Practical 2: Introduction to protein simulation

Practical 2: Introduction to protein simulation Contents Preparation of a typical MD simulation Setup the simulation system Carry out the simulation Trajectory analysis Optional exercises References

In the previous part we've learned what MD simulations are and how to simulate a van der Waals gas. Now it is time to set up a simulation of a biological macromolecule: a small protein. Proteins are nature's universal machines. For example, they are used as building blocks (e.g. collagen in skin, bones and teeth), transporters (e.g. hemoglobin as oxygen transporter in the blood), as reaction catalysts (enzymes like lysozyme that catalyse the breakdown of sugars), and as nano-machines (like myosin that is at the basis of muscle contraction). The protein's structure or molecular architecture is sufficient for some of these functions (like for example in the case of collagen), but for most others the function is intimately linked to internal dynamics. In these cases, evolution has optimised and fine-tuned the protein to exhibit exactly that type of dynamics that is essential for its function. Therefore, if we want to understand protein function, we often first need to understand its dynamics (see references below). Unfortunately, there are no experimental techniques available to study protein dynamics at the atomic resolution at the physiologically relevant time resolution (that can range from seconds or milliseconds down to nanoseconds or even picoseconds). Therefore, computer simulations are employed to numerically simulate protein dynamics. As before, we will use the GROMACS simulation package for this. Today, we will simulate the dynamics of a small, typical protein domain: the B1 domain of protein G. B1 is one of the domains of protein G, a member of an important class of proteins, which form IgG binding receptors on the surface of certain Staphylococcal and Streptococcal strains. These proteins allow the pathogenic bacterium to evade the host immune response by coating the invading bacteria with host antibodies, thereby contributing significantly to the pathogenicity of these bacteria (click here for further background information on this protein). We will now follow a standard protocol to run a typical MD simulation of a protein in a box of water in gromacs. The individual steps are summarized in a flowchart on the right site.

A. Preparation Before a simulation can be started, an initial structure of the protein is required. Fortunately, the structure of the B1 domain of protein G has been solved experimentally, both by x-ray crystallography and NMR. Experimentally solved protein structures are collected and distributed by the Protein Data Bank (PDB). Please open this link in a new browser window and enter "protein G B1" in the search field. Several entries in the PDB should match this query. We will choose the x-ray structure with a high resolution (entry 1PGB with resolution of 1.92 ang) for this study. To download the structure, click on the link "1PGB", and then, under "Download Files", select "PDB File". When prompted, select "save to disk", and save the file to the local hard disk. To have a look at the contents of the file, on the unix prompt, type:

more 1PGB.pdb

As we'll learn in the next practical on protein structure, the file starts with general information about the protein, about the structure, and about the experimental techniques used to determine the structure, as well as literature references where the structure is described in detail. (in "more", press the spacebar to scroll). The data file contains the atomic coordinates of our protein structure with one line per atom. (quit the "more" program by pressing "q"). Now we can have a look at the structure: rasmol 1PGB.pdb

to visualise the structure. We now see a so-called wireframe representation of the protein structure: atoms (with different colors for the different chemical elements: grey for carbon; red for oxygen and blue for nitrogen) are not shown directly, but the bonds between atoms are shown as lines. Under "display", also try other representations such as "sticks", "spacefill", "ball & stick" and "cartoons". Exit rasmol under "file" -> "exit".

