SASSIE tutorial for the 2012 ACNS annual meeting

In this tutorial you will begin using the main SASSIE modules to generate structures for a protein with unstructured regions and find an ensemble of structures that best fits the SANS data.

The SANS data is from a protein (DBD) that is a subunit of a larger protein complex (courtesy of Mike Rodgers, Johns Hopkins U). It contains a ~13 AA residue unstructured region at its C-terminus along with some smaller unstructured regions in other locations. This tutorial will begin with a starting structure that includes all AA residues that were present in the measured SANS sample.

The following SASSIE modules will be covered:

Data Interpolation

Protein Monomer Configuration Generator

Xtal2sas

Chi-Square Filter

Density Plot

Working directory: “/path/of/tutorial/”SASSIE_tutorial/problems/

(note; remember the path to this directory from time of install)

Structure Minimization and Data Interpolation are performed only once before generating configurations. Structure Minimization is a necessary step to ensure you have the lowest-energy, optimized starting structure. This step is skipped in the present tutorial by starting from a structure (4309r2.pdb) that has already been minimized. Data Interpolation is a critical step that will be discussed later on in the tutorial (this allows for the generated scattering profiles to the have the same number of points and Q-range as the SANS data).

The order of these two procedures does not matter. Then, configurations can begin to be explored. SASSIE modules write files in particular hierarchy. SASSIE is started from the working directory. You will choose a project name, which becomes the top directory for that particular project. Each module writes files in a PARTICULAR subdirectory of the project directory. These subdirectory names will become apparent as we work through the tutorial modules. Many temporary files are written as the modules are running. Thus, it is important that ONLY ONE SASSIE program is running from a particular working directory at any time. Multiple modules CANNOT run at the SAME TIME from the SAME WORKING DIRECTORY even if they are using different project names. Otherwise, important files will be overwritten and/or output files will be written in the wrong place, making it impossible for subsequent modules to find them. It is important to be aware of which directory you are in at all times! You can always type, “pwd” from a terminal to find out your current directory.

A working knowledge of the protein sequence and possible flexible regions of the protein is assumed prior to running SASSIE. In this case, there are 3 possible flexible regions. The disordered C-terminal tail consisting of amino acid residues 105-118, a small flexible region defined by residues 46-48 and a third region made up of residues 68-71. Depending on your own system, you may want to include or exclude given linker regions in your favorite protein. Here we will include all 3 regions to allow for maximum Rg converage in order to obtain better fits to the SANS data.

It is also assumed that preliminary analysis has been performed on the SANS data, i.e., Guinier and/or P(r), such that the experimental values for Rg and the forward scattering, I(0), are known. In this case, Guinier fits to the data resulted in Rg = 19.7 Å 0.6 Å and I(0) = 0.042 cm-1.

TO BEGIN:

Open a Linux terminal and go to the “/your/tutorial/path/”SASSIE_tutorial/problems/ working directory. Make sure the file “sassie_gui.py” is present by typing “ls”. If it isn’t there, copy it into the directory.

cp “/your/sassie/path/”sassie_gui.py .

NOTE: the trailing period in the command above.

Data Interpolation

Files: “/your/tutorial/path/” SASSIE_tutorial/problems/

sansdata.sub

Directory:“/your/tutorial/path/”SASSIE_tutorial/problems/data/interpolate

(you will create and populate)

Procedure:

Select the Data Interpolation module and fill in the project name, input filename and output filename fields. The project name can be the same one that you chose for the Structure Minimization. Then, fill out the I(0) and I(0) error fields based the initial fits of the SANS data. Chose a reasonable delta Q and number of points to span the range of the SANS data.

Figure 1. Data Interpolation Screen.

