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Analyze generated data

First step: load required modules

import sys

# Define the path to of the package
package_dir = '/path/to/MICLOT'

# Add the 'miclot' package directory to sys.path
if package_dir not in sys.path:
    sys.path.insert(0, package_dir)

Now you can import the packages:

import miclot.data_analysis as mca

A. Clean data

A.1. Clean structure information

Code

cleaning.structure('/Data/1acb')

Result

Return the dataframe and save it as CSV file.

A.2. Clean neighbor residues

Code

cleaning.neighbor_residues('/Data/1acb')

Result

Return the dataframe and save it as CSV file.

A.3. Clean interactions table

Code

cleaning.interactions_table('/Data/1acb')

Result

Return the dataframe and save it as CSV file.

A.4. Clean neighbor pairs

Code

cleaning.neighbor_pairs('/Data/1acb')

Result

Return the dataframe and save it as CSV file.

B. Concatenate CSV files

B.1. Concatenate any CSV files, based on name (or motif in name)

Code

concatenate.csv_file('/Data', 'uniprot', use_tqdm=True)

Result

Concatenate all CSV file contained 'uniprot' in their name and located in subdirectories of '/Data', and display progress bar. The final file is written as 'final_uniprot.csv' and logfile name 'concatenate_uniprot.log' is created.

B.2. Concatenate all files containing ASA information

Code

df = concatenate.ASA('/Data')
print(df)

Result

The final CSV file is written.

        complex      receptor       ligand    interface   PDB
0  13146.739273  10505.114157  4322.435392  1680.810276  1acb
1  10313.511142   5628.519333  6421.277673  1736.285864  1i8k
2  10064.572511   5926.323958  5809.856860  1671.608307  4h5s
...

B.3. Concatenate all interaction_table files

Code

concatenate.interaction_table('/Data')

Result

The final CSV file is written.

B.4. Concatenate all neighbor_residues files

Code

concatenate.neighbor_residues('/Data')

Result

The final CSV file is written.

B.5. Concatenate all neighbor_pairs files

Code

concatenate.neighbor_pairs('/Data')

Result

The final CSV file is written.

B.6. Concatenate all structure files

Code

concatenate.structure('/Data')

Result

The final CSV file is written.

C. Class `plot`

C.1. Plot minimization energies

C.1.1. Normal usage

It is possible to prive directory or file path in the command.

# directory path
a = plot.minimization('/Data/1acb/')
a.show()

# file path
a = plot.minimization('/Data/1acb/1acb_noHETATM_pqr_fixed_minimization_log.csv')
a.show()

C.1.2. Change the structure name in the title

If you want to change the name in the title, you can modify it using pdb_name argument.

a = plot.minimization('/Data/1acb/1acb_noHETATM_pqr_fixed_minimization_log.csv', pdb_name='Hydrolase/Hydrolase inhibitor')
a.show()

C.1.3. Saving the graph

plot.minimization('/Data/1acb/1acb_noHETATM_pqr_fixed_minimization_log.csv', save_graph=True)

C.1.4. Example of output

D. Remove files

D.1. Remove all generated plots

Code

removed_files, error = remove.plots('/Data/1acb')
print(removed_files)
print(error)

Result

['/Data/1acb/1acb_noHETATM_pqr_fixed_minimization_log_plot_minimization_energies.png']
[]

D.2. Remove all generated clean data

Code

remove.clean_data('/Data/1acb')

Result

Remove all CSV files with 'clean' in their name.

D.3. Remove all generated saved class files

Code

remove.pickles('/Data/1acb')

Result

Remove all pkl.gz files with 'class' in their name.

D.4. Remove any file(s)

Code

remove.files('/Data/1acb', name='hydrolase', file_format='pdb')

Result

Remove any pdb file containing 'hydrolase' in their name in the directory '/Data/1acb'.

E. (Re)Generate the distance map

Important

Normally the distance map is automatically generated by neighbor_residues or neighbor_pairs commands if the file *.distance_map.csv don't exist. But if any problem occure, it'is possible to regenerate it using the following command.

Code

make_distance_map('/Data/1acb')

Result

Generate the file 1acb_distance_map.csv