Molecular Dynamics Simulations HEXA

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.

• solvent accessible surface area

Another important point is the solvent accessible surface area of the protein. With following command, we calculated the average solvent accessibility per residue and per atom over time, and also the solvent accessibility of the protein over the simulation time.

g_sas -f traj_nojump.xtc -s topol.tpr -o solvent-accessible-surface.xvg -oa atomic-sas.xvg -or residue-sas.xvg 

We visualised all of these files with xmgrace.

xmgrace file.xvg
xmgrace -nxy file.xvg

The second command gave us a more detailed output. For the average solvent accessibility per residue and per atom we also got the standard deviation of this calculation which is very useful. For the solvent-accessibility-surface we additionally got the detailed composition of pysicochemical residues over the simulation.

Detailed results

• [Wildtype]
• [Mutation 436]
• [Mutation 485]