A Comprehensive Topological Indicator for Small Molecule Complexity
(Created by the Waldmann Lab at the Max Planck Institute of Molecular Physiology, Dortmund)
The score is intended for assessing molecular topology of organic molecules and to improve upon the idea of the fraction of stereo and sp3 carbons. The score is described in our J. Med. Chem. paper: Spacial Score – A Comprehensive Topological Indicator for Small Molecule Complexity.
--> The SPS indicator is now also a part of the RDKit package and available through the rdkit.Chem.SpacialScore module. SPS script is actively mantained as part of the RDKit package, and thus, it is recommended to calculate the SPS through RDKit.
The script requires RDKit package and NumPy.
To install the required packages through Conda, simply use the environment.yml file:
conda env create -f environment.yml
The script can be used after activation of the just created conda environment:
conda activate my_sps_env
To display the options of spacial_score.py, type:
python spacial_score.py -h
(Please remember that spacial_score.py needs to be in your current directory)
The script can be used directly from a command line, reading either a directly provided SMILES string (-s) or a .csv/.tsv file (-i):
usage: spacial_score.py [-h] [-s SMILES string] [-i filename.ext] [-o filename.ext] [-t] [-v] [-p]
Script for calculating Spacial Score (SPS) or normalised SPS (nSPS) for small molecules.
The script can calculate the scores for a direct SMILES input or for a .csv or .tsv file containing a list of SMILES.
nSPS is calculated by deafult.
optional arguments:
-h, --help show this help message and exit
-s SMILES string Your input SMILES string for which to calculate the score
-i filename.ext Your .csv or .tsv file containing column called "Smiles" which contains SMILES strings. Resutls will be
saved in a new .csv file
-o filename.csv You can specify name of the output .csv file. Not required.
-t Option to calculate total SPS (no normalisation).
-v Option to print verbose results, with information for each atom index.
-p Option to print confirmation after processing of each SMILES string in a file.
To calculate nSPS directly from a SMILES string you can just type:
python spacial_score.py -s CC(C)CBr
Where CC(C)CBr is just an example of a SMILES string (on Linux you may need to use quotation marks "CC(C)CBr"). This returns:
Normalisation Applied: True
SMILES: CC(C)CBr
Calculated nSPS: 9.6
To calculate the un-normalised (total) SPS you need to add option -t:
python spacial_score.py -s CC(C)CBr -t
This returns:
Normalisation Applied: False
SMILES: CC(C)CBr
Calculated SPS: 48
A more verbose output can be achieved with the option -v:
python spacial_score.py -s CC(C)CBr -v
The output:
SMILES: CC(C)CBr
Atom Idx Element Hybrid Stereo Ring Neighbs
------------------------------------------------------------
0 C 3 1 1 1
1 C 3 1 1 9
2 C 3 1 1 1
3 C 3 1 1 4
4 Br 3 1 1 1
------------------------------------------------------------
Total Spacial Score: 48
Per-Atom Score: 9.6
To read in a .csv or .tsv file, please type:
python spacial_score.py -i your_input_file_name.csv -o your_output_file_name.csv
nSPS is calculated by default, and option -t can be used to calculate un-normalised SPS.
Please, remember that your input file needs to contain a column named Smiles containing SMILES which will be used for the calculation of the scores.
Examples of input and output files can be found in the folder named example_input_output_files.
The scores can also be calculated by using function:
def calculate_score_from_smiles(smiles: str, per_atom=False, verbose=False) -> float:
""" Calculates the spacial score as a total SPS or size-normalised, per-atom nSPS for a molecule.
Parameters:
===========
smiles: valid SMILES string
per_atom: flag to denote if the normalised per-atom result (nSPS) should be returned
verbose: flag to denote if the detailed scores for each atom should be printed
Returns:
========
Total or per-atom numeric spacial score for the provided molecule.
"""
The script in spacial_score.py can be tested by running pytest. In the active my_sps_env conda environment type:
pytest
Correct output will look like this:
collected 7 items
test_spacial_score.py ....... [100%]
================================================== 7 passed in 0.48s ==================================================