Question: Why do we start our MD simulations from the experimental determined 3D structure? Isn't it enough to know the proteins amino acid sequence? Go back to Contents

B. Setup We will now prepare the protein structure to be simulated in gromacs. Although we now have a starting structure for our protein, one might have noticed that hydrogen atoms (which would appear white) are still missing from the structure. This is because hydrogen atoms contain too few electrons to be observed by x-ray crystallography at moderate resolutions. Also, gromacs requires a molecular description (or topology) of the molecules to be simulated before we can start, containing information on e.g. which atoms are covalently bonded and other physical information. Both the generation of hydrogen atoms and writing of the topology can be done with the gromacs program pdb2gmx: pdb2gmx -f 1PGB.pdb -o conf.pdb

when prompted for the force-field to be used, choose the number corresponding to the OPLS-AA/L all-atom force field, and SPC/E for water. View the result with: rasmol conf.pdb

See the added hydrogens? The topology file written by pdb2gmx is called "topol.top". Have a look at the contents of

the file using: more topol.top

you will see a list of all the atoms (with masses, charges), followed by bonds (covalent bonds connecting the atoms), angles, dihedral angles etc. Near the very end of the topology (in the "[molecules]" section) there is a summary of the simulation system, including the protein and 24 crystallographic water molecules. The topology file thus contains all the physical information about all interactions between the atoms of the protein (bonds, angles, torsion angles, Lennard-Jones interactions and electrostatic interactions). The next step in setting up the simulation system is to solvate the protein in a water box, to mimick a physiological environment. For that, we first need to define a simulation box. In this case we will generate a rectangular box with the box-edges at least 7 Angstroms apart from the protein surface: editconf -f conf.pdb -o box.pdb -d 0.7

(note that gromacs uses units of nanometers). View the result with rasmol box.pdb

and, in rasmol, type: unitcell true

Now, exit rasmol and fill the simulation box with SPC water using genbox: genbox -cp box.pdb -cs spc216 -o water.pdb -p topol.top

Again, view the output (water.pdb) with rasmol. Now the simulation system is almost ready. Before we can start the dynamics, we must perform an energy minimisation.

Question: Why do we need an energy minimisation step? Wouldn't the crystal structure as it is be a good starting point for MD as it is? For the energy minimisation, we need a parameter file, specifying which type of minimisation should be carried out, the number of steps, etc. For your convenience a file called "em.mdp" has already been prepared and can be downloaded from here. View the file with "more" to see its contents. We use the gromacs preprocessor to prepare our energy minimisation: grompp -f em.mdp -c water.pdb -p topol.top -o em.tpr -maxwarn 2

This collects all the information from em.mdp, the coordinates from water.pdb and the topology from topol.top, checks if the contents are consistent and writes a unified output file: em.tpr, which will be used to carry out the minimisation: mdrun -v -s em.tpr -c em.pdb

The output shows that already the initial energy was rather low, so in this case there were hardly any bad contacts. Having a look at "em.pdb" shows that the structure hardly changed during minimisation. The careful user may have noticed that grompp gave a warning: System has non-zero total charge: -4. Before we continue with the dynamics, we should neutralise this net charge of the simulation system. This is to prevent artefacts that would arise as a side effect caused by the periodic boundary conditions used in the simulation. A net charge would result in an electrostatic repulsion between neighbouring periodic images. Therefore, 4 sodium ions will be added to the system: genion -s em.tpr -o ions.pdb -np 4 -p topol.top

Select the water group ("SOL"), and 4 water molecules will be replaced by sodium ions. The output (ions.pdb) can be checked with rasmol. To better see the ions, type (in rasmol):

select na cpk

Go back to Contents

C. Simulation Just to be on the safe side, we repeat the energy minimisation, now with the ions included (remember to (re)run grompp to create a new run input file whenever changes to the topology, or coordinates have been made): grompp -f em.mdp -c ions.pdb -p topol.top -o em.tpr -maxwarn 2 mdrun -v -s em.tpr -c em.pdb

Now we have all that is required to start the dynamics. Again, a parameter file has been prepared for the simulation, and can be downloaded here. Please browse through the file "md.mdp" (using "more") to get an idea of the simulation parameters. The gromacs online manual describes all parameters in detail here. Please don't worry in this stage about all individual parameters, we've chosen common values typical for protein simulations. Again, we use the gromacs preprocessor to prepare the simulation: grompp -f md.mdp -c em.pdb -p topol.top -o md.tpr -maxwarn 2

and start the simulation! mdrun -v -s md.tpr -c md.pdb -nice 0

The simulation is running now, and depending on the speed and load of the computer, the simulation will run for a number of minutes.

