All of the following scripts must be present in the same directory (script_dir):

class_fit2.py

class_hb.py

class_titr.py

create_titr.py

fitting2.py

fitting_models.py

make_figinstr2.py

misc_functions.py

program_scripts.py

settings.py

figures2.py

To run scripts, you must execute them by typing: "python script_dir/script.py"

Directories:

Files:

1. Create a directory where the analysis will take place (/analysis)

2. Prepare peak list files.

· Sparky Peak List Files: For each spectrum in Sparky, create a peak list file (use the lt command) and save it in the analysis directory.  Files must have a ‘.list’ extension.

· Sparky Save Files: Using the Harms’ sparky_extract-peaks.py program, generate a peak summary file with extension ‘.mjh’.

· Manually created files: Create your own titration file.  File must be tab-delimited and the first row of the file must contain headers.  The file name must end with ‘CS-pH.txt’.

3. Create a titration.log file in the analysis directory.  This file will store the information about the titration – protein, salt condition, temperature, magnet, and the name of the titration experiment.  The name of the experiment is the most critical, as it will be used by downstream programs for plotting purposes.

4. In the analysis directory, run create_titr.py This script will generate.

# Fit control file example

#

# 20060515

#

fit_type: one_site_mHb, fit_program: R, atom_type: CG, res_type: ASP, which: all

ASP_19, not-fitable ASP_21, not-fitable

ASP_40, CS_AH1: 175.37, CS_A_: 179.10, pKa1: 3.85, n1: 0.57

ASP_77, not-fitable ASP_83, not-fitable

ASP_95, not-fitable

ASP_143, CS_AH1: 176.72, CS_A_: 180.08, pKa1: 3.78, n1: 0.76

ASP_146, CS_AH1: 176.84, CS_A_: 180.37, pKa1: 3.85, n1: 0.76

end

fit_type: two_site_b, fit_program: R, atom_type: CG, res_type: ASP, which: select

ASP_21, CS_AH2: 176.60, CS_AH1: 176.20, CS_A_: 179.87, pKa1: 3.01, pKa2: 6.54

end

If a particular resonance can not be fitted (e.g. Asp-77 chemical shift exhibits no pH dependence) then the line should read ‘ASP_77, not-fitable’).

The format of a fit instruction line should be:
[residue type]_[residue number], [parameter_name]: [value], [parameter_name]: [value]
example:

GLU_43, CS_AH1: 179.69, CS_A_: 184.07, pKa1: 4.32, n1: 0.70

ASP_95, fixed~CS_AH1: 178.01, CS_A_: 181.66, pKa1: 2.0, n1: 0.8

Lines that are not read by fitting.py begin with ‘#’. The file is broken up into sections that begin with ‘fit_type’ and end with ‘end’.  Each section uses a different fit model and fits different residue  and atom types.  There are five essential parameters on the fit_type line:

To fix a parameter, please add “fixed~” to the front of the parameter.

6. Run fitting2.py in the analysis directory. This script uses the gnls function in R. This script will read the .fit files and create

7. Create a subdirectory called ‘plots’.

8. Copy (or symbolically link) the titr_fit.pickle file (if already fitted) or the titr.pickle file to the plots directory

9. Within the plots directory, create a figure instruction file by running make_figinstr2.py.  This script will create a file called instructions.txt with plot parameters.  All of the fits performed will be listed in this file

10. Edit the instructions.txt file.  Here is an example file:

rows: 5, columns: 4, page_margins: 0.5_0.5_0.5_0.5

x_range: 1_9, y_amplitude: 4.5, plot_margins: 0.15_0.15_0.15_0.15, show_pKa: y

name: DPPHS_25C_0p10M-KCl_2

figure_1

ASP_19_CG, DPPHS_25C_0p10M-KCl_2: two_site_b--fixed~CS_AH2:177.43

figure_2 ASP_21_CG, DPPHS_25C_0p10M-KCl_2: two_site_b

Instructions for each data set to be plotted is written as follows:
[descriptor], [titration_name]: [fit_name]

GLU_101_CD, DPPHS_25C_0p10M-KCl_2: one_site_mHb

The descriptor contains three fields: residue_type, residue_number, and atom_type.  These fields are combined into one string using ‘_’.

If multiple fits are to be plotted for the same data set, the fit names must be separated by a comma:

one_site_mHb, one_site_mHb--fixed~CS_AH1:179.18

If multiple data sets are to be plotted on the same figure, they only need to be defined on separate lines:

figure_6
ASP_95_CG, DPPHS_25C_0p10M-KCl_3: one_site_mHb--fixed~CS_AH1:178.02
ASP_95_CG, DPPHS_25C_1p00M-KCl_1: one_site_mHb

11. Edit settings.py to incorporate the plot settings for that titration data set:

12. Run figures2.py by typing "figures2.py instructions.txt" in the plots directory.  This will create a instructions_.ps file which you can open in Ghostscript/Ghostview (on Windows) or Preview (on Macs) or display (on Unix).

'DPPHS_25C_0p10M-KCl_1' : {'color': 'black', 'pch': 21, 'bg': 'red'}

NMR Data fitting tool

Documentation