created using the name of the input file, time, and number of
the column in the input file (e.g., FOXO_20_2.txt means 20-s
time point and second column from the input file which was
named FOXO.txt).
3. Open PyMol and load the pdb file with the structure. Using
“copy” (https://pymolwiki.org/index.php/Copy) command,
get the desired number of copies corresponding to the number
of states and conditions prepared in the previous step. Also
name the objects so that the names correspond to the conditions and times from the dataset.
4. Within the PyMol command line, activate script data2bfactor.
py (see Note 39) by the command “run path/data2bfactor.py”
(where “path” stands for the absolute path to the folder, where
the script is saved on your computer), e.g., run C:\Python27
\Scripts\data2bfactor.py.
5. Reset the b factors to a number that is outside the dataset (e.g.,
99). This will later allow you to color the regions that are not
covered by the peptides in the dataset. Enter command “alter
object_name, b¼99” (where “object_name” stands for the
name of an individual object/structure chosen by the user).
6. Color the structure(s) to some neutral, uniform color using
command “color.” E.g., “color grey70.”
7. Apply your data onto the individual structures. Use command
“data2b_res object_name, path.” For example, data2b_res
FOXO_20_WT-MUT, C:\Data\FOXO_20_2.txt (i.e., second
column of the input file for HDXPeptideSplitter.py script
contained difference between wild-type and mutant). Do this
for all structures/objects in PyMol and all input text files.
8. Now select residues with all negative and positive b values,
respectively. Enter commands “select negative, b<0.0” and
“select positive, b>0.0.”
9. Color these selections using commands “spectrum b, selection¼negative,
minimum¼-X,
maximum¼0.0,
palette¼blue_white”
and
“spectrum
b,
selection¼positive,
minimum¼0.0, maximum¼X, palette¼white_red,” where X is
the highest/lowest number in your dataset. Negative (whiteto-blue gradient) differences are regions where the exchange
was lowered, and positive (white-to-red gradient) are regions
with increased deuteration.
10. Finally, differentiate the regions that were not covered by peptides in the dataset. Run command “color black, (b¼99).”
11. Optionally show a colorbar with the scale using command
“ramp_new colorbar, none, [-X, 0.0, X], [blue, white, red].”
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the column in the input file (e.g., FOXO_20_2.txt means 20-s
time point and second column from the input file which was
named FOXO.txt).
3. Open PyMol and load the pdb file with the structure. Using
“copy” (https://pymolwiki.org/index.php/Copy) command,
get the desired number of copies corresponding to the number
of states and conditions prepared in the previous step. Also
name the objects so that the names correspond to the conditions and times from the dataset.
4. Within the PyMol command line, activate script data2bfactor.
py (see Note 39) by the command “run path/data2bfactor.py”
(where “path” stands for the absolute path to the folder, where
the script is saved on your computer), e.g., run C:\Python27
\Scripts\data2bfactor.py.
5. Reset the b factors to a number that is outside the dataset (e.g.,
99). This will later allow you to color the regions that are not
covered by the peptides in the dataset. Enter command “alter
object_name, b¼99” (where “object_name” stands for the
name of an individual object/structure chosen by the user).
6. Color the structure(s) to some neutral, uniform color using
command “color.” E.g., “color grey70.”
7. Apply your data onto the individual structures. Use command
“data2b_res object_name, path.” For example, data2b_res
FOXO_20_WT-MUT, C:\Data\FOXO_20_2.txt (i.e., second
column of the input file for HDXPeptideSplitter.py script
contained difference between wild-type and mutant). Do this
for all structures/objects in PyMol and all input text files.
8. Now select residues with all negative and positive b values,
respectively. Enter commands “select negative, b<0.0” and
“select positive, b>0.0.”
9. Color these selections using commands “spectrum b, selection¼negative,
minimum¼-X,
maximum¼0.0,
palette¼blue_white”
and
“spectrum
b,
selection¼positive,
minimum¼0.0, maximum¼X, palette¼white_red,” where X is
the highest/lowest number in your dataset. Negative (whiteto-blue gradient) differences are regions where the exchange
was lowered, and positive (white-to-red gradient) are regions
with increased deuteration.
10. Finally, differentiate the regions that were not covered by peptides in the dataset. Run command “color black, (b¼99).”
11. Optionally show a colorbar with the scale using command
“ramp_new colorbar, none, [-X, 0.0, X], [blue, white, red].”
HDX-MS of Protein-DNA Complexes
211