Question: How do the parts of energy minimization and MD simulation differ (with reference to energy landscapes)? Go back to Contents

D. Analysis of a gromacs simulation The simulation is running now (or finished) and we can start analysing the results. Let us first see which kind of files have been written by the simulation (mdrun): ls -lrt

We see the following files:

traj.xtc - the trajectory to be used for analyses traj.trr - the trajectory to be used for a restart in case of a crash ener.edr - energies md.log - a LOG file of mdrun md.gro - the final coordinates of the simulation The first analysis step during or after a simulation is usually a visual inspection of the trajectory. For this we will use the gromacs trajectory viewer ngmx. Other possibilities would be VMD , Pymol, or gOpenmol.

vmd md.pdb traj.xtc

Select a group of your interest ("system" might be good for a start), and then, under "Display", click "Animate". Now a animation player button appears near the bottom of the screen, which can be used to view the trajectory. If you wish to filter different simulated components, choose a different group under "Display" and "Filter". We can see that the protein and its surroundings undergo thermal fluctuations, but overall, the protein structure is rather stable, as would be expected on such timescales. A more versatile visualisation is provided by pymol. First, we have to extract the protein coordinates and write to PDB format: trjconv -s md.tpr -f traj.xtc -o traj.pdb -dt 1.

Now, select group 1 (Protein). And view with pymol: /usr/global/whatif/pymol/pymol traj.pdb

On the pymol prompt, type: dss

followed by show cartoon

Play the animation by pressing the play button. For a more quantitative analysis on the protein fluctuations, we can view how fast and how far the protein deviates from the starting (experimental) structure: g_rms -s md.tpr -f traj.xtc

When prompted for groups to be analysed, type "1 1". g_rms has written a file called "rmsd.xvg", which can be viewed with: xmgrace rmsd.xvg

We see the Root Mean Square Deviation (rmsd) from the starting structure, averaged over all protein atoms, as a function of time.

Question: Why is there an intial rise in the rmsd? If we now wish to see if the fluctuations are equally distributed over the protein, or if some residues are more flexible than others, we can type: g_rmsf -s md.tpr -f traj.xtc -oq

Select group "3" (C-alpha). The result can be viewed with: xmgrace rmsf.xvg

We can see that mainly four regions in the protein show a large flexibility: around residues 1, 11, 21 and 38. To see where these residues are located in the protein, type: rasmol bfac.pdb

Under "Colours", select "Temperature". The protein backbone is now shown with the flexibility encoded in the colour. The red (orange, green) regions are relatively flexible and the blue regions are relatively rigid. It can be seen that the alpha-helix and beta-sheet are relatively stable, whereas the loops are more flexible. The simulation not only yields information on the structural properties of the simulation, but also on the energetics. With the program g_energy the energies written by mdrun can be analysed: g_energy -f ener.edr

Select "Potential" and end your selection by pressing enter twice, View the result with: xmgrace energy.xvg

As can be seen, the total potential energy initially rises rapidly after which it relaxes again.

Question: Can you think of an explanation for this behaviour? Please repeat the energy analysis for a number of different energy terms to obtain an impression of their behaviour.

Question: Do you think the length of our simulation is sufficient to provide a faithful picture of the protein's conformations at equillibrium. We continue with a number of more specific analysis, the first of which is an analysis of the secondary structure (alpha-helix, beta-sheet) of the protein during the simulation. First, we need to tell gromacs where the DSSP program for secondary structure calculations can be found: export DSSP=/usr/global/whatif/dssp/dssp

(or, if you get a message "export: Command not found.", you're perhaps using a (t)csh in which case the command should be:) setenv DSSP /usr/global/whatif/dssp/dssp