There is an IMPORTANT ISSUE to be aware of when filling in these fields! The strategy used in SASSIE is to interpolate the data ONCE at the beginning of the process so that the interpolated experimental data can be compared to model SANS curves calculated from the many generated structures without having to re-interpolate each time. However, this means that the delta Q and number of points MUST MATCH the output of whatever software is being used to calculate SANS data from model structures. At present, SASSIE supports Xtal2sas, an internal NCNR program, and Cryson, from the D. Svergun software suite. Table 1 below shows possible values for the Data Interpolation parameters. These parameters can be adjusted accordingly, depending on the values that will be used in the Xtal2sas or Cryson program. Again, the crucial point is that delta Q and the number of points from the output of Xtal2sas or Cryson MUST match those in the interpolated data file. If they don’t match, the comparison to SANS data performed in the Chi-Square Filter module WILL fail!

Table 1. Data Interpolation Parameters for Xtal2sas and Cryson.

Software to be used to Calculate SANS	Qmax (Å-1)	Delta Q (Å-1)	number of points
Xtal2sas	0.3	0.005	60
Cryson	0.3	0.005	61

Run the program by clicking the button at the bottom of the window. Remember to press Return to clear the plot and continue SASSIE when ready.

Examine the output in the black region at the bottom of the screen, in the vmd console window and in the “/your/tutorial/path/”SASSIE_tutorial/problems/data/interpolate subdirectory to determine what information is written.

Monomer Configuration Generator

Files: “/your/tutorial/path/”SASSIE_tutorial/problems/

4309r2.pdb

Directory: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/generate/

(you will create and populate)

Select the Protein Monomer Configuration Generator module and fill in the project name, output filename, input filename in the User Input Section of the window. At this point, it is a good idea to choose a new project name that will be kept the same for the Xtal2sas and the Chi Square Filter modules that will use the input from this module. Fill in the number of trail attempts field.

Figure 2. Protein Monomer Configuration Generator User Input Screen.

The Protein Specific Input section is filled out based on the possible flexible regions in the protein. The number of flexible regions to vary is 3. A value must be present in the MAX [dtheta] field for EACH flexible region. For this example, the default value can be used.

The possible flexible regions are shown in yellow below.

Figure 3. Possible Flexible Regions for DBD Protein.

Based on the table below, fill in the first amino acid per region and the number of contiguous amino acids per region fields.

Table 2. Flexible Region Details for DBD Protein.

Possible flexible regions	Residue range	First amino acid, # of contiguous
1	46-48	46,3
2	68-71	68,4
3	105-118	105,10*

*The number of contiguous amino acids must be shortened for region 1 since it is at the end of the molecule.

Fill in the structure alignment: low residue and structure alignment: high residue fields. This can be any region that is not flexible. For this example, choose region 50-60.

Figure 4. Monomer Configuration Generator Protein Specific Input Screen.

Examine the inputs in the Non-standard/Specialized Input section. For this example, these features are not being used and nothing needs to be changed.

Figure 5. Monomer Configuration Generator Specialized Input Screen.

Run the program by clicking the button at the bottom of the window.

Examine the output in the black region at the bottom of the screen, in the console window and in the “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/generate subdirectory to determine what information is written.

Examine the generated structures by playing the trajectories using the animation buttons in the Main VMD window.

Xtal2sas (Calculation of Model SANS Data)

Files: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/generate/

4309r2.pdb

run_1.dcd (dcd file generated by monomer configuration module)

Directory: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/xtal2sas/

(you will create and populate)

Select the Xtal2sas module and fill in the project name, input filename, output filename in the Data Management Section.

Fill in the maximum Q value and number of I(Q) values in the User Input Section. These values MUST AGREE with the values in the interpolated data file! Thus, be sure that the values entered for Qmax and the number of points will produce model SANS data files with the same number of points, Qmax and delta Q value as the interpolated data file. In this case, the number of I(Q) values is 60 and the maximum Q value is 0.3, so that we can match the data we wrote with the Data Interpolation module.

Fill in the percent of D2O in the solvent by volume (100% in this case), and the fraction of exchangeable hydrogens that are assumed to exchange (0.9 is a reasonable value) in the Neutron Specific Input section.

