IL13Pred: In silico method for designing IL-13 inducing peptides

Introduction

IL13Pred is developed for predicting, desiging, and scanning the interleukin-13 inducing peptides. More information on IL13Pred is available from its web-server https://webs.iiitd.edu.in/raghava/il13pred/ . This page provides information about stnadalone version of IL13Pred. Please read/cite the content about the IL13Pred for complete information including algorithm behind IL13Pred.

Pip installation

The pip version of IL13pred is also available for easy installation and usage of the tool. The following command is required to install the package

pip install il13pred

To know about the available option for the pip package, type the following command:

il13pred -h

Models: In this program, one model has been incorporated for predicting interleukin-13 inducing peptides. The model is trained on IL-13 inducing and non-inducing peptides.

Modules/Jobs: This program implements three modules (job types); i) Predict: for predictin of interleukin-13 inducing peptides, ii) Design: for generating all possible mutant peptides and computing interleukin-13 inducing potential (score) of peptides, iii) Scan: for creating all possible overlapping peptides of given length (window) and computing interleukin-13 inducing potential (score) of these overlapping peptides.

Minimum USAGE: Minimum usage is "python il13pred.py -i peptide.fa," where peptide.fa is a input fasta file. This will predict the interleukin-13 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 il13pred.py -h"

Usage: il13pred.py [-h] -i INPUT
[-o OUTPUT]
[-j {1,2,3}]
[-t THRESHOLD]
[-w {8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35}]
[-d {1,2}]

Arguments Description:
-h, --help: show help message and exit.
-i INPUT, --input: protein or peptide sequence in FASTA format or single sequence per line in single letter code.
-o OUTPUT, --output: File for saving results by default outfile.csv.
-j, --Job Type: 1:predict, 2:design and 3:scan, by default 1.
-t THRESHOLD, --Threshold: Value between 0 to 1 by default 0.06.
-w, or --winleng, --Window Length: 8 to 35 (scan mode only), by default 9.
-d, --Display: 1:Interleukin-13 inducing peptide, 2: All peptides, by default 1

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 peptide sequence in a single line in single letter code (eg. peptide.seq).

Note:
1: In case of predict and design module (job), the length of peptide should be upto 35 amino acids. If a sequence with length more than 35 will be provided, program willtake first 35 residues, and ignore the rest. In case of scan module, minimum length of protein/peptide sequence should be more than or equal to window length (pattern), see peptide.fa.
2: Program will ignore peptides having length less than 8 residues (e.g., protein.fa).

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, please note that the score is propotional to interleukin-13 inducing potential of peptide.

IL13Pred Package Files

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Brief description of the files included is given below:

• INSTALLATION : Installations instructions

• LICENSE : License information

• README.md : This file provide information about this package

• XGB_model : Model file comprising the parameters of XGB classifier

• il13pred.py : Main python program

• 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

• example_predict_output.csv : Example output file for predict module

• example_scan_output.csv : Example output file for scan module

• example_design_output.csv : Example output file for design module

Reference

Jain S., Dhall A., Patiyal S. and Raghava G.P.S. (2022) IL13Pred: A method for predicting immunoregulatory cytokine IL-13 inducing peptides. Computers in Biology and Medicine, 2022: 05297.