Now, perform the actual analysis with: do_dssp -s md.tpr -f traj.xtc -ver 1

select group "1" (protein), and convert the output to PostScript with: g_xpm2ps -f ss.xpm

and view the result with: gv plot.eps

if "gv" is not installed on your computer, try "xpsview", "ghostview" or "gs". As can be seen, the secondary structure is rather stable during the simulation, which is an important validation check of the simulation procedure (and force-field) used. The next thing to analyse is the change in the overall size (or gyration radius) of the protein: g_gyrate -s md.tpr -f traj.xtc

(again, select group "1" for the protein) xmgrace gyrate.xvg

The analysis shows that the gyration radius fluctuates around a stable value and does not show any significant drift. Another important check concerns the behaviour of the protein surface: g_sas -s md.tpr -f traj.xtc

(again, select group "1" for surface calculation and group "1" for output) (Note that if the last command didn't work (didn't produce output for more than 30 seconds), please download a working version of g_sas from here, and make it executable with: chmod +x g_sas

and repeat the g_sas command from above). Now view the total solvent accessible surface area with:

xmgrace -nxy area.xvg

We now see three curves together: black for the hydrophobic accessible surface, red for the hydrophilic accessible surface, and green for the total accessible surface.

Question: Is the total (solvent-accessible) surface constant? Are any hydrophobic groups exposed during the simulation? Go back to Contents

Optional exercises You've probably noticed that in the simulation about only ten percent of the system that was simulated consisted of protein, the rest was water. As we are mainly interested in the protein's motions and not so much in the surrounding water, one could ask if we couldn't forget about the water and rather simulate the protein. That way, we could reach ten times longer simulations with the same computational effort!

Question: Why do you think that it is important to include explicit solvent in the simulation of a protein? To check if your assumption is correct, repeat the simulation of protein G, this time without solvent (to observe the effect more clearly, increase the length of the simulation by changing "nsteps" in the file "md.mdp" by e.g. a factor of ten).

Question: What are the main differences to the protein's structure and dynamics as compared to the solvent simulation? (Hint: use programs like g_rms and g_gyrate to analyse both simulations).

Let's go back to the first step in setting up the system - as we already know, building the topology of our protein can be done with the gromacs program pdb2gmx: pdb2gmx -f 1PGB.pdb -o conf_gromos.pdb

when prompted for the force-field to be used, now choose the GROMOS 43a1 instead of OPLS-AA/L. Use the more and rasmol commands as before to compare the result with the previous configuration - what difference do you find?

Question: How is the level of representation correlated with system size (number of atoms)? Go back to Contents

Further references: Principles of protein structure and basic in biophysics and biochemistry: Stryer, Biochemistry Voet, Fundamentals of Biochemistry Rev. Ed. Cantor and Schimmel, Biophysical Chemistry Part I: The conformation of biological macromolecules

Computer simulations and molecular dynamics: M. Karplus and A. McCammon. Molecular Dynamics simulations of biomolecules Nature structural biology 9: 646-652 (2002).[link] D.C. Rapaport. The Art of Molecular Dynamics Simulations - 2nd edn Cambridge University Press (2004).

Advanced reading: H. Scheraga, M. Khalili and A. Liwo. Protein-Folding Dynamics: Overview of Molecular Simulation Techniques Annual Review of Physical Chemistry 58: 57-83 (2007).[link] K Henzler-Wildman and D Kern. Dynamic personalities of proteins Nature 450: 964-972 (2007). K A Sharp and B Honig. Electrostatic Interactions in Macromolecules: Theory and Applications, Annual Review

of Biophysics and Biophysical Chemistry 19: 301-332 (1990). F M Richards. Areas, Volumes, Packing, and Protein Structure Annual Review of Biophysics and Bioengineering 6: 151-176 (1977). K A Dill, S B Ozkan, M Scott Shell and T R Weikl. The Protein Folding Problem Annual Review of Biophysics 37: 289-316 (2008). Go back to Contents For questions or feedback please contact Bert de Groot / [email protected]