Figure 6. Xtal2sas Screen.

Run the program by clicking the button at the bottom of the window.

Examine the output in the black region at the bottom of the screen, in the console window and in the “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/xtal2sas/ subdirectory to determine what information is written.

Chi-Square Filter

Files: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/

sansdata.dat (interpolated data file copied into working directory)

“/your/tutorial/path/”SASSIE_tutorial/problems/run_1/xtal2sas

*.log

*.iq

Directory: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/filter

(you will create and populate)

Select the Chi-Square Filter module and fill in the project name, the interpolated SAS experiment filename and the experimental I(0) value (given at the beginning of this lab).

Figure 7. Chi-Square Filter Screen

Run the program by clicking the button at the bottom of the window.

Look at the 2 vs Rg plot and the plot of the best, worst and ensemble average model data file(s) vs the SANS data.

Examine the output in the black region at the bottom of the screen, in the console window, and in the ./run_1/filter subdirectory to determine what information is written.

Density Plot for All Generated Structures

Files: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/generate/

4309r2.pdb

run_1.dcd

Procedure:

a)	Select the Density Plot module and fill in the project name, input filename, reference pdb and output filename fields.

Figure 8. Density Plot Screen for All Generated Structures.

b)	Fill in the xlength, ylength and zlength fields with values that are large enough to draw a box around the molecule. The ./run_1/generate/*.minmax files will give an idea of the size of the molecule in each direction. The box should be at least that size. If the box size is too small and the density calculation fails, a larger size can be entered and the calculation can be tried again.

c)	Fill in the number of regions, low regions and high regions fields. The purpose of choosing density plot regions is to be able to represent them separately when they are plotted. This helps visualize certain regions, such as the region that was fixed while generating configurations. The regions are chosen by low and high residue number for each region. One possible choice is shown in the table below. It was chosen based on the location of the 3 flexible regions specified in the Protein Monomer Configuration Generator module and the defined structure alignment region (residues 50-60).

Table 3. Density Plot Regions for DBD Protein.

Region	Low Residue	High Residue
1 (1-49)	1	49
2 (50-67)	50	67
3 (68-104)	68	104
4 (105-118)	105	117*

*Last residue number is omitted since it is at the end of the molecule.

d)	For the first run through, keep the equalweights field at the default value of 1. When the equalweights parameter is set to 1, the weights filename field is not used. Thus, a density plot of all of the generated structures will be produced.

e)	Run the program by clicking the button at the bottom of the window.

f)	Examine the output in the black region at the bottom of the screen, in the console window, and in the ./run_1/density subdirectory to determine what information is written.

Density Plot for Best-Fit Structures to SANS Data

Files: “/your/tutorial/path/”SASSIE_tutorial/problems/run_1/generate/

4309r2.pdb

run_1.dcd

“/your/tutorial/path/”SASSIE_tutorial/problems/run_1/filter/

x2lowweights.txt

Procedure:

a)	Select the Density Plot module and fill in all the fields the same way as for step 1 EXCEPT for the equalweights field. This time, the equalweights value should be set to 0 so that a density plot consisting of ONLY THOSE STRUCTURES flagged in x2lowweights.txt is created.

b)	Run the program by clicking the button at the bottom of the window. (IMPORTANT: when the following window pops up, choose “NO” so that the new density plot date will be populated under the previous directory. The file names will be different so nothing will be overwritten.)

c)	Examine the output in the black region at the bottom of the screen, in the console window and in the ./run_1/density subdirectory to determine what information is written.

d)	Close all SASSIE windows and Close all SASSIE windows and exit SASSIE by clicking the Quit button at the bottom of the SASSIE menu.

Compare All-Structure and Best-Fit Density Plots using VMD

Open VMD. Load the files ending in “complete.cube” from the ./run_1/density subdirectories.

