|This code has been put under version control in the project Pymol-script-repo|
Elastic Network Models (ENM) have been successful in reproducing fluctuations for proteins of native conformations. ENM is a coarse-grained method for modeling protein dynamics, meaning in generally in ENM each residue is represented by one bead in its Alpha Carbon position. These beads are then connected by elastic springs if the distance between two beads fall under a cutoff value (usually within the range of 7 to 15 angstroms). For more details please read here.
PyANM is developed as a cross-platform Pymol Plugin to allow its users to build and visualize Anisotropic Network Models, a member of the ENM family. This plugin allows its users to draw arrows or make movies based on calculated mode motions, to draw all springs used to build the ANM within the protein, to color the protein based on its Mean Square Fluctuations (MSF) calculated from ANM and to export data from ANM for future processing. PyANM also allows its users to change the colors and scales (sizes) for movies or arrows generated by PyANM for better visualization.
- PyANM requires Numerical Python (NumPy) to do all the matrix calculations. If you wish to use PyANM but don't have NumPy on your machine, please follow the download and build instructions here. If you will be using PyANM on a Windows machine, installing a Python distribution such as Anaconda might be easier. After installing NumPy, type the following line inside Pymol and if you don't see any error messages, you now have NumPy ready for Pymol!
- Having SciPy might improve the performance of PyANM but it is not required.
- PyANM has only been tested for Pymol 1.1 and higher, using an earlier version of Pymol might cause problems.
Download pyanm.py from this page, save it on your system, then go to Pymol-->Plugin-->Manage Plugins-->Install..., select the file you have just downloaded and then restart Pymol. Things might be different depending on your Pymol version and your local system, but this should be fairly similar.
After a successful installation, go to Pymol-->Plugin and you will see PyANM, click on it and you should see PyANM's interface just like in figure 1.
Now that you have PyANM installed, let's build one ANM together!
- Type the name of your protein structure under 'Select Structure', this could either be a valid 4-letter PDB (Protein Data Bank) ID or the name of a object you have already loaded into Pymol.
- You could also choose to upload a local file from your system using the 'Browse' button.
- If the check box 'Use only Alpha Carbons' is checked, even if you choose an all-atom structure, PyANM will coarse-grain the structure for you. Otherwise PyANM will build an all-atom ANM if an all-atom structure is used.
- If the check box 'Include HETATMs' is checked, PyANM will include atoms in PDB that starts with HETATM as well.
- So far there are two ANMs available for you to choose in PyANM : the cutoff model as described here and the Parameter Free Model described here, where spring constants are adjusted based on distance between two residues.
- If you choose to use Cutoff Model, you will be able to choose your desired cutoff value. The default value is 12 angstroms, personally I would recommend using any value between 7 angstroms to 15 anstroms.
- If you choose to use Parameter Free Model, you will be able to choose the power t for calculating spring constants for all residue pairs, where spring constant k for residue i and j is calculated as 1/distance(i,j) to the power of t. The default value for power t is 6.
Once you have selected the structure you wish to use as well as the model and its parameters, you should be able to build your ANM simply by clicking 'Build ANM'.A window will pop up telling you your ANM was built successfully once the calculation has finished. For a protein with less than 200 residues, this should take less than 10 seconds.
After building your ANM, you will be able to visualize all the springs in Pymol by simply clicking 'Show Springs' in PyANM.
See Figure 2 for a demonstration of all springs for HIV Protease (PDB ID: 1T3R) using cutoff model with cutoff value set as 12 angstroms.
Color by MSFs
One can also calculate the Mean Square Fluctuations (MSF) with all the modes calculated by ANM. ANM has been successful in getting high correlations between its calculated MSFs and experimental b-factors for most cases. Here PyANM allows you to color the structure based on its calculated MSFs just like Pymol colors a structure with its b-factors. Here the spectrum is from blue to red corresponding to from low values to high values.
Figure 3 shows the same HIV protease in figure 2 colored by its calculated MSFs.
You will be able to make harmonic fluctuation movies for different modes when you click 'Make Movies' after building your ANM. A dialogue will pop up asking for the desired modes you wish to make movies with. Modes are sorted with an ascending frequencies and the first 6 rigid-body modes are already discarded. So modes 1,2,3 will be the first 3 slowest modes.
Instead of making movies for different modes, you can also draw arrows for each residue for different modes. Each arrow's direction will point to the direction where the residue will move and each arrow's length will indicate the moving scale for each residue.
Figure 4 shows the arrows for mode 2 of HIV protease produced by PyANM.
This will allow you to save data calculated from PyANM to your local system for future processing. You can choose to save eigenvalues (frequencies for modes), eigenvectors (modes), MSFs, contact matrix or hessian matrix from Control Panel.
This is where PyANM allows you to change the scale (size) of the movies (arrows), or change color of the arrows (The color of movie objects could simply be changed like you change colors for other objects in Pymol). You could either predefine scales (sizes) or colors you would like before building your ANM or you could change these settings after you have made movies or arrows and these changes will happen real-time.
You could also select what attributes you would like to export to your local system here inside control panel. These data will be written as text files and Numpy-ready for future processing.
Thank you for using PyANM, please feel free to contact me at yuanwang (at) iastate (dot) edu about anything, especially if you are having problems with PyANM.