A computational approach to predict the NF-kB inhibitors using the SMILES information of the molecules.
NF-kBIn is developed to predict the NF-kB inhibitors using the SMILES information of the molecules. In the standalone version, support vector classifier based model is implemented. NF-kBIn is also available as web-server at https://webs.iiitd.edu.in/raghava/nfkbin. Please read/cite the content about the NF-kBIn for complete information including algorithm behind the approach.
The Standalone version of NF-kBIn is written in python3 and following libraries are necessary for the successful run:
- scikit-learn
- Pandas
- Numpy
- openbabel (http://openbabel.org/docs/index.html)
- PaDEL-Descriptor (http://yapcwsoft.com/dd/padeldescriptor/PaDEL-Descriptor.zip)
To know about the available option for the stanadlone, type the following command:
python nfkbin.py -h
To run the example, type the following command:
python3 nfkbin.py -i example_input.txt
This will predict if the submitted molecules are NF-kB inhibitors or not. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma seperated variables).
usage: nfkbin.py [-h]
[-i INPUT
[-o OUTPUT]
[-t THRESHOLD]
[-d {1,2}]
Please provide following arguments for successful run
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: Moleculues in the SMILES format per line
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-t THRESHOLD, --threshold THRESHOLD
Threshold: Value between 0 to 1 by default 0.41
-d {1,2}, --display {1,2}
Display: 1:NF-kB inhibitors only, 2: All molecules, by default 1
Input File: It allow users to provide input in the SMILES format.
Output File: Program will save the results in the CSV format, in case user do not provide output file name, it will be stored in "outfile.csv".
Threshold: User should provide threshold between 0 and 1, by default its 0.16.
Display type: This option allow users to fetch either only NF-kB inhibitors by choosing option 1 or prediction against all molecules by choosing option 2.
It contantain following files, brief descript of these files given below
INSTALLATION : Installations instructions
LICENSE : License information
README.md : This file provide information about this package
model.zip : This zipped file contains the compressed version of model
nfkbin.py : Main python program
example_input.txt : Example file contain molecules in SMILES format
example_output.csv : Example output file