Choose the Molecule Coloring Method and Isosurface Drawing Method. The Isovalue will need to be set to a low number in order for the surface density plots to accurately represent the full configuration space of the ensemble of structures. (The trajectory file and its corresponding pdb file can also be loaded if desired in order to confirm that the isosurface plot is an accurate representation of the structure configuration space.) For this exercise, choose 0.001 for the isovalue. It will need to be typed in by hand in the isovalue field. When comparing isosurfaces, the isovalues should be THE SAME for all.

Choose Isosurface from the pull down menu in the Show field and Solid Surface from the pull down menu in the Draw field. Make the density_lowt surface opaque and the density_eqwt surface transparent. The display should look something like the picture below. The entire configuration space examined in this exercise is shown in blue and the configuration space occupied by the best-fit structures to the SANS data is shown in red.

Figure 9. Single-Region Density Plots for DBD Protein

While this “complete” representation is useful, it doesn’t show which regions of the molecule are occupying which portion of configuration space. In order to better visualize this, the exercise is continued below.

Exit and restart VMD and Load the files ending in “region_1.cube”, “region_2.cube”, “region_3.cube” and “region_4.cube” from the density subdirectories. Be sure to select New Molecule before loading each file. Eight molecules should be loaded in all.

Display the density plots using the Isosurface Drawing Method with an Isovalue of 0.001. Using the parameters in the table below, the display should look something like the picture below the table.

Table 4. Suggested Representations for Density Plot Regions.

File	Coloring Method	Draw
unequalweights_region_1	ColorID 1	Solid Surface transparent
unequalweights_region_2	ColorID 0	Solid Surface opaque
unequalweights_region_3	ColorID 7	Solid Surface transparent
unequalweights_region_3	ColorID 6	Solid Surface transparent
equalweights_region_1	ColorID 1	Wireframe
equalweights_region_2	ColorID 0	Wireframe
equalweights_region_3	ColorID 7	Wireframe
equalweights_region_4	ColorID 6	Wireframe

Figure 10. 4-Region Density Plots for DBD Protein

To make it easier to distinguish the density plot of the total configuration space from that of the best-fit configuration space, the two density plots can be rendered separately. In this case, it is important to make sure that the isosurfaces are being shown on the SAME SCALE so that an accurate comparison can be made. Toggle the D flag in the VMD main window to make the four equalweights regions invisible. (You will need to toggle it for each region.) Render the display of the unequalweights density plot and save the resultant picture file. Then, make the equalweights regions visible and the unequalweights regions invisible by toggling the D flag for all 8 regions. Change the Draw parameter to Solid Surface for each in the Graphical Representations window. Make equalweights_region_2 opaque and the other 3 regions transparent. DON’T change ANYTHING else, especially the scale. Render the display and save the resultant picture file. The density plots can now be compared side-by-side, as long as they are on the same scale, as shown below.

Total Configuration Space	Best-Fit Configuration Space

Figure 11. 4-Region Density Plots for DBD Protein – Rendered Separately

Exit VMD.

References;

Xtal2sas;

Krueger S, Gorshkova I, Brown J, Hoskins J, McKenney KH, Schwarz FP.

Determination of the conformations of cAMP receptor protein and its T127L,S128A mutant with and without cAMP from small angle neutron scattering measurements. (1998) J Biol Chem., 273(32):20001-6.

Cryson;

Svergun D.I., Richard S., Koch M.H.J. Sayers Z., Kuprin S., & Zaccai (1998) Protein hydration in solution: experimental observation by X-ray and neutron scattering Proc. Natl. Acad. Sci. USA, 95, 768-773.S

Links;

NIST Center for Neutron Research (NCNR)/ National Science Foundation (NSF) Summer School on Modeling Neutron Data for Biological Systems

http://www.ncnr.nist.gov/summerschool/ss11/index_model.html

SASSIE program webpage;

http://www.smallangles.net/sassie/