb files were visualised with pymol. Furthermore, we aligned the calculated structures with the start structure with pymol to get a RMSD value. Additionally, we looked at the parts of the protein which are really flexible to see how the structure change over time. |
We visualised the rmsf-per-residue file with xmgrace. The pdb files were visualised with pymol. Furthermore, we aligned the calculated structures with the start structure with pymol to get a RMSD value. Additionally, we looked at the parts of the protein which are really flexible to see how the structure change over time. |
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+ | * Radius of gyration |
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+ | 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. We calculate the radius of gyration with following command: |
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+ | g_gyrate -f traj.xtc -s topol.tpr -o radius-of-gyration.xvg |
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+ | To visualise the result of this calculation we use two different xmgrace commands. |
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+ | With the following command, we got a plot which shows the change of the radius of gyration over simulation time. |
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+ | xmgrace radius-of-gyration.xvg |
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+ | With the next command, we got some more detailed information about the radius of gyration. Therefore, we got the individual components of which the radius of gyration consists. These components correspond to the eigenvalues of the matrix of inertia. Therefore, the first component of the plot correspond to the longest axis of the molecule and vice versa. |
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=== Detailed results === |
=== Detailed results === |
Revision as of 11:06, 20 September 2011
Run the MD simulation
Here we want to give a receipt for how to analyse the MD simulation result as we did it in our section.
- check the trajectory
First of all we checked the trajectory, to see if our simulation finished successfully and the file is not corrupted.
gmxcheck -f traj.xtc
- Visualistation
Next we want to visualise our results:
trjconv -s topol.tpr -f traj.xtc -o protein.pdb -pbc nojump -dt 10 pymol protein.pdb
Still TODO
- create a movie and skip the g_filter step
Still TODO
- energy calculations for pressure, temperature, potential and total energy
In the next analysis step we calculated the energy values for pressure, temperature, potential and total energy with following commands:
echo 13 0 | g_energy -f ener.edr -o pressure.xvg echo 12 0 | g_energy -f ener.edr -o temperature.xvg echo 9 0 | g_energy -f ener.edr -o potential.xvg echo 11 0 | g_energy -f ener.edr -o total_energy.xvg
We visualised the results of the different runs with the xmgrace program:
xmgrace pressure.xvg xmgrace temperature.xvg xmgrace potential.xvg xmgrace total_energy.xvg
- minimum distance between periodic boundary cells
Next, we calculated the minimum distance between periodic boundary cells. A low distance means, that the part of the protein which is in this boundary cell have contacts with itself. This should not be the case, because one part of the protein should not have contacts with the completely equal part of the protein. Therefore, a low periodic boundary cell shows that the quality of the model is bad and the simulation my be wrong. To calculate the minimum distance we used following command:
g_mindist -f traj.xtc -s topol.tpr -od minimal-periodic-distance.xvg -pi
We visualised the results with xmgrace:
xmgrace minimal-periodic-distance.xvg
- RMSF for protein and C-alpha and Pymol analysis of average and bfactor
In the next step, we analysed the root mean square fluctuations for the complete protein and also for the C-alpha atoms. With the RMSF you can calculate the differences between two nearly identical structures. In our case, we have a lot of very similar structures. In general we use the same structure but over the simulation time, the structure moves and therefore we got a lot of very similar, but not equal structures during the simulation. We calculate the RMSF between the start structure and the average structure, which is the average of all structures calculated during the simulation. Furthermore, we also calculated the B-factors of the different residues of the structures. Therefore, we can get a good insight in the flexibility of the protein structure. Furthermore, we calculate this for the complete protein and the C-alpha atoms, to get the possibility to see how flexible the backbone and the residues are. Therefore, we used following commands:
echo 1 0 | g_rmsf -f traj.xtc -s topol.tpr -o rmsf-per-residue.xvg -ox average.pdb -oq bfactors.pdb -res echo 3 0 | g_rmsf -f traj.xtc -s topol.tpr -o rmsf-per-residue_c.xvg -ox average_c.pdb -oq bfactors_c.pdb -res
We visualised the rmsf-per-residue file with xmgrace. The pdb files were visualised with pymol. Furthermore, we aligned the calculated structures with the start structure with pymol to get a RMSD value. Additionally, we looked at the parts of the protein which are really flexible to see how the structure change over time.
- 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. We calculate the radius of gyration with following command:
g_gyrate -f traj.xtc -s topol.tpr -o radius-of-gyration.xvg
To visualise the result of this calculation we use two different xmgrace commands.
With the following command, we got a plot which shows the change of the radius of gyration over simulation time.
xmgrace radius-of-gyration.xvg
With the next command, we got some more detailed information about the radius of gyration. Therefore, we got the individual components of which the radius of gyration consists. These components correspond to the eigenvalues of the matrix of inertia. Therefore, the first component of the plot correspond to the longest axis of the molecule and vice versa.
Detailed results
- [Wildtype]
- [Mutation 436]
- [Mutation 485]