raghavagps / toxinpred3

An improved method for predicting toxicity of the peptides and designing of non-toxic peptides

Toxinpred3.0

A method for predicting toxicity of the peptides

Introduction

ToxinPred3.0 is developed for predicting, mapping and scanning toxic/non-toxic peptides. It uses only composition based features for predicting toxic/non-toxic peptides. The final model also deploys a motif-based module which has been implemented using MERCI. More information on ToxinPred3.0 is available from its web server http://webs.iiitd.edu.in/raghava/toxinpred3. Please read/cite the content about toxinpred3.0 for complete information including algorithm behind the approach.

PIP Installation

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

pip install toxinpred3

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

toxinpred3 -h

Standalone

Standalone version of ToxinPred3.0 is written in python3 and the following libraries are necessary for a successful run:

• scikit-learn
• Pandas
• Numpy

Important Note

• Due to large size of the model file, we have compressed model.
• It is crucial to unzip the file before attempting to use the code or model. The compressed file must be extracted to its original form for the code to function properly.

Minimum USAGE

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

toxinpred3.py -h

To run the example, type the following command:

toxinpred3.py -i peptide.fa

Full Usage:

Following is complete list of all options, you may get these options
usage: toxinpred3.py [-h] 
                     [-i INPUT]
                     [-o OUTPUT]
                     [-t THRESHOLD]
                     [-m {1,2}] 
                     [-d {1,2}]

Please provide following arguments

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
  -t THRESHOLD, --threshold THRESHOLD
                        Threshold: Value between 0 to 1 by default 0.38
  -m {1,2}, -- model Model
                        Model: 1: ML model, 2: Hybrid model, by default 2
  -d {1,2}, --display {1,2}
                        Display: 1:Toxin peptide, 2: All peptides, by
                        default 1

Input File: It allow users to provide input in two format; i) FASTA format (standard) (e.g. peptide.fa) 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).

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 proportional to toxic potential of peptide.

Models: In this program, two models have been incorporated; i) Model1 for predicting given input peptide sequence as toxic and non-toxic peptide using Extra tree based on amino-acid composition (AAC) and di peptide composition (DPC) of the peptide;

ii) Model2 for predicting given input peptide sequence as toxic and non-toxic peptide using Hybrid approach, which is the ensemble of Extra tree + MERCI. It combines the scores generated from machine learning (ET), and MERCI as Hybrid Score, and the prediction is based on Hybrid Score.

ToxinPred3.0 Package Files

It contain following files, brief description of these files given below

INSTALLATION : Installation instructions

LICENSE : License information

merci : This folder contains the program to run MERCI

README.md : This file provide information about this package

toxinpred3.py : Main python program

peptide.fa : Example file contain peptide sequences in FASTA format

peptide.seq : Example file contain peptide sequences in simple format

Installation via PIP

User can install ToxinPred3 via PIP also

pip install toxinpred3