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A Python based virtual screening software!

Project description

Installation (Requires Python 3.9 and above)

Use the following command:

pip install nrgrank

Using NRGRank in a python script:

from nrgrank import process_target, process_ligands, nrgrank_main

Preparatory steps

1. Preprocessing the target

Required Arguments

Argument Description Possible value(s)
target_mol2_path Path to target mol2 file Absolute path
binding_site_file_path Path to binding site file generated by GetCleft Absolute path

Optional Arguments

Flag Description Possible value(s)
create_new_dir A new folder will be created to store generated files True,False
overwrite Allows overwriting existing files True,False

Example command

target_save_dir = process_target(target_mol2_path='foo/bar/target.mol2', binding_site_file_path='foo/bar/bd_site_sph_1.pdb')

2. Preparing the ligands

All ligands for one screen must be in the same mol2 file

Required Arguments

For running on a single mol2 file:

Flag Description Possible value(s)
ligand_path Path to ligand mol2 file Absolute path
conformers_per_molecule Number of conformers per molecule Int

Optional Arguments

Flag Description Possible value(s)
overwrite Allows overwriting existing files True,False
ligand_type Assign a specific ligand type recognised by NRGRank. Can be useful for benchmarking. (str)
output_dir Folder where generated files will be stored Absolute path

Example commands:

ligand_save_dir = process_ligands(ligand_path='foo/bar/ligands.mol2', conformers_per_molecule=1)

NRGRank

Required Flags

Flag Description Possible value(s)
target_name The name of the target. Used for naming the output CSV file when csv_and_pose_name is not specified (str)
preprocessed_target_path Path to the preprocessed target folder (e.g., output from process_target()) Absolute path
preprocessed_ligand_path Path to the preprocessed ligand folder (e.g., output from process_ligand()) Absolute path
result_folder_path Directory path where the docking results will be stored Absolute path

Optional Flags

Flag Description Possible value(s)
result_csv_and_pose_name Custom name for CSV and pose files. If not given, defaults to target_name (str)
ligand_type Type of ligand being processed. Useful when benchmarking with DUD-E "ligand", "active", "decoy"
ligand_slice Slice range of ligands to process list[int] or None
write_info Write informational remarks to output (e.g., .txt log) True, False
write_file Output result file(s) True, False
output_dictionary Output results as a Python dictionary True, False
file_separator Separator character for the result file (CSV/TSV) ",", "\t"
output_header Write a header row in the CSV file True, False
save_time Save time taken per molecule for docking True, False
normalise_score Normalise docking score by number of atoms in molecule True, False
unique_run_id Unique identifier to avoid file name conflicts and used to name ligand poses (str)
user_config Arbitrary keyword arguments for overriding default docking parameters key=value pairs

Example commands:

result_file_path, result_csv_lines = nrgrank_main(target_name='target', 
                   preprocessed_target_path='foo/bar/preprocessed_target', 
                   preprocessed_ligand_path='foo/bar/preprocessed_ligands_1_conf',
                   result_folder_path='foo/bar/results')

Returns the path to the result file and the lines contained in the result csv

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