Several methods have been developed for the prediction of the antigenic regions for subunit vaccines designing. Interleukin-6 (IL-6) is a rapidly produced proinflammatory cytokine generated as an immune response in various infections and tissue injuries. The elevated level of IL-6 causes cytokine release syndrome(CRS) in severe COVID-19 patients. Based on existing knowledge, we develop an in silico tool that allows the user to predict, scan, and map the IL-6 inducing/non-inducing peptides.
Dhall A, Patiyal S, Sharma N, Usmani SS, Raghava GPS (2020) Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19. Brief Bioinform. 22(2):936-945 .
The pip version of IL6pred is also available for easy installation and usage of the tool. The following command is required to install the package
pip install il6pred
To know about the available option for the pip package, type the following command:
il6pred -h
https://webs.iiitd.edu.in/raghava/il6pred/
git clone https://github.com/raghavagps/il6pred
change dir il6pred
unzip RF_model.zip
python il6pred.py -i peptide.fa
IL6Pred is developed for predicting, desiging and scanning interleukin-6 inducing peptides. More information on IL6Pred is abvailble from its web server http://webs.iiitd.edu.in/raghava/il6pred . This page provide information about stnadalone version of IL6Pred. Please read/cite following paper for complete information including algorithm behind IL6Pred.
Models: In this program, one model has been incorporated for predicting interleukin-6 inducing peptides. The model is trained on IL-6 inducing and non-inducing peptides.
Modules/Jobs: This program implement three modules (job types); i) Predict: for predictin interleukin-6 inducing peptides, ii) Design: for generating all possible peptides and computing interleukin-6 inducing potential (score) of peptides, iii) Scan: for creating all possible overlapping peptides of given length (window) and computing interleukin-6 inducing potential (score) of these overlapping peptides.
Minimum USAGE: Minimum usage is "python il6pred.py -i peptide.fa" where peptide.fa is a input fasta file. This will predict the interleukin-6 inducing potential of sequence in fasta format. It will use other parameters by default. It will save output in "outfile.csv" in CSV (comma seperated variables).
Full Usage: Following is complete list of all options, you may get these options by "python il6pred.py -h"
il6pred.py [-h] -i INPUT [-o OUTPUT] [-j {1,2,3}] [-t THRESHOLD]
[-w {5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25}]
[-d {1,2}]
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: protein or peptide sequence in FASTA format or single sequence per line in single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-j {1,2,3}, --job {1,2,3}
Job Type: 1:predict, 2:design and 3:scan, by default 1
-t THRESHOLD, --threshold THRESHOLD
Threshold: Value between 0 to 1 by default 0.11
-w {5,6,7,..,25}, --winleng
Window Length: 5 to 25 (scan mode only), by default 10
-d {1,2}, --display {1,2}
Display: 1:Interleukin-6 inducing peptide, 2: All peptides, by defaIL6Pred
Input File: It allow users to provide input in two format; i) FASTA format (standard) and ii) Simple Format. In case of simple format, file should have one one peptide sequence in a single line in single letter code (eg. peptide.seq). Please note in case of predict and design module (job) length of peptide should be upto 25 amino acids, if more than 25, program will take first 25 residues. In case of scan module, minimum length of protein/peptide sequence should be more than equal to window length (pattern), see peptide.fa . Please note program will ignore peptides having length less than 8 residues (e.g., protein.fa).
Output File: Program will save result in 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, please note score is propotional to interleukin-6 inducing potential of peptide.
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
RF_model : Model file required for running Model 2
il6pred.py : Main python program
outfile.csv : Example output file in csv format
peptide.fa : Example file contain peptide sequenaces in FASTA format
peptide.seq : Example file contain peptide sequenaces in simple format
protein.fa : Example file contain protein sequenaces in FASTA format
Data : This folder contains the files required to run the in-built python scripts.
In case of any query please contact
Prof. G. P. S. Raghava, Head Department of Computational Biology,
Indraprastha Institute of Information Technology (IIIT),
Okhla Phase III, New Delhi 110020 ; Phone:+91-11-26907444;
Email: raghava@iiitd.ac.in Web: http://webs.iiitd.edu.in/raghava/